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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 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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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 ([email protected]). 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).

UNAIDS Data 2021 (UNAIDS, 2021); https://www.unaids.org/en/resources/documents/2021/2021_unaids_data.

Gurdasani, D., Barroso, I., Zeggini, E. & Sandhu, M. S. Genomics of disease risk in globally diverse populations. Nat. Rev. Genet. 20, 520–535 (2019).

Article CAS PubMed Google Scholar

McLaren, P. J. et al. Association study of common genetic variants and HIV-1 acquisition in 6,300 infected cases and 7,200 controls. PLoS Pathog. 9, e1003515 (2013).

Article CAS PubMed PubMed Central Google Scholar

Ahel, D. et al. Poly(ADP-ribose)-dependent regulation of DNA repair by the chromatin remodeling enzyme ALC1. Science 325, 1240–1243 (2009).

Article ADS CAS PubMed PubMed Central Google Scholar

Prevention Gap Report (UNAIDS, 2016).

Mellors, J. W. et al. Quantitation of HIV-1 RNA in plasma predicts outcome after seroconversion. Ann. Intern. Med. 122, 573–579 (1995).

Article CAS PubMed Google Scholar

De Wolf, F. et al. AIDS prognosis based on HIV-1 RNA, CD4+ T-cell count and function: markers with reciprocal predictive value over time after seroconversion. AIDS 11, 1799–1806 (1997).

Article PubMed Google Scholar

Quinn, T. C. et al. Viral load and heterosexual transmission of human immunodeficiency virus type 1. Rakai Project Study Group. N. Engl. J. Med. 342, 921–929 (2000).

Article CAS PubMed Google Scholar

Fideli, U. S. et al. Virologic and immunologic determinants of heterosexual transmission of human immunodeficiency virus type 1 in Africa. AIDS Res. Hum. Retroviruses 17, 901–910 (2001).

Article Google Scholar

McLaren, P. J. & Fellay, J. HIV-1 and human genetic variation. Nat. Rev. Genet. 22, 645–657 (2021).

Article CAS PubMed PubMed Central Google Scholar

Fellay, J. et al. Common genetic variation and the control of HIV-1 in humans. PLoS Genet. 5, e1000791 (2009).

Article PubMed PubMed Central Google Scholar

International HIV Controllers Study. The major genetic determinants of HIV-1 control affect HLA class I peptide presentation. Science 330, 1551–1557 (2010).

Article Google Scholar

McLaren, P. J. et al. Polymorphisms of large effect explain the majority of the host genetic contribution to variation of HIV-1 virus load. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.1514867112 (2015).

Pelak, K. et al. Host determinants of HIV‐1 control in African Americans. J. Infect. Dis. 201, 1141–1149 (2010).

Article CAS PubMed Google Scholar

Mclaren, P. J. et al. Fine-mapping classical HLA variation associated with durable host control of HIV-1 infection in African Americans. Hum. Mol. Genet. 21, 4334–4347 (2012).

Article CAS PubMed PubMed Central Google Scholar

Luo, Y. et al. A high-resolution HLA reference panel capturing global population diversity enables multi-ancestry fine-mapping in HIV host response. Nat. Genet. 53, 1504–1516 (2021).

Article CAS PubMed PubMed Central Google Scholar

Gurdasani, D. et al. The African Genome Variation Project shapes medical genetics in Africa. Nature 517, 327–332 (2015).

Article ADS CAS PubMed Google Scholar

Auton, A. et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).

Article ADS PubMed Google Scholar

Liu, J. Z. et al. Meta-analysis and imputation refines the association of 15q25 with smoking quantity. Nat. Genet. 42, 436–440 (2010).

Article CAS PubMed PubMed Central Google Scholar

Kiepiela, P. et al. Dominant influence of HLA-B in mediating the potential co-evolution of HIV and HLA. Nature 432, 769–775 (2004).

Article ADS CAS PubMed Google Scholar

Leslie, A. et al. Additive contribution of HLA class I alleles in the immune control of HIV-1 infection. J. Virol. 84, 9879–9888 (2010).

Article CAS PubMed PubMed Central Google Scholar

Pelak, K. et al. Host determinants of HIV-1 control in African Americans. J. Infect. Dis. 201, 1141–1149 (2010).

