The Major Genetic Determinants of HIV-1 Control Affect HLA Class I Peptide Presentation

doi:10.1126/science.1195271

Science. Author manuscript; available in PMC 2011 December 11.

Published in final edited form as:

Science. 2010 December 10; 330(6010): 1551–1557.

Published online 2010 November 4. doi: 10.1126/science.1195271

PMCID: PMC3235490

NIHMSID: NIHMS331514

The Major Genetic Determinants of HIV-1 Control Affect HLA Class I Peptide Presentation

The International HIV Controllers Study,^*^† Writing team, Florencia Pereyra,^1,²^‡ Xiaoming Jia,³^‡ Paul J. McLaren,^4,⁵^‡ Amalio Telenti,⁶ Paul I.W. de Bakker, co-chair,^4,^5,^7,⁸^† Bruce D. Walker, co-chair,^1,⁹^‡ Analysis team, Xiaoming Jia,³ Paul J. McLaren, project leaders,^4,⁵ Stephan Ripke,^4,¹⁰ Chanson J. Brumme,¹ Sara L. Pulit,^4,⁵ Amalio Telenti,⁶ Mary Carrington,^1,¹¹ Carl M. Kadie,¹² Jonathan M. Carlson,¹³ David Heckerman,¹³ Paul I.W. de Bakker, chair,^4,^5,^7,⁸^† Study design, Florencia Pereyra,^1,² Paul I.W. de Bakker,^4,^5,^7,⁸^† Robert R. Graham,¹⁴ Robert M. Plenge,^4,¹⁵ Steven G. Deeks,¹⁶ Bruce D. Walker, chair,^1,⁹^† SNP genotyping, HLA typing, and sample management, Lauren Gianniny,⁴ Gabriel Crawford,⁴ Jordan Sullivan,⁴ Elena Gonzalez,⁴ Leela Davies,⁴ Amy Camargo,⁴ Jamie M. Moore,⁴ Nicole Beattie,⁴ Supriya Gupta,⁴ Andrew Crenshaw,⁴ Noël P. Burtt,⁴ Candace Guiducci,⁴ Namrata Gupta,⁴ Mary Carrington,^1,¹¹ Xiaojiang Gao,¹¹ Ying Qi,¹¹ Yuko Yuki,¹¹ HIV controllers recruitment and sample management, Florencia Pereyra, project leader,^1,² Alicja Piechocka-Trocha,¹ Emily Cutrell,¹ Rachel Rosenberg,¹ Kristin L. Moss,¹ Paul Lemay,¹ Jessica O’Leary,¹ Todd Schaefer,¹ Pranshu Verma,¹ Ildiko Toth,¹ Brian Block,¹ Brett Baker,¹ Alissa Rothchild,¹ Jeffrey Lian,¹ Jacqueline Proudfoot,¹ Donna Marie L. Alvino,¹ Seanna Vine,¹ Marylyn M. Addo,¹ Todd M. Allen,¹ Marcus Altfeld,¹ Matthew R. Henn,⁴ Sylvie Le Gall,¹ Hendrik Streeck,¹ Bruce D. Walker, chair,^1,⁹^† AIDS Clinical Trials Group, David W. Haas,¹⁷ Daniel R. Kuritzkes,² Gregory K. Robbins,¹⁸ Robert W. Shafer,¹⁹ Roy M. Gulick,²⁰ Cecilia M. Shikuma,²¹ Richard Haubrich,²² Sharon Riddler,²³ Paul E. Sax,² Eric S. Daar,²⁴ Heather J. Ribaudo,²⁵ HIV controllers referral team, Brian Agan,²⁶ Shanu Agarwal,²⁷ Richard L. Ahern,¹⁸ Brady L. Allen,²⁸ Sherly Altidor,²⁹ Eric L. Altschuler,³⁰ Sujata Ambardar,³¹ Kathryn Anastos,³² Ben Anderson,³³ Val Anderson,³⁴ Ushan Andrady,³⁴ Diana Antoniskis,³⁵ David Bangsberg,^1,¹⁸ Daniel Barbaro,³⁶ William Barrie,³⁷ J. Bartczak,³⁸ Simon Barton,³⁹ Patricia Basden,⁴⁰ Nesli