Evidence map›Paper›PMID 18776933›Full record

ArticlePloS one2008

CCL3L1-CCR5 genotype improves the assessment of AIDS Risk in HIV-1-infected individuals.

Hemant Kulkarni, Brian K Agan, Vincent C Marconi, Robert J O'Connell, Jose F Camargo, Weijing He, Judith Delmar, Kenneth R Phelps, George Crawford, Robert A Clark and 2 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 16% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
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  6. Genetic correlates influencing immunopathogenesis of HIV infection.The Indian journal of medical research · 2011
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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

12 authors at 6 institutions in 1 country.

Hemant KulkarniVeterans Administration Research Center for AIDS and HIV-1 Infection, South Texas Veterans Health Care System, San Antonio, Texas, United States of America.
Brian K Agan
Vincent C Marconi
Robert J O'Connell
Jose F Camargo
Weijing He
Judith Delmar
Kenneth R Phelps
George Crawford
Robert A Clark
Matthew J Dolan
Sunil K Ahuja
South Texas Veterans Health Care System · USThe University of Texas Health Science Center at San Antonio · USUniformed Services University of the Health Sciences · USUnited States Air Force · USAlbany Medical Center Hospital · USBrooke Army Medical Center · US

Funding

Host Genetic Determinants of HIV PathogenesisR37AI046326 · NIAID · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI AHUJA, SUNIL K · 2005 to 2014
$7.8M
CCR5 REGULATION AND PROMOTER VARIANTS IN HIV1 INFECTIONR01AI043279 · NIAID · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI AHUJA, SUNIL K, MUMMIDI, SRINIVAS · 1998 to 2014
$3.6M
Genetic Epidemiology of HAD Susceptibility GenesR01MH069270 · NIMH · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI AHUJA, SUNIL K · 2004 to 2009
$2.1M
NIAID NIH HHS AI043279NIAID NIH HHS HU0001-05-2-0011NIAID NIH HHS R01 AI043279NIAID NIH HHS R37 AI046326NIMH NIH HHS MH069270NIMH NIH HHS R01 MH069270
6 · The paper itself

Abstract

backgroundWhether vexing clinical decision-making dilemmas can be partly addressed by recent advances in genomics is unclear. For example, when to initiate highly active antiretroviral therapy (HAART) during HIV-1 infection remains a clinical dilemma. This decision relies heavily on assessing AIDS risk based on the CD4+ T cell count and plasma viral load. However, the trajectories of these two laboratory markers are influenced, in part, by polymorphisms in CCR5, the major HIV coreceptor, and the gene copy number of CCL3L1, a potent CCR5 ligand and HIV-suppressive chemokine. Therefore, we determined whether accounting for both genetic and laboratory markers provided an improved means of assessing AIDS risk. METHODS AND

findingsIn a prospective, single-site, ethnically-mixed cohort of 1,132 HIV-positive subjects, we determined the AIDS risk conveyed by the laboratory and genetic markers separately and in combination. Subjects were assigned to a low, moderate or high genetic risk group (GRG) based on variations in CCL3L1 and CCR5. The predictive value of the CCL3L1-CCR5 GRGs, as estimated by likelihood ratios, was equivalent to that of the laboratory markers. GRG status also predicted AIDS development when the laboratory markers conveyed a contrary risk. Additionally, in two separate and large groups of HIV+ subjects from a natural history cohort, the results from additive risk-scoring systems and classification and regression tree (CART) analysis revealed that the laboratory and CCL3L1-CCR5 genetic markers together provided more prognostic information than either marker alone. Furthermore, GRGs independently predicted the time interval from seroconversion to CD4+ cell count thresholds used to guide HAART initiation.

conclusionsThe combination of the laboratory and genetic markers captures a broader spectrum of AIDS risk than either marker alone. By tracking a unique aspect of AIDS risk distinct from that captured by the laboratory parameters, CCL3L1-CCR5 genotypes may have utility in HIV clinical management. These findings illustrate how genomic information might be applied to achieve practical benefits of personalized medicine.

Indexed as

GenotypeAcquired Immunodeficiency SyndromeAdultCD4-Positive T-LymphocytesChemokines, CCCohort StudiesFemaleHIV-1HIV InfectionsHumansLikelihood FunctionsMaleProspective StudiesReceptors, CCR5RiskCCL3L1 protein, humanChemokines, CCReceptors, CCR5

Identifiers

PMID18776933
PMCPMC2522281
OpenAlexW2017033386

What OpenQuestion holds

Textmetadata
LicenceCC0
Read underepoch 390

Registered trials

None linked

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.