Use of integrative epigenetic and mRNA expression analyses to identify significantly changed genes and functional pathways in osteoarthritic cartilage.
He A,Ning Y,Wen Y,Cai Y,Xu K,Cai Y,Han J,Liu L,Du Y,Liang X,Li P,Fan Q,Hao J,Wang X,Guo X,Ma T,Zhang F
Bone & joint research
Aim:Osteoarthritis (OA) is caused by complex interactions between genetic and environmental factors. Epigenetic mechanisms control the expression of genes and are likely to regulate the OA transcriptome. We performed integrative genomic analyses to define methylation-gene expression relationships in osteoarthritic cartilage. Patients and Methods:Genome-wide DNA methylation profiling of articular cartilage from five patients with OA of the knee and five healthy controls was conducted using the Illumina Infinium HumanMethylation450 BeadChip (Illumina, San Diego, California). Other independent genome-wide mRNA expression profiles of articular cartilage from three patients with OA and three healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Integrative pathway enrichment analysis of DNA methylation and mRNA expression profiles was performed using integrated analysis of cross-platform microarray and pathway software. Gene ontology (GO) analysis was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Results:We identified 1265 differentially methylated genes, of which 145 are associated with significant changes in gene expression, such as DLX5, NCOR2 and AXIN2 (all p-values of both DNA methylation and mRNA expression < 0.05). Pathway enrichment analysis identified 26 OA-associated pathways, such as mitogen-activated protein kinase (MAPK) signalling pathway (p = 6.25 × 10-4), phosphatidylinositol (PI) signalling system (p = 4.38 × 10-3), hypoxia-inducible factor 1 (HIF-1) signalling pathway (p = 8.63 × 10-3 pantothenate and coenzyme A (CoA) biosynthesis (p = 0.017), ErbB signalling pathway (p = 0.024), inositol phosphate (IP) metabolism (p = 0.025), and calcium signalling pathway (p = 0.032). Conclusion:We identified a group of genes and biological pathwayswhich were significantly different in both DNA methylation and mRNA expression profiles between patients with OA and controls. These results may provide new clues for clarifying the mechanisms involved in the development of OA.: A. He, Y. Ning, Y. Wen, Y. Cai, K. Xu, Y. Cai, J. Han, L. Liu, Y. Du, X. Liang, P. Li, Q. Fan, J. Hao, X. Wang, X. Guo, T. Ma, F. Zhang. Use of integrative epigenetic and mRNA expression analyses to identify significantly changed genes and functional pathways in osteoarthritic cartilage. 2018;7:343-350. DOI: 10.1302/2046-3758.75.BJR-2017-0284.R1.
Unique metabolic activation of adipose tissue macrophages in obesity promotes inflammatory responses.
Boutens Lily,Hooiveld Guido J,Dhingra Sourabh,Cramer Robert A,Netea Mihai G,Stienstra Rinke
AIMS/HYPOTHESIS:Recent studies have identified intracellular metabolism as a fundamental determinant of macrophage function. In obesity, proinflammatory macrophages accumulate in adipose tissue and trigger chronic low-grade inflammation, that promotes the development of systemic insulin resistance, yet changes in their intracellular energy metabolism are currently unknown. We therefore set out to study metabolic signatures of adipose tissue macrophages (ATMs) in lean and obese conditions. METHODS:F4/80-positive ATMs were isolated from obese vs lean mice. High-fat feeding of wild-type mice and myeloid-specific Hif1α mice was used to examine the role of hypoxia-inducible factor-1α (HIF-1α) in ATMs part of obese adipose tissue. In vitro, bone marrow-derived macrophages were co-cultured with adipose tissue explants to examine adipose tissue-induced changes in macrophage phenotypes. Transcriptome analysis, real-time flux measurements, ELISA and several other approaches were used to determine the metabolic signatures and inflammatory status of macrophages. In addition, various metabolic routes were inhibited to determine their relevance for cytokine production. RESULTS:Transcriptome analysis and extracellular flux measurements of mouse ATMs revealed unique metabolic rewiring in obesity characterised by both increased glycolysis and oxidative phosphorylation. Similar metabolic activation of CD14 cells in obese individuals was associated with diabetes outcome. These changes were not observed in peritoneal macrophages from obese vs lean mice and did not resemble metabolic rewiring in M1-primed macrophages. Instead, metabolic activation of macrophages was dose-dependently induced by a set of adipose tissue-derived factors that could not be reduced to leptin or lactate. Using metabolic inhibitors, we identified various metabolic routes, including fatty acid oxidation, glycolysis and glutaminolysis, that contributed to cytokine release by ATMs in lean adipose tissue. Glycolysis appeared to be the main contributor to the proinflammatory trait of macrophages in obese adipose tissue. HIF-1α, a key regulator of glycolysis, nonetheless appeared to play no critical role in proinflammatory activation of ATMs during early stages of obesity. CONCLUSIONS/INTERPRETATION:Our results reveal unique metabolic activation of ATMs in obesity that promotes inflammatory cytokine release. Further understanding of metabolic programming in ATMs will most likely lead to novel therapeutic targets to curtail inflammatory responses in obesity. DATA AVAILABILITY:Microarray data of ATMs isolated from obese or lean mice have been submitted to the Gene Expression Omnibus (accession no. GSE84000).
Uncovering potential lncRNAs and nearby mRNAs in systemic lupus erythematosus from the Gene Expression Omnibus dataset.
Cao Haiyu,Li Dong,Lu Huixiu,Sun Jing,Li Haibin
The aim of this study was to find potential differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in systemic lupus erythematosus. Differentially expressed lncRNAs and mRNAs were obtained in the Gene Expression Omnibus dataset. Functional annotation of differentially expressed mRNAs was performed, followed by protein-protein interaction network analysis. Then, the interaction network of lncRNA-nearby targeted mRNA was built. Several interaction pairs of lncRNA-nearby targeted mRNA including , , , and // were identified. Measles and MAPK were significantly enriched signaling pathways of differentially expressed mRNAs. Our study identified several differentially expressed lncRNAs and mRNAs. And their interactions may play a crucial role in the process of systemic lupus erythematosus.
Translational bioinformatics in mental health: open access data sources and computational biomarker discovery.
Tenenbaum Jessica D,Bhuvaneshwar Krithika,Gagliardi Jane P,Fultz Hollis Kate,Jia Peilin,Ma Liang,Nagarajan Radhakrishnan,Rakesh Gopalkumar,Subbian Vignesh,Visweswaran Shyam,Zhao Zhongming,Rozenblit Leon
Briefings in bioinformatics
Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities arise to explore the biological basis for behavioral health and disease. From individual investigators to large international consortia, researchers have generated rich data sets in the area of mental health, including genomic, transcriptomic, metabolomic, proteomic, clinical and imaging resources. General data repositories such as the Gene Expression Omnibus (GEO) and Database of Genotypes and Phenotypes (dbGaP) and mental health (MH)-specific initiatives, such as the Psychiatric Genomics Consortium, MH Research Network and PsychENCODE represent a wealth of information yet to be gleaned. At the same time, novel approaches to integrate and analyze data sets are enabling important discoveries in the area of mental and behavioral health. This review will discuss and catalog into an organizing framework the increasingly diverse set of MH data resources available, using schizophrenia as a focus area, and will describe novel and integrative approaches to molecular biomarker discovery that make use of mental health data.
Transcriptomic Analysis of the Developmental Similarities and Differences Between the Native Retina and Retinal Organoids.
Cui Zekai,Guo Yonglong,Zhou Yalan,Mao Shengru,Yan Xin,Zeng Yong,Ding Chengcheng,Chan Hon Fai,Tang Shibo,Tang Luosheng,Chen Jiansu
Investigative ophthalmology & visual science
Purpose:We performed a bioinformatic transcriptome analysis to determine the alteration of gene expression between the native retina and retinal organoids in both mice and humans. Methods:The datasets of mouse native retina (GSE101986), mouse retinal organoids (GSE102794), human native retina (GSE104827), and human retinal organoids (GSE119320) were obtained from Gene Expression Omnibus. After normalization, a principal component analysis was performed to categorize the samples. The genes were clustered to classify them. A functional analysis was performed using the bioinformatics tool Gene ontology enrichment to analyze the biological processes of selected genes and cellular components. Results:The development of retinal organoids is slower than that in the native retina. In the early stage, cell proliferation predominates. Subsequently, neural differentiation is dominant. In the later stage, the dominant differentiated cells are photoreceptors. Additionally, the fatty acid metabolic process and mitochondria-related genes are upregulated over time, and the glycogen catabolic process and activin receptors are gradually downregulated in human retinal organoids. However, these trends are opposite in mouse retinal organoids. There are two peaks in mitochondria-related genes, one in the early development period and another during the photoreceptor development period. It takes about five times longer for human retinal development to achieve similar levels of mouse retinal development. Conclusions:Our study reveals the similarities and differences in the developmental features of retinal organoids as well as the corresponding relationship between mouse and human retinal development.
Transcriptome Changes in Relation to Manic Episode.
Lee Ya-Chin,Chao Yu-Lin,Chang Chiao-Erh,Hsieh Ming-Hsien,Liu Kuan-Ting,Chen Hsi-Chung,Lu Mong-Liang,Chen Wen-Yin,Chen Chun-Hsin,Tsai Mong-Hsun,Lu Tzu-Pin,Huang Ming-Chyi,Kuo Po-Hsiu
Frontiers in psychiatry
Bipolar disorder (BD) is highly heritable and well known for its recurrent manic and depressive episodes. The present study focused on manic episode in BD patients and aimed to investigate state-specific transcriptome alterations between acute episode and remission, including messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and micro-RNAs (miRNAs), using microarray and RNA sequencing (RNA-Seq) platforms. BD patients were enrolled with clinical information, and peripheral blood samples collected at both acute and remission status spanning for at least 2 months were confirmed by follow-ups. Symptom severity was assessed by Young Mania Rating Scale. We enrolled six BD patients as the discovery samples and used the Affymetrix Human Transcriptome Array 2.0 to capture transcriptome data at the two time points. For replication, expression data from Gene Expression Omnibus that consisted of 11 BD patients were downloaded, and we performed a mega-analysis for microarray data of 17 patients. Moreover, we conducted RNA sequencing (RNA-Seq) in additional samples of 7 BD patients. To identify intraindividual differentially expressed genes (DEGs), we analyzed data using a linear model controlling for symptom severity. We found that noncoding genes were of majority among the top DEGs in microarray data. The expression fold change of coding genes among DEGs showed moderate to high correlations (∼0.5) across platforms. A number of lncRNAs and two miRNAs ( and ) exhibited high levels of gene expression in the manic state. For coding genes, we reported that the taste function-related genes, including and , may be mania state-specific markers. Additionally, four genes showed a nominal -value of less than 0.05 in all our microarray data, mega-analysis, and RNA-Seq analysis. They were upregulated in the manic state and consisted of , , , and , and their gene expression patterns were further validated by quantitative real-time polymerase chain reaction (PCR) (qRT-PCR). We also performed weight gene coexpression network analysis to identify gene modules for manic episode. Genes in the mania-related modules were different from the susceptible loci of BD obtained from genome-wide association studies, and biological pathways in relation to these modules were mainly related to immune function, especially cytokine-cytokine receptor interaction. Results of the present study elucidated potential molecular targets and genomic networks that are involved in manic episode. Future studies are needed to further validate these biomarkers for their roles in the etiology of bipolar illness.
TPM2 as a potential predictive biomarker for atherosclerosis.
Meng Ling-Bing,Shan Meng-Jie,Qiu Yong,Qi Ruomei,Yu Ze-Mou,Guo Peng,Di Chen-Yi,Gong Tao
Cardiac-cerebral vascular disease (CCVD), is primarily induced by atherosclerosis, and is a leading cause of mortality. Numerous studies have investigated and attempted to clarify the molecular mechanisms of atherosclerosis; however, its pathogenesis has yet to be completely elucidated. Two expression profiling datasets, GSE43292 and GSE57691, were obtained from the Gene Expression Omnibus (GEO) database. The present study then identified the differentially expressed genes (DEGs), and functional annotation of the DEGs was performed. Finally, an atherosclerosis animal model and neural network prediction model was constructed to verify the relationship between hub gene and atherosclerosis. The results identified a total of 234 DEGs between the normal and atherosclerosis samples. The DEGs were mainly enriched in actin filament, actin binding, smooth muscle cells, and cytokine-cytokine receptor interactions. A total of 13 genes were identified as hub genes. Following verification of animal model, the common DEG, Tropomyosin 2 (TPM2), was found, which were displayed at lower levels in the atherosclerosis models and samples. In summary, DEGs identified in the present study may assist clinicians in understanding the pathogenesis governing the occurrence and development of atherosclerosis, and TPM2 exhibits potential as a promising diagnostic and therapeutic biomarker for atherosclerosis.
Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis.
Mei Hao,Li Lianna,Liu Shijian,Jiang Fan,Griswold Michael,Mosley Thomas
We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that and genes were significant over diabetes studies, while and genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.
The Overlap of Lung Tissue Transcriptome of Smoke Exposed Mice with Human Smoking and COPD.
Obeidat Ma'en,Dvorkin-Gheva Anna,Li Xuan,Bossé Yohan,Brandsma Corry-Anke,Nickle David C,Hansbro Philip M,Faner Rosa,Agusti Alvar,Paré Peter D,Stampfli Martin R,Sin Don D
Genome-wide mRNA profiling in lung tissue from human and animal models can provide novel insights into the pathogenesis of chronic obstructive pulmonary disease (COPD). While 6 months of smoke exposure are widely used, shorter durations were also reported. The overlap of short term and long-term smoke exposure in mice is currently not well understood, and their representation of the human condition is uncertain. Lung tissue gene expression profiles of six murine smoking experiments (n = 48) were obtained from the Gene Expression Omnibus (GEO) and analyzed to identify the murine smoking signature. The "human smoking" gene signature containing 386 genes was previously published in the lung eQTL study (n = 1,111). A signature of mild COPD containing 7 genes was also identified in the same study. The lung tissue gene signature of "severe COPD" (n = 70) contained 4,071 genes and was previously published. We detected 3,723 differentially expressed genes in the 6 month-exposure mice datasets (FDR <0.1). Of those, 184 genes (representing 48% of human smoking) and 1,003 (representing 27% of human COPD) were shared with the human smoking-related genes and the COPD severity-related genes, respectively. There was 4-fold over-representation of human and murine smoking-related genes (P = 6.7 × 10) and a 1.4 fold in the severe COPD -related genes (P = 2.3 × 10). There was no significant enrichment of the mice and human smoking-related genes in mild COPD signature. These data suggest that murine smoke models are strongly representative of molecular processes of human smoking but less of COPD.
The application of weighted gene co-expression network analysis in identifying key modules and hub genes associated with disease status in Alzheimer's disease.
Sun Yan,Lin Jinghan,Zhang Liming
Annals of translational medicine
Background:Alzheimer's disease (AD) is the most common neurodegenerative condition that affects more than 15 million individuals globally. However, a predictive molecular biomarker to distinguish the different stages of AD patients is still lacking. Methods:A weighted gene co-expression network analysis (WGCNA) was employed to systematically identify the co-expressed gene modules and hub genes connected with AD development based on a microarray dataset (GSE1297) from the Gene Expression Omnibus (GEO) database. An independent validation cohort, GSE28146, was utilized to assess the diagnostic efficiency for distinguishing the different stages of AD. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) and western blotting analysis were applied to examine the mRNA and protein level of GRIK1, respectively, in AD mice established with the expression of mutant amyloid precursor protein and wild type mice. The morphology of neurons was investigated using phalloidin staining. Results:We identified 16 co-expressed genes modules, with the pink module showing significant association with all three disease statuses [neurofibrillary tangle (NFT), BRAAK, and mini-mental state examination (MMSE)]. Enrichment analysis specified that these modules were enriched in phosphatidylinositol 3-kinase (PI3K) signaling and ion transmembrane transport. The validation cohort GSE28146 confirmed that six hub genes in the pink module could distinguish severe and non-severe AD patients [area under the curve (AUC) >0.7]. These hub genes might act as a biomarker and help to differentiate diverse pathological stages for AD patients. Finally, one of the hubs, GRIK1, was validated by an animal AD model. The mRNA and protein level of GRIK1 in the AD hippocampus was increased compared with the control group (NC) hippocampus. Phalloidin staining showed that dendritic length of the GRIK1 pCDNA3.1 group was shorter than that of the NC group. Conclusions:In summary, we systematically recognized co-expressed gene modules and genes related to AD stages, which gave insight into the fundamental mechanisms of AD progression and revealed some probable targets for the treatment of AD.
Systematic Analysis of Transcriptomic Profile of Chondrocytes in Osteoarthritic Knee Using Next-Generation Sequencing and Bioinformatics.
Chen Yi-Jen,Chang Wei-An,Wu Ling-Yu,Hsu Ya-Ling,Chen Chia-Hsin,Kuo Po-Lin
Journal of clinical medicine
The phenotypic change of chondrocytes and the interplay between cartilage and subchondral bone in osteoarthritis (OA) has received much attention. Structural changes with nerve ingrowth and vascular penetration within OA cartilage may contribute to arthritic joint pain. The aim of this study was to identify differentially expressed genes and potential miRNA regulations in OA knee chondrocytes through next-generation sequencing and bioinformatics analysis. Results suggested the involvement of SMAD family member 3 () and Wnt family member 5A () in the growth of blood vessels and cell aggregation, representing features of cartilage damage in OA. Additionally, 26 dysregulated genes with potential miRNA⁻mRNA interactions were identified in OA knee chondrocytes. Myristoylated alanine rich protein kinase C substrate (), epiregulin (), leucine rich repeat containing 15 (), and phosphodiesterase 3A () expression patterns were similar among related OA cartilage, subchondral bone and synovial tissue arrays in Gene Expression Omnibus database. The Ingenuity Pathway Analysis identified to be associated with the outgrowth of neurite, and novel miRNA regulations were proposed to play critical roles in the pathogenesis of the altered OA knee joint microenvironment. The current findings suggest new perspectives in studying novel genes potentially contributing to arthritic joint pain in knee OA, which may assist in finding new targets for OA treatment.
Syndecan-4 involves in the pathogenesis of rheumatoid arthritis by regulating the inflammatory response and apoptosis of fibroblast-like synoviocytes.
Cai Peian,Lu Zhenhui,Jiang Tongmeng,Wang Zetao,Yang Yifeng,Zheng Li,Zhao Jinmin
Journal of cellular physiology
Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease, and the pathogenesis of RA is still unknown. Rheumatoid arthritis fibroblast-like synoviocytes (RA-FLSs) are of significance in the pathogenesis of RA. In this study, three microarray profiles (GSE55457, GSE55584, and GSE55235) of human joint FLSs from 33 RA patients and 20 normal controls were extracted from the Gene Expression Omnibus Dataset and analyzed to investigate the underlying pathogenesis of RA. As analyzed by the differently expressed genes, gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment, and protein-protein interaction network analysis, syndecan-4 (SDC4), a receptor of multiple cytokines and chemokines, which played a key role in the regulation of inflammatory response, was found to be an essential regulator in RA. To further validate these results, the levels of SDC4, reactive oxygen species (ROS), nitric oxide (NO), inflammation, and apoptosis in RA-FLSs were examined. SDC4-silenced RA-FLSs were also used. The results demonstrated that SDC4 and the level of ROS, NO, and inflammation were highly expressed while the apoptosis was decreased in RA-FLSs compared with normal FLSs. SDC4 silencing significantly suppressed the levels of ROS, NO, and inflammation; elevated the expression of nuclear factor erythroid 2-related factor 2; and promoted the apoptosis of RA-FLSs. Collectively, our results demonstrated a new mechanism of SDC4 in initiating the inflammation and inhibiting the apoptosis of RA-FLSs and that a potential target for the diagnosis and treatment of RA in the clinic might be developed.
Supervised pathway analysis of blood gene expression profiles in Alzheimer's disease.
Moradi Elaheh,Marttinen Mikael,Häkkinen Tomi,Hiltunen Mikko,Nykter Matti
Neurobiology of aging
Early identification and treatment of Alzheimer's disease (AD) is hampered by the lack of easily accessible biomarkers. Currently available fluid biomarkers of AD provide indications of the disease stage; however, these are measured in the cerebrospinal fluid, requiring invasive procedures, which are not applicable at the population level. Thus, gene expression profiling of blood provides a viable alternative as a way to screen individuals at risk of AD. Previous studies have shown that despite the limited permeability of the blood-brain barriers, expression profiles of blood genes can be used for the diagnosis and prognosis of several brain disorders. Here, we propose a new approach to pathway analysis of blood gene expression profiles to classify healthy (control [CTL]), mildly cognitively impaired (mild cognitive impairment [MCI]; preclinical stage of AD), and AD subjects. In the pathway analysis, gene expression data are mapped to pathway scores according to a predefined gene set instead of considering each gene separately. The robustness of the analysis enables detection of weak differences between groups owing to the inherent dimension reduction. Our proposed method for pathway analysis takes advantage of linear discriminant analysis for identifying a linear combination of features best separating groups of subjects within each gene set. The gene expression data were retrieved from Gene Expression Omnibus (batch 1: GSE63060; batch 2: GSE63061). Predefined gene sets for pathway analysis were obtained from the Broad Institute Collection of Curated Pathways. The method achieved a 10-fold cross-validated area under receiver operating characteristic curve of 0.84 for classification of AD versus CTL and 0.80 for classification of mild cognitive impairment versus CTL. These results reveal the good potential of blood-based biomarkers for assisting early diagnosis and disease monitoring of AD.
Specific expression network analysis of diabetic nephropathy kidney tissue revealed key methylated sites.
Wang Yan-Zhe,Xu Wen-Wei,Zhu Ding-Yu,Zhang Nan,Wang Yong-Lan,Ding Miao,Xie Xin-Miao,Sun Lin-Lin,Wang Xiao-Xia
Journal of cellular physiology
Diabetic nephropathy (DN) is one of the most common and serious complication in diabetes patients. However, the evidences of gene regulation mechanism and epigenetic modification with DN remain unclear. Therefore, it is necessary to search regulating genes for early diagnosis on DN. We identified tissue specific genes through mining the gene expression omnibus (GEO) public database, enriched function by gene ontology (GO), and kyoto encyclopedia of genes and genomes (KEGG) analysis, and further compared tissue-specific network. Meanwhile, combining with differentially methylated sites, we explored the association epigenetic modification with the pathogenesis of DN. Glomeruli (Glom) may be the main tissue of signal recognition and tubulointerstitium (Tub) is mainly associated with energy metabolism in the occurrence of DN. By comparing tissue-specific networks between Glom and Tub, we screened 319 genes, which played an important role in multiple tissue on kidney. Among them, ANXA2, UBE2L6, MME, IQGAP, SLC7A7, and PLG played a key role in regulating the incidence of DN. Besides, we also identified 1 up-regulated gene (PIK3C2B) and 39 down-regulated genes (POLR2G, DDB1, and ZNF230, etc.) in the methylated data of Glom specific genes. In the Tub specific expressed genes, we identified two hypo-methylated genes (PPARA and GLS). Tub mainly caused abnormal energy metabolism, and Glom caused the changes in cell connections and histone modification. By analyzing differentially methylated sites and tissue-specific expressed genes, we found the change of methylated status about the core regulating genes may be a potential factor in the pathogenesis of DN.
Single-cell RNA sequencing of oocytes from ovarian endometriosis patients reveals a differential transcriptomic profile associated with lower quality.
