Skip to content
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
immunology and microbiology
HIV-1 coreceptor usage and CXCR4-specific viral load predict clinical disease progression during combination antiretroviral therapy
AIDS, Volume 22, No. 4, Year 2008
Notification
URL copied to clipboard!
Description
BACKGROUND: Although combination antiretroviral therapy (cART) dramatically reduces rates of AIDS and death, a minority of patients experience clinical disease progression during treatment. OBJECTIVE: To investigate whether detection of CXCR4(X4)-specific strains or quantification of X4-specific HIV-1 load predict clinical outcome. METHODS: From the Swiss HIV Cohort Study, 96 participants who initiated cART yet subsequently progressed to AIDS or death were compared with 84 contemporaneous, treated nonprogressors. A sensitive heteroduplex tracking assay was developed to quantify plasma X4 and CCR5 variants and resolve HIV-1 load into coreceptor-specific components. Measurements were analyzed as cofactors of progression in multivariable Cox models adjusted for concurrent CD4 cell count and total viral load, applying inverse probability weights to adjust for sampling bias. RESULTS: Patients with X4 variants at baseline displayed reduced CD4 cell responses compared with those without X4 strains (40 versus 82 cells/μl; P = 0.012). The adjusted multivariable hazard ratio (HR) for clinical progression was 4.8 [95% confidence interval (CI) 2.3-10.0] for those demonstrating X4 strains at baseline. The X4-specific HIV-1 load was a similarly independent predictor, with HR values of 3.7 (95% CI, 1.2-11.3) and 5.9 (95% CI, 2.2-15.0) for baseline loads of 2.2-4.3 and > 4.3 log10 copies/ml, respectively, compared with < 2.2 log10 copies/ml. CONCLUSIONS: HIV-1 coreceptor usage and X4-specific viral loads strongly predicted disease progression during cART, independent of and in addition to CD4 cell count or total viral load. Detection and quantification of X4 strains promise to be clinically useful biomarkers to guide patient management and study HIV-1 pathogenesis. © 2008 Lippincott Williams & Wilkins, Inc.
Authors & Co-Authors
Weiser, Barbara
United States, Albany
New York State Department of Health
United States, Albany
Albany Medical College
Philpott, Sean M.
United States, Albany
New York State Department of Health
United States, Washington
Path
Klimkait, Thomas
Switzerland, Basel
Universitat Basel
Burger, Harold
United States, Albany
New York State Department of Health
United States, Albany
Albany Medical College
Ramirez Kitchen, Christina M.
United States, Los Angeles
University of California, Los Angeles
Bürgisser, Ph
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Gorgievski, Meri
Switzerland, Bern
University of Bern
Perrin, Luc Henri
Switzerland, Geneva
University Hospital
Piffaretti, Jean Claude L.
Unknown Affiliation
Ledergerber, Bruno
Switzerland, Zurich
Universitatsspital Zurich
Battegay, Manuel
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Bernasconi, Enos
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Böni, Jürg
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Bucher, Heíner C.C.
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Calmy, Alexandra L.
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Cattacin, Sandro
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Cavassini, Matthias L.
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Dubs, Rolf W.
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Egger, Matthias
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Elzi, Luigia
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Erb, Peter
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Fischer, Marek
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Flepp, Markus J.
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Fontana, Adriano
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Francioli, Patrick B.
Switzerland, Lausanne
Centre Hospitalier Universitaire Vaudois
Furrer, Hansjakob
Unknown Affiliation
Gayet-Ageron, Angèle
Unknown Affiliation
Günthard, Hüldrych Fritz
Unknown Affiliation
Hirsch, Hans H.
Unknown Affiliation
Hirschel, Bernard J.
Unknown Affiliation
Hösli, Irene Mathilde
Unknown Affiliation
Kahlert, Christian R.
Unknown Affiliation
Kaiser, Laurent K.
Unknown Affiliation
Karrer, Urs
Unknown Affiliation
Keiser, Olivia
Unknown Affiliation
Kind, Christian H.
Unknown Affiliation
Martinetti, Gladys
Unknown Affiliation
Martínez de Tejada, Begoῆa
Unknown Affiliation
Müller, Nicolas J.
Unknown Affiliation
Nadal, David
Unknown Affiliation
Opravil, Milos
Unknown Affiliation
Paccaud, Fred Michel
Unknown Affiliation
Pantaleo, Giuseppe P.
Unknown Affiliation
Regenass, Stephan
Unknown Affiliation
Rickenbach, Martin
Unknown Affiliation
Rudin, Christoph
Unknown Affiliation
Schmid, Patrick
Unknown Affiliation
Schültze, Detlev
Unknown Affiliation
Schüpbach, Jörg Rg
Unknown Affiliation
Speck, Roberto F.
Unknown Affiliation
Taffé, Patrick
Unknown Affiliation
Tarr, Philip E.
Unknown Affiliation
Telenti, Amalio
Unknown Affiliation
Trkola, Alexandra
Unknown Affiliation
Vernazza, Pietro Luigi
Unknown Affiliation
Weber, Rainer
Unknown Affiliation
Yerly, Sabine T.B.D.
Unknown Affiliation
Statistics
Citations: 71
Authors: 57
Affiliations: 9
Identifiers
Doi:
10.1097/QAD.0b013e3282f4196c
ISSN:
02699370
Research Areas
Environmental
Health System And Policy
Infectious Diseases
Study Design
Cohort Study
Study Approach
Quantitative