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Africa-specific human genetic variation near CHD1L associates with HIV-1 load

An Author Correction to this article was published on 05 September 2023

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Abstract

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 CHD1L associates 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.

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Fig. 1: GWAS analysis identifies a locus on chromosome 1 that is associated with HIV spVL in individuals with African ancestries.
Fig. 2: The viral-load-decreasing effect of rs59784663(G).
Fig. 3: CHD1L expression decreases single-round HIV infection in U2OS cells.
Fig. 4: KO of CHD1L increases HIV-1 infection in human-iPS cell-derived macrophages.

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Data availability

Access to individual-level genotyping data is restricted to investigators from institutions that join the International Collaboration for the Genomics of HIV (ICGH) by signing the ICGH collaboration agreement, which is obtainable on request (jacques.fellay@epfl.ch). Owing to the highly sensitive nature of the HIV diagnostic of all study participants, the risk associated with potential re-identification was deemed to be very high by the IRBs, preventing broader sharing of individual-level data. The GWAS summary statistics are deposited in the NHGRI-EBI Catalog of human genome-wide association studies (https://www.ebi.ac.uk/gwas/home) under accession number GCST90269914. RNA-seq data are available at NCBI (PRJEB18581) and the eQTL results are available at GitHub (https://github.com/smontgomlab/AFGR).

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Acknowledgements

We thank S. Z. Shapiro and S. Carrington-Lawrence. This research was supported by the Cambridge NIHR BRC Cell Phenotyping Hub; Funding EPFL School of Life Sciences; Medical Research Council UK grant MR/N02043/X; National Institute for Health Research, UK (Cambridge Biomedical Research Centre), Cambridge Clinical Academic Reserve; Swiss National Science Foundation (SNF 310030L_197721); Sanger core grant (WT206194); and H3ABioNet, supported by the National Institutes of Health Common Fund under grant number U24HG006941. The National Institutes of Health grants and contracts supporting this work are U01 HL146240, U01 HL146201, U01 HL146208, U01 HL146333, P30 AI117943, R01 AI165236 and U54 AI170792. This study was supported in part by the Italian Ministry of University PRIN project 2017TYTWZ3 and by the Italian Ministry of health RF-2019-12369226 to G.P. J.M.M. received a personal 80:20 research grant from Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain, during 2017–2023. This study has been financed in part within the framework of the SHCS, supported by the Swiss National Science Foundation (grant no. 201369), by SHCS project no. 841 and by the SHCS research foundation. The data are gathered by the Five Swiss University Hospitals, two Cantonal Hospitals, 15 affiliated hospitals and 36 private physicians (listed at http://www.shcs.ch/180-health-care-providers). This project has been funded in part with federal funds from the Frederick National Laboratory for Cancer Research, under contract no. 75N91019D00024 and by the Intramural Research Program of the NIH, Frederick National Lab, Center for Cancer Research. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does the mention of trade names, commercial products or organizations imply endorsement by the US Government. This work was supported in part by IAVI funded by the United States Agency for International Development (USAID). The full list of IAVI donors is available at http://www.iavi.org. The contents of this manuscript are the responsibility of the authors and do not necessarily reflect the views of USAID or the US Government. J.F.H. received an award from the Gilead Sciences Research Scholars Program in HIV. H.G.’s fellowship is from Sidney Sussex College, Cambridge. S.F. is supported by the Wellcome Trust (grant no. 220740/Z/20/Z)

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  1. Deceased: Andrea De Luca, Francis A. Plummer

