Comparison of msp genotyping and a 24 SNP molecular assay for differentiating Plasmodium falciparum recrudescence from reinfection.
Fulakeza Joseph,McNitt Sarah,Vareta Jimmy,Saidi Alex,Mvula Godfrey,Taylor Terrie,Mathanga Don P,Small Dylan S,Skarbinski Jacek,Gutman Julie R,Seydel Karl
Malaria journal
BACKGROUND:Current World Health Organization guidelines for conducting anti-malarial drug efficacy clinical trials recommend genotyping Plasmodium falciparum genes msp1 and msp2 to distinguish recrudescence from reinfection. A more recently developed potential alternative to this method is a molecular genotyping assay based on a panel of 24 single nucleotide polymorphism (SNP) markers. METHODS:Performance parameters of these two genotyping methods were compared using data from two recently completed drug efficacy trials. Blood samples from two anti-malarial therapeutic trials were analysed by both msp genotyping and the 24 SNP assay. Additionally, to conserve time and resources, the statistical program R was used to select the most informative SNPs for a set of unrelated Malawian samples to develop a truncated SNP-based assay for the region surrounding Blantyre, Malawi. The ability of this truncated assay to distinguish reinfection from recrudescence when compared to the full 24 SNP assay was then analysed using data from the therapeutic trials. RESULTS:A total of 360 samples were analysed; 66 for concordance of msp and SNP barcoding methodologies, and 294 for assessing the most informative of the 24 SNP markers. SNP genotyping performed comparably to msp genotyping, with only one case of disagreement among the 50 interpretable results, where the SNP assay identified the sample as reinfection and the msp typing as recrudescence. Furthermore, SNP typing was more robust; only 6% of samples were uninterpretable by SNP typing, compared to 19.7% when msp genotyping was used. For discriminating reinfection from recrudescence, a truncated 6 SNP assay was found to perform at 95.1% the accuracy of the full 24 SNP bar code. CONCLUSIONS:The use of SNP analysis has similar sensitivity to the standard msp genotyping in determining recrudescence from reinfection. Although more expensive, SNP typing is faster and less work intensive. Limiting the assay to those SNPs most informative in the geographical region of interest may further decrease the workload and the cost, making this technique a feasible and affordable alternative in drug efficacy trials.
10.1186/s12936-019-2695-0
A Novel Alzheimer-Associated SNP in Tmp21 Increases Amyloidogenesis.
Zhang Xiaojie,Wu Yili,Cai Fang,Liu Shengchun,Bromley-Brits Kelley,Xia Kun,Song Weihong
Molecular neurobiology
Recent studies suggest that TMP21 is a selective modulator of γ-secretase and its dysregulation affects APP processing, leading to increased Aβ generation. However, the genetic association between Tmp21 and Alzheimer's disease (AD) remains elusive. In this study, we identified that a novel single-nucleotide polymorphism (SNP) rs12435391 (IVS4-28T>C) in intron 4 of Tmp21 was genetically associated with AD. We found that allele C of the SNP rs12435391 did not affect splicing site recognition, but it significantly increased TMP21 gene expression. The stability of Tmp21 pre-mRNA and the transcription of Tmp21 were not affected by allele C of the SNP rs12435391. However, allele C of the SNP rs12435391 significantly increased the splicing efficiency of Tmp21 pre-mRNA, leading to the elevation of mature mRNA. Furthermore, allele C of the SNP rs12435391 significantly reduced C83 level and increased Aβ generation. Taken together, our study suggests that TMP21 is genetically associated with Alzheimer's disease, with the novel Tmp21 SNP as a risk factor for Alzheimer's pathogenesis.
10.1007/s12035-017-0459-9
p53-responsive TLR8 SNP enhances human innate immune response to respiratory syncytial virus.
Menendez Daniel,Snipe Joyce,Marzec Jacqui,Innes Cynthia L,Polack Fernando P,Caballero Mauricio T,Schurman Shepherd H,Kleeberger Steven R,Resnick Michael A
The Journal of clinical investigation
The Toll-like receptor 8 (TLR8) has an important role in innate immune responses to RNA viral infections, including respiratory syncytial virus (RSV). We previously reported that TLR8 expression was increased directly by the tumor suppressor and transcription factor p53 via a single nucleotide polymorphism (SNP) (rs3761624) in the TLR8 promoter, thereby placing TLR8 in the p53/immune axis. Because this SNP is in linkage disequilibrium with other SNPs associated with several infectious diseases, we addressed the combined influence of p53 and the SNP on downstream inflammatory signaling in response to a TLR8 cognate ssRNA ligand. Using human primary lymphocytes, p53 induction by chemotherapeutic agents such as ionizing radiation caused SNP-dependent synergistic increases in IL-6 following incubation with an ssRNA ligand, as well as TLR8 RNA and protein expression along with p53 binding at the TLR-p53 SNP site. Because TLR8 is X-linked, the increases were generally reduced in heterozygous females. We found a corresponding association of the p53-responsive allele with RSV disease severity in infants hospitalized with RSV infection. We conclude that p53 can strongly influence TLR8-mediated immune responses and that knowledge of the p53-responsive SNP can inform diagnosis and prognosis of RSV disease and other diseases that might have a TLR8 component, including cancer.
10.1172/JCI128626
Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-wide SNP Data.