Ferrero Hortensia,Corachán Ana,Aguilar Alejandra,Quiñonero Alicia,Carbajo-García María Cristina,Alamá Pilar,Tejera Alberto,Taboas Esther,Muñoz Elkin,Pellicer Antonio,Domínguez Francisco
Human reproduction (Oxford, England)
STUDY QUESTION:Do oocytes from women with ovarian endometriosis (OE) have a different transcriptomic profile than those from healthy women? SUMMARY ANSWER:Oocytes from endometriosis patients, independently of whether they came from the affected ovary, exhibited a differential transcriptomic profile compared to oocytes from healthy egg donors. WHAT IS KNOWN ALREADY:Studies of endometriosis have sought to determine whether OE affects oocyte quality. While many reports indicate that oocytes recovered from endometriotic ovaries may be affected by the disease, other studies have found no significant differences among oocyte/embryo quality and fertilization, implantation and pregnancy rates in women with endometriosis. STUDY DESIGN, SIZE, DURATION:This prospective study compared metaphase II (MII) oocytes (n = 16) from endometriosis patients (n = 7) to oocytes (n = 16) from healthy egg donors (n = 5) by single-cell RNA sequencing (scRNA-seq). Participants were recruited between December 2016 and February 2018 at IVI-RMA Valencia and Vigo clinics. PARTICIPANTS/MATERIALS, SETTING, METHODS:Human MII oocytes were collected from healthy egg donors and OE patients aged 18-34 years, with a body mass index of <30 and >6 pre-antral follicles. RNA was extracted, cDNA was generated and libraries were constructed and sequenced. scRNA-seq data libraries were processed and statistically analysed. Selected genes were validated by quantitative real-time PCR. MAIN RESULTS AND THE ROLE OF CHANCE:Our scRNA-seq results revealed an effect of endometriosis on global transcriptome behaviour in oocytes from endometriotic ovaries. The highest number of differentially expressed genes (DEGs) was found when oocytes from women with OE were compared to oocytes from healthy donors [520 DEGs (394 upregulated and 126 downregulated)], independently of whether oocytes came from an affected or unaffected ovary. Among the top 20 significant DEGs in this comparison, most were upregulated, including APOE, DUSP1, G0S2, H2AFZ, ID4, MGST1 and WEE1. PXK was the only downregulated gene. Subsequently, functional analysis showed 31 enriched functions deregulated in endometriosis patients (Benjamini P < 0.1), being 16 significant enriched functions considering Benjamini P < 0.05, which involved in biological processes and molecular functions, such as steroid metabolism, response to oxidative stress and cell growth regulation. In addition, our functional analysis showed enrichment for mitochondria, which are an important cellular component in oocyte development. Other functions important in embryo development, such as angiogenesis and methylation, were also significantly enriched. LARGE SCALE DATA:All raw sequencing data are submitted in Gene Expression Omnibus (GEO) under accession number (PRJNA514416). LIMITATIONS, REASONS FOR CAUTION:This study was restricted only to OE and thereby other anatomical entities, such as peritoneal and deep infiltrating endometriosis, were not considered. This is a descriptive study with a limited number of samples reflecting the difficulty to recruit human oocytes, especially from women with endometriosis. WIDER IMPLICATIONS OF THE FINDINGS:This study suggests that OE exhibits a global transcriptomic effect on oocytes of patients in OE, independently if they come from an affected or unaffected ovary and alters key biological processes and molecular functions related to steroid metabolism, response to oxidative stress and cell growth regulation, which reduce oocyte quality. STUDY FUNDING/COMPETING INTEREST(S):This research was supported by IVI Foundation, the Spanish Ministry of Economy and Competitiveness through the Miguel Servet programme (CPII018/00002 to F.D.), the Sara Borrell Program (CD15/00057 to H.F.) and the VALi+d Programe (Generalitat Valenciana); ACIF/2016/444 to A.C.). The authors have no conflicts of interest to declare. TRIAL REGISTRATION NUMBER:None.
S1PR1-Associated Molecular Signature Predicts Survival in Patients with Sepsis.
Feng Anlin,Rice Amanda D,Zhang Yao,Kelly Gabriel T,Zhou Tong,Wang Ting
Shock (Augusta, Ga.)
BACKGROUND:Sepsis is a potentially life-threatening complication of an underlying infection that quickly triggers tissue damage in multiple organ systems. To date, there are no established useful prognostic biomarkers for sepsis survival prediction. Sphingosine-1-phosphate (S1P) and its receptor S1P receptor 1 (S1PR1) are potential therapeutic targets and biomarkers for sepsis, as both are active regulators of sepsis-relevant signaling events. However, the identification of an S1PR1-related gene signature for prediction of survival in sepsis patients has yet to be identified. This study aims to find S1PR1-associated biomarkers which could predict the survival of patients with sepsis using gene expression profiles of peripheral blood to be used as potential prognostic and diagnostic tools. METHODS:Gene expression analysis from sepsis patients enrolled in published datasets from Gene Expression Omnibus was utilized to identify both S1PR1-related genes (co-expression genes or functional-related genes) and sepsis survival-related genes. RESULTS:We identified 62-gene and 16-gene S1PR1-related molecular signatures (SMS) associated with survival of patients with sepsis in discovery cohort. Both SMS genes are significantly enriched in multiple key immunity-related pathways that are known to play critical roles in sepsis development. Meanwhile, the SMS performs well in a validation cohort containing sepsis patients. We further confirmed our SMSs, as newly developed gene signatures, perform significantly better than random gene signatures with the same gene size, in sepsis survival prognosis. CONCLUSIONS:Our results have confirmed the significant involvement of S1PR1-dependent genes in the development of sepsis and provided new gene signatures for predicting survival of sepsis patients.
Retinal and circulating miRNA expression patterns in diabetic retinopathy: An in silico and in vivo approach.
Platania Chiara Bianca Maria,Maisto Rosa,Trotta Maria Consiglia,D'Amico Michele,Rossi Settimio,Gesualdo Carlo,D'Amico Giovanbattista,Balta Cornel,Herman Hildegard,Hermenean Anca,Ferraraccio Franca,Panarese Iacopo,Drago Filippo,Bucolo Claudio
British journal of pharmacology
BACKGROUND AND PURPOSE:Diabetic retinopathy, a secondary complication of diabetes mellitus, can lead to irreversible vision loss. Currently, no treatment is approved for early phases of diabetic retinopathy. Modifications of the expression pattern of miRNAs could be involved in the early retinal damage of diabetic subjects. Therefore, we aimed at identification of dysregulated miRNAs-mRNA interactions that might be biomarkers and pharmacological targets for diagnosis and treatment of early diabetic retinopathy. METHODS:A focused set of miRNAs was predicted through a bioinformatic analysis accessing to Gene Expression Omnibus dataset and enrichment of information approach (GENEMANIA-Cytoscape). Identification of miRNAs-mRNA interactions was carried out with miRNET analysis. Diabetes was induced in C57BL6J mice by streptozotocin and samples analysed at 5 and 10 weeks after diabetes induction. Retinal ultrastructure of diabetic mice was analysed through electron microscopy. We used Real-time PCR, western blot analysis, elisa, and immunohistochemistry to study expression of miRNAs and possible targets of dysregulated miRNAs. KEY RESULTS:We found that miR-20a-5p, miR-20a-3p, miR-20b, miR-106a-5p, miR-27a-5p, miR-27b-3p, miR-206-3p, and miR-381-3p were dysregulated in the retina and serum of diabetic mice. VEGF, brain-derived neurotrophic factor (BDNF), PPAR-α, and cAMP response element-binding protein 1 (CREB1) are targets of dysregulated miRNAs, which then modulated protein expression in diabetic retina. We found structural modifications in retinas from diabetic mice. CONCLUSIONS AND IMPLICATIONS:Serum and retina of diabetic mice express eight dysregulated miRNAs, which modified the expression of VEGF, BDNF, PPAR-α, and CREB1, before vasculopathy in diabetic retinas.
Reconstruction and Analysis of the lncRNA-miRNA-mRNA Network Based on Competitive Endogenous RNA Reveal Functional lncRNAs in Dilated Cardiomyopathy.
Tao Lichan,Yang Ling,Huang Xiaoli,Hua Fei,Yang Xiaoyu
Frontiers in genetics
Dilated cardiomyopathy (DCM) is an important cause of sudden death and heart failure with an unknown etiology. Recent studies have suggested that long non-coding RNA (lncRNA) can interact with microRNA (miRNA) and indirectly interact with mRNA through competitive endogenous RNA (ceRNA) activities. However, the mechanism of ceRNA in DCM remains unclear. In this study, a miRNA array was first performed using heart samples from DCM patients and healthy controls. For further validation, we conducted real-time quantitative reverse transcription (RT)-PCR using samples from DCM patients and a doxorubicin-induced rodent model of cardiomyopathy, revealing that miR-144-3p and miR-451a were down-regulated, and miR-21-5p was up-regulated. Based on the ceRNA theory, we constructed a global triple network using data from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI-GEO) and our miRNA array. The lncRNA-miRNA-mRNA network comprised 22 lncRNA nodes, 32 mRNA nodes, and 11 miRNA nodes. Hub nodes and the number of relationship pairs were then analyzed, and the results showed that two lncRNAs (NONHSAT001691 and NONHSAT006358) targeting miR-144/451 were highly related to DCM. Then, cluster module and random walk with restart for the ceRNA network were analyzed and identified four lncRNAs (NONHSAT026953/NONHSAT006250/NONHSAT133928/NONHSAT041662) targeting miR-21 that were significantly related to DCM. This study provides a new strategy for research on DCM or other diseases. Furthermore, lncRNA-miRNA pairs may be regarded as candidate diagnostic biomarkers or potential therapeutic targets of DCM.
Reappraisal of FDA approved drugs against Alzheimer's disease based on differential gene expression and protein interaction network analysis: an in silico approach.
G N S Hema Sree,Ganesan Rajalekshmi Saraswathy,Murahari Manikanta,Burri Raghunadha R
Journal of biomolecular structure & dynamics
Alzheimer's disease (AD), a most prevailing neurodegenerative disorder with turbulence in cognitive and behavioural abilities, epitomizes one of the highest unmet medical requirements. The current AD treatment focuses merely on symptomatic relief, this explains a dearth in drug research oriented towards unwinding of disease specific druggable targets. On the other hand, toxicity and poor bioavailability hamper the evolution of novel chemical entities (NCE) in clinical trials. Drug repurposing offers a gateway to rejuvenate new therapeutic applications for existing approved drugs. This study concentrates on the identification of potential druggable AD targets and screening of FDA approved drugs with a concept of drug repurposing. differentially expressed genes (DEGs) were identified in frontal cortex, temporal cortex and hippocampus in AD patients from Gene Expression Omnibus (GEO) dataset GSE36980. Protein-protein interaction (PPI) analysis revealed SERPINA3 and BDNF to possess high node degree interaction with literature derived candidate genes (LDGs) in AD males and females, respectively, thus were selected as potential AD targets. Subsequently, FDA approved drugs were screened through the above shortlisted targets and were ranked based on molecular docking and MM-GBSA energy calculations using Glide and Prime tools, respectively. Drugs possessing best docking score and maximum binding energy were further evaluated through molecular dynamics simulation studies, which revealed the affinity of Tiludronic acid and Olsalazine towards SERPINA3 and BDNF, respectively.
Potentially critical roles of TNPO1, RAP1B, ZDHHC17, and PPM1B in the progression of coronary atherosclerosis through microarray data analysis.
Zhang Xiaohui,Sun Renhua,Liu Liping
Journal of cellular biochemistry
OBJECTIVE:This study aimed to identify more potentially critical genes associated with atherosclerotic coronary artery disease (CAD). MATERIALS AND METHODS:Gene expression profile of GSE12288 was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened in atherosclerotic CAD samples compared with controls, followed by weighed gene coexpression network analysis (WGCNA) by which the most significant module was identified. Gene coexpression network was constructed based on genes in the most significant module, and functional annotation was also performed. In addition, microRNAs (miRNAs) that were directly associated with CAD were screened from the literature, and the miRNA-target regulatory network was constructed based on genes in the most significant module, followed by Gene Ontology (GO) and pathway enrichment analysis. Furthermore, we used another data set of GSE42148 from the GEO database to perform data validation. RESULTS:WGCNA analysis showed that the turquoise module may have the most important role in atherosclerotic CAD. Genes in this module were involved in translational elongation and intracellular signal transduction. Besides, we identified five confirmed CAD-related miRNAs. TNPO1, RAP1B, and ZDHHC17 could be targeted by four of these miRNAs. Genes such as PPM1B could be regulated by three miRNAs. Moreover, TNPO1 and ZDHHC17 were involved in the GO terms associated with protein localization and transport and the immune system; RAP1B and PPM1B were linked with intracellular signal transduction-related pathways. In addition, PPM1B and ZDHHC17 had accordantly significant expression changes in another data set GSE42148. CONCLUSION:TNPO1, RAP1B, ZDHHC17, and PPM1B may play essential roles in the progression of coronary atherosclerosis.
Polycystic Ovary Syndrome: Novel and Hub lncRNAs in the Insulin Resistance-Associated lncRNA-mRNA Network.
Zhao Jun,Huang Jiayu,Geng Xueying,Chu Weiwei,Li Shang,Chen Zi-Jiang,Du Yanzhi
Frontiers in genetics
Polycystic ovary syndrome (PCOS) is a common metabolic and reproductive disorder with an increasing risk for type 2 diabetes. Insulin resistance is a common feature of women with PCOS, but the underlying molecular mechanism remains unclear. This study aimed to screen critical long non-coding RNAs (lncRNAs) that might play pivotal roles in insulin resistance, which could provide candidate biomarkers and potential therapeutic targets for PCOS. Gene expression profiles of the skeletal muscle in patients with PCOS accompanied by insulin resistance and healthy patients were obtained from the publicly available Gene Expression Omnibus (GEO) database. A global triple network including RNA-binding protein, mRNA, and lncRNAs was constructed based on the data from starBase. Then, we extracted an insulin resistance-associated lncRNA-mRNA network (IRLMN) by integrating the data from starBase and GEO. We also performed a weighted gene co-expression network analysis (WGCNA) on the differentially expressed genes between the women with and without PCOS, to identify hub lncRNAs. Additionally, the findings of key lncRNAs were examined in an independent GEO dataset. The expression level of in ovarian granulosa cells was increased in patients with PCOS compared with that in control women. Levels were also increased in PCOS patients with higher BMI, hyperinsulinemia, and higher HOMA-IR values. As a result, was identified as a hub lncRNA based on IRLMN and WGCNA and was highly expressed in ovarian granulosa cells, skeletal muscle, and subcutaneous and omental adipose tissues of patients with insulin resistance. This study showed the differences between lncRNA and mRNA profiles from healthy women and women with PCOS and insulin resistance. Here, we demonstrated that RP11-151A6.4 might play a vital role in insulin resistance, androgen excess, and adipose dysfunction in patients with PCOS. Further study concerning RP11-151A6.4 could elucidate the underlying mechanisms of insulin resistance.
Peripheral Biomarkers in Schizophrenia: A Meta-Analysis of Microarray Gene Expression Datasets.
Piras Ignazio S,Manchia Mirko,Huentelman Matthew J,Pinna Federica,Zai Clement C,Kennedy James L,Carpiniello Bernardo
The international journal of neuropsychopharmacology
BACKGROUND:Schizophrenia is a severe psychiatric disorder with a complex pathophysiology. Given its prevalence, high risk of mortality, early onset, and high levels of disability, researchers have attempted to develop early detection strategies for facilitating timely pharmacological and/or nonpharmacological interventions. Here, we performed a meta-analysis of publicly available gene expression datasets in peripheral tissues in schizophrenia and healthy controls to detect consistent patterns of illness-associated gene expression. We also tested whether our earlier finding of a downregulation of NPTX2 expression in the brain of schizophrenia patients replicated in peripheral tissues. METHODS:We conducted a systematic search in the Gene Expression Omnibus repository (https://www.ncbi.nlm.nih.gov/gds/) and identified 3 datasets matching our inclusion criteria: GSE62333, GSE18312, and GSE27383. After quality controls, the total sample size was: schizophrenia (n = 71) and healthy controls (n = 57) (schizophrenia range: n = 12-40; healthy controls range: n = 8-29). RESULTS:The results of the meta-analysis conducted with the GeneMeta package revealed 2 genes with a false discovery rate < 0.05: atlastin GTPase 3 (ATL3) (upregulated) and arachidonate 15-lipoxygenase, type B (ALOX15B) (downregulated). The result for ATL3 was confirmed using the weighted Z test method, whereas we found a suggestive signal for ALOX15B (false discovery rate < 0.10). CONCLUSIONS:These data point to alterations of peripheral expression of ATL3 in schizophrenia, but did not confirm the significant association signal found for NPTX2 in postmortem brain samples. These findings await replication in newly recruited schizophrenia samples as well as complementary analysis of their encoded peptides in blood.
Pattern of gene expression in different stages of schizophrenia: Down-regulation of NPTX2 gene revealed by a meta-analysis of microarray datasets.
Manchia Mirko,Piras Ignazio S,Huentelman Matthew J,Pinna Federica,Zai Clement C,Kennedy James L,Carpiniello Bernardo
European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
Schizophrenia (SCZ) is a severe psychiatric disorder with a genetic susceptibility. Alterations in neurochemical signaling, as well as changes in brain structure and function, manifest during the course of SCZ and are likely causative of the symptoms shown by affected individuals. However, little is known about the timing of these changes, particularly in the pre-morbid and prodromal phases of SCZ. Here, we performed a gene-based and pathway-based meta-analysis of 5 microarray datasets from human induced pluripotent stem cells (hiPSCs)-derived neurons and post-mortem brain tissue from SCZ and healthy controls (HC), with the underlying assumption they might represent the neurobiological make-up of SCZ in the pre-morbid and chronic stages of illness, respectively. Thus, we identified 1 microarray expression profiling dataset of hiPSCs-derived neurons (GSE25673) and performed a systematic search of microarray expression profiling datasets from SCZ post-mortem brain publicly available on the Gene Expression Omnibus (GEO) repository. We selected 4 different SCZ post-mortem brain microarray expression profiling datasets (GSE17612, GSE21935, GSE12649, and GSE21338) according to specific inclusion and exclusion criteria. We downloaded raw data and performed quality controls, differential expression analysis, and gene-based, as well as pathway-based meta-analysis. Neuronal pentraxin 2 (NPTX2) gene was consistently down-regulated across all datasets, with highly significant association in the meta-analysis (FDR<1.0E-04). These results highlight the heuristic value of microarray meta-analysis and suggest a role of NPTX2 as a disease biomarker, provided that it achieves biological validation in future studies examining whether this down-regulation has predictive value with respect to the developmental trajectory of SCZ.
Overexpression of TIM-3 in Macrophages Aggravates Pathogenesis of Pulmonary Fibrosis in Mice.
Wang Yu,Kuai Qiyuan,Gao Fenghua,Wang Yanbing,He Min,Zhou Hong,Han Gencheng,Jiang Xingwei,Ren Suping,Yu Qun
American journal of respiratory cell and molecular biology
Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disorder and lacks effective treatments because of unclear mechanisms. Aberrant function of alveolar macrophages is directly linked to pulmonary fibrosis. Here, we show TIM-3 (T-cell immunoglobulin domain and mucin domain-3), a key regulator of macrophage function, aggravates pulmonary fibrosis. TIM-3 mRNA of patients with IPF was analyzed based on the Gene Expression Omnibus and Array Express databases. Lung pathology and profibrotic molecules were assessed in a bleomycin (BLM)-induced pulmonary fibrosis model using wild-type (WT) and TIM-3 transgenic (TIM-3-TG) mice. Macrophage cells, RAW264.7, were then applied to investigate the effect of macrophage TIM-3 under BLM exposure . Macrophage depletion and adoptive-transfer experiments were finally performed to examine lung morphology and profibrotic molecules. TIM-3 expression was increased both in patients with IPF and in our BLM-induced mouse model. TIM-3-TG mice developed more serious pathological changes in lung tissue and higher expressions of TGF-β1 (transforming growth factor-β1) and IL-10 than WT mice. After BLM treatment, TGF-β1 and IL-10 expression was significantly decreased in RAW264.7 cells after TIM-3 knock-out, whereas it was increased in TIM-3-TG peritoneal macrophages. The scores of pulmonary fibrosis in WT and TIM-3-TG mice were significantly reduced, and there was no difference between them after macrophage depletion. Furthermore, WT mice receiving adoptive macrophages from TIM-3-TG mice also had more serious lung fibrosis and increased expression of TGF-β1 and IL-10 than those receiving macrophages from WT mice. Our findings revealed that overexpressed TIM-3 in alveolar macrophages aggravated pulmonary fibrosis.
Novel Therapeutics Identification for Fibrosis in Renal Allograft Using Integrative Informatics Approach.
Li Li,Greene Ilana,Readhead Benjamin,Menon Madhav C,Kidd Brian A,Uzilov Andrew V,Wei Chengguo,Philippe Nimrod,Schroppel Bernd,He John Cijiang,Chen Rong,Dudley Joel T,Murphy Barbara
Chronic allograft damage, defined by interstitial fibrosis and tubular atrophy (IF/TA), is a leading cause of allograft failure. Few effective therapeutic options are available to prevent the progression of IF/TA. We applied a meta-analysis approach on IF/TA molecular datasets in Gene Expression Omnibus to identify a robust 85-gene signature, which was used for computational drug repurposing analysis. Among the top ranked compounds predicted to be therapeutic for IF/TA were azathioprine, a drug to prevent acute rejection in renal transplantation, and kaempferol and esculetin, two drugs not previously described to have efficacy for IF/TA. We experimentally validated the anti-fibrosis effects of kaempferol and esculetin using renal tubular cells in vitro and in vivo in a mouse Unilateral Ureteric Obstruction (UUO) model. Kaempferol significantly attenuated TGF-β1-mediated profibrotic pathways in vitro and in vivo, while esculetin significantly inhibited Wnt/β-catenin pathway in vitro and in vivo. Histology confirmed significantly abrogated fibrosis by kaempferol and esculetin in vivo. We developed an integrative computational framework to identify kaempferol and esculetin as putatively novel therapies for IF/TA and provided experimental evidence for their therapeutic activities in vitro and in vivo using preclinical models. The findings suggest that both drugs might serve as therapeutic options for IF/TA.
Novel blood-based microRNA biomarker panel for early diagnosis of chronic pancreatitis.
Xin Lei,Gao Jun,Wang Dan,Lin Jin-Huan,Liao Zhuan,Ji Jun-Tao,Du Ting-Ting,Jiang Fei,Hu Liang-Hao,Li Zhao-Shen
Chronic pancreatitis (CP) is an inflammatory disease characterized by progressive fibrosis of pancreas. Early diagnosis will improve the prognosis of patients. This study aimed to obtain serum miRNA biomarkers for early diagnosis of CP. In the current study, we analyzed the differentially expressed miRNAs (DEmiRs) of CP patients from Gene Expression Omnibus (GEO), and the DEmiRs in plasma of early CP patients (n = 10) from clinic by miRNA microarrays. Expression levels of DEmiRs were further tested in clinical samples including early CP patients (n = 20), late CP patients (n = 20) and healthy controls (n = 18). The primary endpoints were area under curve (AUC) and expression levels of DEmiRs. Four DEmiRs (hsa-miR-320a-d) were obtained from GEO CP, meanwhile two (hsa-miR-221 and hsa-miR-130a) were identified as distinct biomarkers of early CP by miRNA microarrays. When applied on clinical serum samples, hsa-miR-320a-d were accurate in predicting late CP, while hsa-miR-221 and hsa-miR-130a were accurate in predicting early CP with AUC of 100.0% and 87.5%. Our study indicates that miRNA expression profile is different in early and late CP. Hsa-miR-221 and hsa-miR-130a are biomarkers of early CP, and the panel of the above 6 serum miRNAs has the potential to be applied clinically for early diagnosis of CP.
Multitranscriptome analyses reveal prioritized genes specifically associated with liver fibrosis progression independent of etiology.
