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HIV-1 remains a global health crisis1, highlighting the need to identify new targets for therapies. Here, given the disproportionate HIV-1 burden and marked human genome diversity in Africa2, we assessed the genetic determinants of control of set-point viral load in 3,879 people of African ancestries living with HIV-1 participating in the international collaboration for the genomics of HIV3. We identify a previously undescribed association signal on chromosome 1 where the peak variant associates with an approximately 0.3 log10-transformed copies per ml lower set-point viral load per minor allele copy and is specific to populations of African descent. The top associated variant is intergenic and lies between a long intergenic non-coding RNA (LINC00624) and the coding gene CHD1L, which encodes a helicase that is involved in DNA repair4. Infection assays in iPS cell-derived macrophages and other immortalized cell lines showed increased HIV-1 replication in CHD1L-knockdown and CHD1L-knockout cells. We provide evidence from population genetic studies that Africa-specific genetic variation near CHD1Lassociates with HIV replication in vivo. Although experimental studies suggest that CHD1L is able to limit HIV infection in some cell types in vitro, further investigation is required to understand the mechanisms underlying our observations, including any potential indirect effects of CHD1L on HIV spread in vivo that our cell-based assays cannot recapitulate.

Fine-mapping to plausible causal variation may be more effective in multi-ancestry cohorts, particularly in the MHC, which has population-specific structure. To enable such studies, we constructed a large (n= 21,546) HLA reference panel spanning five global populations based on whole-genome sequences. Despite population-specific long-range haplotypes, we demonstrated accurate imputation at G-group resolution (94.2%, 93.7%, 97.8% and 93.7% in admixed African (AA), East Asian (EAS), European (EUR) and Latino (LAT) populations). Applying HLA imputation to genome-wide association study data for HIV-1 viral load in three populations (EUR, AA and LAT), we obviated effects of previously reported associations from population-specific HIV studies and discovered a novel association at position 156 in HLA-B. We pinpointed the MHC association to three amino acid positions (97, 67 and 156) marking three consecutive pockets (C, B and D) within the HLA-B peptide-binding groove, explaining 12.9% of trait variance.

Over the past four decades, research on the natural history of HIV infection has described how HIV wreaks havoc on human immunity and causes AIDS. HIV host genomic research, which aims to understand how human genetic variation affects our response to HIV infection, has progressed from early candidate gene studies to recent multi-omic efforts, benefiting from spectacular advances in sequencing technology and data science. In addition to invading cells and co-opting the host machinery for replication, HIV also stably integrates into our own genome. The study of the complex interactions between the human and retroviral genomes has improved our understanding of pathogenic mechanisms and suggested novel preventive and therapeutic approaches against HIV infection.

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Multiple genome-wide studies have identified associations between outcome of human immunodeficiency virus (HIV) infection and polymorphisms in and around the gene encoding the HIV co-receptor CCR5, but the functional basis for the strongest of these associations, rs1015164A/G, is unknown. We found that rs1015164 marks variation in an activating transcription factor 1 binding site that controls expression of the antisense long noncoding RNA (lncRNA) CCR5AS. Knockdown or enhancement of CCR5AS expression resulted in a corresponding change in CCR5 expression on CD4+T cells. CCR5AS interfered with interactions between the RNA-binding protein Raly and the CCR5 3' untranslated region, protecting CCR5 messenger RNA from Raly-mediated degradation. Reduction in CCR5 expression through inhibition of CCR5AS diminished infection of CD4+T cells with CCR5-tropic HIV in vitro. These data represent a rare determination of the functional importance of a genome-wide disease association where expression of a lncRNA affects HIV infection and disease progression.

Purpose:The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics.Methods:We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers.Results:A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865?ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%.Conclusions:The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine.Genet Med 18 8, 814–822.

The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics.

Supplemental Digital Content is available in the text

Efavirenz and abacavir are components of recommended first-line regimens for HIV-1 infection. We used genome-wide genotyping and clinical data to explore genetic associations with virologic failure among patients randomized to efavirenz-containing or abacavir-containing regimens in AIDS Clinical Trials Group (ACTG) protocols.

Atazanavir-associated hyperbilirubinemia can cause premature discontinuation of atazanavir and avoidance of its initial prescription. We used genomewide genotyping and clinical data to characterize determinants of atazanavir pharmacokinetics and hyperbilirubinemia in AIDS Clinical Trials Group protocol A5202.

The impact of host genetic variation on determining the differential outcomes after HIV infection has been studied by two approaches: targeting of candidate genes and genome-wide association studies (GWASs). The overlap in genetic variants that has been identified by these two means has essentially been restricted to variants near to the human leukocyte antigen (HLA) class I genes, although variation in the CCR5locus, which was first shown to have an effect on HIV outcomes using the candidate gene approach, does reach significance genome-wide when very large samples sizes (i.e. thousands) are used in GWAS. Overall, many of the variants identified by the candidate gene approach are likely to be spurious, as no additional variants apart from a novel variant near the HLA-Cgene have been consistently identified by GWAS. Variants with low frequency andor low impact on HIV outcomes are likely to exist in the genome and there could be many of them, but these are not identifiable, given current GWAS sample sizes. Several loci centrally involved in the immune response, including the immunoglobulin genes, T-cell receptor loci, or leukocyte receptor complex, are either poorly covered on the GWAS chips or difficult to interpret due to their repetitive nature andor the presence of insertiondeletion polymorphisms in the region. These loci warrant further interrogation, but genetic characterization of these regions across a range of individuals will first be required. Finally, synergistic interactions between loci may affect outcome after infection, as suggested by associations of specific, functionally relevant HLA and killer cell immunoglobulin-like receptor variants with HIV disease outcomes, and these require further consideration as well.

ABSTRACTAdvances in microarray technology have allowed for the monitoring of thousands of genes simultaneously. This technology is of particular interest to immunologists studying infectious diseases, because it provides tremendous potential for investigating host-pathogen interactions at the level of immune gene expression. To date, many studies have focused either on cell lines, where the physiological relevance is questionable, or on mixed cell populations, where the contributions of individual subpopulations are unknown. In the present study, we perform an intrasubject comparison of antigen-stimulated immune gene expression profiles between a mixed population of peripheral blood mononuclear cells (PBMC) and the two predominant cell types found in PBMC, CD4+and CD8+T lymphocytes. We show that the microarray profiles of CD4+and CD8+T lymphocytes differ from each other as well as from that of the mixed cell population. The independence of the gene expression profiles of different cell types is demonstrated with a ubiquitous antigen (Candida albicans) as well as with a disease-specific antigen (human immunodeficiency virus p24). This study has important implications for microarray studies of host immunity and underscores the importance of profiling the expression of specific cell types.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.