Article CAS PubMed Google Scholar

Dean, M. et al. Genetic restriction of HIV-1 infection and progression to AIDS by a deletion allele of the CKR5 structural gene. Science 273, 1856–1862 (1996).

Article ADS CAS PubMed Google Scholar

Novembre, J., Galvani, A. P. & Slatkin, M. The geographic spread of the CCR5 Delta32 HIV-resistance allele. PLoS Biol. 3, e339 (2005).

Article PubMed PubMed Central Google Scholar

MacArthur, J. et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. 45, D896–D901 (2017).

Article CAS PubMed Google Scholar

Lule, S. A. et al. A genome-wide association and replication study of blood pressure in Ugandan early adolescents. Mol. Genet. Genomic Med. 7, e00950 (2019).

Article PubMed PubMed Central Google Scholar

GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45, 580–585 (2013).

Article Google Scholar

Raj, T. et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes. Science 344, 519–523 (2014).

Article ADS CAS PubMed PubMed Central Google Scholar

Nédélec, Y. et al. Genetic ancestry and natural selection drive population differences in immune responses to pathogens. Cell 167, 657–669 (2016).

Article PubMed Google Scholar

Mogil, L. S. et al. Genetic architecture of gene expression traits across diverse populations. PLoS Genet. 14, e1007586 (2018).

Article PubMed PubMed Central Google Scholar

Shang, L. et al. Genetic architecture of gene expression in European and African Americans: an eQTL mapping study in GENOA. Am. J. Hum. Genet. 106, 496–512 (2020).

Article CAS PubMed PubMed Central Google Scholar

Randolph, H. E. et al. Genetic ancestry effects on the response to viral infection are pervasive but cell type specific. Science 374, 1127–1133 (2021).

Article ADS CAS PubMed PubMed Central Google Scholar

Kichaev, G. et al. Integrating functional data to prioritize causal variants in statistical fine-mapping studies. PLoS Genet. 10, e1004722 (2014).

Article PubMed PubMed Central Google Scholar

de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015).

Article PubMed PubMed Central Google Scholar

Gottschalk, A. J. et al. Poly(ADP-ribosyl)ation directs recruitment and activation of an ATP-dependent chromatin remodeler. Proc. Natl Acad. Sci. USA 106, 13770–13774 (2009).

Article ADS CAS PubMed PubMed Central Google Scholar

Ha, H. C. et al. Poly(ADP-ribose) polymerase-1 is required for efficient HIV-1 integration. Proc. Natl Acad. Sci. USA 98, 3364–3368 (2001).

Article ADS CAS PubMed PubMed Central Google Scholar

Yu, D., Liu, R., Yang, G. & Zhou, Q. The PARP1-Siah1 axis controls HIV-1 transcription and expression of Siah1 substrates. Cell Rep. 23, 3741–3749 (2018).

Article CAS PubMed PubMed Central Google Scholar

Di Primio, C. et al. Single-cell imaging of HIV-1 provirus (SCIP). Proc. Natl Acad. Sci. USA 110, 5636–5641 (2013).

Article ADS PubMed PubMed Central Google Scholar

Zhang, F. & Bieniasz, P. D. HIV-1 Vpr induces cell cycle arrest and enhances viral gene expression by depleting CCDC137. eLife 9, e55806 (2020).

Article PubMed PubMed Central Google Scholar

Orenstein, J. M., Fox, C. & Wahl, S. M. Macrophages as a source of HIV during opportunistic infections. Science 276, 1857–1861 (1997).

Article CAS PubMed Google Scholar

Igarashi, T. et al. Macrophage are the principal reservoir and sustain high virus loads in rhesus macaques after the depletion of CD4+ T cells by a highly pathogenic simian immunodeficiency virus/HIV type 1 chimera (SHIV): implications for HIV-1 infections of humans. Proc. Natl Acad. Sci. USA 98, 658–663 (2001).

Article ADS CAS PubMed PubMed Central Google Scholar

Andrade, V. M. et al. A minor population of macrophage-tropic HIV-1 variants is identified in recrudescing viremia following analytic treatment interruption. Proc. Natl Acad. Sci. USA 117, 9981–9990 (2020).