Chen Wei,Wu Xiaoning,Yan Xuzhen,Xu Anjian,Yang Aiting,You Hong
American journal of physiology. Gastrointestinal and liver physiology
Elimination or suppression of causative factors can raise the possibility of liver fibrosis regression. However, different injurious stimuli will give fibrosis from somewhat different etiologies, which, in turn, may hamper the discovery of liver fibrosis-specific therapeutic drugs. Therefore, the analogical cellular and molecular events shared by various etiology-evoked liver fibrosis should be clarified. Our present study systematically integrated five publicly available transcriptomic data sets regarding liver fibrosis with different etiologies from the Gene Expression Omnibus database and performed a series of bioinformatics analyses and experimental verifications. A total of 111 significantly upregulated and 16 downregulated genes were identified specific to liver fibrosis independent of any etiology. These genes were predominately enriched in some Kyoto Encyclopedia of Genes and Genomes pathways, including the "PI3K-AKT signaling pathway," "Focal adhesion," and "ECM-receptor interaction." Subsequently, five prioritized liver fibrosis-specific genes, including COL4A2, THBS2, ITGAV, LAMB1, and PDGFRA, were screened. These genes were positively associated with each other and liver fibrosis progression. In addition, they could robustly separate all stages of samples in both training and validation data sets with diverse etiologies when they were regarded as observed variables applied to principal component analysis plots. Expressions of all five genes were confirmed in activated primary mouse hepatic stellate cells (HSCs) and transforming growth factor β1-treated LX-2 cells. Moreover, THBS2 protein was enhanced in liver fibrosis rodent models, which could promote HSC activation and proliferation and facilitate NOTCH1/JAG1 expression in HSCs. Overall, our current study may provide potential targets for liver fibrosis therapy and aid to a deeper understanding of the molecular underpinnings of liver fibrosis. Prioritized liver fibrosis-specific genes THBS2, COL4A2, ITGAV, LAMB1, and PDGFRA were identified and significantly associated with liver fibrosis progression and could be combined to discriminate liver fibrosis stages regardless of any etiology. Among the identified prioritized liver fibrosis-specific targets, THBS2 protein was confirmed to be enhanced in liver fibrosis rodent models, which could promote hepatic stellate cell (HSC) activation and proliferation and facilitate NOTCH1/JAG1 expression in HSCs.
Multiple-microarray analysis for identification of hub genes involved in tubulointerstial injury in diabetic nephropathy.
Zeng Mengru,Liu Jialu,Yang Wenxia,Zhang Shumin,Liu Fuyou,Dong Zheng,Peng Youming,Sun Lin,Xiao Li
Journal of cellular physiology
Diabetic nephropathy (DN) is a primary cause of renal failure. However, studies providing renal gene expression profiles of diabetic tubulointerstitial injury are scarce and its molecular mechanisms still await clarification. To identify vital genes involved in the diabetic tubulointerstitial injury, three microarray data sets from gene expression omnibus (GEO) were downloaded. A total of 127 differentially expressed genes (DEGs) were identified by limma package. Gene set enrichment analysis (GSEA) plots showed that sister chromatid cohesion was the most significant enriched gene set positively correlated with the DN group while retinoid X receptor binding was the most significant enriched gene set positively correlated with the control group. Enriched Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of DEGs mostly included extracellular matrix organization, extracellular space, extracellular matrix structural constituent, and Staphylococcus aureus infection. Twenty hub genes from three significant modules were ascertained by Cytoscape. Correlation analysis and subgroup analysis between hub genes and clinical features of DN showed that ALB, ANXA1, APOH, C3, CCL19, COL1A2, COL3A1, COL4A1, COL6A3, CXCL6, DCN, EGF, HRG, KNG1, LUM, SERPINA3, SPARC, SRGN, and TIMP1 may involve in diabetic tubulointerstitial injury. ConnectivityMap analysis indicated the most significant three compounds are 5182598, thapsigargin and 5224221. In conclusion, this study may provide new insights into the molecular mechanisms underlying diabetic tubulointerstitial injury as well as potential targets for diagnosis and therapeutics of DN.
Molecular Networks of Involved in Degradation of Lignocellulosic Biomass Revealed from Metadata Analysis of Open Access Gene Expression Data.
Kameshwar Ayyappa Kumar Sista,Qin Wensheng
International journal of biological sciences
To understand the common gene expression patterns employed by during lignocellulose degradation, we have retrieved genome wide transcriptome datasets from NCBI GEO database and analyzed using customized analysis pipeline. We have retrieved the top differentially expressed genes and compared the common significant genes among two different growth conditions. Genes encoding for cellulolytic (GH1, GH3, GH5, GH12, GH16, GH45) and hemicellulolytic (GH10, GH27, GH31, GH35, GH47, GH51, GH55, GH78, GH95) glycoside hydrolase classes were commonly up regulated among all the datasets. Fenton's reaction enzymes (iron homeostasis, reduction, hydrogen peroxide generation) were significantly expressed among all the datasets under lignocellulolytic conditions. Due to the evolutionary loss of genes coding for various lignocellulolytic enzymes (including several cellulases), employs hemicellulolytic glycoside hydrolases and Fenton's reactions for the rapid depolymerization of plant cell wall components. Different classes of enzymes involved in aromatic compound degradation, stress responsive and detoxification mechanisms (cytochrome P450 monoxygenases) were found highly expressed in complex plant biomass substrates. We have reported the genome wide expression patterns of genes coding for information, storage and processing (KOG), tentative and predicted molecular networks involved in cellulose, hemicellulose degradation and list of significant protein-ID's commonly expressed among different lignocellulolytic growth conditions.
microRNA profile datasets of murine macrophages infected with different strains of Leptospira spp.
Garcia Leandro E,Junior Erivelto C A,Bragato Jaqueline P,Melo Larissa M,Lima Valéria F M,Peiró Juliana R,Arnold Daniel R,Marinho Márcia,Lopes Flavia L
MicroRNAs play an important role in the regulation of immune responses. The influence of epigenetic mechanisms, particularly RNA-mediated post-transcriptional regulation of host immune responses has been proven vital following infections by different pathogens, and bacteria can modulated host miRNAs. Global miRNA expression analysis from macrophages infected in vitro with different strains of Leptospira spp was performed using miRNA 4.1 microarray strips. Leptospirosis is a bacterial zoonosis of global importance, responsible for significant morbidity and mortality worldwide. Despite considerable advances, much is yet to be discovered about disease pathogenicity, particularly in regards to host-pathogen interactions. We present here a high-quality dataset examining the microtranscriptome of murine macrophages J774A.1 following 8h of infection with virulent, attenuated and saprophyte strains of Leptospira. Metadata files were submitted to the Gene Expression Omnibus (GEO) repository.
Metadata Analysis of Gene Expression Data Identified Common CAZymes Encoding Gene Expression Profiles Involved in Cellulose and Hemicellulose Degradation.
Kameshwar Ayyappa Kumar Sista,Qin Wensheng
International journal of biological sciences
In literature, extensive studies have been conducted on popular wood degrading white rot fungus, about its lignin degrading mechanisms compared to the cellulose and hemicellulose degrading abilities. This study delineates cellulose and hemicellulose degrading mechanisms through large scale metadata analysis of gene expression data (retrieved from NCBI GEO) to understand the common expression patterns of differentially expressed genes when cultured on different growth substrates. Genes encoding glycoside hydrolase classes commonly expressed during breakdown of cellulose such as GH-5,6,7,9,44,45,48 and hemicellulose are GH-2,8,10,11,26,30,43,47 were found to be highly expressed among varied growth conditions including simple customized and complex natural plant biomass growth mediums. Genes encoding carbohydrate esterase class enzymes CE (1,4,8,9,15,16) polysaccharide lyase class enzymes PL-8 and PL-14, and glycosyl transferases classes GT (1,2,4,8,15,20,35,39,48) were differentially expressed in natural plant biomass growth mediums. Based on these results, on natural plant biomass substrates was found to express lignin and hemicellulose degrading enzymes more than cellulolytic enzymes except GH-61 (LPMO) class enzymes, in early stages. It was observed that the fate of transcriptome is significantly affected by the wood substrate provided. We believe, the gene expression findings in this study plays crucial role in developing genetically efficient microbe with effective cellulose and hemicellulose degradation abilities.
Key genes and functional coexpression modules involved in the pathogenesis of systemic lupus erythematosus.
Yan Shushan,Wang Weijie,Gao Guohong,Cheng Min,Wang Xiaodong,Wang Zengyan,Ma Xiufen,Chai Chunxiang,Xu Donghua
Journal of cellular physiology
We performed a systematic review of genome-wide gene expression datasets to identify key genes and functional modules involved in the pathogenesis of systemic lupus erythematosus (SLE) at a systems level. Genome-wide gene expression datasets involving SLE patients were searched in Gene Expression Omnibus and ArrayExpress databases. Robust rank aggregation (RRA) analysis was used to integrate those public datasets and identify key genes associated with SLE. The weighted gene coexpression network analysis (WGCNA) was adapted to identify functional modules involved in SLE pathogenesis, and the gene ontology enrichment analysis was utilized to explore their functions. The aberrant expressions of several randomly selected key genes were further validated in SLE patients through quantitative real-time polymerase chain reaction. Fifteen genome-wide gene expression datasets were finally included, which involved a total of 1,778 SLE patients and 408 healthy controls. A large number of significantly upregulated or downregulated genes were identified through RRA analysis, and some of those genes were novel SLE gene signatures and their molecular roles in etiology of SLE remained vague. WGCNA further successfully identified six main functional modules involved in the pathogenesis of SLE. The most important functional module involved in SLE included 182 genes and mainly enriched in biological processes, including defense response to virus, interferon signaling pathway, and cytokine-mediated signaling pathway. This study identifies a number of key genes and functional coexpression modules involved in SLE, which provides deepening insights into the molecular mechanism of SLE at a systems level and also provides some promising therapeutic targets.
Integrative Analyses of Genes Associated with Subcutaneous Insulin Resistance.
Pujar Manoj Kumar,Vastrad Basavaraj,Vastrad Chanabasayya
Insulin resistance is present in the majority of patients with non-insulin-dependent diabetes mellitus (NIDDM) and obesity. In this study, we aimed to investigate the key genes and potential molecular mechanism in insulin resistance. Expression profiles of the genes were extracted from the Gene Expression Omnibus (GEO) database. Pathway and Gene Ontology (GO) enrichment analyses were conducted at Enrichr. The protein⁻protein interaction (PPI) network was settled and analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) database constructed by Cytoscape software. Modules were extracted and identified by the PEWCC1 plugin. The microRNAs (miRNAs) and transcription factors (TFs) which control the expression of differentially expressed genes (DEGs) were analyzed using the NetworkAnalyst algorithm. A database (GSE73108) was downloaded from the GEO databases. Our results identified 873 DEGs (435 up-regulated and 438 down-regulated) genetically associated with insulin resistance. The pathways which were enriched were pathways in complement and coagulation cascades and complement activation for up-regulated DEGs, while biosynthesis of amino acids and the Notch signaling pathway were among the down-regulated DEGs. Showing GO enrichment were cardiac muscle cell⁻cardiac muscle cell adhesion and microvillus membrane for up-regulated DEGs and negative regulation of osteoblast differentiation and dendrites for down-regulated DEGs. Subsequently, myosin VB (MYO5B), discs, large homolog 2(DLG2), axin 2 (AXIN2), protein tyrosine kinase 7 (PTK7), Notch homolog 1 (NOTCH1), androgen receptor (AR), cyclin D1 (CCND1) and Rho family GTPase 3 (RND3) were diagnosed as the top hub genes in the up- and down-regulated PPI network and modules. In addition, GATA binding protein 6 (GATA6) , ectonucleotide pyrophosphatase/phosphodiesterase 5 (ENPP5), cyclin D1 (CCND1) and tubulin, beta 2A (TUBB2A) were diagnosed as the top hub genes in the up- and down-regulated target gene⁻miRNA network, while tubulin, beta 2A (TUBB2A), olfactomedin-like 1 (OLFML1), prostate adrogen-regulated mucin-like protein 1 (PARM1) and aldehyde dehydrogenase 4 family, member A1 (ALDH4A1)were diagnosed as the top hub genes in the up- and down-regulated target gene⁻TF network. The current study based on the GEO database provides a novel understanding regarding the mechanism of insulin resistance and may provide novel therapeutic targets.
Integrated DNA methylation and gene expression analysis in the pathogenesis of coronary artery disease.
Miao Liu,Yin Rui-Xing,Zhang Qing-Hui,Hu Xi-Jiang,Huang Feng,Chen Wu-Xian,Cao Xiao-Li,Wu Jin-Zhen
To evaluate DNA methylation sites and gene expression associated with coronary artery disease (CAD) and the possible pathological mechanism involved, we performed (1) genome-wide DNA methylation and mRNA expression profiling in peripheral blood datasets from the Gene Expression Omnibus repository of CAD samples and controls; (2) functional enrichment analysis and differential methylation gene regulatory network construction; (3) validation tests of 11 differential methylation positions of interest and the corresponding gene expression; and (4) correlation analysis for DNA methylation and mRNA expression data. A total of 669 differentially expressed mRNAs were matched to differentially methylated genes. After disease ontology, Kyoto Encyclopedia of Genes and Genomes pathway, gene ontology, protein-protein interaction and network construction and module analyses, 11 differentially methylated positions (DMPs) corresponding to 11 unique genes were observed: - cg26949694, - cg24381155, - cg02223351, - cg11267527, - cg27637738, - cg13104385, - cg20545410, - cg25613180, - cg00559992, - cg27178677 and - cg09247619. After validation tests of 11 DMPs of interest and the corresponding gene expression, we found that was less hypomethylated in the CAD group, whereas the relative expression of , and was lower in CAD samples, and and methylation was negatively correlated with their expression. This study identified the correlation between DNA methylation and gene expression and highlighted the importance of in CAD pathogenesis.
Integrated bioinformatics analysis identifies microRNA-376a-3p as a new microRNA biomarker in patient with coronary artery disease.
Du Lei,Xu Zhimin,Wang Xuhui,Liu Fang
American journal of translational research
INTRODUCTION:Coronary artery disease (CAD) is a major global health problem with high incidence and mortality. Despite many advances in treatment, the prognosis of patients with CAD still remains poor. Therefore, this study aimed to identify potential biomarkers and targets associated with the progression of CAD. METHODS:Two gene expression profile datasets (GSE20681 and GSE12288), and two microRNA (miRNA) expression profile datasets (GSE59421 and GSE105449) were downloaded from the Gene Expression Omnibus (GEO) database; R language was used to screen out the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs), respectively. In addition, five online bioinformatics tools (miRWalk et al.) were used to identify the target genes of DEMs, and miRNA-gene network was constructed using Cytoscape software. Moreover, CCK-8, flow cytometry assays were used to detect the cell proliferation and apoptosis in human umbilical vein endothelial cells (HUVECs). Meanwhile, the dual luciferase reporter system assay was used to explore the interaction of miR-376a-3p and NRIP1 in HUVECs. RESULTS:In the present study, 150 common DEGs and 5 common DEMs were screened using a Venn diagram in R language. First, a total of 6812 target genes were identified from the overlapping DEMs. Second, 26 overlapping dysregulated genes from 150 overlapping DEGs and 6812 miRNA target genes were identified. Meanwhile, 43 miRNA-gene regulatory pairs were obtained between the 5 common DEMs and 26 dysregulated genes. Downregulation of miR-376a-3p significantly inhibited the proliferation of HUVECs via inducing apoptosis. Moreover, overexpression of miR-376a-3p markedly inhibited the growth of HUVECs via downregulating NRIP1. CONCLUSION:In this study, miR-376a-3p-NRIP1 pair might involve in the progression of CAD, implying that miR-376a-3p may be a therapeutic target for the treatment of CAD.
Integrated analysis of the proteome and transcriptome in a MCAO mouse model revealed the molecular landscape during stroke progression.
Li Litao,Dong Lipeng,Xiao Zhen,He Weiliang,Zhao Jingru,Pan Henan,Chu Bao,Cheng Jinming,Wang Hebo
Journal of advanced research
Strokes usually results in long-term disability and death, and they occur worldwide. Recently, increased research on both on the physiopathological mechanisms and the transcriptome during stroke progression, have highlighted the relationship between stroke progression and immunity, with a special focus on inflammation. Here, we applied proteome analysis to a middle carotid artery occlusion (MCAO) mouse model at 0 h, 6 h, 12 h and 24 h, in which proteome profiling was performed with 23 samples, and 41 differentially expressed proteins (DEPs) were identified. Bioinformatics studies on our data revealed the importance of the immune response and particularly identified the inflammatory response, cytokine- cytokine receptor interactions, the innate immune response and reactive oxygen species (ROS) during stroke progression. In addition, we compared our data with multiple gene expression omnibus (GEO) datasets with and without a time series, in which similar pathways were identified, and three proteins, C3, Apoa4 and S100a9, were highlighted as markers or drug targets for stroke; these three proteins were significantly upregulated in the MCAO model, both in our proteomic data and in the GEO database.
Integrated Analysis of Multiple Microarray Studies to Identify Novel Gene Signatures in Non-alcoholic Fatty Liver Disease.
Jia Xi,Zhai Tianyu
Frontiers in endocrinology
Non-alcoholic fatty liver disease (NAFLD) is a well-known cause of liver dysfunction and has become a common chronic liver disease in many countries. However, the intrinsic molecular mechanisms underlying the pathogenesis of NAFLD have not yet been fully elucidated. We obtained the gene expression datasets of NAFLD through the Gene Expression Omnibus (GEO) database. Subsequently, robust rank aggregation (RRA) method was used to identify differentially expressed genes (DEGs) between NAFLD patients and controls. Gene functional annotation and PPI network analysis were performed to explore the potential function of the DEGs. Finally, we used a sequencing dataset GSE126848 to validate our results. In this study, GSE48452, GSE66676, GSE72756, GSE63067, GSE89632, and GSE107231 were included, including 125 NAFLD patients and 116 control patients. The RRA integrated analysis determined 96 significant DEGs (50 up-regulated and 46 down-regulated) and the most significant gene aberrantly expressed in NAFLD was ENO3 (-value = 7.17E-05), followed by CYP7A1 (-value = 9.04E-05), and P4HA1 (-value = 1.67E-04). Carboxylic acid metabolic process (GO:0019752; -value = 1.39E-03) was the most significantly enriched for biological process in GO (gene ontology) analysis. KEGG pathway enrichment analysis showed that steroid hormone biosynthesis (hsa00140; -value = 6.68E-03) and PPAR signaling pathway (hsa03320; -value = 9.95E-03) were significantly enriched. Based on the results of the PPI and the results of the RRA, we finally defined the four most critical genes as the hub genes, including ENO3, CYP7A1, P4HA1, and CYP1A1. Our integrated analysis identified novel gene signatures and will contribute to the understanding of comprehensive molecular changes in NAFLD.
Integrated analysis of gene expression profiles identifies transcription factors potentially involved in psoriasis pathogenesis.
Zeng Fanfan,Liu Hongbo,Lu Di,Liu Qianqian,Chen Huoying,Zheng Fang
Journal of cellular biochemistry
Psoriasis is a common inflammatory skin disease mediated by cells and molecules in both the innate and adaptive immune systems. Recently, gene expression profile analysis revealed a large set of immune-related differentially expressed genes (DEGs) in psoriasis. However, the associations between these DEGs and their transcriptional regulation mechanisms have not been completely elucidated. In this study, several psoriasis Gene Expression Omnibus data sets were systematically analyzed using bioinformatics tools to uncover important transcription factors (TFs) that regulate the expression of immune-related DEGs and further enhance our understanding of psoriasis pathogenesis. Common DEGs encoding chemokines, cytokines, antimicrobial peptides, and keratins were identified in psoriasis, and extensive correlations existed among these DEGs. Several common TFs that bind the promoters of the DEGs, including the well-known signal transducer and activator of transcription 1 (STAT1), STAT3, and nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) as well as ETS homologous factor (EHF), Fos-like antigen 1 (FOSL1), and Forkhead box C1 (FOXC1), which are rarely studied in psoriasis, were also identified. STAT1, EHF, FOSL1, STAT3, and NFKB1 were positively correlated with these DEGs in psoriasis lesions, whereas FOXC1 was negatively correlated with most DEGs. The decreased expression of the DEGs was accompanied by the downregulation of STAT1, EHF, FOSL1, STAT3, and NFKB1 and the upregulation of FOXC1 upon blocking interleukin 17 (IL-17) or tumor necrosis factor α signaling in psoriasis. Additionally, the downregulation of IL37 in psoriasis was negatively correlated with STAT1 and CXCL10, which are associated with Th1 responses. These results suggest that TFs play an important role in the pathogenesis of psoriasis, and interfering with the activity of key TFs may be a promising therapeutic strategy for psoriasis.
Integrated Analysis and Identification of Novel Biomarkers in Parkinson's Disease.
Chi Jieshan,Xie Qizhi,Jia Jingjing,Liu Xiaoma,Sun Jingjing,Deng Yuanfei,Yi Li
Frontiers in aging neuroscience
Parkinson's disease (PD) is a quite common neurodegenerative disorder with a prevalence of approximately 1:800-1,000 in subjects over 60 years old. The aim of our study was to determine the candidate target genes in PD through meta-analysis of multiple gene expression arrays datasets and to further combine mRNA and miRNA expression analyses to identify more convincing biological targets and their regulatory factors. Six included datasets were obtained from the Gene Expression Omnibus database by systematical search, including five mRNA datasets (150 substantia nigra samples in total) and one miRNA dataset containing 32 peripheral blood samples. A chip meta-analysis of five microarray data was conducted by using the metaDE package and 94 differentially expressed (DE) mRNAs were comprehensively obtained. And 19 deregulated DE miRNAs were obtained through the analysis of one miRNAs dataset by Qlucore Omics Explorer software. An interaction network formed by DE mRNAs, DE miRNAs, and important pathways was discovered after we analyzed the functional enrichment, protein-protein interactions, and miRNA targetome prediction analysis. In conclusion, this study suggested that five significantly downregulated mRNAs (MAPK8, CDC42, NDUFS1, COX4I1, and SDHC) and three significantly downregulated miRNAs (miR-126-5p, miR-19-3p, and miR-29a-3p) were potentially useful diagnostic markers in clinic, and lipid metabolism (especially non-alcoholic fatty liver disease pathway) and mitochondrial dysregulation may be the keys to biochemically detectable molecular defects. However, the role of these new biomarkers and molecular mechanisms in PD requires further experiments and and further clinical evidence.
Immunoglobulin M, a novel molecule of myocardial cells of mice.
Zhu Zhu,Zhang Meng,Shao Wenwei,Wang Pingzhang,Gong Xiaoting,Ma Junfan,Qiu Xiaoyan,Wang Bin
The international journal of biochemistry & cell biology
BACKGROUND:Immunoglobulins(Igs)play an important role in host defence and were initially thought to be expressed solely by B cells. However, recent data suggest that Igs are also expressed in other lineages. Recently, Ig transcripts were detected in cardiomyocytes, but whether the functional Ig protein is expressed by cardiomyocytes has not been thoroughly elucidated. METHODS:Gene Expression Omnibus (GEO) microarray database analysis was used to analyse IgM heavy chain expression in the myocardium of mice. Immunohistochemistry (IHC), ELISA and Western blot were used to identify IgM in cardiomyocytes of both Balb/c mice and μMT mice (B cell-deficient mice), as well as in cultured cardiomyocytes of neonatal mice and in the myocardial cell line HL-1. Moreover, RT-PCR and cDNA sequencing were used to determine the VDJ rearrangement of the IgM heavy chain. RESULTS:In this study, we first analysed transcription of the IgM heavy chain in heart tissue in mice by mining the GEO database, and we observed that IgM heavy chain transcripts were expressed in heart tissues. Subsequently, IgM was found to be expressed in cardiomyocytes in mice; the IgM was primarily localized on the cell membranes and intercalated discs of murine heart cells and in the cytoplasm and cell membranes of isolated cardiomyocytes and HL-1. Importantly, the functional IgM heavy chain transcripts exhibit a unique VDJ rearrangement pattern. Furthermore, IgM can be secreted and deposited in the extracellular space of the myocardium under ischaemic/hypoxic conditions. CONCLUSIONS:Our data indicate for the first time that IgM is expressed by cardiomyocytes in mice and suggest that its physiological function warrants further investigation.
Identifying Key Genes and Functionally Enriched Pathways in Sjögren's Syndrome by Weighted Gene Co-Expression Network Analysis.