Zhao Xiang,Luan Yi-Zhao,Zuo Xiaoyu,Chen Ye-Da,Qin Jiheng,Jin Lv,Tan Yiqing,Lin Meihua,Zhang Naizun,Liang Yan,Rao Shao-Qi
Genomics, proteomics & bioinformatics
Coronary artery disease (CAD) is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism (SNP) profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium (WTCCC) SNP datasets of CAD and control samples were used to assess the joint effect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene-gene interactions involved in these susceptible pathways with their protein-protein interaction (PPI) knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer's disease, non-alcoholic fatty liver disease, and Huntington's disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer's disease. These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer's disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.
10.1016/j.gpb.2016.04.008
Single Nucleotide Polymorphism (SNP) in the Adiponectin Gene and Cardiovascular Disease.
Chirumbolo Salvatore
Iranian biomedical journal
Dear Editor, The recent article by Mohammadzadeh et al.[1] on the latest issue of this Journal showed that the T allele +276G/T SNP of ADIPOQ gene is more associated with the increasing risk of coronary artery disease (CAD) in subjects with type 2 diabetes. Adipocytes were described in myocardial tissue of CAD patients and their role recently discussed[2,3]. Susceptibility to CAD by polymorphism in the Q gene of adiponectin has been reported for 3'-UTR, which harbours some genetic loci associated with metabolic risks and atherosclerosis[4]. Actually, previous studies have shown that the haplotype SNP +276G>T was associated with a decreased risk of CAD, after adjustment for potential confounding factors, therefore some controversial opinion still exists[5]. This evidence should be associated with the role exerted by adipocytes and adiponectin in heart physiology. In particular, in hypertensive disorder complicating pregnancy (HDCP), by investigating the population frequency of alleles, genotypes, and haplotypes of two single nucleotide polymorphisms (SNPs), namely +45T>G (rs2241766) and +276G>T (rs1501299), some authors found that the SNP +276 TT genotype was significantly associated with protection against HDCP, when compared to the pooled G genotypes[6]. Moreover, the same +276G/T SNP haplotype was strongly associated with biliary atresia, an intractable neonatal inflammatory and obliterative cholangiopathy, leading to progressive fibrosis and cirrhosis[7]. CAD is closely related to adiponectin biology. The same isoforms of adiponectin seem to be not associated to CAD severity but to glucose metabolism and its impairment[8]. In the paper by Mohammadzadeh et al.[1], T allele in +276G/T SNP haplotype is highly associated with CAD in subjects with type 2 diabetes, but this linkage should be reappraised if related much more to diabetes rather than CAD. Association of T allele in the indicated SNP with CAD may be an indirect consequence of type 2 diabetes, as reported by others[9] or a direct marker for CAD affected patients[10]. The paper by Mohammadzadeh et al.[1] assesses data coming elsewhere from literature but raises important concerns about the suitability of ADIPOQ SNPs in diagnosing susceptibility to CAD and the relationship with plasma adiponectin level. In normal, non diabetic, normoglycemic subject, this relationship does not seem to work. Therefore the question is how much predictive this SNP haplotype may be to foresee metabolic syndrome and CAD onset risk in young health subjects? Maybe, the role of adiponectin in cardiovascular physiology depends on its ability to target adiponectin receptors and to negatively regulate obesity. Some authors reported in healthy volunteers an absence of correlation between circulating adiponectin levels and biochemical markers, particularly lipoproteins and suggested that SNP +276G>T was related to an independent effect on adiponectin levels and on lipoprotein metabolism[11]. On the contrary, adiponectin genetic variants and SNP +276G>T was associated with increasing susceptibility of type 2 diabetes and plasma glucose impairment[12]. The interesting study by Mohammadzadeh et al.[1] suggests that SNP of ADIPOQ +276G>T should be related to susceptibility to glucose metabolism, while indirectly to lipid metabolism and fat-related cardiovascular damage.
10.7508/ibj.2016.04.001
Explaining the disease phenotype of intergenic SNP through predicted long range regulation.
Chen Jingqi,Tian Weidong
Nucleic acids research
Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes.
10.1093/nar/gkw519
A Multi-tissue Transcriptome Analysis of Human Metabolites Guides Interpretability of Associations Based on Multi-SNP Models for Gene Expression.
Ndungu Anne,Payne Anthony,Torres Jason M,van de Bunt Martijn,McCarthy Mark I
American journal of human genetics
There is particular interest in transcriptome-wide association studies (TWAS) gene-level tests based on multi-SNP predictive models of gene expression-for identifying causal genes at loci associated with complex traits. However, interpretation of TWAS associations may be complicated by divergent effects of model SNPs on phenotype and gene expression. We developed an iterative modeling scheme for obtaining multi-SNP models of gene expression and applied this framework to generate expression models for 43 human tissues from the Genotype-Tissue Expression (GTEx) Project. We characterized the performance of single- and multi-SNP models for identifying causal genes in GWAS data for 46 circulating metabolites. We show that: (A) multi-SNP models captured more variation in expression than did the top cis-eQTL (median 2-fold improvement); (B) predicted expression based on multi-SNP models was associated (false discovery rate < 0.01) with metabolite levels for 826 unique gene-metabolite pairs, but, after stepwise conditional analyses, 90% were dominated by a single eQTL SNP; (C) among the 35% of associations where a SNP in the expression model was a significant cis-eQTL and metabolomic-QTL (met-QTL), 92% demonstrated colocalization between these signals, but interpretation was often complicated by incomplete overlap of QTLs in multi-SNP models; and (D) using a "truth" set of causal genes at 61 met-QTLs, the sensitivity was high (67%), but the positive predictive value was low, as only 8% of TWAS associations (19% when restricted to colocalized associations at met-QTLs) involved true causal genes. These results guide the interpretation of TWAS and highlight the need for corroborative data to provide confident assignment of causality.
10.1016/j.ajhg.2020.01.003