Article ADS CAS PubMed PubMed Central Google Scholar

Buchrieser, J., James, W. & Moore, M. D. Human induced pluripotent stem cell-derived macrophages share ontogeny with MYB-independent tissue-resident macrophages. Stem Cell Rep. 8, 334–345 (2017).

Article CAS Google Scholar

Sattentau, Q. J. & Stevenson, M. Macrophages and HIV-1: an unhealthy constellation. Cell Host Microbe 19, 304–310 (2016).

Article CAS PubMed PubMed Central Google Scholar

van Wilgenburg, B., Browne, C., Vowles, J. & Cowley, S. A. Efficient, long term production of monocyte-derived macrophages from human pluripotent stem cells under partly-defined and fully-defined conditions. PLoS ONE 8, e71098 (2013).

Article ADS PubMed PubMed Central Google Scholar

Popejoy, A. B. & Fullerton, S. M. Genomics is failing on diversity. Nature 538, 161–164 (2016).

Article ADS CAS PubMed PubMed Central Google Scholar

Honeycutt, J. B. et al. Macrophages sustain HIV replication in vivo independently of T cells. J. Clin. Invest. 126, 1353–1366 (2016).

Article PubMed PubMed Central Google Scholar

Kruize, Z. & Kootstra, N. A. The role of macrophages in HIV-1 persistence and pathogenesis. Front. Microbiol. 10, 2828 (2019).

Article PubMed PubMed Central Google Scholar

ICOVID-19 Host Genetics Initiative. Mapping the human genetic architecture of COVID-19. Nature https://doi.org/10.1038/s41586-021-03767-x (2021).

Ssemwanga, D. et al. Multiple HIV-1 infections with evidence of recombination in heterosexual partnerships in a low risk Rural Clinical Cohort in Uganda. Virology 411, 113–131 (2011).

Article CAS PubMed Google Scholar

Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

Article CAS PubMed PubMed Central Google Scholar

Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

Article CAS PubMed Google Scholar

Delaneau, O., Zagury, J. F. & Marchini, J. Improved whole-chromosome phasing for disease and population genetic studies. Nat. Methods 10, 5–6 (2013).

Article CAS PubMed Google Scholar

Howie, B., Fuchsberger, C., Stephens, M., Marchini, J. & Abecasis, G. R. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat. Genet. 44, 955–959 (2012).

Article CAS PubMed PubMed Central Google Scholar

Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).

Article CAS PubMed PubMed Central Google Scholar

Guan, Y. Detecting structure of haplotypes and local ancestry. Genetics 196, 625–642 (2014).

Article PubMed PubMed Central Google Scholar

Asiki, G. et al. The general population cohort in rural south-western Uganda: a platform for communicable and non-communicable disease studies. Int. J. Epidemiol. 42, 129–141 (2013).

Article PubMed PubMed Central Google Scholar

Gurdasani, D. et al. Uganda genome resource enables insights into population history and genomic discovery in Africa. Cell 179, 984–1002 (2019).

Article CAS PubMed PubMed Central Google Scholar

Roadmap Epigenomics Consortium et al.Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

Article PubMed Central Google Scholar

Hnisz, D. et al. Super-enhancers in the control of cell identity and disease. Cell 155, 934–947 (2013).

Article CAS PubMed Google Scholar

Maurano, M. T. et al. Systematic localization of common disease-associated variation in regulatory DNA. Science 337, 1190–1195 (2012).

Article ADS CAS PubMed PubMed Central Google Scholar

Lizio, M. et al. Gateways to the FANTOM5 promoter level mammalian expression atlas. Genome Biol. 16, 22 (2015).

Article CAS PubMed PubMed Central Google Scholar

Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

Article PubMed PubMed Central Google Scholar

Shabalin, A. A. Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics 28, 1353–1358 (2012).

Article CAS PubMed PubMed Central Google Scholar

Hormozdiari, F. et al. Colocalization of GWAS and eQTL signals detects target genes. Am. J. Hum. Genet. 99, 1245–1260 (2016).

Article CAS PubMed PubMed Central Google Scholar

Sellou, H. et al. The poly(ADP-ribose)-dependent chromatin remodeler Alc1 induces local chromatin relaxation upon DNA damage. Mol. Biol. Cell 27, 3791–3799 (2016).