Yao Qiuming,Song Zhenyu,Wang Bin,Qin Qiu,Zhang Jin-An
Frontiers in genetics
Sjögren's syndrome (SS) is an autoimmune disease characterized by dry mouth and eyes. To date, the exact molecular mechanisms of its etiology are still largely unknown. The aim of this study was to identify SS related key genes and functionally enriched pathways using the weighted gene co-expression network analysis (WGCNA). We downloaded the microarray data of 190 SS patients and 32 controls from Gene Expression Omnibus (GEO). Gene network was constructed and genes were classified into different modules using WGCNA. In addition, for the hub genes in the most related module to SS, gene ontology analysis was applied. The expression profile and diagnostic capacity (ROC curve) of interested hub genes were verified using a dataset from the GEO. Moreover, gene set enrichment analysis (GSEA) was also performed. A total of 1483 differentially expressed genes were filtered. Weighted gene coexpression network was constructed and genes were classified into 17 modules. Among them, the turquoise module was most closely associated with SS, which contained 278 genes. These genes were significantly enriched in 10 Gene Ontology terms, such as response to virus, immune response, defense response, response to cytokine stimulus, and the inflammatory response. A total of 19 hub genes (GBP1, PARP9, EPSTI1, LOC400759, STAT1, STAT2, IFIH1, EIF2AK2, TDRD7, IFI44, PARP12, FLJ20035, PARP14, ISGF3G, XAF1, RSAD2,LY6E, IFI44L, and DDX58) were identified. The expression levels of the five interested genes including EIF2AK2, GBP1, PARP12, PARP14, and TDRD7 were also confirmed. ROC curve analysis determined that the above five genes' expression can distinguish SS from controls (the area under the curve is all greater than 0.7). GSEA suggests that the SS samples with highly expressed EIF2AK2 or TDRD7 genes are correlated with inflammatory response, interferon α response, and interferon γ response. The present study applied WGCNA to generate a holistic view of SS and provide a basis for the identification of potential pathways and hub genes that may be involved in the development of SS.
Identifying a combined biomarker for bisphosphonate-related osteonecrosis of the jaw.
Kim Ki-Yeol,Zhang Xianglan,Cha In-Ho
Clinical implant dentistry and related research
BACKGROUND:For this study, the aim was to identify combined biomarkers associated with bisphosphonate-related osteonecrosis of the jaw (BRONJ). MATERIALS AND METHODS:Microarray data for GSE7116 were downloaded from the Gene Expression Omnibus database, which contains 26 samples, including without ONJ, and 5 healthy volunteers. The combined biomarkers were identified using principal component analysis, and the pathway enrichment analyses were performed using the DAVID online tool. RESULTS:Two hundred differently expressed genes between groups were detected according to the significances. From functional annotation, Y-box binding protein 1 and heterogeneous nuclear ribonucleoprotein C were found to be included in the most significant 10 pathways. Ten combined gene sets were identified that were effective in classifying multiple myeloma (MM) with ONJ and MM without ONJ. CONCLUSION:Identifying combined gene expression profiles is expected to contribute to more personalized management of BRONJ and to improve existing therapies, and it will be helpful in finding new therapies by identifying more predictive biomarkers.
Identification of Transcriptional Metabolic Dysregulation in Subtypes of Pituitary Adenoma by Integrated Bioinformatics Analysis.
Hu Jintao,Yin Huachun,Li Bo,Yang Hui
Diabetes, metabolic syndrome and obesity : targets and therapy
Background:Pituitary adenoma (PA) is a prevalent intracranial tumor. Metabolites differ between pituitary tumor and healthy tissues or among different tumor subtypes. However, the transcriptional changes in metabolic enzymes, which are usually seemed as targets for metabolic therapy, remain unidentified. Methods:Using microarray data for 160 samples from the Gene Expression Omnibus database, across the four most common tumor subtypes, we present the integrated identification of differentially expressed genes (DEGs) between tumors and controls. Results:Subtype-specific DEGs revealed 1081 prolactin tumor-specific DEGs, 437 nonfunctioning tumor-specific DEGs, and 217 common DEGs among the four subtypes. Functional enrichment showed that a lot of biological functions related to metabolism had changed. Twenty-one prolactin and twenty-three nonfunctioning tumor-specific metabolic-related DEGs are mainly involved in fatty acid and nucleotide metabolism, redox reaction, and gluconeogenesis. Eighteen metabolic-related DEGs enriched in the metabolism of xenobiotics by the cytochrome P450 pathway, sulfur metabolism, retinoid metabolism, and glucose homeostasis were abnormal in all subtypes of PA. Conclusion:Based on a comprehensive bioinformatics analysis of the available PA-related transcriptomics data, we identified specific DEGs related to metabolism, and some of them might be new attractive therapeutic targets. Especially, PDK4 and PCK1 might be new attractive biomarkers and therapeutic targets.
Identification of the molecular subgroups in coronary artery disease by gene expression profiles.
Peng Xiao-Yan,Wang Yong,Hu Haibo,Zhang Xian-Jin,Li Qi
Journal of cellular physiology
Coronary artery disease (CAD) is the most common type of cardiovascular disease and becomes a leading cause of death worldwide. Aiming to uncover the underlying molecular features for different types of CAD, we classified 352 CAD cases into three subgroups based on gene expression profiles, which were retrieved from the Gene Expression Omnibus database. Also, these subgroups present different expression patterns and clinical characteristics. To uncover the transcriptomic differences between the subgroups, weighted gene co-expression analysis (WGCNA) was used and identified six subgroup-specific WGCNA modules. Characterization of the WCGNA modules revealed that lipid metabolism pathways, specifically upregulated in subgroup I, might be an indicator of increased severity. Moreover, subgroup II was considered as an early-stage of CAD because of normal-like gene expression patterns. In contrast, the mammalian target of rapamycin signaling pathway was significantly upregulated in subgroup III. Although subgroups II and III did not have a significant prognostic difference, their intrinsic biological characteristics were highly different, suggesting that the transcriptome classification may represent risk factors of both age and the intrinsic biological characteristics. In conclusion, the transcriptome classification of CAD cases revealed that cases from different subgroups may have their unique gene expression patterns, indicating that patients in each subgroup should receive more personalized treatment.
Identification of the Biomarkers and Pathological Process of Osteoarthritis: Weighted Gene Co-expression Network Analysis.
Gu Hui-Yun,Yang Min,Guo Jia,Zhang Chao,Lin Lu-Lu,Liu Yang,Wei Ren-Xiong
Frontiers in physiology
Osteoarthritis (OA) is a joint disease resulting in high rates of disability and low quality of life. The initial site of OA (bone or cartilage) is uncertain. The aim of the current study was to explore biomarkers and pathological processes in subchondral bone samples. The gene expression profile GSE51588 was downloaded from the Gene Expression Omnibus database. Fifty subchondral bone [knee lateral tibial (LT) and medial tibial (MT)] samples from 40 OA and 10 non-OA subjects were analyzed. After data preprocessing, 5439 genes were obtained for weighted gene co-expression network analysis. Highly correlated genes were divided into 19 modules. The yellow module was found to be highly correlated with OA ( = 0.71, = 1e-08) and the brown module was most associated with the differences between the LT and MT regions ( = 0.77, = 1e-10). Gene ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment indicated that the yellow module was enriched in a variety of components including proteinaceous extracellular matrix and collagen trimers, involved in protein digestion and absorption, axon guidance, ECM-receptor interaction, and the PI3K-Akt signaling pathway. In addition, the brown module suggests that the differences between the early (LT) and end (MT) stage of OA are associated with extracellular processes and lipid metabolism. Finally, 45 hub genes in the yellow module (COL24A1, COL5A2, COL3A1, MMP2, COL6A1, etc.) and 72 hub genes in the brown module (LIPE, LPL, LEP, SLC2A4, FABP4, ADH1B, ALDH4A1, ADIPOQ, etc.) were identified. Hub genes were validated using samples from cartilage (GSE57218). In summary, 45 hub genes and 72 hub genes in two modules are associated with OA. These hub genes could provide new biomarkers and drug targets in OA. Further studies focusing on subchondral bone are required to validate these hub genes and better understand the pathological process of OA.
Identification of significant gene biomarkers of low back pain caused by changes in the osmotic pressure of nucleus pulposus cells.
Zhao Changsong,Quan Xuemin,He Jie,Zhao Rugang,Zhang Yao,Li Xin,Sun Sheng,Ma Rui,Zhang Qiang
The incidence of intervertebral disc (IVD) degeneration disease, caused by changes in the osmotic pressure of nucleus pulposus (NP) cells, increases with age. In general, low back pain is associated with IVD degeneration. However, the mechanism and molecular target of low back pain have not been elucidated, and there are no data suggesting specific biomarkers of low back pain. Therefore, the research aims to identify and verify the significant gene biomarkers of low back pain. The differentially expressed genes (DEGs) were screened in the Gene Expression Omnibus (GEO) database, and the identification and analysis of significant gene biomarkers were also performed with various bioinformatics programs. A total of 120 patients with low back pain were recruited. Before surgery, the degree of pain was measured by the numeric rating scale (NRS), which enables comparison of the pain scores from individuals. After surgery, IVD tissues were obtained, and NP cells were isolated. The NP cells were cultured in two various osmotic media, including iso-osmotic media (293 mOsm/kg HO) to account for the morbid environment of NP cells in IVD degeneration disease and hyper-osmotic media (450 mOsm/kg HO) to account for the normal condition of NP cells in healthy individuals. The relative mRNA expression levels of CCL5, OPRL1, CXCL13, and SST were measured by quantitative real-time PCR in the in vitro analysis of the osmotic pressure experiments. Finally, correlation analysis and a neural network module were employed to explore the linkage between significant gene biomarkers and pain. A total of 371 DEGs were identified, including 128 downregulated genes and 243 upregulated genes. Furthermore, the four genes (CCL5, OPRL1, SST, and CXCL13) were identified as significant gene biomarkers of low back pain (P < 0.001) based on univariate linear regression, and CCL5 (odds ratio, 34.667; P = 0.003) and OPRL1 (odds ratio, 19.875; P < 0.001) were significantly related to low back pain through multivariate logistic regression. The expression of CCL5 and OPRL1 might be correlated with low back pain in patients with IVD degeneration disease caused by changes in the osmotic pressure of NP cells.
Identification of rare variants in novel candidate genes in pulmonary atresia patients by next generation sequencing.
Shi Xin,Zhang Li,Bai Kai,Xie Huilin,Shi Tieliu,Zhang Ruilin,Fu Qihua,Chen Sun,Lu Yanan,Yu Yu,Sun Kun
Computational and structural biotechnology journal
Pulmonary atresia (PA) is a rare congenital heart defect (CHD) with complex manifestations and a high mortality rate. Since the genetic determinants in the pathogenesis of PA remain elusive, a thorough identification of the genetic factors through whole exome sequencing (WES) will provide novel insights into underlying mechanisms of PA. We performed WES data from PA/VSD (n = 60), PA/IVS (n = 20), TOF/PA (n = 20) and 100 healthy controls. Rare variants and novel genes were identified using variant-based association and gene-based burden analysis. Then we explored the expression pattern of our candidate genes in endothelium cell lines, pulmonary artery tissues, and embryonic hearts. 56 rare damage variants of 7 novel candidate genes ( and ) were certified to have function in PA pathogenesis for the first time. In our research, the genetic pattern among PA/VSD, PA/IVS and TOF/PA were different to some degree. Taken together, our findings contribute new insights into the molecular basis of this rare congenital birth defect.
Identification of potential pathogenic genes associated with osteoporosis.
Xia B,Li Y,Zhou J,Tian B,Feng L
Bone & joint research
OBJECTIVES:Osteoporosis is a chronic disease. The aim of this study was to identify key genes in osteoporosis. METHODS:Microarray data sets GSE56815 and GSE56814, comprising 67 osteoporosis blood samples and 62 control blood samples, were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in osteoporosis using Limma package (3.2.1) and Meta-MA packages. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to identify biological functions. Furthermore, the transcriptional regulatory network was established between the top 20 DEGs and transcriptional factors using the UCSC ENCODE Genome Browser. Receiver operating characteristic (ROC) analysis was applied to investigate the diagnostic value of several DEGs. RESULTS:A total of 1320 DEGs were obtained, of which 855 were up-regulated and 465 were down-regulated. These differentially expressed genes were enriched in Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways, mainly associated with gene expression and osteoclast differentiation. In the transcriptional regulatory network, there were 6038 interactions pairs involving 88 transcriptional factors. In addition, the quantitative reverse transcriptase-polymerase chain reaction result validated the expression of several genes (VPS35, FCGR2A, TBCA, HIRA, TYROBP, and JUND). Finally, ROC analyses showed that VPS35, HIRA, PHF20 and NFKB2 had a significant diagnostic value for osteoporosis. CONCLUSION:Genes such as VPS35, FCGR2A, TBCA, HIRA, TYROBP, JUND, PHF20, NFKB2, RPL35A and BICD2 may be considered to be potential pathogenic genes of osteoporosis and may be useful for further study of the mechanisms underlying osteoporosis.: B. Xia, Y. Li, J. Zhou, B. Tian, L. Feng. Identification of potential pathogenic genes associated with osteoporosis. 2017;6:640-648. DOI: 10.1302/2046-3758.612.BJR-2017-0102.R1.
Identification of potential miRNA biomarkers for traumatic osteonecrosis of femoral head.
Liu Guan-Zhi,Chen Chen,Kong Ning,Tian Run,Li Yi-Yang,Li Zhe,Wang Kun-Zheng,Yang Pei
Journal of cellular physiology
Traumatic osteonecrosis of femoral head (TONFH) is a common orthopedic disease caused by physical injury in hip. However, the unclear pathogenesis mechanism of TONFH and lacking of simple noninvasive early diagnosis method cause the necessity of hip replacement for most patients with TONFH. In this study, we aimed to identify circulating microRNAs (miRNAs) by integrated bioinformatics analyses as potential biomarker of TONFH. mRNA expression profiles were downloaded from the Gene Expression Omnibus database. Then we combined two miRNA screen methods: Weighted gene co-expression network analysis and fold change based differentially expressed miRNAs analysis. As a result, we identified 14 key miRNAs as potential biomarkers for TONFH. Besides, 302 target genes of these miRNAs were obtained and the miRNA-mRNA interaction network was constructed. Furthermore, the results of Kyoto Encyclopedia of Gene and Genome pathway analysis, Gene Ontology function analysis, protein-protein interaction (PPI) network analysis and PPI network module analysis showed close correlation between these 14 key miRNAs and TONFH. Then we established receiver operating characteristic curves and identified 6-miRNA signature with highly diagnosis value including miR-93-5p (area under the curve [AUC] = 0.93), miR-1324 (AUC = 0.92), miR-4666a-3p (AUC = 0.92), miR-5011-3p (AUC = 0.92), and miR-320a (AUC = 0.89), miR-185-5p (AUC = 0.89). Finally, the results of quantitative real-time polymerase chain reaction confirmed the significantly higher expression of miR-93-5p and miR-320a in the serum of patients with ONFH. These circulating miRNAs could serve as candidate early diagnosis markers and potential treatment targets of TONFH.
Identification of potential mechanism and hub genes for neuropathic pain by expression-based genome-wide association study.
Gu Yu,Qiu Zhuolin,Cheng Nan,Chen Chaojin,Hei Ziqing,Li Xiang
Journal of cellular biochemistry
Neuropathic pain (NP) is a common pathological pain state with limited effective treatments. This study was designed to identify potential mechanisms and candidate genes using gene expression-based genome-wide association study (eGWAS). All NP-related microarray experiments were obtained from Gene Expression Omnibus and ArrayExpress. Significantly dysregulated genes were identified between experimental and untreated groups, and the number of microarray experiments in which each gene was dysregulated was calculated. Significantly dysregulated genes were ranked according to P values of the chi-square test. Using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes database, we performed functional and pathway enrichment analysis. Protein-protein interaction (PPI) network and module analysis was performed using Cytoscape software. A total of 115 candidate genes were identified from 19 independent microarray experiments by eGWAS based on the Bonferroni threshold ( P < 2.97 × 10 ). Immune and inflammatory responses, and complement and coagulation cascades, were respectively the most enriched biological process and pathways for candidate genes. The hub genes with highest connectivity in PPI network and two modules Ccl2 and Jun, and Ctss application of the eGWAS methodology can identify mechanisms and candidate genes associated with NP. Our results support the validity and prevalence of inflammatory and immune mechanisms across different NP models, and Ccl2, Jun, and Ctss may be the hub genes for NP.
Identification of Potential Key Genes Associated with Adipogenesis through Integrated Analysis of Five Mouse Transcriptome Datasets.
Zhang Song,Wang Li,Li Shijun,Zhang Wenzhen,Ma Xueyao,Cheng Gong,Yang Wucai,Zan Linsen
International journal of molecular sciences
Adipose tissue is the most important energy metabolism and secretion organ, and these functions are conferred during the adipogenesis process. However, the cause and the molecular events underlying adipogenesis are still unclear. In this study, we performed integrated bioinformatics analyses to identify vital genes involved in adipogenesis and reveal potential molecular mechanisms. Five mouse high-throughput expression profile datasets were downloaded from the Gene Expression Omnibus (GEO) database; these datasets contained 24 samples of 3T3-L1 cells during adipogenesis, including 12 undifferentiated samples and 12 differentiated samples. The five datasets were reanalyzed and integrated to select differentially expressed genes (DEGs) during adipogenesis via the robust rank aggregation (RRA) method. Functional annotation of these DEGs and mining of key genes were then performed. We also verified the expression levels of some potential key genes during adipogenesis. A total of 386 consistent DEGs were identified, with 230 upregulated genes and 156 downregulated genes. Gene Ontology (GO) analysis showed that the biological functions of the DEGs primarily included fat cell differentiation, lipid metabolic processes, and cell adhesion. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these DEGs were mainly associated with metabolic pathways, the peroxisome proliferator-activated receptor (PPAR) signaling pathway, regulation of lipolysis in adipocytes, the tumor necrosis factor (TNF) signaling pathway, and the FoxO signaling pathway. The 30 most closely related genes among the DEGs were identified from the protein⁻protein interaction (PPI) network and verified by real-time quantification during 3T3-L1 preadipocyte differentiation. In conclusion, we obtained a list of consistent DEGs during adipogenesis through integrated analysis, which may offer potential targets for the regulation of adipogenesis and treatment of adipose dysfunction.
Identification of novel therapeutic targets for neuropathic pain based on gene expression patterns.
Zhu Di,Liu Kang,Wan Cheng-Liang,Lu Jangnin,Zhao Hong-Xia
Journal of cellular physiology
Neuropathic pain (NP) caused by nerve injury or dysfunction is one of the most challenging neurological diseases. In-depth study of disease signatures contributes to the development of novel target treatment for NP. In this study, we analyzed expression profiles of qualified NP datasets (GSE24982 and GSE63442) deposited at Gene Expression Omnibus database by systematic bioinformatics approaches. We analyzed the differentially expressed genes of high and low pain compared with normal control group, and between spinal nerve ligation (SNL) injury model and sham-operation group. A total of 1,243 upregulated and 1,533 downregulated genes were identified in GSE24982, 380 upregulated and 355 downregulated genes were identified in GSE63442. By comparing low-pain samples with the corresponding sham-operation group, we identified 457 upregulated and 409 downregulated genes. Overlapping genes were screened out and signaling pathway and expression regulation model analyses were performed. SCN10A and SST were identified as biomarkers for NP. In conclusion, our study showed the expression pattern of gene about NP. These identified biomarkers could serve as potential therapeutic targets for treating NP.
Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods.
Hu Wei-Ping,Zeng Ying-Ying,Zuo Yi-Hui,Zhang Jing
International journal of chronic obstructive pulmonary disease
Purpose:By reanalyzing the gene expression profile GSE76925 in the Gene Expression Omnibus database using bioinformatic methods, we attempted to identify novel candidate genes promoting the development of emphysema in patients with COPD. Patients and methods:According to the Quantitative CT data in GSE76925, patients were divided into mild emphysema group (%LAA-950<20%, n=12) and severe emphysema group (%LAA-950>50%, n=11). Differentially expressed genes (DEGs) were identified using Agilent GeneSpring GX v11.5 (corrected -value <0.05 and |Fold Change|>1.3). Known driver genes of COPD were acquired by mining literatures and retrieving databases. Direct protein-protein interaction network (PPi) of DEGs and known driver genes was constructed by STRING.org to screen the DEGs directly interacting with driver genes. In addition, we used STRING.org to obtain the first-layer proteins interacting with DEGs' products and constructed the indirect PPi of these interaction proteins. By merging the indirect PPi with driver genes' PPi using Cytoscape v3.6.1, we attempted to discover potential pathways promoting emphysema's development. Results:All the patients had COPD with severe airflow limitation (age=62±8, FEV%=28±12). A total of 57 DEGs (including 12 pseudogenes) and 135 known driving genes were identified. Direct PPi suggested that GPR65, GNB4, P2RY13, NPSR1, BCR, BAG4, and IMPDH2 were potential pathogenic genes. GPR65 could regulate the response of immune cells to the acidic microenvironment, and NPSR1's expression on eosinophils was associated with asthma's severity and IgE level. Indirect merging PPi demonstrated that the interacting network of TP53, IL8, CCR2, HSPA1A, ELANE, PIK3CA was associated with the development of emphysema. IL8, ELANE, and PIK3CA were molecules involved in the pathological mechanisms of emphysema, which also in return proved the role of TP53 in emphysema. Conclusion:Candidate genes such as GPR65, NPSR1, and TP53 may be involved in the progression of emphysema.
Identification of macrophage-related candidate genes in lupus nephritis using bioinformatics analysis.
Shu Bingyan,Fang Yi,He Weichun,Yang Junwei,Dai Chunsun
Lupus nephritis (LN) is a chronic autoimmune disorder. Here we try to identify the candidate genes in macrophages related to LN. We performed a systematic search in the Gene Expression Omnibus (GEO) database for microarray in human mononuclear cells and mouse macrophages of LN. The results of clustering and venn analysis of different GEO datasets showed that 8 genes were up-regulated and 2 genes down-regulated in samples from both human and mouse LN. The data from gene network and GO analysis revealed that CD38 and CCL2 were localized in the core of the network. Immunofluorescence staining showed that CD38 expression was markedly increased in macrophages from kidneys with LN. Our study identifies the gene expression profile for macrophages and demonstrated the induction of CCL2 and CD38 in macrophages from patients with LN. However, regarding the limited patient number included in this study, the results are preliminary and more studies are still needed to further decipher the macrophage-related candidate genes for the pathogenesis of LN.
Identification of lncRNAs involved in biological regulation in early age-related macular degeneration.
Zhu Wei,Meng Yi-Fang,Xing Qian,Tao Jian-Jun,Lu Jiong,Wu Yan
International journal of nanomedicine
BACKGROUND:Age-related macular degeneration (AMD) is one of the most common causes of adult blindness in developed countries. However, the role of long noncoding RNAs (lncRNAs) in the development and progression of early AMD is unclear. METHODS:We established the lncRNA profile of early AMD by reannotation of microarrays from the gene expression omnibus database. Quantitative real-time polymerase chain reaction was used to determine the expression of selected lncRNAs. RESULTS:The expression profiles of 9 cases of AMD and 7 controls were studied. A total of 266 differentially expressed genes (DEGs) were detected (94 upregulated and 172 downregulated). Among all the DEGs, 64 were lncRNAs. Advanced bioinformatics analyses demonstrated that differentially expressed lncRNAs could play significant roles in visual perception, sensory perception of light stimulus, and cognition. The pathway analyses showed that the two most significantly influenced Kyoto Encyclopedia of Genes and Genomes pathways were those of phototransduction and purine metabolism. By the analyses of the key lncRNAs, it was found that RP11-234O6.2 was downregulated in the aging retinal pigment epithelium (RPE) cellular model. Exogenous RP11-234O6.2 treatment led to increased cell viability and improved apoptosis but it did not affect the cell migration ability of aging RPE cells. CONCLUSION:This study indicated that lncRNAs are differentially expressed in early AMD and may produce important regulative effects. An lncRNA, RP11-234O6.2, might be involved in the biological regulation of early AMD and have therapeutic potential.
Identification of Key Modules and Hub Genes of Keloids with Weighted Gene Coexpression Network Analysis.
