Trial report in Pharmacogenetics and genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 22% of its field
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
8 citing papers in PubMed, 11 citations in OpenAlex.
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
9 authors at 2 institutions in 1 country.
Anurag VermaaThe Center for Systems Genomics, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park bBiomedical and Translational Informatics, Geisinger Health System, Danville, Pennsylvania cLos Angeles Biomedical Research Institute at Harbor, UCLA Medical Center, Torrance, California dUniversity of Rochester Medical Center, Rochester eDepartment of Pharmacy Practice, Center for Integrated Global Biomedical Sciences, University at Buffalo, SUNY, Buffalo, New York fVanderbilt University School of Medicine gMeharry Medical College, Nashville, Tennessee, USA.
Yuki Bradford
Shefali S Verma
Sarah A Pendergrass
Eric S Daar
Charles Venuto
Gene D Morse
Marylyn D Ritchie
David W Haas
Creative Commons · USPennsylvania State University · US
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
Validation, CLIA and Qualification (VQC): Enhancing the RS ratio as a tool for AIDS Clinical Trial Group (ACTG) tuberculosis trialsUM1AI106701 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Grace M Aldrovandi · 2014 to 2026
$116.8M
Virus & Reservoirs CoreP30AI045008 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI DAVID S METZGER · 1999 to 2026
$78.6M
STATISTICAL AND DATA MANAGEMENT CENTERU01AI038855 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI HUGHES, MICHAEL DAVID · 1996 to 2006
$78.1M
Virology, Immunology, and Microbiology CoreP30AI050410 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVID M. MARGOLIS · 2001 to 2026
$76.9M
Virology and Molecular Biomarkers CoreP30AI050409 · NIAID · EMORY UNIVERSITY · PI Ann M Chahroudi, Colleen F Kelley · 2002 to 2026
$74.0M
Statistical and Data Management Center for the AIDS Clinical Trials GroupU01AI068634 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI HUGHES, MICHAEL DAVID · 2006 to 2010
$71.9M
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
CTSA INFRASTRUCTURE FOR PEDIATRIC RESEARCHUL1RR024156 · NCRR · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2006 to 2011
backgroundHigh-throughput approaches are increasingly being used to identify genetic associations across multiple phenotypes simultaneously. Here, we describe a pilot analysis that considered multiple on-treatment laboratory phenotypes from antiretroviral therapy-naive patients who were randomized to initiate antiretroviral regimens in a prospective clinical trial, AIDS Clinical Trials Group protocol A5202. PARTICIPANTS AND
methodsFrom among 5 9545 294 polymorphisms imputed genome-wide, we analyzed 2544, including 2124 annotated in the PharmGKB, and 420 previously associated with traits in the GWAS Catalog. We derived 774 phenotypes on the basis of context from six variables: plasma atazanavir (ATV) pharmacokinetics, plasma efavirenz (EFV) pharmacokinetics, change in the CD4+ T-cell count, HIV-1 RNA suppression, fasting low-density lipoprotein-cholesterol, and fasting triglycerides. Permutation testing assessed the likelihood of associations being by chance alone. Pleiotropy was assessed for polymorphisms with the lowest P-values.
resultsThis analysis included 1181 patients. At P less than 1.5×10, most associations were not by chance alone. Polymorphisms with the lowest P-values for EFV pharmacokinetics (CYPB26 rs3745274), low-density lipoprotein -cholesterol (APOE rs7412), and triglyceride (APOA5 rs651821) phenotypes had been associated previously with those traits in previous studies. The association between triglycerides and rs651821 was present with ATV-containing regimens, but not with EFV-containing regimens. Polymorphisms with the lowest P-values for ATV pharmacokinetics, CD4 T-cell count, and HIV-1 RNA phenotypes had not been reported previously to be associated with that trait.
conclusionUsing data from a prospective HIV clinical trial, we identified expected genetic associations, potentially novel associations, and at least one context-dependent association. This study supports high-throughput strategies that simultaneously explore multiple phenotypes from clinical trials' datasets for genetic associations.
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.
Multiphenotype association study of patients randomized to initiate antiretroviral regimens in AIDS Clinical Trials Group protocol A5202. · full record | OpenQuestion