Article CAS PubMed PubMed Central Google Scholar

Lund, M. E., To, J., O’Brien, B. A. & Donnelly, S. The choice of phorbol 12-myristate 13-acetate differentiation protocol influences the response of THP-1 macrophages to a pro-inflammatory stimulus. J. Immunol. Methods 430, 64–70 (2016).

Article CAS PubMed Google Scholar

Lieu, P. T., Fontes, A., Vemuri, M. C. & Macarthur, C. C. Generation of induced pluripotent stem cells with CytoTune, a non-integrating Sendai virus. Methods Mol. Biol. 997, 45–56 (2013).

Article CAS PubMed Google Scholar

Bressan, R. B. et al. Efficient CRISPR/Cas9-assisted gene targeting enables rapid and precise genetic manipulation of mammalian neural stem cells. Development 144, 635–648 (2017).

CAS PubMed PubMed Central Google Scholar

Hodgkins, A. et al. WGE: a CRISPR database for genome engineering. Bioinformatics 31, 3078–3080 (2015).

Article CAS PubMed PubMed Central Google Scholar

Tate, P. H. & Skarnes, W. C. Bi-allelic gene targeting in mouse embryonic stem cells. Methods 53, 331–338 (2011).

Article CAS PubMed PubMed Central Google Scholar

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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. 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)

These authors contributed equally: Paul J. McLaren, Immacolata Porreca, Gennaro Iaconis, Hoi Ping Mok, Subhankar Mukhopadhyay, Emre Karakoc

These authors jointly supervised this work: Gordon Dougan, Andrew M. L. Lever, Deepti Gurdasani, Harriet Groom, Manjinder S. Sandhu, Jacques Fellay

Sexually Transmitted and Blood-Borne Infections Division at JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Manitoba, Canada

Paul J. McLaren, Riley H. Tough & Jeffrey F. Tuff

Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Manitoba, Canada

Paul J. McLaren, Riley H. Tough, Ma Luo & Francis A. Plummer

Wellcome Trust Sanger Institute, Hinxton, UK

Immacolata Porreca, Emre Karakoc, Cristina Pomilla, Tommy Carstensen, Tarryn Porter, Andrew Bassett & Gordon Dougan

Department of Medicine, University of Cambridge, Cambridge, UK

Gennaro Iaconis, Hoi Ping Mok, Tommy Carstensen, Isobel Jarvis, Gordon Dougan, Andrew M. L. Lever & Harriet Groom

Peter Gorer Department of Immunobiology, School of Immunology and Microbial Sciences, King’s College London, London, UK

Subhankar Mukhopadhyay & Cher S. Kiar

Institute of Microbiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland

Sara Cristinelli & Angela Ciuffi

Global Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

István Bartha, Christian W. Thorball & Jacques Fellay

Swiss Institute of Bioinformatics, Lausanne, Switzerland

István Bartha, Christian W. Thorball, Paolo Angelino & Jacques Fellay

Precision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland

Christian W. Thorball & Jacques Fellay

The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda

Segun Fatumo

Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK

Segun Fatumo

The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA

William C. Skarnes

Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

Marianne K. DeGorter, Mohana Prasad Sathya Moorthy & Stephen B. Montgomery

Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA

Mohana Prasad Sathya Moorthy & Stephen B. Montgomery

Division of Infectious Diseases, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

Eun-Young Kim, Miriam Walter, Lacy M. Simons, Kireem Nam, Judd F. Hultquist & Steven M. Wolinsky

Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD, USA

Arman Bashirova & Mary Carrington

Laboratory of Integrative Cancer Immunology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA

Arman Bashirova & Mary Carrington

Bridge HIV, San Francisco Department of Public Health, San Francisco, CA, USA

Susan Buchbinder

Ragon Institute of MGH, MIT and Harvard, Boston, MA, USA

Mary Carrington & Bruce D. Walker

Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, Modena, Italy

Andrea Cossarizza

University Division of Infectious Diseases, Siena University Hospital, Siena, Italy

Andrea De Luca

Department of Medical Biotechnologies, University of Siena, Siena, Italy

Andrea De Luca

Epidemiology and Biostatistics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

James J. Goedert

Institute for Genomic Medicine, Columbia University, New York, NY, USA

David B. Goldstein

Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA

David W. Haas & Simon Mallal

Department of Global Health, University of Washington, Seattle, WA, USA

Joshua T. Herbeck

GenOmics and Translational Research Center and Fellow Program, RTI International, Research Triangle Park, NC, USA