Liu Wenhui,Huang Xiaolu,Liang Xiao,Zhou Yiwen,Li Haizhou,Yu Qingxiong,Li Qingfeng
Plastic and reconstructive surgery
BACKGROUND:Keloid scarring impairs patients' quality of life, and although many therapeutic strategies have been developed, most remain unsatisfactory because of limited understanding of the mechanisms underlying keloid development. METHODS:A microarray gene expression data set from keloid tissue was acquired from the Gene Expression Omnibus. Differentially expressed genes in fibroblasts and keratinocytes underwent functional annotation and pathway analysis. Weighted gene coexpression network analysis was applied to identify the gene targets of keloid scars within differentially expressed genes. Modules and hub genes for keloids were identified. Enrichment analysis was undertaken to verify the modules' and hub genes' relationship with keloids. RESULTS:Enrichment analysis and pathway analysis showed gene ontology terms and pathways related to keloids. Each cell type generated three modules in weighted gene coexpression network analysis, with one module most related to keloids. Enrichment analysis showed that the modules concerned are enriched with terms related to keloids. Three hub genes were selected for fibroblasts and keratinocytes, and their relationship to keloids was verified. Immunohistochemical staining verified expression change of some hub genes. CONCLUSIONS:This is the first study to describe the gene networks underlying keloids. Modules and hub genes generated in the present study are highly related to keloids and may identify novel therapeutic targets for treatment of keloids. CLINICAL QUESTION/LEVEL OF EVIDENCE:Therapeutic, V.
Identification of key lncRNAs contributing to diabetic nephropathy by gene co-expression network analysis.
Shang Jin,Wang Shuai,Jiang Yumin,Duan Yiqi,Cheng Genyang,Liu Dong,Xiao Jing,Zhao Zhanzheng
LncRNA is reported to have important role in diabetic nephropathy (DN). Here, we aim to identify key lncRNAs of DN using bioinformatics and systems biological methods. METHOD:Five microarray data sets from Gene Expression Omnibus (GEO) database were included. Probe sets were re-annotated. In the training set, differential expressed genes (DEGs) were identified. Weighted gene co-expression network analysis (WGCNA) was constructed to screen diabetic-related hub genes and reveal their potential biological function. Two more human data sets and mouse data sets were used as validation sets. RESULTS:A total of 424 DEGs, including 10 lncRNAs, were filtered in the training data set. WGCNA and enrichment analysis of hub genes showed that inflammation and metabolic disorders are prominent in DN. Three key lncRNAs (NR_130134.1, NR_029395.1 and NR_038335.1) were identified. These lncRNAs are also differently expressed in another two human data sets. Functional enrichment of the mouse data sets showed consistent changes with that in human, indicating similar changes in gene expression pattern of DN and confirmed confidence of our analysis. Human podocytes and mesangial cells were culture in vitro. QPCR and fluorescence in situ hybridization were taken out to validate the expression and relationship of key lncRNAs and their related mRNAs. Results were also consistent with our analysis. CONCLUSIONS:Inflammation and metabolic disorders are prominent in DN. We identify three lncRNAs that are involved in these processes possibly by interacting with co-expressed mRNAs.
Identification of key genes in human airway epithelial cells in response to respiratory pathogens using microarray analysis.
Li Yinghua,Liu Guangnan,Zhang Jianquan,Zhong Xiaoning,He Zhiyi
BACKGROUND:Airway epithelium is the primary target for pathogens. It functions not only as a mechanical barrier, but also as an important sentinel of the innate immune system. However, the interactions and processes between host airway epithelium and pathogens are not fully understood. RESULTS:In this study, we identified responses of the human airway epithelium cells to respiratory pathogen infection. We retrieved three mRNA expression microarray datasets from the Gene Expression Omnibus database, and identified 116 differentially expressed genes common to all three datasets. Gene functional annotations were performed using Gene Ontology and pathway analyses. Using protein-protein interaction network analysis and text mining, we identified a subset of genes functioned as a group and associated with infection, inflammation, tissue adhesion, and receptor internalization in infected epithelial cells. These genes were further identified in BESE-2B cells in response to Talaromyces marneffei by Real-Time quantitative PCR (qRT-PCR). In addition, we performed an in silico prediction of microRNA-target interactions and examined our findings. CONCLUSIONS:Using bioinformatics analysis, we identified several genes that may serve as biomarkers for the diagnosis or the surveillance of early respiratory tract infection, and identified additional genes and miRNAs that warrant further fundamental experimental research.
Identification of key genes and pathways in benign prostatic hyperplasia.
Ke Zhi-Bin,Cai Hai,Wu Yu-Peng,Lin Yun-Zhi,Li Xiao-Dong,Huang Jin-Bei,Sun Xiong-Lin,Zheng Qing-Shui,Xue Xue-Yi,Wei Yong,Xu Ning
Journal of cellular physiology
Benign prostatic hyperplasia (BPH) is one of the most common causes of lower urinary tract symptoms (LUTS) in elderly man. However, the underlying molecular mechanisms of BPH have not been completely elucidated. We identified the key genes and pathways by using analysis of Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using edgeR. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for the DEGs by Database for Annotation, Visualization and Integrated Discovery (DAVID) database and ConsensusPathDB, respectively. Then, protein-protein interaction (PPI) networks were established by the Search Tool for the Retrieval of Interacting Genes (STRING) database and visualized by Cytoscape software. Finally, we identified 660 DEGs ultimately including 268 upregulated genes and 392 downregulated genes. GO analysis revealed that DEGs were mainly enriched in extracellular exosome, identical protein binding, mitochondrial adenosine triphosphate (ATP) synthesis coupled proton transport, extracelluar matrix, focal adhesion, cytosol, Golgi apparatus, cytoplasm, protein binding, and Golgi membrane. Focal adhesion pathway, FoxO signaling pathway, and autophagy pathway were selected. Ubiquitin-conjugating enzyme E2 C (UBE2C), serine/threonine kinase (AKT1), mitogen-activated protein kinase 1 (MAPK1), cyclin B1 (CCNB1), polo-like kinase 1 (PLK1) were filtrated as the hub genes according to the degree of connectivity from the PPI network. The five hub genes including UBE2C, AKT1, MAPK1, CCNB1, PLK1 may play key roles in the pathogenesis of benign prostatic hyperplasia (BPH). Focal adhesion pathway, FoxO signaling pathway, and autophagy pathway may be crucial for the progression of BPH.
Identification of key genes and pathways associated with osteogenic differentiation of adipose stem cells.
Zhao Xinyuan,Liang Minlu,Li Xiaona,Qiu Xiaoling,Cui Li
Journal of cellular physiology
Adipose stem cells (ASCs) are considered a great alternative source of mesenchymal stem cells (MSCs) and have shown great promise on tissue engineering and regenerative medicine applications, including bone repair. However, the underlying mechanisms regulating the osteogenic differentiation of ASCs remain poorly known. Gene expression profiles of GSE63754 and GSE37329 were downloaded from gene expression omnibus database. R software and Bioconductor packages were used to compare and identify the differentially expressed genes (DEGs) before and after ASC osteogenic differentiation. The common significant DEGs between GSE63754 and GSE37329 were then subjected to gene ontology (GO) enrichment analysis, ingenuity pathway analysis (IPA), and protein-protein interactions (PPIs) networks analysis. One of the central node genes FOXO1 was selected for further investigation. A total of 142 up- and 69 downregulated genes were aberrantly expressed in both GSE63754 and GSE37329. GO analysis revealed that these DEGs were associated with extracellular matrix organization, proteinaceous extracellular matrix, and Wnt-protein binding. IPA analysis showed that canonical pathways, such as FXR/RXR activation, adipogenesis pathway, and LXR/RXR activation, were involved in regulating osteogenic differentiation of ASCs. A total of three subnetworks and 39 nodes were identified with PPI network and MCODE plugin. Moreover, suppression of one central node gene FOXO1 inhibited the osteogenic differentiation of ASCs. Our study provides a registry of genes and pathways that play important roles in regulating osteogenic differentiation of ASCs, which might have potential therapeutic applications in bone regeneration and bone tissue engineering.
Identification of key biomarkers in diabetic nephropathy via bioinformatic analysis.
Zeng Mengru,Liu Jialu,Yang Wenxia,Zhang Shumin,Liu Fuyou,Dong Zheng,Peng Youming,Sun Lin,Xiao Li
Journal of cellular biochemistry
Diabetic nephropathy (DN) is a major cause of end-stage renal disease. Although intense efforts have been made to elucidate the pathogenesis, the molecular mechanisms of DN remain to be clarified. To identify the candidate genes in the progression of DN, microarray datasets GSE30122, GSE30528, and GSE47183 were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein-protein interaction network was constructed and the module analysis was performed using the Search Tool for the Retrieval of Interacting Genes and Cytoscape. A total of 61 DEGs were identified. The enriched functions and pathways of the DEGs included glomerulus development, extracellular exosome, collagen binding, and the PI3K-Akt signaling pathway. Fifteen hub genes were identified and biological process analysis revealed that these genes were mainly enriched in acute inflammatory response, inflammatory response, and blood vessel development. Correlation analysis between unexplored hub genes and clinical features of DN suggested that COL6A3, MS4A6A,PLCE1, TNNC1, TNNI1, TNN2, and VSIG4 may involve in the progression of DN. In conclusion, DEGs and hub genes identified in this study may deepen our understanding of molecular mechanisms underlying the progression of DN, and provide candidate targets for diagnosis and treatment of DN.
Identification of hub-methylated differentially expressed genes in patients with gestational diabetes mellitus by multi-omic WGCNA basing epigenome-wide and transcriptome-wide profiling.
Chen Min,Yan Jianying,Han Qing,Luo Jinying,Zhang Qinjian
Journal of cellular biochemistry
Gestational diabetes mellitus (GDM), defined as dysglycaemia that is detected during pregnancy for the first time, has become a global health burden. GDM was found to be correlated to epigenetic changes, which would cause abnormal expression of placental genes. In the present study, we performed multi-omic weighted gene coexpression network analysis (WGCNA) to systematically identify the hub genes for GDM using both epigenome- and transcriptome-wide microarray data. Two microarray datasets (GSE70493 and GSE70494) were downloaded from the Gene Expression Omnibus (GEO) database. GEO2R was used to screen differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between normal and GDM samples, separately. The results of WGCNA found that 15 modules were identified and the MEblack module had a significantly negative correlation with GDM (r = -.28, P = .03). GO enrichment analysis by BinGO of the MEblack module showed that genes were primarily enriched for the presentation of antigen processing, regulation of interferon-α production and interferon-γ-mediated signaling pathway. By comparing the DEGs, DMGs and hub genes in the coexpression network, we identified five hypermethylated, lowly expressed genes (ABLIM1, GRHL1, HLA-F, NDRG1, and SASH1) and one hypomethylated, highly expressed gene (EIF3F) as GDM-related hub DMGs. Moreover, the expression levels of ABLIM1, GRHL1, HLA-F, NDRG1, and SASH11 in the GDM patients and healthy controls were validated by a real-time quantitative polymerase chain reaction. Finally, gene set enrichment analysis showed that the biological function of cardiac muscle contraction was enriched for four GDM-related hub DMGs (ABLIM1, GRHL1, NDRG1, and SASH1). Analysis of this study revealed that dysmethylated hub genes in GDM placentas might affect the placental function and thus, take part in GDM pathogenesis and fetal cardiac development.
Identification of Hub Genes and Key Pathways Associated With Bipolar Disorder Based on Weighted Gene Co-expression Network Analysis.
Liu Yang,Gu Hui-Yun,Zhu Jie,Niu Yu-Ming,Zhang Chao,Guo Guang-Ling
Frontiers in physiology
Bipolar disorder (BD) is a complex mental disorder with high mortality and disability rates worldwide; however, research on its pathogenesis and diagnostic methods remains limited. This study aimed to elucidate potential candidate hub genes and key pathways related to BD in a pre-frontal cortex sample. Raw gene expression profile files of GSE53987, including 36 samples, were obtained from the gene expression omnibus (GEO) database. After data pre-processing, 10,094 genes were selected for weighted gene co-expression network analysis (WGCNA). After dividing highly related genes into 19 modules, we found that the pink, midnight blue, and brown modules were highly correlated with BD. Functional annotation and pathway enrichment analysis for modules, which indicated some key pathways, were conducted based on the Enrichr database. One of the most remarkable significant pathways is the Hippo signaling pathway and its positive transcriptional regulation. Finally, 30 hub genes were identified in three modules. Hub genes with a high degree of connectivity in the PPI network are significantly enriched in positive regulation of transcription. In addition, the hub genes were validated based on another dataset (GSE12649). Taken together, the identification of these 30 hub genes and enrichment pathways might have important clinical implications for BD treatment and diagnosis.
Identification of gene expression profiles and key genes in subchondral bone of osteoarthritis using weighted gene coexpression network analysis.
Guo Sheng-Min,Wang Jian-Xiong,Li Jin,Xu Fang-Yuan,Wei Quan,Wang Hai-Ming,Huang Hou-Qiang,Zheng Si-Lin,Xie Yu-Jie,Zhang Chi
Journal of cellular biochemistry
Osteoarthritis (OA) significantly influences the quality life of people around the world. It is urgent to find an effective way to understand the genetic etiology of OA. We used weighted gene coexpression network analysis (WGCNA) to explore the key genes involved in the subchondral bone pathological process of OA. Fifty gene expression profiles of GSE51588 were downloaded from the Gene Expression Omnibus database. The OA-associated genes and gene ontologies were acquired from JuniorDoc. Weighted gene coexpression network analysis was used to find disease-related networks based on 21756 gene expression correlation coefficients, hub-genes with the highest connectivity in each module were selected, and the correlation between module eigengene and clinical traits was calculated. The genes in the traits-related gene coexpression modules were subject to functional annotation and pathway enrichment analysis using ClusterProfiler. A total of 73 gene modules were identified, of which, 12 modules were found with high connectivity with clinical traits. Five modules were found with enriched OA-associated genes. Moreover, 310 OA-associated genes were found, and 34 of them were among hub-genes in each module. Consequently, enrichment results indicated some key metabolic pathways, such as extracellular matrix (ECM)-receptor interaction (hsa04512), focal adhesion (hsa04510), the phosphatidylinositol 3'-kinase (PI3K)-Akt signaling pathway (PI3K-AKT) (hsa04151), transforming growth factor beta pathway, and Wnt pathway. We intended to identify some core genes, collagen (COL)6A3, COL6A1, ITGA11, BAMBI, and HCK, which could influence downstream signaling pathways once they were activated. In this study, we identified important genes within key coexpression modules, which associate with a pathological process of subchondral bone in OA. Functional analysis results could provide important information to understand the mechanism of OA.
Identification of gene coexpression modules, hub genes, and pathways related to spinal cord injury using integrated bioinformatics methods.
Wang Tienan,Wu Baolin,Zhang Xiuzhi,Zhang Meng,Zhang Shuo,Huang Wei,Liu Tao,Yu Weiting,Li Junlei,Yu Xiaobing
Journal of cellular biochemistry
Spinal cord injury (SCI) is characterized by dramatic neurons loss and axonal regeneration suppression. The underlying mechanism associated with SCI-induced immune suppression is still unclear. Weighted gene coexpression network analysis (WGCNA) is now widely applied for the identification of the coexpressed modules, hub genes, and pathways associated with clinic traits of diseases. We performed this study to identify hub genes associated with SCI development. Gene Expression Omnibus (GEO) data sets GSE45006 and GSE20907 were downloaded and the significant correlativity and connectivity between them were detected using WGCNA. Three significant consensus modules, including 567 eigengenes, were identified from the master GSE45006 data following the preconditions of approximate scale-free topology for WGCNA. Further bioinformatics analysis showed these eigengenes were involved in inflammatory and immune responses in SCI. Three hub genes Rac2, Itgb2, and Tyrobp and one pathway "natural killer cell-mediated cytotoxicity" were identified following short time-series expression miner, protein-protein interaction network, and functional enrichment analysis. Gradually upregulated expression patterns of Rac2, Itgb2, and Tyrobp genes at 0, 3, 7, and 14 days after SCI were confirmed based on GSE45006 and GSE20907 data set. Finally, we found that Rac2, Itgb2, and Tyrobp genes might take crucial roles in SCI development through the "natural killer cell-mediated cytotoxicity" pathway.
Identification of differentially expressed genes in synovial tissue of rheumatoid arthritis and osteoarthritis in patients.
Li Wen Chao,Bai De Lei,Xu Yang,Chen Hui,Ma Rui,Hou Wen Bo,Xu Rui Jiang
Journal of cellular biochemistry
Rheumatoid arthritis (RA) and osteoarthritis (OA) are the common joints disorder in the world. Although they have showed the analogous clinical manifestation and overlapping cellular and molecular foundation, the pathogenesis of RA and OA were different. The pathophysiologic mechanisms of arthritis in RA and OA have not been investigated thoroughly. Thus, the aim of study is to identify the potential crucial genes and pathways associated with RA and OA and further analyze the molecular mechanisms implicated in genesis. First, we compared gene expression profiles in synovial tissue between RA and OA from the National Center of Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. Gene Expression Series (GSE) 1919, GSE55235, and GSE36700 were downloaded from the GEO database, including 20 patients of OA and 21 patients of RA. Diﬀerentially expressed genes (DEGs) including "CXCL13," "CD247," "CCL5," "GZMB," "IGKC," "IL7R," "UBD///GABBR1," "ADAMDEC1," "BTC," "AIM2," "SHANK2," "CCL18," "LAMP3," "CR1," and "IL32." Second, Gene Ontology analyses revealed that DEGs were signiﬁcantly enriched in integral component of extracellular space, extracellular region, and plasma membrane in the molecular function group. Signaling pathway analyses indicated that DEGs had common pathways in chemokine signaling pathway, cytokine-cytokine receptor interaction, and cytosolic DNA-sensing pathway. Third, DEGs showed the complex DEGs protein-protein interaction network with the Coexpression of 83.22%, Shared protein domains of 8.40%, Colocalization of 4.76%, Predicted of 2.87%, and Genetic interactions of 0.75%. In conclusion, the novel DEGs and pathways between RA and OA identified in this study may provide new insight into the underlying molecular mechanisms of RA.
Identification of biomarkers, pathways and potential therapeutic agents for white adipocyte insulin resistance using bioinformatics analysis.
Zhang Yemin,Zheng Yuyang,Fu Yalin,Wang Changhua
For the better understanding of insulin resistance (IR), the molecular biomarkers in IR white adipocytes and its potential mechanism, we downloaded two mRNA expression profiles from Gene Expression Omnibus (GEO). The white adipocyte samples in two databases were collected from the human omental adipose tissue of IR obese (IRO) subjects and insulin-sensitive obese (ISO) subjects, respectively. We identified 86 differentially expressed genes (DEGs) between the IRO and ISO subjects using limma package in R software. Gene Set Enrichment Analysis (GSEA) provided evidence that the most gene sets enriched in kidney mesenchyme development in the ISO subjects, as compared with the IRO subjects. The Gene Ontology (GO) analysis indicated that the most significantly enriched in cellular response to interferon-gamma. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the DEGs were most significantly enriched in cytokine-cytokine receptor interaction. Protein-Protein Interaction (PPI) network was performed with the STRING, and the top 10 hub genes were identified with the Cytohubba. CMap analysis found several small molecular compounds to reverse the altered DEGs, including dropropizine, aceclofenac, melatonin, and so on. Our outputs could empower the novel potential targets to treat omental white adipocyte insulin resistance, diabetes, and diabetes-related diseases.
Host-response-based gene signatures for tuberculosis diagnosis: A systematic comparison of 16 signatures.
Warsinske Hayley,Vashisht Rohit,Khatri Purvesh
BACKGROUND:The World Health Organization (WHO) and Foundation for Innovative New Diagnostics (FIND) have published target product profiles (TPPs) calling for non-sputum-based diagnostic tests for the diagnosis of active tuberculosis (ATB) disease and for predicting the progression from latent tuberculosis infection (LTBI) to ATB. A large number of host-derived blood-based gene-expression biomarkers for diagnosis of patients with ATB have been proposed to date, but none have been implemented in clinical settings. The focus of this study is to directly compare published gene signatures for diagnosis of patients with ATB across a large, diverse list of publicly available gene expression datasets, and evaluate their performance against the WHO/FIND TPPs. METHODS AND FINDINGS:We searched PubMed, Gene Expression Omnibus (GEO), and ArrayExpress in June 2018. We included all studies irrespective of study design and enrollment criteria. We found 16 gene signatures for the diagnosis of ATB compared to other clinical conditions in PubMed. For each signature, we implemented a classification model as described in the corresponding original publication of the signature. We identified 24 datasets containing 3,083 transcriptome profiles from whole blood or peripheral blood mononuclear cell samples of healthy controls or patients with ATB, LTBI, or other diseases from 14 countries in GEO. Using these datasets, we calculated weighted mean area under the receiver operating characteristic curve (AUROC), specificity at 90% sensitivity, and negative predictive value (NPV) for each gene signature across all datasets. We also compared the diagnostic odds ratio (DOR), heterogeneity in DOR, and false positive rate (FPR) for each signature using bivariate meta-analysis. Across 9 datasets of patients with culture-confirmed diagnosis of ATB, 11 signatures had weighted mean AUROC > 0.8, and 2 signatures had weighted mean AUROC ≤ 0.6. All but 2 signatures had high NPV (>98% at 2% prevalence). Two gene signatures achieved the minimal WHO TPP for a non-sputum-based triage test. When including datasets with clinical diagnosis of ATB, there was minimal reduction in the weighted mean AUROC and specificity of all but 3 signatures compared to when using only culture-confirmed ATB data. Only 4 signatures had homogeneous DOR and lower FPR when datasets with clinical diagnosis of ATB were included; other signatures either had heterogeneous DOR or higher FPR or both. Finally, 7 of 16 gene signatures predicted progression from LTBI to ATB 6 months prior to sputum conversion with positive predictive value > 6% at 2% prevalence. Our analyses may have under- or overestimated the performance of certain ATB diagnostic signatures because our implementation may be different from the published models for those signatures. We re-implemented published models because the exact models were not publicly available. CONCLUSIONS:We found that host-response-based diagnostics could accurately identify patients with ATB and predict individuals with high risk of progression from LTBI to ATB prior to sputum conversion. We found that a higher number of genes in a signature did not increase the accuracy of the signature. Overall, the Sweeney3 signature performed robustly across all comparisons. Our results provide strong evidence for the potential of host-response-based diagnostics in achieving the WHO goal of ending tuberculosis by 2035, and host-response-based diagnostics should be pursued for clinical implementation.
High expression of EZH2 as a marker for the differential diagnosis of malignant and benign myogenic tumors.
Zhang Ning,Zeng Zhi,Li Shaobo,Wang Fei,Huang Peng
Overlap in morphologic features between malignant and benign myogenic tumors, such as leiomyosarcoma (LMS) vs. leiomyoma as well as rhabdomyosarcoma (RMS) vs. rhabdomyoma, often makes differential diagnosis difficult and challenging. Here the expressions of Enhancer of Zeste Homolog 2 (EZH2), Suppressor of Zeste 12 (SUZ12), retinoblastoma protein associated protein 46 (RbAp46), Embryonic Ectoderm Development (EED) and ki-67 protein were detected by immunohistochemistry to evaluate their values in differential diagnosis. The expression of EZH2 mRNA was investigated by analyzing the Gene Expression Omnibus Datasets. The results demonstrated that EZH2 protein was detected in 81.25% (26/32) of LMS and 70.58% (36/51) of RMS, whereas none of leiomyoma (n = 16), rhabdomyoma (n = 15) and normal tissues (n = 31) showed positive immunostaining (p < 0.05). EZH2 protein was found to have a sensitivity of 91.30% and specificity of 100% in distinguishing well-differentiated LMS from cellular leiomyoma, and a sensitivity of 92.86% and specificity of 100% in distinguishing well-differentiated embryonal rhabdomyosarcoma (ERMS) from fetal rhabdomyoma. Besides, the expression of EZH2 mRNA was higher in LMS and RMS than in benign tumors (p < 0.05). The expressions of SUZ12 and RbAp46 protein were higher in RMS than in rhabdomyoma (p < 0.05). Conclusively, the high expression of EZH2 is a promising marker in distinguishing well-differentiated LMS from cellular leiomyoma, or well-differentiated ERMS from fetal rhabdomyoma, and the upregulation of EZH2 protein expression may occur at transcriptional level.
