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Genome-wide association study reveals genetic variants associated with HIV-1C infection in a Botswana study population.

ABSTRACT: Although there have been many studies of gene variant association with different stages of HIV/AIDS progression in United States and European cohorts, few gene-association studies have assessed genic determinants in sub-Saharan African populations, which have the highest density of HIV infections worldwide. We carried out genome-wide association studies on 766 study participants at risk for HIV-1 subtype C (HIV-1C) infection in Botswana. Three gene associations (AP3B1, PTPRA, and NEO1) were shown to have significant association with HIV-1C acquisition. Each gene association was replicated within Botswana or in the United States-African American or United States-European American AIDS cohorts or in both. Each associated gene has a prior reported influence on HIV/AIDS pathogenesis. Thirteen previously discovered AIDS restriction genes were further replicated in the Botswana cohorts, extending our confidence in these prior AIDS restriction gene reports. This work presents an early step toward the identification of genetic variants associated with and affecting HIV acquisition or AIDS progression in the understudied HIV-1C afflicted Botswana population.

SUBMITTER: Shevchenko AK

PROVIDER: S-EPMC8672799 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Genome-wide association study reveals genetic variants associated with HIV-1C infection in a Botswana study population.

Shevchenko Andrey K AK Zhernakova Daria V DV Malov Sergey V SV Komissarov Alexey A Kolchanova Sofia M SM Tamazian Gaik G Antonik Alexey A Cherkasov Nikolay N Kliver Sergey S Turenko Anastasiia A Rotkevich Mikhail M Evsyukov Igor I Vlahov David D Thami Prisca K PK Gaseitsiwe Simani S Novitsky Vladimir V Essex Myron M O'Brien Stephen J SJ

Proceedings of the National Academy of Sciences of the United States of America 20211101 47

Although there have been many studies of gene variant association with different stages of HIV/AIDS progression in United States and European cohorts, few gene-association studies have assessed genic determinants in sub-Saharan African populations, which have the highest density of HIV infections worldwide. We carried out genome-wide association studies on 766 study participants at risk for HIV-1 subtype C (HIV-1C) infection in Botswana. Three gene associations (<i>AP3B1</i>, <i>PTPRA</i>, and < ...[more]

PMID: 34782459

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Project description:BackgroundDetermining patterns of HIV transmission is increasingly important for the most efficient use of modern prevention interventions. HIV phylogeny can provide a better understanding of the mechanisms underlying HIV transmission networks in communities.MethodsTo reconstruct the structure and dynamics of a local HIV/AIDS epidemic, the phylogenetic relatedness of HIV-1 subtype C env sequences obtained from 785 HIV-infected community residents in the northeastern sector of Mochudi, Botswana, during 2010-2013 was estimated. The genotyping coverage was estimated at 44%. Clusters were defined based on relatedness of HIV-1C env sequences and bootstrap support of splits.ResultsThe overall proportion of clustered HIV-1C env sequences was 19.1% (95% CI 17.5% to 20.8%). The proportion of clustered sequences from Mochudi was significantly higher than the proportion of non-Mochudi sequences that clustered, 27.0% vs. 14.7% (p = 5.8E-12; Fisher exact test). The majority of clustered Mochudi sequences (90.1%; 95% CI 85.1% to 93.6%) were found in the Mochudi-unique clusters. None of the sequences from Mochudi clustered with any of the 1,244 non-Botswana HIV-1C sequences. At least 83 distinct HIV-1C variants, or chains of HIV transmission, in Mochudi were enumerated, and their sequence signatures were reconstructed. Seven of 20 genotyped seroconverters were found in 7 distinct clusters.ConclusionsThe study provides essential characteristics of the HIV transmission network in a community in Botswana, suggests the importance of high sampling coverage, and highlights the need for broad HIV genotyping to determine the spread of community-unique and community-mixed viral variants circulating in local epidemics. The proposed methodology of cluster analysis enumerates circulating HIV variants and can work well for surveillance of HIV transmission networks. HIV genotyping at the community level can help to optimize and balance HIV prevention strategies in trials and combined intervention packages.

Project description:We used Affymetrix U133A 2.0 chips to better understand transcriptional changes associated with HIV-1 infection and perinatal transmission in human PBMCS obtained from young adult mothers with infants in Botswana in vivo. HIV seropositive and drug naÃ¯ve samples:; GSM94333, GSM94334, GSM94335, GSM94336, GSM94337, GSM94338, GSM94340, GSM94342, GSM94343, GSM94345, GSM94351, GSM94353, GSM94354, GSM94355, GSM94357, GSM94358, GSM94360, GSM94361, GSM94362, GSM94364, GSM94365, GSM94367, GSM94369, GSM94370, GSM94378; HIV seronegative samples:; GSM92590, GSM92788, GSM92789, GSM92790, GSM92791, GSM92792, GSM92793, GSM92794, GSM92795, GSM92796, GSM92797, GSM92798, GSM92799, GSM92800, GSM92801, GSM92802, GSM92803, GSM92804, GSM92805, GSM92806; HIV seropositive transmitter mothers:; GSM94333, GSM94334, GSM94335, GSM94336, GSM94337, GSM94338, GSM94340, GSM94342, GSM94343, GSM94345, GSM94378; HIV seropositive nontransmitter mothers:; GSM94351, GSM94353, GSM94354, GSM94355, GSM94357, GSM94358, GSM94360, GSM94361, GSM94362, GSM94364, GSM94365, GSM94367, GSM94369, GSM94370 Experiment Overall Design: Total RNA was extracted from peripheral blood and processed for microarray hybridizations that were conducted using U133A 2.0 chips (Affymetrix, Santa Clara, CA). The 22,777 gene-probes were filtered based on presence/absence, resulting in data for 11,705 gene-probes. The array data sets were then analyzed for differential expression based on HIV status (seronegative, seropositive) and transmitter status (transmitter: TR, nontransmitter: NTR) using BADGE version 1.0, a computer program implementing a Bayesian approach to identify differentially expressed genes (Sebastiani et al, Nat.Gen, 2005). Once differentially expressed genes were identified by BADGE, the biologically enriched categories were identified, as recently described (Montano et al, Int Immunol, 2006), by implementing a stand-alone version of the EASE statistical software (Hosack et al, Genome Biol., 2003). Selected genes were validated using realtime reverse transcription PCR.

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Genome-wide association study reveals genetic variants associated with HIV-1C infection in a Botswana study population.

Publications

Genome-wide association study reveals genetic variants associated with HIV-1C infection in a Botswana study population.

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