Basgoz,¹⁸ Suzane Bazner,¹ Nicholaos C. Bellos,⁴¹ Anne M. Benson,⁴⁰ Judith Berger,⁴² Nicole F. Bernard,⁴³ Annette M. Bernard,⁴⁴ Christopher Birch,¹ Stanley J. Bodner,⁴⁵ Robert K. Bolan,⁴⁶ Emilie T. Boudreaux,⁴⁷ Meg Bradley,¹ James F. Braun,⁴⁸ Jon E. Brndjar,⁴⁹ Stephen J. Brown,⁵⁰ Katherine Brown,⁵¹ Sheldon T. Brown,⁵² Jedidiah Burack,⁵³ Larry M. Bush,⁵⁴ Virginia Cafaro,⁵⁵ Omobolaji Campbell,¹⁸ John Campbell,⁵⁶ Robert H. Carlson,⁵⁷ J. Kevin Carmichael,⁵⁸ Kathleen K. Casey,⁵⁹ Chris Cavacuiti,⁶⁰ Gregory Celestin,⁶¹ Steven T. Chambers,⁶² Nancy Chez,⁶³ Lisa M. Chirch,⁶⁴ Paul J. Cimoch,⁶⁵ Daniel Cohen,⁶⁶ Lillian E. Cohn,⁶⁷ Brian Conway,⁶⁸ David A. Cooper,⁶⁹ Brian Cornelson,⁶⁰ David T. Cox,⁷⁰ Michael V. Cristofano,⁷¹ George Cuchural, Jr.,⁷² Julie L. Czartoski,⁷³ Joseph M. Dahman,⁷⁴ Jennifer S. Daly,⁷⁵ Benjamin T. Davis,¹⁸ Kristine Davis,⁷⁶ Sheila M. Davod,¹⁸ Steven G. Deeks,¹⁶ Edwin DeJesus,⁷⁷ Craig A. Dietz,⁷⁸ Eleanor Dunham,⁶⁴ Michael E. Dunn,⁷⁹ Todd B. Ellerin,⁸⁰ Joseph J. Eron,⁸¹ John J.W. Fangman,⁸² Claire E. Farel,² Helen Ferlazzo,⁸³ Sarah Fidler,⁸⁴ Anita Fleenor-Ford,⁸⁵ Renee Frankel,⁸⁶ Kenneth A. Freedberg,¹⁸ Neel K. French,⁸⁷ Jonathan D. Fuchs,⁸⁸ Jon D. Fuller,⁸⁹ Jonna Gaberman,⁹⁰ Joel E. Gallant,⁹¹ Rajesh T. Gandhi,¹⁸ Efrain Garcia,⁹² Donald Garmon,⁹³ Joseph C. Gathe, Jr.,⁹⁴ Cyril R. Gaultier,⁹⁵ Wondwoosen Gebre,⁹⁶ Frank D. Gilman,⁹⁷ Ian Gilson,⁹⁸ Paul A. Goepfert,⁹⁹ Michael S. Gottlieb,¹⁰⁰ Claudia Goulston,¹⁰¹ Richard K. Groger,¹⁰² T. Douglas Gurley,¹⁰³ Stuart Haber,¹⁰⁴ Robin Hardwicke,¹⁰⁵ W. David Hardy,²⁴ P. Richard Harrigan,¹⁰⁶ Trevor N. Hawkins,¹⁰⁷ Sonya Heath,⁹⁹ Frederick M. Hecht,¹⁶ W. Keith Henry,¹⁰⁸ Melissa Hladek,¹⁰⁹ Robert P. Hoffman,¹¹⁰ James M. Horton,¹¹¹ Ricky K. Hsu,¹¹² Gregory D. Huhn,¹¹³ Peter Hunt,¹⁶ Mark J. Hupert,³⁶ Mark L. Illeman,¹¹⁴ Hans Jaeger,¹¹⁵ Robert M. Jellinger,¹¹⁶ Mina John,¹¹⁷ Jennifer A. Johnson,² Kristin L. Johnson,¹⁸ Heather Johnson,³⁶ Kay Johnson,¹¹⁸ Jennifer Joly,⁶⁴ Wilbert C. Jordan,¹¹⁹ Carol A. Kauffman,¹²⁰ Homayoon Khanlou,¹²¹ Robert K. Killian,¹²² Arthur Y. Kim,¹⁸ David D. Kim,¹²³ Clifford A. Kinder,¹²⁴ Jeffrey T. Kirchner,¹²⁵ Laura Kogelman,¹²⁶ Erna Milunka Kojic,¹²⁷ P. Todd Korthuis,¹²⁸ Wayne Kurisu,⁹⁷ Douglas S. Kwon,¹ Melissa LaMar,⁹³ Harry Lampiris,¹⁶ Massimiliano Lanzafame,¹²⁹ Michael M. Lederman,¹³⁰ David M. Lee,²⁸ Jean M.L. Lee,⁷³ Marah J. Lee,¹³¹ Edward T.Y. Lee,¹³² Janice Lemoine,¹³³ Jay A. Levy,¹⁶ Josep M. Llibre,¹³⁴ Michael A. Liguori,¹¹² Susan J. Little,²² Anne Y. Liu,² Alvaro J. Lopez,¹³⁵ Mono R. Loutfy,¹³⁶ Dawn Loy,¹³⁷ Debbie Y. Mohammed,³⁰ Alan Man,³⁵ Michael K. Mansour,¹⁸ Vincent C. Marconi,¹³⁸ Martin Markowitz,¹³⁹ Rui Marques,¹⁴⁰ Jeffrey N. Martin,¹⁶ Harold L. Martin, Jr.,¹⁴¹ Kenneth Hugh Mayer,⁶⁶ M. Juliana McElrath,⁷³ Theresa A. McGhee,¹⁴² Barbara H. McGovern,¹²⁶ Katherine McGowan,² Dawn McIntyre,⁵⁹ Gavin X. Mcleod,¹⁴³ Prema Menezes,⁸¹ Greg Mesa,¹⁴⁴ Craig E. Metroka,²⁹ Dirk Meyer-Olson,¹⁴⁵ Andy O. Miller,¹⁴⁶ Kate Montgomery,¹⁴⁷ Karam C. Mounzer,¹⁴⁸ Ellen H. Nagami,¹ Iris Nagin,¹⁴⁹ Ronald G. Nahass,¹⁵⁰ Margret O. Nelson,¹⁸ Craig Nielsen,¹⁵¹ David L. Norene,¹⁵² David H. O’Connor,¹⁵³ Bisola O. Ojikutu,¹⁸ Jason Okulicz,¹⁵⁴ Olakunle O. Oladehin,¹⁸ Edward C. Oldfield, III,¹⁵⁵ Susan A. Olender,¹⁵⁶ Mario Ostrowski,¹³⁶ William F. Owen, Jr.,¹⁵⁷ Eunice Pae,¹ Jeffrey Parsonnet,¹⁵⁸ Andrew M. Pavlatos,¹⁵⁹ Aaron M. Perlmutter,¹⁶⁰ Michael N. Pierce,²¹⁸ Jonathan M. Pincus,¹⁶¹ Leandro Pisani,¹⁶² Lawrence Jay Price,¹⁶³ Laurie Proia,¹⁶⁴ Richard C. Prokesch,¹³⁷ Heather Calderon Pujet,¹⁶⁵ Moti Ramgopal,¹⁶⁶ Almas Rathod,¹ Michael Rausch,¹⁶⁷ J. Ravishankar,¹⁶⁸ Frank S. Rhame,¹⁶⁹ Constance Shamuyarira Richards,¹⁷⁰ Douglas D. Richman,²² Gregory K. Robbins,¹⁸ Berta Rodes,¹⁷¹ Milagros Rodriguez,¹⁶² Richard C. Rose, III,¹⁷² Eric S. Rosenberg,¹⁸ Daniel Rosenthal,¹⁷³ Polly E. Ross,¹⁷⁴ David S. Rubin,¹⁷⁵ Elease Rumbaugh,³⁵ Luis Saenz,¹⁶² Michelle R. Salvaggio,¹⁷⁶ William C. Sanchez,¹⁷⁷ Veeraf M. Sanjana,¹⁷⁸ Steven Santiago,¹⁶² Wolfgang Schmidt,¹⁷⁹ Hanneke Schuitemaker,¹⁸⁰ Philip M. Sestak,¹⁸¹ Peter Shalit,¹⁸² William Shay,¹⁰⁴ Vivian N. Shirvani,¹⁸³ Vanessa I. Silebi,¹⁸⁴ James M. Sizemore, Jr.,¹⁸⁵ Paul R. Skolnik,⁸⁹ Marcia Sokol-Anderson,¹⁸⁶ James M. Sosman,¹⁵³ Paul Stabile,¹⁸⁷ Jack T. Stapleton,¹⁸⁸ Sheree Starrett,¹⁸⁹ Francine Stein,⁸³ Hans-Jurgen Stellbrink,¹⁹⁰ F. Lisa Sterman,¹⁹¹ Valerie E. Stone,¹⁸ David R. Stone,¹⁹² Giuseppe Tambussi,¹⁹³ Randy A. Taplitz,²² Ellen M. Tedaldi,¹⁹⁴ Amalio Telenti,⁶ William Theisen,² Richard Torres,¹⁹⁵ Lorraine Tosiello,¹⁹⁶ Cecile Tremblay,¹⁹⁷ Marc A. Tribble,¹⁹⁸ Phuong D. Trinh,¹⁹⁹ Alice Tsao,¹ Peggy Ueda,¹ Anthony Vaccaro,²⁰⁰ Emilia Valadas,²⁰¹ Thanes J. Vanig,²⁰² Isabel Vecino,²⁰³ Vilma M. Vega,¹³⁷ Wenoah Veikley,¹⁰⁷ Barbara H. Wade,²⁰⁴ Charles Walworth,⁶⁵ Chingchai Wanidworanun,²⁰⁵ Douglas J. Ward,²⁰⁶ Daniel A. Warner,²⁰⁷ Robert D. Weber,²⁰⁸ Duncan Webster,²⁰⁹ Steve Weis,²⁰³ David A. Wheeler,²¹⁰ David J. White,²¹¹ Ed Wilkins,²¹² Alan Winston,⁸⁴ Clifford G. Wlodaver,²¹³ Angelique van’t Wout,¹⁸⁰ David P. Wright,²¹⁴ Otto O. Yang,²⁴ David L. Yurdin,²¹⁵ Brandon W. Zabukovic,²¹⁶ Kimon C. Zachary,¹⁸ Beth Zeeman,¹ and Meng Zhao²¹⁷