H19 promote calcium oxalate nephrocalcinosis-induced renal tubular epithelial cell injury via a ceRNA pathway.
Liu Haoran,Ye Tao,Yang Xiaoqi,Liu Jianhe,Jiang Kehua,Lu Hongyan,Xia Ding,Peng Ejun,Chen Zhiqiang,Sun Fa,Tang Kun,Ye Zhangqun
BACKGROUND:Intrarenal calcium oxalate (CaOx) crystals induce inflammation and kidney tubular cell injury, which are processes that involve TLR4/NF-κB signalling. A recent genome-wide gene expression profile analysis of Randall's plaques in CaOx stone patients revealed that the expression of the long noncoding RNA H19 was significantly upregulated. However, to date, its role in kidney CaOx stones has not been reported. METHOD:A Gene Expression Omnibus (GEO) dataset was utilized to analyse gene expression profiles. Luciferase reporter, Western blotting, qRT-PCR, immunofluorescence staining and reactive oxygen species (ROS) assays were employed to study the molecular mechanism of HMGB1/TLR4/NF-κB regulation by H19 and miR-216b. In vitro and in vivo assays were performed to further confirm the proinflammatory and prooxidative stress effects. FINDING:H19 expression was significantly increased and positively correlated with the expression levels of HMGB1, TLR4 and NF-κB in Randall's plaques and glyoxylate-induced CaOx nephrocalcinosis mouse models. H19 interacted with miR-216b and suppressed its expression. Additionally, miR-216b inhibited HMGB1 expression by directly binding its 3'-untranslated region. Moreover, H19 downregulation inhibited HMGB1, TLR4 and NF-κB expression and suppressed CaOx nephrocalcinosis-induced renal tubular epithelial cell injury, NADPH oxidase, and oxidative stress in vivo and in vitro. Interestingly, miR-216b inhibition partially reversed the inhibitory effect of H19 knockdown on HMGB1 expression. INTERPRETATION:We determined that H19 might serve as a facilitator in the process of CaOx nephrocalcinosis-induced oxidative stress and renal tubular epithelial cell injury, and we revealed that the interaction between H19 and miR-216b could exert its effect via the HMGB1/TLR4/NF-κB pathway. FUNDING:This work was supported by the National Nature Science Foundation of China (Nos. 8196030190, 8190033175, 81370805, 81470935, 81900645, 81500534, and 81602236).
Global transcriptome analysis to identify critical genes involved in the pathology of osteoarthritis.
Zhang X,Bu Y,Zhu B,Zhao Q,Lv Z,Li B,Liu J
Bone & joint research
Objectives:The aim of this study was to identify key pathological genes in osteoarthritis (OA). Methods:We searched and downloaded mRNA expression data from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) of joint synovial tissues from OA and normal individuals. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses were used to assess the function of identified DEGs. The protein-protein interaction (PPI) network and transcriptional factors (TFs) regulatory network were used to further explore the function of identified DEGs. The quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the result of bioinformatics analysis. Electronic validation was performed to verify the expression of selected DEGs. The diagnosis value of identified DEGs was accessed by receiver operating characteristic (ROC) analysis. Results:A total of 1085 DEGs were identified. KEGG pathway analysis displayed that Wnt was a significantly enriched signalling pathway. Some hub genes with high interactions such as USP46, CPVL, FKBP5, FOSL2, GADD45B, PTGS1, and ZNF423 were identified in the PPI and TFs network. The results of qRT-PCR showed that GADD45B, ADAMTS1, and TFAM were down-regulated in joint synovial tissues of OA, which was consistent with the bioinformatics analysis. The expression levels of USP46, CPVL, FOSL2, and PTGS1 in electronic validation were compatible with the bio-informatics result. CPVL and TFAM had a potential diagnostic value for OA based on the ROC analysis. Conclusion:The deregulated genes including USP46, CPVL, FKBP5, FOSL2, GADD45B, PTGS1, ZNF423, ADAMTS1, and TFAM might be involved in the pathology of OA.: X. Zhang, Y. Bu, B. Zhu, Q. Zhao, Z. Lv, B. Li, J. Liu. Global transcriptome analysis to identify critical genes involved in the pathology of osteoarthritis. 2018;7:298-307. DOI: 10.1302/2046-3758.74.BJR-2017-0245.R1.
Genome-wide Integration Study of Circulating miRNAs and Peripheral Whole-Blood mRNAs of Male Acute Ischemic Stroke Patients.
Xue Yang,Yin Pengqi,Li Guozhong,Zhong Di
Several circulating microRNAs (miRNAs) have been proved to serve as stable biomarkers in blood for acute ischemic stroke (AIS). However, the functions of these biomarkers remain elusive. By conducting the integration analysis of circulating miRNAs and peripheral whole-blood mRNAs using bioinformatics methods, we explored the biological role of these circulating markers in peripheral whole blood at the genome-wide level. Stroke-related circulating miRNA profile data (GSE86291) and peripheral whole-blood mRNA expression data (GSE16561) were collected from the Gene Expression Omnibus (GEO) datasets. We selected male patients to avoid any gender differences in stroke pathology. Male stroke-related miRNAs (M-miRNAs) and mRNAs (M-mRNAs) were detected using GEO2R. Nine M-miRNAs (five up- and four down-regulated) were applied to TargetScan to predict the possible target mRNAs. Next, we intersected these targets with the M-mRNAs (38 up- and three down-regulated) to obtain the male stroke-related overlapped mRNAs (Mo-mRNAs). Finally, we analyzed biological functions of Mo-mRNAs using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and constructed networks among the Mo-mRNAs, overlapped M-miRNAs (Mo-miRNAs), and their functions. The Mo-mRNAs were enriched in functions such as platelet degranulation, immune response, and pathways associated with phagosome biology and Staphylococcus aureus infection. This study provides an integrated view of interactions among circulating miRNAs and peripheral whole-blood mRNAs involved in the pathophysiological processes of male AIS.
Gene Expression Profiling of Two Epilepsy Models Reveals the ECM/Integrin signaling Pathway is Involved in Epiletogenesis.
Han Chun-Lei,Zhao Xue-Min,Liu Yun-Peng,Wang Kai-Liang,Chen Ning,Hu Wei,Zhang Jian-Guo,Ge Ming,Meng Fan-Gang
The molecular mechanisms underlying the development of epilepsy, i.e., epileptogenesis, are due to altered expression of a series of genes. Global expression profiling of temporal lobe epilepsy is confounded by a number of factors, including the variability among animal species, animal models, and tissue sampling time-points. In this study, we pooled two microarray datasets of the most used pilocarpine and kainic acid epilepsy models from the Gene Expression Omnibus database. A total of 567 known and novel genes were commonly differentially expressed across the two models. Pathway analyses demonstrated that the dysregulated genes were involved in 46 pathways. Real-time PCR and western blot analysis confirmed the activation of extracellular matrix (ECM)/integrin signaling pathways. Moreover, targeting ECM/integrin signaling inhibits astrocyte activation and promotes neuron injury in the hippocampus of epileptic mice. This study may provide a "gene/pathway database" that with further investigation can determine the mechanisms underlining epileptogenesis and the possible targets for neuron protection in the hippocampus after status epilepticus.
Gene expression of sphingolipid metabolism pathways is altered in hidradenitis suppurativa.
Dany Mohammed,Elston Dirk
Journal of the American Academy of Dermatology
BACKGROUND:Hidradenitis suppurativa (HS) is a debilitating skin disease characterized by painful recurrent nodules and abscesses caused by chronic inflammation. Early events in the development of HS are believed to occur in the folliculopilosebaceous unit; however, the signaling pathways behind this mechanism are unknown. Sphingolipids, such as ceramide, are essential components of the skin and appendages and have important structural and signaling roles. OBJECTIVE:We sought to explore whether the gene expression of enzymes involved in sphingolipid metabolic pathways is altered in HS. METHODS:A microarray data set including 30 samples was used to compare the expression of sphingolipid-related enzymes in inflammatory skin lesions from HS patients (n = 17) with the expression in clinically healthy skin tissue (n = 13). Differential expression of sphingolipid metabolism-related genes was analyzed using Gene Expression Omnibus 2R. RESULTS:HS lesional skin samples have significantly decreased expression of enzymes generating ceramide and sphingomyelin, increased expression of enzymes catabolizing ceramide to sphingosine, and increased expression of enzymes converting ceramide to galactosylceramide and gangliosides. LIMITATIONS:Limitations of this study include assessing the expression of sphingolipid-related enzymes without assessing the levels of the related sphingolipids. CONCLUSION:Our study suggests that sphingolipid metabolism is altered in HS lesional skin compared with normal skin.
Enterovirus-associated changes in blood transcriptomic profiles of children with genetic susceptibility to type 1 diabetes.
Lietzen Niina,An Le T T,Jaakkola Maria K,Kallionpää Henna,Oikarinen Sami,Mykkänen Juha,Knip Mikael,Veijola Riitta,Ilonen Jorma,Toppari Jorma,Hyöty Heikki,Lahesmaa Riitta,Elo Laura L
AIMS/HYPOTHESIS:Enterovirus infections have been associated with the development of type 1 diabetes in multiple studies, but little is known about enterovirus-induced responses in children at risk for developing type 1 diabetes. Our aim was to use genome-wide transcriptomics data to characterise enterovirus-associated changes in whole-blood samples from children with genetic susceptibility to type 1 diabetes. METHODS:Longitudinal whole-blood samples (356 samples in total) collected from 28 pairs of children at increased risk for developing type 1 diabetes were screened for the presence of enterovirus RNA. Seven of these samples were detected as enterovirus-positive, each of them collected from a different child, and transcriptomics data from these children were analysed to understand the individual-level responses associated with enterovirus infections. Transcript clusters with peaking or dropping expression at the time of enterovirus positivity were selected as the enterovirus-associated signals. RESULTS:Strong signs of activation of an interferon response were detected in four children at enterovirus positivity, while transcriptomic changes in the other three children indicated activation of adaptive immune responses. Additionally, a large proportion of the enterovirus-associated changes were specific to individuals. An enterovirus-induced signature was built using 339 genes peaking at enterovirus positivity in four of the children, and 77 of these genes were also upregulated in human peripheral blood mononuclear cells infected in vitro with different enteroviruses. These genes separated the four enterovirus-positive samples clearly from the remaining 352 blood samples analysed. CONCLUSIONS/INTERPRETATION:We have, for the first time, identified enterovirus-associated transcriptomic profiles in whole-blood samples from children with genetic susceptibility to type 1 diabetes. Our results provide a starting point for understanding the individual responses to enterovirus infections in blood and their potential connection to the development of type 1 diabetes. DATA AVAILABILITY:The datasets analysed during the current study are included in this published article and its supplementary information files ( www.btk.fi/research/computational-biomedicine/1234-2 ) or are available from the Gene Expression Omnibus (GEO) repository (accession GSE30211).
Elucidating the molecular pathways and immune system transcriptome during ischemia-reperfusion injury in renal transplantation.
Zhang Jinhua,Wei Xiangling,Tang Zuofu,Miao Bin,Luo Yingxun,Hu Xiao,Luo You,Zhou Yu,Na Ning
Ischemia reperfusion injury (IRI) is a major challenge for renal transplantation. This study was performed to explore the mechanisms and potential molecular targets involved in renal IRI. In this study, the gene datasets GSE43974 and GSE126805 from the Gene Expression Omnibus database, which include ischemic and reperfused renal specimens, were analyzed to determine differentially expressed genes (DEGs). Gene ontology annotations, Kyoto Encyclopedia of Genes and Genomes analysis, and gene set enrichment analysis were performed to determine the pathways that are significantly enriched during ischemia and reperfusion. We also determined the microenvironment cell types xCell and performed correlation analyses to reveal the relationship between the molecular pathways and microenvironment cell infiltration. We found 77 DEGs (76 up- and 1 downregulated) and 323 DEGs (312 up- and 11 downregulated) in the GSE43974 and GSE126805 datasets, respectively. Similar signaling pathway enrichment patterns were observed between the two datasets. The combined analyses demonstrate that the NOD-like receptor signaling pathway and its two downstream signaling pathways, MAPK and NF-kβ, are the major significantly enriched pathways. The xCell analysis identified immune cells that are significantly changed after reperfusion, including hematopoietic stem cells, M2 macrophages, monocytes, Treg cells, conventional dendritic cells, and pro B-cells. Enrichment scores of the NOD-like receptor signaling pathway and its downstream pathways during IRI was significantly correlated with the change levels in class-switched memory B-cell and hematopoietic stem cells in both datasets. These data reveal the important role of the NOD-like receptor signaling pathway during IRI, and the close relationship between this pathway and infiltration of specific immune cell types. Our data provide compelling insights into the pathogenesis and potential therapeutic targets for renal IRI.
EA15, MIR22, LINC00472 as diagnostic markers for diabetic kidney disease.
Wang Yan-Zhe,Zhu Ding-Yu,Xie Xin-Miao,Ding Miao,Wang Yong-Lan,Sun Lin-Lin,Zhang Nan,Shen E,Wang Xiao-Xia
Journal of cellular physiology
This study aimed to investigate the molecular mechanisms of diabetic kidney disease (DKD) and to explore new potential therapeutic strategies and biomarkers for DKD. First we analyzed the differentially expressed changes between patients with DKD and the control group using the chip data in Gene Expression Omnibus (GEO) database. Then the gene chip was subjected to be annotated again, so as to screen long noncoding RNAs (lncRNAs) and study expression differences of these lncRNAs in DKD and controlled samples. At last, the function of the differential lncRNAs was analyzed. A total of 252 lncRNAs were identified, and 14 were differentially expressed. In addition, there were 1,629 differentially expressed messenger RNAs (mRNAs) genes, and proliferation and apoptosis adapter protein 15 (PEA15), MIR22, and long intergenic nonprotein coding RNA 472 ( LINC00472) were significantly differentially expressed in DKD samples. Through functional analysis of the encoding genes coexpressed by the three lncRNAs, we found these genes were mainly enriched in type 1 diabetes and autoimmune thyroid disease pathways, whereas in Gene Ontology (GO) function classification, they were also mainly enriched in the immune response, type I interferon signaling pathways, interferon-γ mediated signaling pathways, and so forth. To summary, we identified EA15, MIR22, and LINC00472 may serve as the potential diagnostic markers of DKD.
Dysregulation of multiple metabolic networks related to brain transmethylation and polyamine pathways in Alzheimer disease: A targeted metabolomic and transcriptomic study.
Mahajan Uma V,Varma Vijay R,Griswold Michael E,Blackshear Chad T,An Yang,Oommen Anup M,Varma Sudhir,Troncoso Juan C,Pletnikova Olga,O'Brien Richard,Hohman Timothy J,Legido-Quigley Cristina,Thambisetty Madhav
BACKGROUND:There is growing evidence that Alzheimer disease (AD) is a pervasive metabolic disorder with dysregulation in multiple biochemical pathways underlying its pathogenesis. Understanding how perturbations in metabolism are related to AD is critical to identifying novel targets for disease-modifying therapies. In this study, we test whether AD pathogenesis is associated with dysregulation in brain transmethylation and polyamine pathways. METHODS AND FINDINGS:We first performed targeted and quantitative metabolomics assays using capillary electrophoresis-mass spectrometry (CE-MS) on brain samples from three groups in the Baltimore Longitudinal Study of Aging (BLSA) (AD: n = 17; Asymptomatic AD [ASY]: n = 13; Control [CN]: n = 13) (overall 37.2% female; mean age at death 86.118 ± 9.842 years) in regions both vulnerable and resistant to AD pathology. Using linear mixed-effects models within two primary brain regions (inferior temporal gyrus [ITG] and middle frontal gyrus [MFG]), we tested associations between brain tissue concentrations of 26 metabolites and the following primary outcomes: group differences, Consortium to Establish a Registry for Alzheimer's Disease (CERAD) (neuritic plaque burden), and Braak (neurofibrillary pathology) scores. We found significant alterations in concentrations of metabolites in AD relative to CN samples, as well as associations with severity of both CERAD and Braak, mainly in the ITG. These metabolites represented biochemical reactions in the (1) methionine cycle (choline: lower in AD, p = 0.003; S-adenosyl methionine: higher in AD, p = 0.005); (2) transsulfuration and glutathione synthesis (cysteine: higher in AD, p < 0.001; reduced glutathione [GSH]: higher in AD, p < 0.001); (3) polyamine synthesis/catabolism (spermidine: higher in AD, p = 0.004); (4) urea cycle (N-acetyl glutamate: lower in AD, p < 0.001); (5) glutamate-aspartate metabolism (N-acetyl aspartate: lower in AD, p = 0.002); and (6) neurotransmitter metabolism (gamma-amino-butyric acid: lower in AD, p < 0.001). Utilizing three Gene Expression Omnibus (GEO) datasets, we then examined mRNA expression levels of 71 genes encoding enzymes regulating key reactions within these pathways in the entorhinal cortex (ERC; AD: n = 25; CN: n = 52) and hippocampus (AD: n = 29; CN: n = 56). Complementing our metabolomics results, our transcriptomics analyses also revealed significant alterations in gene expression levels of key enzymatic regulators of biochemical reactions linked to transmethylation and polyamine metabolism. Our study has limitations: our metabolomics assays measured only a small proportion of all metabolites participating in the pathways we examined. Our study is also cross-sectional, limiting our ability to directly test how AD progression may impact changes in metabolite concentrations or differential-gene expression. Additionally, the relatively small number of brain tissue samples may have limited our power to detect alterations in all pathway-specific metabolites and their genetic regulators. CONCLUSIONS:In this study, we observed broad dysregulation of transmethylation and polyamine synthesis/catabolism, including abnormalities in neurotransmitter signaling, urea cycle, aspartate-glutamate metabolism, and glutathione synthesis. Our results implicate alterations in cellular methylation potential and increased flux in the transmethylation pathways, increased demand on antioxidant defense mechanisms, perturbations in intermediate metabolism in the urea cycle and aspartate-glutamate pathways disrupting mitochondrial bioenergetics, increased polyamine biosynthesis and breakdown, as well as abnormalities in neurotransmitter metabolism that are related to AD.
Diurnal rhythms in the white adipose tissue transcriptome are disturbed in obese individuals with type 2 diabetes compared with lean control individuals.
Stenvers Dirk Jan,Jongejan Aldo,Atiqi Sadaf,Vreijling Jeroen P,Limonard Eelkje J,Endert Erik,Baas Frank,Moerland Perry D,Fliers Eric,Kalsbeek Andries,Bisschop Peter H
AIMS/HYPOTHESIS:Animal studies have indicated that disturbed diurnal rhythms of clock gene expression in adipose tissue can induce obesity and type 2 diabetes. The importance of the circadian timing system for energy metabolism is well established, but little is known about the diurnal regulation of (clock) gene expression in obese individuals with type 2 diabetes. In this study we aimed to identify key disturbances in the diurnal rhythms of the white adipose tissue transcriptome in obese individuals with type 2 diabetes. METHODS:In a case-control design, we included six obese individuals with type 2 diabetes and six healthy, lean control individuals. All participants were provided with three identical meals per day for 3 days at zeitgeber time (ZT, with ZT 0:00 representing the time of lights on) 0:30, 6:00 and 11:30. Four sequential subcutaneous abdominal adipose tissue samples were obtained, on day 2 at ZT 15:30, and on day 3 at ZT 0:15, ZT 5:45 and ZT 11:15. Gene expression was measured using RNA sequencing. RESULTS:The core clock genes showed reduced amplitude oscillations in the individuals with type 2 diabetes compared with the healthy control individuals. Moreover, in individuals with type 2 diabetes, only 1.8% (303 genes) of 16,818 expressed genes showed significant diurnal rhythmicity, compared with 8.4% (1421 genes) in healthy control individuals. Enrichment analysis revealed a loss of rhythm in individuals with type 2 diabetes of canonical metabolic pathways involved in the regulation of lipolysis. Enrichment analysis of genes with an altered mesor in individuals with type 2 diabetes showed decreased activity of the translation initiating pathway 'EIF2 signaling'. Individuals with type 2 diabetes showed a reduced diurnal rhythm in postprandial glucose concentrations. CONCLUSIONS/INTERPRETATION:Diurnal clock and metabolic gene expression rhythms are decreased in subcutaneous adipose tissue of obese individuals with type 2 diabetes compared with lean control participants. Future investigation is needed to explore potential treatment targets as identified by our study, including clock enhancement and induction of EIF2 signalling. DATA AVAILABILITY:The raw sequencing data and supplementary files for rhythmic expression analysis and Ingenuity Pathway Analysis have been deposited in NCBI Gene Expression Omnibus (GEO series accession number GSE104674).
Differential coexpression networks in bronchiolitis and emphysema phenotypes reveal heterogeneous mechanisms of chronic obstructive pulmonary disease.
Qin Jiangyue,Yang Ting,Zeng Ni,Wan Chun,Gao Lijuan,Li Xiaoou,Chen Lei,Shen Yongchun,Wen Fuqiang
Journal of cellular and molecular medicine
Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with multiple molecular mechanisms. To investigate and contrast the molecular processes differing between bronchiolitis and emphysema phenotypes of COPD, we downloaded the GSE69818 microarray data set from the Gene Expression Omnibus (GEO), which based on lung tissues from 38 patients with emphysema and 32 patients with bronchiolitis. Then, weighted gene coexpression network analysis (WGCNA) and differential coexpression (DiffCoEx) analysis were performed, followed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analysis (KEGG) analysis. Modules and hub genes for bronchiolitis and emphysema were identified, and we found that genes in modules linked to neutrophil degranulation, Rho protein signal transduction and B cell receptor signalling were coexpressed in emphysema. DiffCoEx analysis showed that four hub genes (IFT88, CCDC103, MMP10 and Bik) were consistently expressed in emphysema patients; these hub genes were enriched, respectively, for functions of cilium assembly and movement, proteolysis and apoptotic mitochondrial changes. In our re-analysis of GSE69818, gene expression networks in relation to emphysema deepen insights into the molecular mechanism of COPD and also identify some promising therapeutic targets.
Different epigenetic clocks reflect distinct pathophysiological features of multiple sclerosis.
Theodoropoulou Eleftheria,Alfredsson Lars,Piehl Fredrik,Marabita Francesco,Jagodic Maja
Accumulating evidence links epigenetic age to diseases and age-related conditions, but little is known about its association with multiple sclerosis (MS). We estimated epigenetic age acceleration measures using DNA methylation from blood or sorted cells of MS patients and controls. In blood, sex (p = 4.39E-05) and MS (p = 2.99E-03) explained the variation in age acceleration, and isolated blood cell types showed different epigenetic age. Intrinsic epigenetic age acceleration and extrinsic epigenetic age acceleration were only associated with sex (p = 2.52E-03 and p = 1.58E-04, respectively), while PhenoAge Acceleration displayed positive association with MS (p = 3.40E-02). Different age acceleration measures are distinctly influenced by phenotypic factors, and they might measure separate pathophysiological aspects of MS. DNA methylation data can be accessed at Gene Expression Omnibus database under accession number GSE35069, GSE43976, GSE106648, GSE130029, GSE130030.
Different Biological Pathways Are Up-regulated in the Elderly With Asthma: Sputum Transcriptomic Analysis.