    Authors

    Contributions

    Conceptualization: P.J.M., I.P., G.I., H.P.M., S. Mukhopadhyay, E.K., S.B.M., S.M.W., G.D., A.M.L.L., D.G., H.G., M.S.S. and J.F. Data curation: P.J.M., I.P., G.I., E.K., I.B., C.W.T., M.K.D., M.P.S.M. and H.G. Performed experiments: I.P., G.I., H.P.M., S. Mukhopadhyay, C.S.K., A. Ciuffi, G.I., S.C., E.K., L.M.S., J.F.H. and H.G. Data analysis: P.J.M., I.P., G.I., H.P.M., S. Mukhopadhyay, E.K., I.B., A. Ciuffi, C.W.T., R.H.T., S.C., P.A., T.C., S.F., T.P., I.J., W.C.S., A. Bassett, M.K.D., M.P.S.M., J.F.T., E.K., J.F.H., S.B.M., H.G. and D.G. Administration: I.P., C.P., D.G., M.S.S. and J.F. Provision of resources: M.W., L.M.S., A. Bashirova, S.B., M.C., A. Cossarizza, A.D.L., J.J.G., D.B.G., W.K., G.D.K., N.A.K., A.H.K., O.L., M.L., S. Mallal, J.M.-P., L.M., J.M.M., P.M., A.A.M., J.I.M., N.O., F.P., F.A.P., G.P., M.A.P., A.R., I.T., A.T., B.D.W., C.A.W., S.M.W. and J.-F.Z. Writing: P.J.M., I.P., E.K., D.G., H.G., M.S.S. and J.F. All of the authors edited the manuscript.

    Corresponding authors

    Correspondence to Paul J. McLaren, Manjinder S. Sandhu or Jacques Fellay.

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    Extended data figures and tables

    Extended Data Fig. 1 A discovery genome-wide association analysis identifies a potentially novel locus associated with HIV spVL in individuals with African ancestries.

    a, Genome-wide association results of the impact of common polymorphisms on HIV-1 spVL in the discovery set of 2,682 individuals of African ancestry. Genetic variants (yellow/brown diamonds) are plotted by chromosome position (GRCh37, x-axis) and statistical significance (y-axis). The dashed line indicates the screening threshold for significance (P < 5 × 10−8). Variants in two genomic regions, the HLA region on chromosome 6 and a novel chromosome 1 locus, are significantly associated with spVL. The top associated variant per region is listed above the association peak. b, Association results across the newly identified chromosome 1 region in the discovery sample of 2,682 individuals of African ancestry. Variants (boxes and diamond) are plotted by position (GRCh37) and –log10(P). The top associated variant, rs73001655 (P = 3.2 × 10−8) is represented by the red diamond. Association was calculated per group using linear regression and meta-analysed across groups. Additional variants are coloured by their correlation to rs73001655 calculated from the African subset of the 1000 Genomes Project reference phase 3 sample. Arrows below the dashed line indicate the location and direction of transcription of protein-coding genes (green) and non-coding RNA (blue).

    Extended Data Fig. 2 Genome-wide association results of the impact of common polymorphisms on HIV-1 spVL in the combined set of 3,879 individuals with African ancestries.

    Genetic variants (yellow/brown triangles) are plotted by chromosome position (GRCh37, x-axis) and statistical significance (–log10(P), y-axis). The dashed line indicates the threshold for genome-wide significance in samples with African ancestries (P < 5 × 10−9). Variants in two regions are significantly associated with spVL. The top associated variant per region is listed above the association peak.

    Extended Data Fig. 3 Characterization and infection assays in Jurkat CHD1L mono and biallelic knockout mutants.

    a, Western blot for CHD1L shows reduced (E5) and ablated (F1, F5, E1, H4) CHD1L expression, consistent with the respective genotypes. Levels of GAPDH are shown as loading control. b,c, The percentage of GFP positive cells (b) and viable cells (c) in CHD1L knockout clones was evaluated by flow cytometry at 48 h post-infection with different concentrations of NL4-3-deltaEnv-GFP/VSV-G (0-300 ng of p24). d, The percentage of GFP positive cells was evaluated at different time points (24, 36, 48 h) post-transduction with 300ng of p24 NL4-3-deltaEnv-GFP/VSV-G virus.