¹Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology (MIT) and Harvard, Boston, MA, USA

²Department of Medicine, Division of Infectious Disease, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

³Harvard-MIT Division of Health Sciences and Technology, Boston, MA, USA

⁴Broad Institute of Harvard and MIT, Cambridge, MA, USA

⁵Department of Medicine, Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

⁶Institute of Microbiology, University of Lausanne, Lausanne, Switzerland

⁷Department of Medical Genetics, Division of Biomedical Genetics, University Medical Center Utrecht, Netherlands

⁸Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Netherlands

⁹Howard Hughes Medical Institute, Chevy Chase, MD, USA

¹⁰Department of Medicine, Center for Human Genetic Research, MGH, Harvard Medical School, Boston, MA, USA

¹¹Cancer and Inflammation Program, Laboratory of Experimental Immunology, SAIC-Frederick, NCI-Frederick, Frederick, MD, USA

¹²Microsoft Research, Redmond, WA, USA

¹³Microsoft Research, Los Angeles, CA, USA

¹⁴Genentech, South San Francisco, CA, USA

¹⁵Department of Medicine, Division of Rheumatology, Immunology and Allergy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

¹⁶University of California San Francisco, San Francisco, CA, USA

¹⁷Vanderbilt University School of Medicine, Nashville, TN, USA

¹⁸MGH, Harvard Medical School, Boston, MA, USA

¹⁹Stanford University, Palo Alto, CA, USA

²⁰Weill Medical College of Cornell University, New York, NY, USA

²¹Hawaii Center for AIDS, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, USA

²²University of California San Diego, San Diego, CA, USA

²³University of Pittsburgh, Pittsburgh, PA, USA

²⁴University of California Los Angeles, Los Angeles, CA, USA

²⁵Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA

²⁶Infectious Disease Clinical Research Program, Uniformed Services University of the Health Sciences, Bethesda, MD, USA

²⁷Summa Health System, Akron, OH, USA

²⁸Uptown Physicians Group, Dallas, TX, USA

²⁹St. Luke’s Roosevelt Hospital, New York, NY, USA

³⁰New Jersey Medical School, University Hospital, Newark, NJ, USA

³¹Infectious Disease Physicians, Annandale, VA, USA

³²Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA

³³St. Leonards Medical Centre, St. Leonards, Australia

³⁴Ysbyty Gwynedd Hospital, Gwynedd, UK

³⁵Kaiser Permanente, Portland, OR, USA

³⁶Tarrant County Infectious Disease Associates, Fort Worth, TX, USA

³⁷Private Practice of William Barrie, Toronto, Canada

³⁸Rowan Tree Medical, Wilton Manors, FL, USA

³⁹Chelsea and Westminster Hospital, St. Stephen’s Centre, London, UK

⁴⁰Beaver Street Family Practice, Flagstaff, AZ, USA

⁴¹Southwest Infectious Disease Associates, Dallas, TX, USA

⁴²St. Barnabas Hospital, Bronx, NY, USA

⁴³Research Institute, McGill University Health Centre, Montreal General Hospital, Montreal, Canada

⁴⁴Thacker, Thompson and Bernard, Atlanta, GA, USA

⁴⁵Vanderbilt University School of Medicine, Hermitage, TN, USA

⁴⁶LA Gay and Lesbian Center, Los Angeles, CA, USA

⁴⁷Louisiana State University Health Sciences Center, University Medical Center East Clinic, Lafayatte, LA, USA

⁴⁸Physicians’ Research Network, Callen-Lorde Community Health Center, New York, NY, USA

