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Brumme Z, Wang B, Nair K, Brumme C, de Pierres C, Reddy S, Julg B, Moodley E, Thobakgale C, Lu Z, van der Stok M, Bishop K, Mncube Z, Chonco F, Yuki Y, Frahm N, Brander C, Carrington M, Freedberg K, Kiepiela P, Goulder P, Walker B, Ndung’u T, Losina E. Impact of select immunologic and virologic biomarkers on CD4 cell count decrease in patients with chronic HIV-1 subtype C infection: results from Sinikithemba Cohort, Durban, South Africa. Clin Infect Dis 2009; 49:956-64. [PMID: 19663693 PMCID: PMC2777678 DOI: 10.1086/605503] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND The extent to which immunologic and clinical biomarkers influence human immunodeficiency virus type 1 (HIV-1) infection outcomes remains incompletely characterized, particularly for non-B subtypes. On the basis of data supporting in vitro HIV-1 protein-specific CD8 T lymphocyte responses as correlates of immune control in cross-sectional studies, we assessed the relationship of these responses, along with established HIV-1 biomarkers, with rates of CD4 cell count decrease in individuals infected with HIV-1 subtype C. METHODS Bivariate and multivariate mixed-effects models were used to assess the relationship of baseline CD4 cell count, plasma viral load, human leukocyte antigen (HLA) class I alleles, and HIV-1 protein-specific CD8 T cell responses with the rate of CD4 cell count decrease in a longitudinal population-based cohort of 300 therapy-naive, chronically infected adults with baseline CD4 cell counts >200 cells/mm(3) and plasma viral loads >500 copies/mL over a median of 25 months of follow-up. RESULTS In bivariate analyses, baseline CD4 cell count, plasma viral load, and possession of a protective HLA allele correlated significantly with the rate of CD4 cell count decrease. No relationship was observed between HIV-1 protein-specific CD8 T cell responses and CD4 cell count decrease. Results from multivariate models incorporating baseline CD4 cell counts (201-350 vs >350 cells/mm(3)), plasma viral load (< or =100,000 vs >100,000 copies/mL), and HLA (protective vs not protective) yielded the ability to discriminate CD4 cell count decreases over a 10-fold range. The fastest decrease was observed among individuals with CD4 cell counts >350 cells/mm(3) and plasma viral loads >100,000 copies/mL with no protective HLA alleles (-59 cells/mm(3) per year), whereas the slowest decrease was observed among individuals with CD4 cell counts 201-350 cells/mm(3), plasma viral loads < or =100,000 copies/mL, and a protective HLA allele (-6 cells/mm(3) per year). CONCLUSIONS The combination of plasma viral load and HLA class I type, but not in vitro HIV-1 protein-specific CD8 T cell responses, differentiates rates of CD4 cell count decrease in patients with chronic subtype-C infection better than either marker alone.
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Affiliation(s)
- Zabrina Brumme
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Boston MA, USA
| | - Bingxia Wang
- Program in HIV Outcomes Research, Massachusetts General Hospital, Boston MA, USA
| | - Kriebashne Nair
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Chanson Brumme
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Boston MA, USA
| | - Chantal de Pierres
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Shabashini Reddy
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Boris Julg
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Boston MA, USA
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Eshia Moodley
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Christina Thobakgale
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Zhigang Lu
- Program in HIV Outcomes Research, Massachusetts General Hospital, Boston MA, USA
| | - Mary van der Stok
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Karen Bishop
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Zenele Mncube
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Fundisiwe Chonco
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Yuko Yuki
- Cancer and Inflammation Program, Laboratory of Experimental Immunology, SAIC-Frederick, Inc., NCI-Frederick, Frederick, MD
| | - Nicole Frahm
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Boston MA, USA
| | - Christian Brander
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Boston MA, USA
| | - Mary Carrington
- Cancer and Inflammation Program, Laboratory of Experimental Immunology, SAIC-Frederick, Inc., NCI-Frederick, Frederick, MD
| | - Kenneth Freedberg
- Program in HIV Outcomes Research, Massachusetts General Hospital, Boston MA, USA
| | - Photini Kiepiela
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Philip Goulder
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Boston MA, USA
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
- Department of Pediatrics, Nuffield Department of Medicine, Oxford, UK
| | - Bruce Walker
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Boston MA, USA
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Thumbi Ndung’u
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Boston MA, USA
- HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban South Africa
| | - Elena Losina
- Program in HIV Outcomes Research, Massachusetts General Hospital, Boston MA, USA
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McKinnon LR, Mao X, Kimani J, Wachihi C, Semeniuk C, Mendoza M, Liang B, Luo M, Fowke KR, Plummer FA, Ball TB. Epitope mapping of HIV-specific CD8+ T cells in a cohort dominated by clade A1 infection. PLoS One 2009; 4:e6965. [PMID: 19750221 PMCID: PMC2735720 DOI: 10.1371/journal.pone.0006965] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2009] [Accepted: 07/28/2009] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND CD8+ T cell responses are often detected at large magnitudes in HIV-infected subjects, and eliciting these responses is the central aim of many HIV-1 vaccine strategies. Population differences in CD8+ T cell epitope specificity will need to be understood if vaccines are to be effective in multiple geographic regions. METHODOLOGY/PRINCIPAL FINDINGS In a large Kenyan cohort, we compared responsive CD8+ T cell HIV-1 Env overlapping peptides (OLPs) to Best Defined Epitopes (BDEs), many of which have been defined in clade B infection. While the majority of BDEs (69%) were recognized in this population, nearly half of responsive OLPs (47%) did not contain described epitopes. Recognition frequencies of BDEs were inversely correlated to epitopic sequence differences between clade A1 and BDE (P = 0.019), and positively selected residues were more frequent in "new" OLPs (without BDEs). We assessed the impact of HLA and TAP binding on epitope recognition frequencies, focusing on predicted and actual epitopes in the HLA B7 supertype. CONCLUSIONS/SIGNIFICANCE Although many previously described CD8 epitopes were recognized, several novel CD8 epitopes were defined in this population, implying that epitope mapping efforts have not been completely exhausted. Expansion of these studies will be critical to understand population differences in CD8 epitope recognition.
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Affiliation(s)
- Lyle R McKinnon
- Department of Medical Microbiology, University of Manitoba, Winnipeg, Canada.
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