    Extended Data Fig. 4 Impact of CHD1L overexpression on HIV replication in THP-1 differentiated cells.

    a, Experimental design. THP-1 were transduced with lentiviral particles encoding, either CHD1L IRES mcherry (CHD1L), or mCherry alone as a control (CTR), or left untreated (NT). Successfully transduced cells were sorted by FACS. The resulting sorted monocyte populations were differentiated into macrophages during 48 h in presence of 25 nM PMA and let recover for 24 h additional hours. Differentiated cell lines were infected with the single-round amphotropic HIVeGFP/VSV.G virus. b, Western blot confirming CHD1L overexpression in THP-1 cells transduced with CHD1L-encoding vector. c, Extracellular p24 was measured by ELISA at day 3 post-infection (n = 4). Results are normalized to the NT sample at day 3, mean and individual values of at least two experiments in triplicate are plotted. Multiple comparison One-way ANOVA showed statistical significance between CTR and CHD1L overexpressing cells (p < 0.005).

    Extended Data Fig. 5 Infection of iPSC-derived macrophages (iPSDMs) with the HIV-1 vector, NL4-3-deltaEnv-GFP/VSV-G.

    a, Experimental design: VSV-G pseudotyped HIV-1 vector was used to infect iPSDMs. Viral activity was assessed by GFP expression through flow cytometry analysis. b,c, Gating strategy for uninfected (b) and infected (c) WT cells of a single experiment. Live cells were selected by light scattering exclusion of debris (left panels) and dead cells exclusion by DRAQ-7 staining (middle panels). To circumvent autofluorescence, GFP-positivity was controlled through FL1/FL2 comparison (right panels). d,e, Raw infection data for WT and CHD1L knockout iPSDMs. Data refer to Fig. 4c and d of the main text. Data from individual wells of each experiment are reported as raw percentage of GFP positive cells. *, ** and *** represent statistically significant differences (p ≤ 0.05, 0.01 and 0.001, respectively) between WT and mutant clones using Wilcoxon matched-pairs signed rank test. #, ## represent statistically significant differences (p ≤ 0.05 and 0.01, respectively) between the CHD1L+/− A12 clone and the CHD1L−/− C12 and C11 clones using Wilcoxon matched-pairs signed rank test.

    Extended Data Fig. 6 Viral Gag particle release from WT and CHD1L knockout macrophages.

    Viral Gag particle release was measured by p24 ELISA assay on the culture supernatants at different time points post-transduction. The three graphs show independent biological replicates. A12 cells were not available for all time points. Data are reported as the average and standard deviation of duplicate p24 ELISA readings. In each independent replicate, C12 was significantly different from WT as determined by repeated measures ANOVA (1: F (6, 12) = 188.8, P < 0.0001, 2: F (5, 10) = 503.6, P < 0.0001, 3: F (5, 10) = 81.58, P < 0.0001).

    Extended Data Fig. 7 p24 release from CHD1L KO cells infected with replication competent HIV.BE_GIN.

    Raw supernatant p24 values corresponding to Fig. 4h in the main text.

    Extended Data Fig. 8 Assessing the impact of CHD1L knock-out in primary monocyte-derived macrophages on HIV infection.

    a, CHD1L was efficiently knocked out in primary MDMs by 3 of 5 crRNP constructs and a combined, multiplexed pool. b, Percent infected cells 4 days post-challenge as measured by flow cytometry showed an increase in three of the four CHD1L knockout pools compared to the non-targeting control, but these differences were not statistically significant. c,d, p24 levels in the culture supernatants as measured by ELISA were lower in CHD1L knockout cell pools 2 days post-infection (c), but recovered to the level of the non-targeting control by 4 days post-infection (d).

    Extended Data Table 1 Association result for genome-wide significant variants on chromosome 1 influencing HIV-1 spVL in individuals of African ancestries in the discovery, replication and combined samples

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    McLaren, P.J., Porreca, I., Iaconis, G. et al. Africa-specific human genetic variation near CHD1L associates with HIV-1 load. Nature 620, 1025–1030 (2023). https://doi.org/10.1038/s41586-023-06370-4

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