⁴⁹Brndjar Medical Associates, Allentown, PA, USA

⁵⁰AIDS Research Alliance, Los Angeles, CA, USA

⁵¹David Powell Community Health Center, Austin, TX, USA

⁵²James J. Peters VA Medical Center, Bronx, NY, USA

⁵³Sunrise Medical Group, Brooklyn, NY, USA

⁵⁴University of Miami-Miller School of Medicine, Lake Worth, FL, USA

⁵⁵WellSpring Medical Group, San Francisco, CA, USA

⁵⁶Moses Cone Health System, Greensboro, NC, USA

⁵⁷HealthPartners Infectious Disease, St Paul, MN, USA

⁵⁸El Rio Special Immunology Associates, Tuscon, AZ, USA

⁵⁹Jersey Shore University Medical Center, Neptune, NJ, USA

⁶⁰St. Michaels Hospital, Toronto, Canada

⁶¹The Brooklyn Hospital Center, PATH Center, Brooklyn, NY, USA

⁶²University of Otago, Christchurch, New Zealand

⁶³H.E.L.P./Project Samaritan, Bronx, NY, USA

⁶⁴David E. Rogers Center for HIV/AIDS Care, Southampton, NY, USA

⁶⁵Center for Special Immunology, Fountain Valley, CA, USA

⁶⁶Fenway Community Health, Boston, MA, USA

⁶⁷9th Street Internal Medicine Associates, Philadelphia, PA, USA

⁶⁸University of British Columbia, Vancouver, Canada

⁶⁹National Centre in HIV Epidemiology and Clinical Research, Sydney, Australia

⁷⁰Metro Infectious Disease Consultants, Indianapolis, IN, USA

⁷¹John H. Stroger Hospital of Cook County, Chicago, IL, USA

⁷²New England Quality Care Alliance, Braintree, MA, USA

⁷³Fred Hutchinson Cancer Research Center, Seattle, WA, USA

⁷⁴Desert AIDS Project, Palm Springs, CA, USA

⁷⁵University of Massachusetts Memorial Medical Center, Worcester, MA, USA

⁷⁶University of Iowa Hospitals and Clinics, Iowa City, IA, USA

⁷⁷Orlando Immunology Center, Orlando, FL, USA

⁷⁸The Kansas City Free Health Clinic, Kansas City, MO, USA

⁷⁹Private Practice of Michael E. Dunn, M.D., Tampa, FL, USA

⁸⁰South Shore Hospital, Weymouth, MA, USA

⁸¹University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

⁸²AIDS Resource Center of Wisconsin, Milwaukee, WI, USA

⁸³Visiting Nurse Association of Central New Jersey, Community Health Center, Asbury Park, NJ, USA

