Dataset Information

PHENOME-WIDE INTERACTION STUDY (PheWIS) IN AIDS CLINICAL TRIALS GROUP DATA (ACTG).

ABSTRACT: Association studies have shown and continue to show a substantial amount of success in identifying links between multiple single nucleotide polymorphisms (SNPs) and phenotypes. These studies are also believed to provide insights toward identification of new drug targets and therapies. Albeit of all the success, challenges still remain for applying and prioritizing these associations based on available biological knowledge. Along with single variant association analysis, genetic interactions also play an important role in uncovering the etiology and progression of complex traits. For gene-gene interaction analysis, selection of the variants to test for associations still poses a challenge in identifying epistatic interactions among the large list of variants available in high-throughput, genome-wide datasets. Therefore in this study, we propose a pipeline to identify interactions among genetic variants that are associated with multiple phenotypes by prioritizing previously published results from main effect association analysis (genome-wide and phenome-wide association analysis) based on a-priori biological knowledge in AIDS Clinical Trials Group (ACTG) data. We approached the prioritization and filtration of variants by using the results of a previously published single variant PheWAS and then utilizing biological information from the Roadmap Epigenome project. We removed variants in low functional activity regions based on chromatin states annotation and then conducted an exhaustive pairwise interaction search using linear regression analysis. We performed this analysis in two independent pre-treatment clinical trial datasets from ACTG to allow for both discovery and replication. Using a regression framework, we observed 50,798 associations that replicate at p-value 0.01 for 26 phenotypes, among which 2,176 associations for 212 unique SNPs for fasting blood glucose phenotype reach Bonferroni significance and an additional 9,970 interactions for high-density lipoprotein (HDL) phenotype and fasting blood glucose (total of 12,146 associations) reach FDR significance. We conclude that this method of prioritizing variants to look for epistatic interactions can be used extensively for generating hypotheses for genomewide and phenome-wide interaction analyses. This original Phenome-wide Interaction study (PheWIS) can be applied further to patients enrolled in randomized clinical trials to establish the relationship between patient's response to a particular drug therapy and non-linear combination of variants that might be affecting the outcome.

SUBMITTER: Verma SS

PROVIDER: S-EPMC4722952 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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PHENOME-WIDE INTERACTION STUDY (PheWIS) IN AIDS CLINICAL TRIALS GROUP DATA (ACTG).

Verma Shefali S SS Frase Alex T AT Verma Anurag A Pendergrass Sarah A SA Mahony Shaun S Haas David W DW Ritchie Marylyn D MD

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing 20160101

Association studies have shown and continue to show a substantial amount of success in identifying links between multiple single nucleotide polymorphisms (SNPs) and phenotypes. These studies are also believed to provide insights toward identification of new drug targets and therapies. Albeit of all the success, challenges still remain for applying and prioritizing these associations based on available biological knowledge. Along with single variant association analysis, genetic interactions also ...[more]

PMID: 26776173

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Project description:BackgroundThe association of inflammatory biomarkers with clinical events after antiretroviral therapy initiation is unclear.MethodsA5202 randomized 1857 treatment-naive subjects to abacavir/lamivudine or tenofovir-DF/emtricitabine with efavirenz or atazanavir/ritonavir. Substudy A5224s measured inflammatory biomarkers on subjects with available plasma from baseline and week 24 or 96. An exploratory analysis of the association of high-sensitivity C-reactive protein, interleukin-6 (IL-6), soluble receptors of tumor necrosis factor α (sTNF)-RI, sTNF-RII, TNF-α, soluble vascular cellular adhesion molecules (sVCAM-1), and soluble intercellular adhesion molecules (sICAM-1) with times to AIDS and to non-AIDS events used Cox proportional hazards models.ResultsAnalysis included 244 subjects; 85% men and 48% white non-Hispanic with median age 39 years, HIV-1 RNA of 4.6 log10 copies per milliliter, and CD4 of 240 cells per microliter. Overall, 13 AIDS events (9 opportunistic infections, 3 AIDS-cancers, and 1 recurrent bacterial pneumonia) and 18 non-AIDS events (6 diabetes, 4 cancers, 3 cardiovascular, and 5 pneumonias) occurred. Higher baseline IL-6, sTNF-RI, sTNF-RII, and sICAM-1 were significantly associated with increased risk of AIDS-defining events. Adjustment for baseline HIV-1 RNA did not change results, whereas adjusting for baseline CD4 count left only sTNF-RI and sICAM-1 significantly associated with increased risk. Time-updated values of IL-6, sTNFR-I and II, and sICAM-1 were also associated with an increased risk. For non-AIDS events, only higher baseline high-sensitivity C-reactive protein was significantly associated with increased risk, whereas higher IL-6 was marginally associated with higher risk. Analyses of time-updated biomarker values showed tumor necrosis factor α to be significantly associated with increased risk, even after adjustment for antiretroviral therapy, and CD4 count or HIV-1 RNA.ConclusionsHigher levels of several inflammatory biomarkers were independently associated with increased risk of AIDS and non-AIDS events.

Dataset Information

PHENOME-WIDE INTERACTION STUDY (PheWIS) IN AIDS CLINICAL TRIALS GROUP DATA (ACTG).

Publications

PHENOME-WIDE INTERACTION STUDY (PheWIS) IN AIDS CLINICAL TRIALS GROUP DATA (ACTG).

Similar Datasets

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