Eric O. Johnson

Medical Research Council/Uganda Virus Research Institute & London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda

Pontiano Kaleebu

London School of Hygiene and Tropical Medicine, London, UK

Pontiano Kaleebu

Center for Family Health Research—Zambia, Lusaka, Zambia

William Kilembe

Department of Epidemiology, Johns Hopkins University, Baltimore, MD, USA

Gregory D. Kirk

Department of Experimental Immunology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands

Neeltje A. Kootstra

Community Health Research Division, RTI International, Berkeley, CA, USA

Alex H. Kral

Université Paris Saclay, Inserm UMR1184, CEA, Le Kremlin-Bicêtre, France

Olivier Lambotte

APHP, Department of Clinical Immunology, Bicêtre Hospital, Le Kremlin-Bicêtre, France

Olivier Lambotte

Vaccine and Therapeutics Laboratory, Medical and Scientific Affairs, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Manitoba, Canada

Ma Luo

Institute for Immunology & Infectious Diseases, Murdoch University, Perth, Western Australia, Australia

Simon Mallal

University of Vic—Central University of Catalonia, Vic, Spain

Javier Martinez-Picado

IrsiCaixa AIDS Research Institute, Badalona, Spain

Javier Martinez-Picado

Catalan Institution for Research and Advanced Studies, Barcelona, Spain

Javier Martinez-Picado

CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain

Javier Martinez-Picado & José M. Miro

INSERM U1018, Université Paris-Saclay, Le Kremlin Bicêtre, France

Laurence Meyer

AP-HP, Hôpital de Bicêtre, Département d’Épidémiologie, Le Kremlin Bicêtre, France

Laurence Meyer

Infectious Diseases Service, Hospital Clinic—Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain

José M. Miro

National Health Laboratory Service, South Africa and University of KwaZulu-Natal, Durban, South Africa

Pravi Moodley

Department of Diabetes and Endocrinology, School of Clinical Medicine, University of KwaZulu-Natal, Durban, South Africa

Ayesha A. Motala & Fraser Pirie

Department of Microbiology, University of Washington, Seattle, WA, USA

James I. Mullins

Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark

Niels Obel

Division of Immunology, Transplantation and Infectious Diseases, San Raffaele Scientific Institute, Milan, Italy

Guido Poli

School of Medicine, Vita-Salute San Raffaele University, Milan, Italy

Guido Poli

International AIDS Vaccine Initiative, New York, NY, USA

Matthew A. Price

Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA

Matthew A. Price

Department of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

Andri Rauch

Laboratoire d’Immunologie, Hôpital Robert Debré Paris, Paris, France

Ioannis Theodorou

Institute of Medical Virology, University of Zurich, Zurich, Switzerland

Alexandra Trkola

Howard Hughes Medical Institute, Chevy Chase, MD, USA

Bruce D. Walker

Basic Research Laboratory, Molecular Genetic Epidemiology Section, Frederick National Laboratory for Cancer Research and Cancer Innovative Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, MD, USA

Cheryl A. Winkler

Laboratoire Génomique, Bioinformatique et Chimie Moléculaire, EA7528, Conservatoire National des Arts et Métiers, HESAM Université, Paris, France

Jean-François Zagury

Department of Medicine, National University of Singapore, Singapore, Singapore

Andrew M. L. Lever

Queen Mary University of London, London, UK

Deepti Gurdasani

Kirby Institute, University of New South Wales, Sydney, New South Wales, Australia

Deepti Gurdasani

Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK

Manjinder S. Sandhu

MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK

Manjinder S. Sandhu

Omnigen Biodata, Cambridge, UK

Manjinder S. Sandhu

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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.

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

The authors declare no competing interests.

Nature thanks Luke Jostins-Dean, Nico Lachmann, Lluis Quintana-Murci and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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).

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.

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.

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).

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.

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).

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

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).

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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 (2023). https://doi.org/10.1038/s41586-023-06370-4

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Received: 28 November 2018

Accepted: 26 June 2023

Published: 02 August 2023

DOI: https://doi.org/10.1038/s41586-023-06370-4

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