Evidence map›Paper›PMID 26776173›Full record

ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2016

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

Shefali S Verma, Alex T Frase, Anurag Verma, Sarah A Pendergrass, Shaun Mahony, David W Haas, Marylyn D Ritchie

Abstract read
PubMed Full text at PMC
In one paragraph

Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. AIDS research and human retroviruses · 2021
    Article
  3. Article
  4. Review
  5. Article
  6. PRECISION MEDICINE: FROM DIPLOTYPES TO DISPARITIES TOWARDS IMPROVED HEALTH AND THERAPIES.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shefali S VermaCenter for System Genomics, The Pennsylvania State University, University Park, PA 16802, USA;
Alex T Frase
Anurag Verma
Sarah A Pendergrass
Shaun Mahony
David W Haas
Marylyn D Ritchie

Funding

Leadership and Operations Center (LOC), AIDS Clinical Trials Group (ACTG); LOC 1/UM1AI068636 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Joseph J Eron, RAJESH T GANDHI · 2011 to 2026
$1073.1M
Statistical and Data Management Center (SDMC), AIDS Clinical Trials Group (ACTG)UM1AI068634 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Marlene Ann Cooper, Michael David Hughes · 2011 to 2026
$246.6M
WOMEN'S HEALTH AGENDAU01AI038858 · NIAID · SOCIAL AND SCIENTIFIC SYSTEMS, INC. · PI BENSON, CONSTANCE ANN · 1996 to 2008
$157.5M
AIDS Clinical Trials Group NetworkU01AI068636 · NIAID · SOCIAL AND SCIENTIFIC SYSTEMS, INC. · PI KURITZKES, DANIEL R. · 2006 to 2010
$147.1M
Virus & Reservoirs CoreP30AI045008 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI DAVID S METZGER · 1999 to 2026
$78.6M
Virology, Immunology, and Microbiology CoreP30AI050410 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVID M. MARGOLIS · 2001 to 2026
$76.9M
ZONA-FREE HAMSTER OVA ASSAY AS AN INDICATOR OF MALE FERTILITYM01RR000425 · NCRR · LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER · PI ANDERSON, GAIL V · 1985 to 2011
$74.2M
Virology and Molecular Biomarkers CoreP30AI050409 · NIAID · EMORY UNIVERSITY · PI Ann M Chahroudi, Colleen F Kelley · 2002 to 2026
$74.0M
University of North Carolina Global HIV Prevention and Treatment Clinical Trials Unit 2024 SupplementUM1AI069423 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Joseph J Eron, MINA CHRISTINE HOSSEINIPOUR · 2012 to 2026
$71.8M
Vaccine Response and Immunotherapeutics SWGP30AI094189 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Richard E. Chaisson · 2012 to 2026
$67.0M
CTSA INFRASTRUCTURE FOR PEDIATRIC RESEARCHUL1RR025780 · NCRR · UNIVERSITY OF COLORADO DENVER · PI SOKOL, RONALD J. · 2008 to 2011
$61.3M
CTSA INFRASTRUCTURE FOR PEDIATRIC RESEARCHUL1RR024156 · NCRR · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2006 to 2011
$53.0M
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6 · The paper itself

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.

Indexed as

Polymorphism, Single NucleotideAcquired Immunodeficiency SyndromeClinical Trials as TopicComputational BiologyDatabases, GeneticEpistasis, GeneticGenetic Association StudiesHumansKnowledge BasesLinear ModelsNonlinear DynamicsPhenotype

Identifiers

PMID26776173
PMCPMC4722952

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.