Kim Byung Keun,Lee Hyun Seung,Sohn Kyoung Hee,Lee Suh Young,Cho Sang Heon,Park Heung Woo
Allergy, asthma & immunology research
BACKGROUND:Elderly asthma (EA) is increasing, but the pathogenesis is unclear. This study aimed to identify EA-related biological pathways by analyzing genome-wide gene expression profiles in sputum cells. METHODS:A total of 3,156 gene probes with significantly differential expressions between EA and healthy elderly controls were used for a hierarchical clustering of genes to identify gene clusters. Gene set enrichment analysis provided biological information, with replication from Gene Expression Omnibus expression profiles. RESULTS:Fifty-five EA patients and 10 elderly control subjects were enrolled. Two distinct gene clusters were found. Cluster 1 (n = 35) showed a lower eosinophil proportion in sputum and less severe airway obstruction compared to cluster 2 (n = 20). The replication data set also identified 2 gene clusters (clusters 1' and 2'). Among 5 gene sets significantly enriched in cluster 1 and 3 gene sets significantly enriched in cluster 2, we confirmed that 2 were significantly enriched in the replication data set (OXIDATIVE_PHOSPHORYLATION gene set in cluster 1 and EPITHELIAL MESENCHYMAL TRANSITION gene set in cluster 2'). CONCLUSIONS:The findings of 2 distinct gene clusters in EA and different biological pathways in each gene cluster suggest 2 different pathogenesis mechanisms underlying EA.
Diabetogenic Effects of Immunosuppression: An Integrative Analysis.
Bhat Mamatha,Pasini Elisa,Das Aninditee,Baciu Cristina,Angeli Marc,Humar Atul,Watt Kymberly D,Allard Johane
BACKGROUND:Posttransplant diabetes mellitus (PTDM) affects up to 50% of solid organ transplant recipients and compromises long-term outcomes. The goal of this study was to investigate how immunosuppressants affect gene expression in a manner that increases diabetes risk, by performing integrative analysis on publicly available, high-throughput gene expression data. METHODS:All high-throughput gene expression datasets of solid organ transplant recipients were retrieved from the Gene Expression Omnibus. Significantly dysregulated genes and pathways were determined, and those in common with type 2 diabetes were identified. THP-1 and HepG2 cells were exposed in vitro to tacrolimus, and validation of genes involved in insulin signaling and glucose metabolism was performed using specific arrays. These cells were then treated with the hypoglycemic agents, metformin, and insulin to assess for appropriate reversion of specific diabetogenic genes. RESULTS:Insulin signaling and secretion were the most commonly dysregulated pathways that overlapped with diabetes in transplant recipients. KRAS, GRB2, PCK2, BCL2L1, INSL3, DOK3, and PTPN1 were among the most significantly upregulated genes in both immunosuppression and diabetes subsets and were appropriately reverted by metformin as confirmed in vitro. CONCLUSIONS:We discovered that the significantly dysregulated genes in the context of immunosuppression are implicated in insulin signaling and insulin secretion, as a manifestation of pancreatic β-cell function. In vitro validation confirmed key diabetes-related genes in the context of immunosuppression. Further analysis and in vitro validation revealed that metformin optimally reverts diabetogenic genes dysregulated in the context of immunosuppression. The optimal therapeutic management of posttransplant diabetes mellitus needs to be further investigated, taking into account the mechanistic impact of immunosuppressants.
Deduction of Novel Genes Potentially Involved in Osteoblasts of Rheumatoid Arthritis Using Next-Generation Sequencing and Bioinformatic Approaches.
Chen Yi-Jen,Chang Wei-An,Hsu Ya-Ling,Chen Chia-Hsin,Kuo Po-Lin
International journal of molecular sciences
The role of osteoblasts in peri-articular bone loss and bone erosion in rheumatoid arthritis (RA) has gained much attention, and microRNAs are hypothesized to play critical roles in the regulation of osteoblast function in RA. The aim of this study is to explore novel microRNAs differentially expressed in RA osteoblasts and to identify genes potentially involved in the dysregulated bone homeostasis in RA. RNAs were extracted from cultured normal and RA osteoblasts for sequencing. Using the next generation sequencing and bioinformatics approaches, we identified 35 differentially expressed microRNAs and 13 differentially expressed genes with potential microRNA-mRNA interactions in RA osteoblasts. The 13 candidate genes were involved mainly in cell-matrix adhesion, as classified by the Gene Ontology. Two genes of interest identified from RA osteoblasts, A-kinase anchoring protein 12 () and leucin rich repeat containing 15 (), were found to express more consistently in the related RA synovial tissue arrays in the Gene Expression Omnibus database, with the predicted interactions with miR-183-5p and miR-146a-5p, respectively. The Ingenuity Pathway Analysis identified as one of the genes involved in protein kinase A signaling and the function of chemotaxis, interconnecting with molecules related to neovascularization. The findings indicate new candidate genes as the potential indicators in evaluating therapies targeting chemotaxis and neovascularization to control joint destruction in RA.
Deciphering psoriasis. A bioinformatic approach.
Melero Juan L,Andrades Sergi,Arola Lluís,Romeu Antoni
Journal of dermatological science
BACKGROUND:Psoriasis is an immune-mediated, inflammatory and hyperproliferative disease of the skin and joints. The cause of psoriasis is still unknown. The fundamental feature of the disease is the hyperproliferation of keratinocytes and the recruitment of cells from the immune system in the region of the affected skin, which leads to deregulation of many well-known gene expressions. OBJECTIVE:Based on data mining and bioinformatic scripting, here we show a new dimension of the effect of psoriasis at the genomic level. METHODS:Using our own pipeline of scripts in Perl and MySql and based on the freely available NCBI Gene Expression Omnibus (GEO) database: DataSet Record GDS4602 (Series GSE13355), we explore the extent of the effect of psoriasis on gene expression in the affected tissue. RESULTS:We give greater insight into the effects of psoriasis on the up-regulation of some genes in the cell cycle (CCNB1, CCNA2, CCNE2, CDK1) or the dynamin system (GBPs, MXs, MFN1), as well as the down-regulation of typical antioxidant genes (catalase, CAT; superoxide dismutases, SOD1-3; and glutathione reductase, GSR). We also provide a complete list of the human genes and how they respond in a state of psoriasis. CONCLUSION:Our results show that psoriasis affects all chromosomes and many biological functions. If we further consider the stable and mitotically inheritable character of the psoriasis phenotype, and the influence of environmental factors, then it seems that psoriasis has an epigenetic origin. This fit well with the strong hereditary character of the disease as well as its complex genetic background.
, and Affect the Development of Chronic Obstructive Pulmonary Disease.
Yang Danlei,Yan Ying,Hu Fen,Wang Tao
International journal of chronic obstructive pulmonary disease
Purpose:Chronic obstructive pulmonary disease (COPD) is a progressive lung disease characterized by poor airflow. The purpose of this study was to explore the mechanisms involved in the development of COPD. Patients and Methods:The mRNA expression profile GSE100281, consisting of 79 COPD and 16 healthy samples, was acquired from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) between COPD samples and healthy samples were analyzed using the limma package. Functional enrichment analysis for the DEGs was carried out using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool. Furthermore, DEG-compound pairs were predicted using the Comparative Toxicogenomics Database. The KEGG metabolite IDs corresponding to the compounds were also obtained through the MetaboAnalyst pipeline. Based on the diffusion algorithm, the metabolite network was constructed. Finally, the expression levels of key genes were determined using quantitative PCR (qPCR). Results:There were 594 DEGs identified between the COPD and healthy samples, including 242 upregulated and 352 downregulated genes. A total of 696 DEG-compound pairs, such as -C00469 (ethanol) and -C00389 (quercetin) pairs, were predicted. , and were included in the top 10 DEG-compound pairs. Additionally, 57 metabolites were obtained. In particular, hsa04750 (inflammatory mediator regulation of TRP channels)-C00469 (ethanol) and hsa04152 (AMPK signaling pathway)-C00389 (quercetin) pairs were found in the metabolite network. The results of qPCR showed that the expression of , and was consistent with that predicted using bioinformatic analysis. Conclusion:, and may play important functions in the development and progression of COPD.
Curcumin Modulates DNA Methyltransferase Functions in a Cellular Model of Diabetic Retinopathy.
Maugeri Andrea,Mazzone Maria Grazia,Giuliano Francesco,Vinciguerra Manlio,Basile Guido,Barchitta Martina,Agodi Antonella
Oxidative medicine and cellular longevity
Hyperglycaemia-induced oxidative stress appears to be involved in the aetiology of diabetic retinopathy (DR), a major public health issue, via altering DNA methylation process. We investigated the effect of hyperglycaemia on retinal DNA methyltransferase (DNMT) expression in diabetic mice, using Gene Expression Omnibus datasets. We also evaluated the effect of curcumin both on high glucose-induced reactive oxygen species (ROS) production and altered DNMT functions, in a cellular model of DR. We observed that three months of hyperglycaemia, in insulin-deficient Ins2 mice, decrease DNMT1 and DNMT3a expression levels. In retinal pigment epithelium (RPE) cells, we also demonstrated that high glucose-induced ROS production precedes upregulation of DNMT expression and activity, suggesting that changes in DNMT function could be mediated by oxidative stress via a potential dual effect. The early effect results in decreased DNMT activity, accompanied by the highest ROS production, while long-term oxidative stress increases DNMT activity and DNMT1 expression. Interestingly, treatment with 25 M curcumin for 6 hours restores ROS production, as well as DNMT functions, altered by the exposure of RPE to acute and chronic high glucose concentration. Our study suggests that curcumin may represent an effective antioxidant compound against DR, via restoring oxidative stress and DNMT functions, though further studies are recommended.
Construction of asthma related competing endogenous RNA network revealed novel long non-coding RNAs and potential new drugs.
Liao Yifang,Li Ping,Wang Yanxia,Chen Hong,Ning Shangwei,Su Dongju
BACKGROUND:Asthma is a heterogeneous disease characterized by chronic airway inflammation. Long non-coding RNA can act as competing endogenous RNA to mRNA, and play significant role in many diseases. However, there is little known about the profiles of long non-coding RNA and the long non-coding RNA related competing endogenous RNA network in asthma. In current study, we aimed to explore the long non-coding RNA-microRNA-mRNA competing endogenous RNA network in asthma and their potential implications for therapy and prognosis. METHODS:Asthma-related gene expression profiles were downloaded from the Gene Expression Omnibus database, re-annotated with these genes and identified for asthma-associated differentially expressed mRNAs and long non-coding RNAs. The long non-coding RNA-miRNA interaction data and mRNA-miRNA interaction data were downloaded using the starBase database to construct a long non-coding RNA-miRNA-mRNA global competing endogenous RNA network and extract asthma-related differentially expressed competing endogenous RNA network. Finally, functional enrichment analysis and drug repositioning of asthma-associated differentially expressed competing endogenous RNA networks were performed to further identify key long non-coding RNAs and potential therapeutics associated with asthma. RESULTS:This study constructed an asthma-associated competing endogenous RNA network, determined 5 key long non-coding RNAs (MALAT1, MIR17HG, CASC2, MAGI2-AS3, DAPK1-IT1) and identified 8 potential new drugs (Tamoxifen, Ruxolitinib, Tretinoin, Quercetin, Dasatinib, Levocarnitine, Niflumic Acid, Glyburide). CONCLUSIONS:The results suggested that long non-coding RNA played an important role in asthma, and these novel long non-coding RNAs could be potential therapeutic target and prognostic biomarkers. At the same time, potential new drugs for asthma treatment have been discovered through drug repositioning techniques, providing a new direction for the treatment of asthma.
Computational systems biology approach to identify novel pharmacological targets for diabetic retinopathy.
Platania Chiara Bianca Maria,Leggio Gian Marco,Drago Filippo,Salomone Salvatore,Bucolo Claudio
Diabetic retinopathy was included by the World Health Organization in the eye disease priority list. Up to now, only proliferative diabetic retinopathy can be treated with approved drugs, such as intravitreal anti-vascular endothelial growth factor (VEGF) agents or steroids. In this perspective, there is the urgent need to explore novel pharmacological targets for treatment of diabetic retinopathy. Drug discovery todays exploits the noticeable ability of computational systems biology methods to identify novel drug targets in complex pathologies bearing multifactorial etiology and wide and varying symptomatology. This is especially true for diseases, where the identification of specific molecular mechanisms, and thus drug targets, is a challenging, when not impossible, task. Within this framework, we applied a systems biology approach to identify novel drug targets for diabetic retinopathy. The complexity of diabetic retinopathy was investigated through the analysis of transcriptomics data, retrieved from Gene Expression Omnibus Dataset repository (GEO) datasets. Analysis of GEO datasets was carried out with an enrichment-information approach, which gave as output a series of complex gene-pathway and drug-gene networks. Analysis of these networks identified genes and biological pathways related with inflammation, fibrosis and G protein-coupled receptors that are potentially involved in development of the disease. This analysis provided new clues on novel pharmacological targets, useful to treat diabetic retinopathy.
Comprehensive bioinformatics analysis of trabecular meshwork gene expression data to unravel the molecular pathogenesis of primary open-angle glaucoma.
Liesenborghs Ilona,Eijssen Lars M T,Kutmon Martina,Gorgels Theo G M F,Evelo Chris T,Beckers Henny J M,Webers Carroll A B,Schouten Johannes S A G
PURPOSE:Performing bioinformatics analyses using trabecular meshwork (TM) gene expression data in order to further elucidate the molecular pathogenesis of primary open-angle glaucoma (POAG), and to identify candidate target genes. METHODS:A systematic search in Gene Expression Omnibus and ArrayExpress was conducted, and quality control and preprocessing of the data was performed with ArrayAnalysis.org. Molecular pathway overrepresentation analysis was performed with PathVisio using pathway content from three pathway databases: WikiPathways, KEGG and Reactome. In addition, Gene Ontology (GO) analysis was performed on the gene expression data. The significantly changed pathways were clustered into functional categories which were combined into a network of connected genes. RESULTS:Ninety-two significantly changed pathways were clustered into five functional categories: extracellular matrix (ECM), inflammation, complement activation, senescence and Rho GTPase signalling. ECM included pathways involved in collagen, actin and cell-matrix interactions. Inflammation included pathways entailing NF-κB and arachidonic acid. The network analysis showed that several genes overlap between the inflammation cluster on the one hand, and the ECM, complement activation and senescence clusters on the other hand. GO analysis, identified additional clusters, related to development and corticosteroids. CONCLUSION:This study provides an overview of the processes involved in the molecular pathogenesis of POAG in the TM. The results show good face validity and confirm findings from histological, biochemical, genome-wide association and transcriptomics studies. The identification of known points of action for drugs, such as Rho GTPase, arachidonic acid, NF-κB, prostaglandins and corticosteroid clusters, supports the value of this approach to identify potential drug targets.
Comprehensive analysis of aberrantly expressed profiles of messenger RNA in alcoholic liver disease.
Sun Jinhui,Li Baolong,Sun Antao,Zhao Kunpeng,Ma Yanchun,Zhao Jiuli,Pan Hui,Song Qingrui,Wang Yan,Yu Chunyu,Wang Cui,Zhang Huan,Zhang Wenwen,Kong Chenfan
Journal of cellular biochemistry
BACKGROUND:Alcoholic liver disease (ALD) is one of the major cause of morbidity and mortality of clinical liver disease worldwide. Until today, although many general therapies are carried out and several molecular targets have been proposed to act as the potential therapeutic targets, more accurate molecular targets and more effective therapeutic methods remain needed. MATERIAL AND METHODS:In the study, we analyze the differential expression genes (DEGs) between the patients with ALD and healthy controls. Gene Ontology enrichment and KEGG signaling pathway analysis are performed to identify the function of DEGs. Some significant molecules are proposed to act as the potential therapeutic targets for ALD. RNA data of 15 ALD tissues and 7 normal tissues for RNA expression analysis were obtained. DEGs in ALD samples compared with normal tissues identified through the limma R package and subjected to network analysis. RESULTS:As a result, we obtained a total of 274 DEGs that mainly involved in biological processes related to the angiogenesis, stress reaction, synthesis, and metabolism of organic acids. Network analysis obtained several genes with high network degree and fold change. Some significant molecules are proposed to act as the potential therapeutic targets for ALD. CONCLUSIONS:Our research identified some new progression-related genes of alcohol liver diseases, which could be regarded as the new targets for the early diagnosis and therapeutic management in ALD.
Comprehensive analyses of DNA methylation and gene expression profiles of Kawasaki disease.
Chang Danqi,Qian Cheng,Li Hang,Feng Hong
Journal of cellular biochemistry
OBJECTIVE:Kawasaki disease (KD) is a childhood febrile vasculitis with unknown etiology. Epigenetic regulation in the gene expression dynamics has become increasingly important in KD. Thus, we performed an integrated analysis of DNA methylation and gene expression data to identify novel molecular mechanisms and key functional genes in KD. METHODS:DNA methylation (GSE84624) and gene expression (GSE68004) datasets were downloaded from Gene Expression Omnibus. Methylated-differentially expressed genes (mDEGs) were documented as the overlapping genes between the differentially methylated genes (DMGs) in GSE84624 and differentially expressed genes (DEGs) in GSE68004. Functional enrichment analyses of the mDEGs were conducted using DAVID database. Protein-protein interaction (PPI) network was then constructed to obtain the hub genes involved in KD using STRING database. RESULTS:A total of 1389 DMGs and 1362 DEGs were screened out between KD and control samples. Overlapping of them resulted in four hypermethylated/downregulated and 187 hypomethylated/upregulated genes. These mDEGs were mainly enriched in inflammation response, innate immune response, and blood coagulation, and signaling pathways such as platelet activation, osteoclast differentiation, and chemokine signaling pathway. PPI network analyses identified MAPK14 and PHLPP1 as the hub genes involved in KD, which could distinguish KD from other common pediatric febrile diseases. In addition, the methylation and expression levels of MAPK14 and PHLPP1 were validated in other independent datasets. CONCLUSION:This study provides an integrated view of interactions among DNA methylation and gene expression in patients with KD. MAPK14 and PHLPP1 are the key genes influenced by methylation and may serve as candidate biomarkers for KD.
Clinical value of ARG1 in acute myocardial infarction patients: Bioinformatics-based approach.
Zhang Rui,Ji Zhenjun,Qu Yangyang,Yang Mingming,Su Yamin,Zuo Wenjie,Zhao Qingyou,Ma Genshan,Li Yongjun
Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
BACKGROUND:In this study, we aimed to explore key genes as biomarker for diagnosis AMI through using Bioinformatics tools. METHODS:GSE4648 and GSE60993 were downloaded from Gene Expression Omnibus (GEO). DEGs in GSE4648 and GSE60993 were selected to run GO enrichment, KEGG pathway, and PPI network. Hub genes in DEGS of GSE4648 and GSE60993 were selected out according to Molecular Complex Detection (MCODE) and overlapping genes were further screened out. Finally, the most important gene of coincide genes was used for deeper clinical study of patients with AMI. RESULTS:A total of 41 and 173 DEGs were screened out in GSE4648 and GSE60993 respectively. GO and KEGG analysis showed similar biological process, cellular Component and molecular function of these two group DEGs. PPI network of these two group DEGs were built and 19 key genes of GSE4648 were selected out according to MCODE, while 48 key genes of GSE60993 were selected out. Overlapping genes of these 19 and 48 genes included PLAUR, ARG1, FOS, and IL1R2, and fold change (FC) of ARG1 was the biggest. Therefore, ARG1 was detected in 46 controls and 115 AMI patients by ELISA, and ARG1 was significantly upregulated in AMI group. Pearson correlation analysis indicated ARG1 was positive correlated with gensini score (R = 0.378). ROC curve revealed that area under ROC curve (AUC) of ARG1 was 77.6%. CONCLUSION:Therefore, ARG1 might play an important role in the development of AMI and could be used as biomarker of AMI.
Circulating miR-3659 may be a potential biomarker of dyslipidemia in patients with obesity.
Miao Liu,Yin Rui-Xing,Pan Shang-Ling,Yang Shuo,Yang De-Zhai,Lin Wei-Xiong
Journal of translational medicine
BACKGROUND:The present study attempted to identify potential key genes and miRNAs of dyslipidemia in obese, and to investigate the possible mechanisms associated with them. METHODS:The microarray data of GSE66676 were downloaded, including 67 obese samples from the Gene Expression Omnibus (GEO) database. The weighted gene co-expression network (WGCNA) analysis was performed using WGCNA package and grey60 module was considered as the highest correlation. Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for this module were performed by clusterProfiler and DOSE package. A protein-protein interaction (PPI) network was established using Cytoscape software, and significant modules were analyzed using molecular complex detection. RESULTS:Collagen type I alpha 1 chain gene (COL1A1) had the best significant meaning. After bioinformatic analysis, we identified four miRNAs (hsa-miR-3659, hsa-miR-4658, hsa-miR151a-5p and hsa-miR-151b) which can bind SNPs in 3'UTR in COL1A1. After validation with RT-qPCR, only two miRNAs (hsa-miR-3659 and hsa-miR151a-5p) had statistical significance. CONCLUSIONS:The area of 0.806 for miR-3659 and 0.769 for miR-151a-5p under the ROC curve (AUC) may have good diagnostic value for dyslipidemia. Circulating miR-3659 may be a potential biomarker of dyslipidemia in patients with obesity.
Choroid plexus genes for CSF production and brain homeostasis are altered in Alzheimer's disease.
Kant Shawn,Stopa Edward G,Johanson Conrad E,Baird Andrew,Silverberg Gerald D
Fluids and barriers of the CNS
BACKGROUND:The roles of the choroid plexus (CP) and cerebrospinal fluid (CSF) production have drawn increasing attention in Alzheimer's disease (AD) research. Specifically, studies document markedly decreased CSF production and turnover in moderate-to-severe AD. Moreover, reduced CP function and CSF turnover lead to impaired clearance of toxic metabolites, likely promote neuroinflammation, and may facilitate neuronal death during AD progression. We analyzed CP gene expression in AD compared with control subjects, specifically considering those genes involved with CSF production and CP structural integrity. METHODS:The Brown-Merck Gene Expression Omnibus (GEO) database (CP transcripts) was mined to examine changes in gene expression in AD compared to controls with a focus on assorted genes thought to play a role in CSF production. Specifically, genes coding for ion transporters in CP epithelium (CPE) and associated enzymes like Na-K-ATPase and carbonic anhydrase, aquaporins, mitochondrial transporters/enzymes, blood-cerebrospinal fluid barrier (BCSFB) stability proteins, and pro-inflammatory mediators were selected for investigation. Data were analyzed using t test p-value and fold-change analysis conducted by the GEO2R feature of the GEO database. RESULTS:Significant expression changes for several genes were observed in AD CP. These included disruptions to ion transporters (e.g., the solute carrier gene SLC4A5, p = 0.004) and associated enzyme expressions (e.g., carbonic anhydrase CA4, p = 0.0001), along with decreased expression of genes involved in BCSFB integrity (e.g., claudin CLDN5, p = 0.039) and mitochondrial ATP synthesis (e.g., adenosine triphosphate ATP5L, p = 0.0004). Together all changes point to disrupted solute transport at the blood-CSF interface in AD. Increased expression of pro-inflammatory (e.g., interleukin IL1RL1, p = 0.00001) and potential neurodegenerative genes (e.g., amyloid precursor APBA3, p = 0.002) also implicate disturbed CP function. CONCLUSIONS:Because the altered expression of numerous transcripts in AD-CP help explain decreased CSF production in AD, these findings represent a first step towards identifying novel therapeutic targets in AD.
Central and Peripheral Changes in FOS Expression in Schizophrenia Based on Genome-Wide Gene Expression.
Huang Jing,Liu Fangkun,Wang Bolun,Tang Hui,Teng Ziwei,Li Lehua,Qiu Yan,Wu Haishan,Chen Jindong
Frontiers in genetics
Schizophrenia is a chronic, debilitating neuropsychiatric disorder. Multiple transcriptomic gene expression profiling analysis has been used to identify schizophrenia-associated genes, unravel disease-associated biomarkers, and predict clinical outcomes. We aimed to identify gene expression regulation, underlying pathways, and their roles in schizophrenia pathogenesis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of fibroblasts, lymphoblasts, and post-mortem brains of schizophrenia patients. Our analysis demonstrated high FOS expression in non-neural peripheral samples and low FOS expression in brain tissues of schizophrenia patients compared with healthy controls. FOS exhibited predictive value for schizophrenia patients in these datasets. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that "amphetamine addiction" was among the top 10 significantly enriched KEGG pathways. FOS and FOSB, which are implicated in the amphetamine addiction pathway, were up-regulated in schizophrenia fibroblast samples. Protein-protein interaction (PPI) network analysis revealed that proteins closely interacting with FOS-encoded protein were also involved in the amphetamine addiction pathway. Pearson correlation test indicated that FOS showed positive correlation with genes in the amphetamine pathway. The results revealed that FOS was acceptable as a biomarker for schizophrenia and may be involved in schizophrenia pathogenesis.
