Publication Details

AFRICAN RESEARCH NEXUS

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Human leukocyte antigens and HIV type 1 viral load in early and chronic infection: Predominance of evolving relationships

PLoS ONE, Volume 5, No. 3, Article e9629, Year 2010

Background: During untreated, chronic HIV-1 infection, plasma viral load (VL) is a relatively stable quantitative trait that has clinical and epidemiological implications. Immunogenetic research has established various human genetic factors, especially human leukocyte antigen (HLA) variants, as independent determinants of VL set-point. Methodology/Principal Findings: To identify and clarify HLA alleles that are associated with either transient or durable immune control of HIV-1 infection, we evaluated the relationships of HLA class I and class II alleles with VL among 563 seroprevalent Zambians (SPs) who were seropositive at enrollment and 221 seroconverters (SCs) who became seropositive during quarterly follow-up visits. After statistical adjustments for non-genetic factors (sex and age), two unfavorable alleles (A*3601 and DRB1*0102) were independently associated with high VL in SPs (p<0.01) but not in SCs. In contrast, favorable HLA variants, mainly A*74, B*13, B*57 (or Cw*18), and one HLA-A and HLA-C combination (A*30+Cw*03), dominated in SCs; their independent associations with low VL were reflected in regression beta estimates that ranged from - 0.47±0.23 to 20.9260.32 log10 in SCs (p<0.05). Except for Cw*18, all favorable variants had diminishing or vanishing association with VL in SPs (p≤0.86). Conclusions/Significance: Overall, each of the three HLA class I genes had at least one allele that might contribute to effective immune control, especially during the early course of HIV-1 infection. These observations can provide a useful framework for ongoing analyses of viral mutations induced by protective immune responses. © 2010 Tang et al.
Statistics
Citations: 47
Authors: 10
Affiliations: 3
Identifiers
Research Areas
Genetics And Genomics
Infectious Diseases
Study Design
Cohort Study
Study Approach
Quantitative