⁸⁴Imperial College, London, UK

⁸⁵Heartland Clinic, Paducah, KY, USA

⁸⁶Morristown Memorial Hospital, Morristown, NJ, USA

⁸⁷Private Practice of Neel K. French, M.D., Chicago, IL, USA

⁸⁸San Francisco Department of Public Health, San Francisco, CA, USA

⁸⁹Boston University Medical Center, Boston, MA, USA

⁹⁰Baystate Medical Center, Springfield, MA, USA

⁹¹Johns Hopkins University School of Medicine, Baltimore, MD, USA

⁹²Private Practice of Efrain Garcia, M.D., Miami, FL, USA

⁹³The Rockefeller University, New York, NY, USA

⁹⁴Private Practice of Joseph C. Gathe Jr., M.D., Houston, TX, USA

⁹⁵Tower Infectious Disease, Los Angeles, CA, USA

⁹⁶Nassau University Medical Center, East Meadow, NY, USA

⁹⁷Sharp Rees Stealy Medical Center, San Diego, CA, USA

⁹⁸Medical College of Wisconsin, Milwaukee, WI, USA

⁹⁹University of Alabama, Birmingham, Birmingham, AL, USA

¹⁰⁰Synergy Hematology and Oncology, Los Angeles, CA, USA

¹⁰¹University of Utah, Salt Lake City, UT, USA

¹⁰²South Dayton Acute Care Consultants, Dayton, OH, USA

¹⁰³T. Douglas Gurley, M.D., Atlanta, GA, USA

¹⁰⁴St. Vincent’s Hospital, New York, NY, USA

¹⁰⁵University of Texas Health Science Center, Houston, TX, USA

¹⁰⁶British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada

¹⁰⁷Southwest C.A.R.E. Center, Santa Fe, NM, USA

¹⁰⁸Hennepin County Medical Center, Minneapolis, MN, USA

¹⁰⁹The Catholic University of America, School of Nursing, Washington, DC, USA

¹¹⁰Mercy Medical Center, Springfield, MA, USA

¹¹¹CMC Myers Park Medical Center, Charlotte, NC, USA

¹¹²New York University Medical Center, New York, NY, USA

¹¹³The Ruth M. Rothshon Care Center, Chicago, IL, USA

¹¹⁴Feldman Medical Group, San Francisco, CA, USA

¹¹⁵HIV Research and Clinical Care Centre, Munich, Germany

¹¹⁶Albany Medical College, Albany, NY, USA

¹¹⁷Murdoch University, Murdoch, Australia

¹¹⁸University of Cincinnati, Cincinnati, OH, USA

¹¹⁹OASIS Clinic, Los Angeles, CA, USA

¹²⁰VA Ann Arbor Healthcare System, Ann Arbor, MI, USA

¹²¹AIDS Healthcare Foundation, Los Angeles, CA, USA

¹²²Capitol Hill Medical, Seattle, WA, USA

¹²³Astor Medical Group, New York, NY, USA

¹²⁴The Kinder Medical Group, Miami, FL, USA

¹²⁵Lancaster General Hospital, Lancaster, PA, USA

¹²⁶Tufts Medical Center, Boston, MA, USA

¹²⁷Alpert Medical School of Brown University, Providence, RI, USA

¹²⁸Oregon Health and Science University, Portland, OR, USA

¹²⁹G.B. Rossi Hospital, Verona, Italy

¹³⁰Case Western Reserve University, Cleveland, OH, USA

¹³¹LifeWay, Fort Lauderdale, FL, USA

¹³²Saint Claire Medical Associate, Toronto, Canada

¹³³Greater Lawrence Family Health Center, Lawrence, MA, USA

¹³⁴Hospital Universitari Germans Trias i Pujol, Barcelona, Spain

¹³⁵Infectious Disease Consultants, Tucker, GA, USA

¹³⁶University of Toronto, Toronto, Canada

¹³⁷Infectious Disease Associates, Sarasota, FL, USA

¹³⁸Emory University, School of Medicine, Atlanta, GA, USA

¹³⁹Aaron Diamond AIDS Research Center, Rockefeller University, New York, NY, USA

¹⁴⁰Deruico Doencas Infecciosas, Porto, Portugal

¹⁴¹Park Nicollet Clinic, St. Louis, MN, USA

¹⁴²Absolute Care, Atlanta, GA, USA

¹⁴³College of Physicians and Surgeons, Columbia University, New York, NY, USA

¹⁴⁴Highland Medical Associates, Hendersonville, NC, USA

¹⁴⁵Medizinische Hochschule, Abteilung Klinische Immunologie, Hannover, Germany

¹⁴⁶Hospital for Special Surgery, New York, NY, USA

¹⁴⁷Family Practice Specialists,Phoenix,AZ,USA

¹⁴⁸Philadelphia FIGHT, Philadelphia, PA, USA

¹⁴⁹Lower East Side Service Center, New York, NY, USA

¹⁵⁰Infectious Diseases Care, Hillsborough, NJ, USA

¹⁵¹University of Colorado, Denver, Aurora, CO, USA

¹⁵²Sutter Medical Group, Sacramento, CA, USA

¹⁵³University of Wisconsin in Madison, Madison, WI, USA

¹⁵⁴Brooke Army Medical Center, San Antonio, TX, USA

¹⁵⁵Eastern Virginia Medical School, Norfolk, VA, USA

¹⁵⁶Columbia University Medical Center, New York, NY, USA

¹⁵⁷CA Pacific Medical Center, San Francisco, CA, USA

¹⁵⁸Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA

¹⁵⁹St. Joseph Hospital, Chicago, IL, USA

¹⁶⁰Aaron M. Perlmutter, M.D., Beverly Hills, CA, USA

¹⁶¹Codman Square Health Center, Dorchester, MA, USA

¹⁶²CARE Resource, Miami, FL, USA

¹⁶³Castro-Mission Health Center, San Francisco, CA, USA

¹⁶⁴Rush Medical College, Chicago, IL, USA

¹⁶⁵Boulder Community Hospital, Boulder, CO, USA

¹⁶⁶Midway Immunology and Research Center, Fort Pierce, FL, USA

¹⁶⁷Aerztezentrum Nollendorfplatz, Berlin, Germany

¹⁶⁸State University of New York Downstate Medical Center, Brooklyn, NY, USA

¹⁶⁹Clinic 42, Minneapolis, MN, USA

¹⁷⁰King Edward Memorial Hospital, Paget, Bermuda

¹⁷¹Fundacion para la Investigacion Biomedica del Hospital Carlos III, Madrid, Spain

¹⁷²Summit Medical Group, Knoxville, TN, USA

¹⁷³Medical Consultants of South Florida, Coral Springs, FL, USA

¹⁷⁴Western North Carolina Community Health Services, Asheville, NC, USA

¹⁷⁵New York Hospital Medical Center of Queens, Flushing, NY, USA

¹⁷⁶University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA

¹⁷⁷Georgetown University Medical Center, Washington, DC, USA

¹⁷⁸Village Care Health Center, New York, NY, USA

¹⁷⁹Aerzteforum Seestrasse, Berlin, Germany

¹⁸⁰Academic Medical Center Amsterdam, Amsterdam, Netherlands

¹⁸¹St. Paul’s Hospital, Vancouver, Canada

¹⁸²Swedish Medical Center, Seattle, WA, USA

¹⁸³Cedars-Sinai Medical Center, Los Angeles, CA, USA

¹⁸⁴Mercy Hospital, Miami, FL, USA

¹⁸⁵University of Tennessee, Chattanooga, TN, USA

¹⁸⁶St. Louis University, St Louis, MO, USA

¹⁸⁷William F. Ryan Community Health Center, New York, NY, USA

¹⁸⁸The University of Iowa, Iowa City, IA, USA

¹⁸⁹Rivington House and Village Care, New York, NY, USA

¹⁹⁰Infektionsmedizinisches Centrum Hamburg, Hamburg, Germany

¹⁹¹California Pacific Medical Center, San Francisco, CA, USA

¹⁹²Lemuel Shattuck Hospital, Boston, MA, USA

¹⁹³Fondazione San Raffaele Del Monte Tabor, Milan, Italy

¹⁹⁴Temple University School of Medicine, Philadelphia, PA, USA

¹⁹⁵Yale University School of Medicine, Bridgeport, CT, USA

¹⁹⁶Jersey City Medical Center, Jersey City, NJ, USA

¹⁹⁷University of Montreal, Montreal, Canada

¹⁹⁸Baylor University Medical Center, Dallas, TX, USA

¹⁹⁹Montgomery Infectious Disease Associates, Silver Spring, MD, USA

²⁰⁰Northwestern University, Chicago, IL, USA

²⁰¹Hospital de Santa Maria, Faculdade de Medicina de Lisboa, Lisbon, Portugal

²⁰²Spectrum Medical Group, Phoenix, AZ, USA

²⁰³University of North Texas Health Science Center, Fort Worth, TX, USA

²⁰⁴Infectious Diseases Associates of Northwest Florida, Pensacola, FL, USA

²⁰⁵Private Practice of Chingchai Wanidworanun, M.D., Arlington, VA, USA

²⁰⁶Dupont Circle Physician’s Group, Washington, DC, USA

²⁰⁷Consultive Medicine, Daytona Beach, FL, USA

²⁰⁸Infectious Disease Specialists, Colorado Springs, CO, USA

²⁰⁹Saint John Regional Hospital, Saint John, Canada

²¹⁰Clinical Alliance for Research and Education-Infectious Diseases, Annandale, VA, USA