Bioinformatics-based identification of potential microRNA biomarkers in frequent and non-frequent exacerbators of COPD.
Liu Xiao,Qu Jingge,Xue Weixiao,He Liangai,Wang Jun,Xi Xuejiao,Liu Xiaoxia,Yin Yunhong,Qu Yiqing
International journal of chronic obstructive pulmonary disease
Objectives:MicroRNAs (miRNAs) play essential roles in the development of COPD. In this study, we aimed to identify and validate potential miRNA biomarkers in frequent and non-frequent exacerbators of COPD patients using bioinformatic analysis. Materials and methods:The candidate miRNA biomarkers in COPD were screened from Gene Expression Omnibus (GEO) dataset and identified using GEO2R online tool. Then, we performed bioinformatic analyses including target prediction, gene ontology (GO), pathway enrichment analysis and construction of protein-protein interaction (PPI) network. Furthermore, the expression of the identified miRNAs in peripheral blood monocular cells (PBMCs) of COPD patients was validated using quantitative real-time polymerase chain reaction (qRT-PCR). Results:MiR-23a, miR-25, miR-145 and miR-224 were identified to be significantly downregulated in COPD patients compared with healthy controls. GO analysis showed the four miRNAs involved in apoptotic, cell differentiation, cell proliferation and innate immune response. Pathway analysis showed that the targets of these miRNAs were associated with p53, TGF-β, Wnt, VEGF and MAPK signal pathway. In healthy controls, the miR-25 and miR-224 levels were significantly decreased in smokers compared with nonsmokers (<0.001 and <0.05, respectively). In COPD patients, the levels of miR-23a, miR-25, miR-145 and miR-224 were associated with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages. Notably, miR-23a and miR-145 were significantly elevated in non-frequent exacerbators compared with frequent exacerbators (<0.05), and miR-23a showed higher area under the receiver-operator characteristic curve (AUROC) than miR-145 (0.707 vs 0.665, <0.05). Conclusion:MiR-23a, miR-25, miR-145 and miR-224 were associated with the development of COPD, and miR-23a might be a potential biomarker for discriminating the frequent exacerbators from non-frequent exacerbators.
Bioinformatics Analysis of Weighted Genes in Diabetic Retinopathy.
You Zhi-Peng,Zhang Yu-Lan,Li Bing-Yang,Zhu Xin-Gen,Shi Ke
Investigative ophthalmology & visual science
Purpose:Intricate signaling networks and transcriptional regulators translate pathogen recognition into defense responses. The aim of this study was to identify the weighted genes involved in diabetic retinopathy (DR) in different rodent models of diabetes. Methods:We performed a gene coexpression analysis of publicly available microarray data, namely, the GSE19122 dataset from the Gene Expression Omnibus database. We conducted gene coexpression analysis on the microarray data to identify modules of functionally related coexpressed genes that are differentially expressed in different rodent models. We leveraged a richly curated expression dataset and used weighted gene coexpression network analysis to construct an undirected network. We screened 30 genes in the most closely related module. A protein-protein interaction network was constructed for the genes in the most related module using the Search Tool for the Retrieval of Interacting Genes. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed for the 30 genes. Results:Five visual perception-related genes (Pde6g, Guca1a, Rho, Sag, and Prph2) were significantly upregulated. Based on the competing endogenous RNA hypothesis, a link between the long noncoding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) and visual perception-related mRNAs was constructed using bioinformatics tools. Six potential microRNAs (miR-155-5p, miR-1a-3p, miR-122-5p, miR-223-3p, miR-125b-5p, and miR-124-3p) were also screened. Conclusions:MALAT1 might play important roles in DR by regulating Sag and Guca1a through miR-124-3p and regulating Pde6g through miR-125b-5p.
Bioinformatics Analysis Identifies p53 as a Candidate Prognostic Biomarker for Neuropathic Pain.
Gao Yibo,Sun Na,Wang Lieju,Wu Ying,Ma Longfei,Hong Juncong,Ren Jinxuan,Zhu Bin,Yu Lina,Yan Min
Frontiers in genetics
Neuropathic pain (NP) is a type of chronic pain that is different from the common type of pain. The mechanisms of NP are still poorly understood. Exploring the key genes and neurobiological changes in NP could provide important diagnostic and treatment tools for clinicians. GSE24982 is an mRNA-seq dataset that we downloaded from the Gene Expression Omnibus database to identify key genes in NP. Differentially expressed genes (DEGs) were identified using the BRB-ArrayTools software and R. Functional and pathway enrichment analyses of the DEGs were performed using Metascape. A protein-protein interaction network was created and visualized using Cytoscape. A total of 123 upregulated DEGs were obtained. Among these genes, p53 was the node with the highest degree; hence, we validated it experimentally using a chronic constriction injury mouse model. Our results showed that overexpression of the p53 gene, and the subsequent increase in caspase-3 expression, in dorsal root ganglion neurons led to increased apoptotic changes in these neurons. p53 may therefore be partly responsible for the development of chronic constriction injury-induced NP.
Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke.
Zou Rongjun,Zhang Dingwen,Lv Lei,Shi Wanting,Song Zijiao,Yi Bin,Lai Bingjia,Chen Qian,Yang Songran,Hua Ping
Journal of translational medicine
BACKGROUND:Atrial fibrillation (AF) is one of the most prevalent sustained arrhythmias, however, epidemiological data may understate its actual prevalence. Meanwhile, AF is considered to be a major cause of ischemic strokes due to irregular heart-rhythm, coexisting chronic vascular inflammation, and renal insufficiency, and blood stasis. We studied co-expressed genes to understand relationships between atrial fibrillation (AF) and stroke and reveal potential biomarkers and therapeutic targets of AF-related stroke. METHODS:AF-and stroke-related differentially expressed genes (DEGs) were identified via bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE79768 and GSE58294, respectively. Subsequently, extensive target prediction and network analyses methods were used to assess protein-protein interaction (PPI) networks, Gene Ontology (GO) terms and pathway enrichment for DEGs, and co-expressed DEGs coupled with corresponding predicted miRNAs involved in AF and stroke were assessed as well. RESULTS:We identified 489, 265, 518, and 592 DEGs in left atrial specimens and cardioembolic stroke blood samples at < 3, 5, and 24 h, respectively. LRRK2, CALM1, CXCR4, TLR4, CTNNB1, and CXCR2 may be implicated in AF and the hub-genes of CD19, FGF9, SOX9, GNGT1, and NOG may be associated with stroke. Finally, co-expressed DEGs of ZNF566, PDZK1IP1, ZFHX3, and PITX2 coupled with corresponding predicted miRNAs, especially miR-27a-3p, miR-27b-3p, and miR-494-3p may be significantly associated with AF-related stroke. CONCLUSION:AF and stroke are related and ZNF566, PDZK1IP1, ZFHX3, and PITX2 genes are significantly associated with novel biomarkers involved in AF-related stroke.
Bioinformatic Analysis Identifies Potential Key Genes in the Pathogenesis of Turner Syndrome.
Wang Hao,Zhu Hui,Zhu Wenjiao,Xu Yue,Wang Nan,Han Bing,Song Huaidong,Qiao Jie
Frontiers in endocrinology
Turner syndrome (TS) is a sex chromosome aneuploidy with a variable spectrum of symptoms including short stature, ovarian failure and skeletal abnormalities. The etiology of TS is complex, and the mechanisms driving its pathogenesis remain unclear. In our study, we used the online Gene Expression Omnibus (GEO) microarray expression profiling dataset GSE46687 to identify differentially expressed genes (DEGs) between monosomy X TS patients and normal female individuals. The relevant data on 26 subjects with TS (45,XO) and 10 subjects with the normal karyotype (46,XX) was investigated. Then, tissue-specific gene expression, functional enrichment, and protein-protein interaction (PPI) network analyses were performed, and the key modules were identified. In total, 25 upregulated and 60 downregulated genes were identified in the differential expression analysis. The tissue-specific gene expression analysis of the DEGs revealed that the system with the most highly enriched tissue-specific gene expression was the hematologic/immune system, followed by the skin/skeletal muscle and neurologic systems. The PPI network analysis, construction of key modules and manual screening of tissue-specific gene expression resulted in the identification of the following five genes of interest: , and . and are involved in the hematologic/immune system, and are related to the circulatory system, and is related to skeletal abnormalities. In addition, several genes of interest with possible roles in the pathogenesis of TS were identified as being associated with the hematologic/immune system or metabolism. This discovery-driven analysis may be a useful method for elucidating novel mechanisms underlying TS. However, more experiments are needed to further explore the relationships between these genes and TS in the future.
Analysis of gene expression and methylation datasets identified ADAMTS9, FKBP5, and PFKBF3 as biomarkers for osteoarthritis.
Li ZhaoFang,Zhang RongQiang,Yang XiaoLi,Zhang DanDan,Li BaoRong,Zhang Di,Li Qiang,Xiong YongMin
Journal of cellular physiology
BACKGROUND:Osteoarthritis (OA) is a kind of chronic osteoarthropathy and degenerative joint disease. Epigenetic regulation in the gene expression dynamics has become increasingly important in OA. We performed a combined analysis of two types of microarray datasets (gene expression and DNA methylation) to identify methylation-based key biomarkers to provide a better understanding of molecular biological mechanisms of OA. METHODS:We obtained two expression profiling datasets (GSE55235, GSE55457) and one DNA methylation profiling data set (GSE63695) from the Gene Expression Omnibus. First, differentially expressed genes (DEGs) between patients with OA and controls were identified using the Limma package in R(v3.4.4). Then, function enrichment analysis of DEGs was performed using a DAVID database. For DNA methylation datasets, ChAMP methylation analysis package was used to identify differential methylation genes (DMGs). Finally, a comprehensive analysis of DEGs and DMGs was conducted to identify genes that exhibited differential expression and methylation simultaneously. RESULTS:We identified 112 DEGs and 2,896 DMGs in patients with OA compared with controls. Functional analysis of DEGs obtained that inflammatory responses, immune responses, and positive regulation of apoptosis, tumor necrosis factor (TNF) signaling pathway, and osteoclast differentiation may be involved in the pathogenesis of OA. Cross-analysis revealed 26 genes that exhibited differential expression and methylation in OA. Among them, ADAMTS9, FKBP5, and PFKBF3 were identified as valuable methylation-based biomarkers for OA. CONCLUSION:In summary, our study identified different molecular features between patients with OA and controls. This may provide new clues for clarifying the pathogenetic mechanisms of OA.
Analysis of differentially expressed genes in rheumatoid arthritis and osteoarthritis by integrated microarray analysis.
Journal of cellular biochemistry
BACKGROUND:Rheumatoid arthritis (RA) and osteoarthritis (OA) were two major types of joint diseases. This study aimed to explore the mechanism underlying OA and RA and analyze their difference by integrated analysis of multiple gene expression data sets. METHODS:Gene expression data sets of RA and OA were downloaded from The Gene Expression Omnibus. Shared and specific differentially expressed genes (DEGs) in RA and OA were identified by integrated analysis of multiple gene expression data sets. Functional annotation and protein-protein interaction (PPI) network construction of OA- and RA-specific DEGs were performed to further explore the molecular mechanisms underlying RA and OA and analyze the mechanism differences between them. RESULTS:Compared with normal controls, 3757 and 2598 DEGs were identified in RA and OA, respectively. Among them, 2176 DEGs were RA-specific DEGs and 1017 DEGs were OA-specific DEGs. Moreover, the expression of 17 DEGs played opposite pattern in RA and OA compared with normal controls. Chemokine signaling pathway and oxidative phosphorylation were significantly enriched pathways for RA- and OA-specific DEGs, respectively. BIRC2 and CSNK1E were respective hub genes of RA- and OA-specific PPI network. CONCLUSION:Our findings provided clues for the specific mechanism and developing specific biomarkers for RA and OA.
Analysis of Differentially Expressed Genes in Coronary Artery Disease by Integrated Microarray Analysis.
Balashanmugam Meenashi Vanathi,Shivanandappa Thippeswamy Boreddy,Nagarethinam Sivagurunathan,Vastrad Basavaraj,Vastrad Chanabasayya
Coronary artery disease (CAD) is a major cause of end-stage cardiac disease. Although profound efforts have been made to illuminate the pathogenesis, the molecular mechanisms of CAD remain to be analyzed. To identify the candidate genes in the advancement of CAD, microarray dataset GSE23766 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified, and pathway and gene ontology (GO) enrichment analyses were performed. The protein-protein interaction network was constructed and the module analysis was performed using the Biological General Repository for Interaction Datasets (BioGRID) and Cytoscape. Additionally, target genes-miRNA regulatory network and target genes-TF regulatory network were constructed and analyzed. There were 894 DEGs between male human CAD samples and female human CAD samples, including 456 up regulated genes and 438 down regulated genes. Pathway enrichment analyses revealed that DEGs (up and down regulated) were mostly enriched in the superpathway of steroid hormone biosynthesis, ABC transporters, oxidative ethanol degradation III and Complement and coagulation cascades. Similarly, geneontology enrichment analyses revealed that DEGs (up and down regulated) were mostly enriched in the forebrain neuron differentiation, filopodium membrane, platelet degranulation and blood microparticle. In the PPI network and modules (up and down regulated), MYC, NPM1, TRPC7, UBC, FN1, HEMK1, IFT74 and VHL were hub genes. In the target genes-miRNA regulatory network and target genes-TF regulatory network (up and down regulated), TAOK1, KHSRP, HSD17B11 and PAH were target genes. In conclusion, the pathway and GO ontology enriched by DEGs may reveal the molecular mechanism of CAD. Its hub and target genes, MYC, NPM1, TRPC7, UBC, FN1, HEMK1, IFT74, VHL, TAOK1, KHSRP, HSD17B11 and PAH were expected to be new targets for CAD. Our finding provided clues for exploring molecular mechanism and developing new prognostics, diagnostic and therapeutic strategies for CAD.
An Investigation about Gene Modules Associated with hDPSC Differentiation for Adolescents.
Xu Wenjing,Li Jianqiang,Li Juan,Yang Ji-Jiang,Wang Qing,Liu Bo,Qiu Weiliang
Stem cells international
Dental pulp stem cells (DPSCs) have the property of self-renewal and multidirectional differentiation so that they have the potential for future regenerative therapy of various diseases. The latest breakthrough in the biology of stem cells and the development of regenerative biology provides an effective strategy for regenerative therapy. However, in the medium promoting differentiation during long-term passage, DPSCs would lose their differentiation capability. Some efforts have been made to find genes influencing human DPSC (hDPSC) differentiation based on hDPSCs isolated from adults. However, hDPSC differentiation is a very complex process, which involves multiple genes and multielement interactions. The purpose of this study is to detect sets of correlated genes (i.e., gene modules) that are associated to hDPSC differentiation at the crown-completed stage of the third molars, by using weighted gene coexpression network analysis (WGCNA). Based on the gene expression dataset GSE10444 from Gene Expression Omnibus (GEO), we identified two significant gene modules: yellow module (742 genes) and salmon module (9 genes). The WEB-based Gene SeT AnaLysis Toolkit showed that the 742 genes in the yellow module were enriched in 59 KEGG pathways (including Wnt signaling pathway), while the 9 genes in the salmon module were enriched in one KEGG pathway (neurotrophin signaling pathway). There were 660 (7) genes upregulated at P10 and 82 (2) genes downregulated at P10 in the yellow (salmon) module. Our results provide new insights into the differentiation capability of hDPSCs.
An integrated transcriptomic analysis of autism spectrum disorder.
He Yi,Zhou Yuan,Ma Wei,Wang Juan
Autism spectrum disorder (ASD) is not a single disease but a set of disorders. To find clues of ASD pathogenesis in transcriptomic data, we performed an integrated transcriptomic analysis of ASD. After screening based on several standards in Gene Expression Omnibus (GEO) database, we obtained 11 series of transcriptomic data of different human tissues of ASD patients and healthy controls. Multidimensional scaling analysis revealed that datasets from the same tissue had bigger similarity than from different tissues. Functional enrichment analysis demonstrated that differential expressed genes were significantly enriched in inflammation/immune response, mitochondrion-related function and oxidative phosphorylation. Interestingly, genes enriched in inflammation/immune response were up-regulated in the brain tissues and down-regulated in the blood. In addition, drug prediction provided several compounds which might reverse gene expression profiles of ASD patients. And we also replicated the methods and criteria of transcriptomic analysis with datasets of ASD animal models and healthy controls, the results from animal models consolidated the results of transcriptomic analysis of ASD human tissues. In general, the results of our study may provide researchers a new sight of understanding the etiology of ASD and clinicians the possibilities of developing medical therapies.
Alzheimer's disease master regulators analysis: search for potential molecular targets and drug repositioning candidates.
Vargas D M,De Bastiani M A,Zimmer E R,Klamt F
Alzheimer's research & therapy
BACKGROUND:Alzheimer's disease (AD) is a multifactorial and complex neuropathology that involves impairment of many intricate molecular mechanisms. Despite recent advances, AD pathophysiological characterization remains incomplete, which hampers the development of effective treatments. In fact, currently, there are no effective pharmacological treatments for AD. Integrative strategies such as transcription regulatory network and master regulator analyses exemplify promising new approaches to study complex diseases and may help in the identification of potential pharmacological targets. METHODS:In this study, we used transcription regulatory network and master regulator analyses on transcriptomic data of human hippocampus to identify transcription factors (TFs) that can potentially act as master regulators in AD. All expression profiles were obtained from the Gene Expression Omnibus database using the GEOquery package. A normal hippocampus transcription factor-centered regulatory network was reconstructed using the ARACNe algorithm. Master regulator analysis and two-tail gene set enrichment analysis were employed to evaluate the inferred regulatory units in AD case-control studies. Finally, we used a connectivity map adaptation to prospect new potential therapeutic interventions by drug repurposing. RESULTS:We identified TFs with already reported involvement in AD, such as ATF2 and PARK2, as well as possible new targets for future investigations, such as CNOT7, CSRNP2, SLC30A9, and TSC22D1. Furthermore, Connectivity Map Analysis adaptation suggested the repositioning of six FDA-approved drugs that can potentially modulate master regulator candidate regulatory units (Cefuroxime, Cyproterone, Dydrogesterone, Metrizamide, Trimethadione, and Vorinostat). CONCLUSIONS:Using a transcription factor-centered regulatory network reconstruction we were able to identify several potential molecular targets and six drug candidates for repositioning in AD. Our study provides further support for the use of bioinformatics tools as exploratory strategies in neurodegenerative diseases research, and also provides new perspectives on molecular targets and drug therapies for future investigation and validation in AD.
Altered Long Non-Coding RNA Transcriptomic Profiles in Ischemic Stroke.
He Wenzhen,Wei Duncan,Cai De,Chen Siqia,Li Shunxian,Chen Wenjie
Human gene therapy
A previous study described the important regulatory roles of microRNAs (miRNAs) in ischemic stroke. However, the functional significance of long non-coding RNA (lncRNAs) in ischemic stroke was largely unknown. This study aimed to identify lncRNA profiling and elucidate the regulatory mechanisms in the pathophysiology of stroke. RNA sequencing was performed on the blood of three ischemic stroke patients and three normal controls. Differential expression analysis was used to identify differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). After further correlation and co-expression analysis, the corresponding co-expression networks and miRN-lncRNA-mRNA interaction network were then constructed. The expression of DElncRNAs and DEmRNAs was verified in Gene Expression Omnibus. RNA sequencing and subsequent bioinformatics analysis produced a total of 61 DElncRNAs (14 upregulated and 47 downregulated) and 673 DEmRNAs (432 upregulated and 241 downregulated). LOC105372881 and LOC101929707 were the most highly increased and decreased lncRNAs in ischemic stroke. LncRNA-mRNA co-expression networks were constructed according to 3,008 positively co-expressed and 607 negatively co-expressed lncRNA-mRNA pairs. The DElncRNAs may play roles in the pathways of glycolysis/gluconeogenesis, arrhythmogenic right ventricular cardiomyopathy, adherens junction, lysosome, and hematopoietic cell lineage by regulating their co-expressed mRNAs. Combined with previous data, a miRNA-lncRNA-mRNA interaction network for ischemic stroke was constructed. Based on GSE22255, the expression of six DElncRNAs (CEBPA-AS1, LINC00884, HCG27, MATN1-AS1, HCG26, and LINC01184) and 11 DEmRNAs (TREML4, AHSP, PI3, TESC, ANXA3, OAS1, OAS2, IFI6, ISG15, IFI44L, and LY6E) was similar to the current sequencing data. This study is the first to identify blood lncRNAs in human ischemic stroke using RNA sequencing. The findings may be the foundation for understanding the potential role of lncRNAs in ischemic stroke.
A Meta-Analysis of Multiple Whole Blood Gene Expression Data Unveils a Diagnostic Host-Response Transcript Signature for Respiratory Syncytial Virus.
Barral-Arca Ruth,Gómez-Carballa Alberto,Cebey-López Miriam,Bello Xabier,Martinón-Torres Federico,Salas Antonio
International journal of molecular sciences
Respiratory syncytial virus (RSV) is one of the major causes of acute lower respiratory tract infection worldwide. The absence of a commercial vaccine and the limited success of current therapeutic strategies against RSV make further research necessary. We used a multi-cohort analysis approach to investigate host transcriptomic biomarkers and shed further light on the molecular mechanism underlying RSV-host interactions. We meta-analyzed seven transcriptome microarray studies from the public Gene Expression Omnibus (GEO) repository containing a total of 922 samples, including RSV, healthy controls, coronaviruses, enteroviruses, influenzas, rhinoviruses, and coinfections, from both adult and pediatric patients. We identified > 1500 genes differentially expressed when comparing the transcriptomes of RSV-infected patients against healthy controls. Functional enrichment analysis showed several pathways significantly altered, including immunologic response mediated by RSV infection, pattern recognition receptors, cell cycle, and olfactory signaling. In addition, we identified a minimal 17-transcript host signature specific for RSV infection by comparing transcriptomic profiles against other respiratory viruses. These multi-genic signatures might help to investigate future drug targets against RSV infection.
A comprehensive bioinformatics analysis on multiple Gene Expression Omnibus datasets of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis.
Huang Shanzhou,Sun Chengjun,Hou Yuchen,Tang Yunhua,Zhu Zebin,Zhang Zhiheng,Zhang Yixi,Wang Linhe,Zhao Qiang,Chen Mao-Gen,Guo Zhiyong,Wang Dongping,Ju Weiqiang,Zhou Qi,Wu Linwei,He Xiaoshun
Fatty liver disease is one of the leading causes of chronic damage in western countries. Approximately 25% of adults in the United States have fatty livers in the absence of excessive alcohol consumption, a condition termed nonalcoholic fatty liver disease (NAFLD). Little is known about the prevalence and genetic background of NAFLD or the factors that determine its development. In this study, we used the Gene-Cloud of Biotechnology Information bioinformatics platform to carry out a comprehensive bioinformatics analysis identifying differentially expressed genes (DEGs), key biological processes and intersecting pathways. We imported 3 Gene Expression Omnibus datasets (GSE31803, GSE49541, and GSE63067). Then, we assessed the expression of the DEGs in clinical samples. We found that CD24 was the only gene co-expressed in all 3 datasets. "Glycolysis/gluconeogenesis", "p53 signaling pathway" and "glycine, serine and threonine metabolism" were 3 common pathways related to the fatty liver process. In NAFLD tissues, CD24, COL1A1, LUM, THBS2 and EPHA3 were upregulated, and PZP was downregulated. CD24 is a core gene among these DEGs and have not yet been studied of its impact on NAFLD. Co-expressed genes, common biological processes and intersecting pathways identified in the study might play an important role in NAFLD progression. Further studies are needed to elucidate the mechanism of these potential genes and pathways in NAFLD.