²¹¹Hawthorn House, Birmingham Heartlands Hospital, Birmingham, UK

²¹²North Manchester General Hospital, Manchester, UK

²¹³Private Practice of Clifford Wlodaver, Midwest City, OK, USA

²¹⁴Central Texas Clinical Research, Austin, TX, USA

²¹⁵Primary Health Care, Des Moines, IA, USA

²¹⁶Memorial Neighborhood Health Center Central Clinic, South Bend, IN, USA

²¹⁷United Health Services Hospitals, Binghamton, NY, USA

²¹⁸All Med and Rehabilitation of New York, Bronx, NY, USA

^†To whom correspondence should be addressed. Email: bwalker/at/partners.org (B.D.W.); Email: pdebakker/at/rics.bwh.harvard.edu (P.I.W.d.B.)

^‡These authors contributed equally to this work.

^*All authors with their contributions and affiliations appear at the end of this paper.

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Abstract

Infectious and inflammatory diseases have repeatedly shown strong genetic associations within the major histocompatibility complex (MHC); however, the basis for these associations remains elusive. To define host genetic effects on the outcome of a chronic viral infection, we performed genome-wide association analysis in a multiethnic cohort of HIV-1 controllers and progressors, and we analyzed the effects of individual amino acids within the classical human leukocyte antigen (HLA) proteins. We identified >300 genome-wide significant single-nucleotide polymorphisms (SNPs) within the MHC and none elsewhere. Specific amino acids in the HLA-B peptide binding groove, as well as an independent HLA-C effect, explain the SNP associations and reconcile both protective and risk HLA alleles. These results implicate the nature of the HLA–viral peptide interaction as the major factor modulating durable control of HIV infection.

Hiv infection is characterized by acute viremia, often in excess of 5 million viral particles per milliliter of plasma, followed by an average 100-fold or greater decline to a relatively stable plasma virus load set point (1). In the absence of antiretroviral therapy, the level of viremia is associated with the rate of CD4⁺ T cell decline and progression to AIDS. There is substantial interperson variability in the virus load set point, with most individuals having stable levels exceeding 10,000 RNA copies/ml. Yet a small number of people demonstrate sustained ability to control HIV replication without therapy. Such individuals, referred to as HIV controllers, typically maintain stable CD4⁺ cell counts, do not develop clinical disease, and are less likely to transmit HIV to others (2).

To determine the genetic basis for this rare phenomenon, we established a multinational consortium (www.hivcontrollers.org) to recruit HIV-1 controllers, who are defined by at least three measurements of plasma virus load (VL) < 2000 RNA copies/ml over at least a 12-month period in the absence of antiviral therapy. We performed a genome-wide association study (GWAS) in the HIV controllers (median VL, CD4 count, and disease duration of 241 copies/ml, 699 cells/mm³, and 10 years, respectively) and treatment-naïve chronically infected individuals with advanced disease (median VL and CD4 count of 61,698 copies/ml and 224 cells/mm³, respectively) enrolled in antiviral treatment studies led by the AIDS Clinical Trials Group. After quality control and imputation on the basis of HapMap Phase 3 (3), we obtained data on 1,384,048 single-nucleotide polymorphisms (SNPs) in 974 controllers (cases) and 2648 progressors (controls) from multiple populations (table S1).

After stratification into European, African American, and Hispanic ethnic groups (fig. S1), we tested each SNP for association using logistic regression, including the major principal components as covariates to correct for population substructure (4). In the largest group, comprising 1712 individuals of European ancestry, we identified 313 SNPs with genome-wide significance, defined by P < 5 × 10⁻⁸ due to correction for multiple comparisons (table S2). All SNPs that reached genome-wide significance were located in the major histocompatibility complex (MHC) region on chromosome 6 (Fig. 1A). We obtained similar results for the other two ethnic groups and in a meta-analysis of all participants (fig. S2). We also performed a genome-wide analysis to test the influence of local chromosomal ancestry in the African American sample (4), but we detected no signal outside the MHC (figs. S3 and S4). The impact of the MHC was further underscored when we specifically tested published associations related to HIV disease progression outside the MHC. Only variants in the CCR5-CCR2 locus—namely, CCR5Δ32 deletion polymorphism (5), C927T in CCR5 (6), and Val⁶⁴→Ile⁶⁴ in CCR2 (7)—replicate with nominal statistical significance in our study (Fig. 1B and table S3).

Fig. 1

Genome-wide association results in the European sample. (A) Manhattan plot of 1.3 million autosomal SNPs. Only SNPs in the MHC on chromosome 6 reach genome-wide significance, indicated by the horizontal dotted line (P < 5 × 10⁻⁸ (more ...)

Closer examination of the significant SNPs within the MHC showed that they are located within a 3-Mb region concentrated around class I human leukocyte antigen (HLA) genes (fig. S5), but extensive linkage disequilibrium (LD) makes precise assignment of causal variants challenging (8). Therefore, we used stepwise regression to define independent markers associated with host control. From the initial set of 313 SNPs that reached genome-wide significance in the European sample, for which the greatest numbers of participants were available, we found only four independent markers of association (Table 1). rs9264942, located 35 kb upstream of HLA-C and a putative variant associated with HLA-C expression levels [odds ratio (OR) = 2.9, P = 2.8 × 10⁻³⁵, where an OR > 1 indicates a protective effect], and rs2395029, a proxy for HLA-B*57:01 (OR = 5.3, P = 9.7 × 10⁻²⁶), had been previously reported to be associated with virus load set point after acute infection (9). We also defined rs4418214, a noncoding SNP near MICA (OR = 4.4, P = 1.4 × 10⁻³⁴), and rs3131018 in PSORS1C3, a gene implicated in psoriasis (OR = 2.1, P = 4.2 × 10⁻¹⁶). These four SNPs explain 19% of the observed variance of host control in the European sample; together with those in CCR5, these SNPs explain 23%, using Nagelkerke’s approximation (Fig. 1C) (10).

Table 1

Association results for the independent SNPs in the MHC identified with stepwise regression in the European and African American samples. The odds ratio and frequency is given for the A1 allele, where OR > 1 indicates a protective effect. Odds (more ...)

In the smaller African American sample, we observed 33 SNPs with genome-wide significance, four of which were identified as independent markers, but all differed from those in the European sample (Table 1). This suggests that shared causal variants are tagged by different SNPs in these two populations or that the mechanism of control differs with ethnicity. Only rs2523608 was previously identified, in a recent study of virus load set point in African Americans (11). Despite no evidence for historical recombination (D’ = 1), this SNP is only weakly correlated (r² < 0.1) with HLA-B*57:03, the class I allele most strongly associated with durable control of HIV in populations of African ancestry (11-13). In the Hispanic sample, which was much smaller, the most significant SNP was rs2523590, 2 kb upstream of HLA-B, also identified in the African American sample described here.

Given the localization of significant SNPs entirely to the HLA class I region, as well as previous studies showing HLA alleles to affect disease progression (13-20), we next sought to evaluate whether these SNP and HLA associations might be due to specific amino acids within HLA. Because HLA types were available for only a portion of the entire cohort, we developed a method to impute classical HLA alleles and their corresponding amino acid sequences (4) on the basis of haplotype patterns in an independent data set collected by the Type 1 Diabetes Genetics Consortium (T1DGC) (21). This data set contains genotype data for 639 SNPs in the MHC that overlap with genotyped SNPs in our GWAS and classical HLA types for class I and II loci at four-digit resolution in 2767 unrelated individuals of European descent.

We imputed HLA types in the European sample of our study and validated the imputations by comparing to empirical four-digit HLA typing data collected for class I loci in a subset (n = 371) of the HIV controllers. The quality of the imputations was such that the imputed and true frequencies for all HLA alleles in this subset were in near-perfect agreement (Fig. 2A) (r² = 0.99). Furthermore, the positive predictive value was 95.2% and the sensitivity was 95.2% at two-digit resolution (92.7 and 95.6%, respectively, at four-digit resolution) for HLA alleles with frequency >2% (Fig. 2B). This indicates that the performance of the imputation was generally excellent for common alleles, consistent with previous work (22). We used HLA allele imputations in all participants (even those with HLA types defined by sequencing) for association analyses to avoid systematic bias between cases and controls. Lower imputation quality would only decrease power, not increase the false-positive rate, because cases and controls would be equally affected.

Fig. 2

Imputation quality of classical HLA alleles in the European sample. (A) Concordance between imputed (y-axis) and observed (x-axis) frequencies of classical HLA types in 371 HIV-1 controllers with four-digit HLA types obtained through Sanger sequencing. (more ...)

We tested all HLA alleles for association via logistic regression, adjusting for the same covariates used in SNP analysis (tables S4 and S5). The most significant HLA association is B*57:01 (OR = 5.5, P = 1.4 × 10⁻²⁶), which explains the proxy association of rs2395029 in HCP5. With the use of stepwise regression modeling in the European sample of controllers and progressors, we were able to implicate B*57:01, B*27:05, B*14/Cw*08:02, B*52, and A*25 as protective alleles and B*35 and Cw*07 as risk alleles. These associations are consistent with earlier studies that highlighted a role for HLA class I loci (13-20), and particularly HLA-B alleles in control of HIV, which indicated that the imputations are robust. Collectively explaining 19% of the variance of host control, these HLA allele associations are consistent with the effects of the four independent SNPs.

Virus-infected cells are recognized by CD8⁺ T cells after presentation of short viral peptides within the binding groove of HLA class I, and HIV-specific CD8⁺ T cells are strongly associated with control (23). We thus evaluated whether the SNP associations identified in the GWAS, and the HLA associations derived from imputation, might be due to specific amino acid positions within the HLA molecules, particularly those involved in the interaction between the viral peptide and the HLA class I molecule. Using the official DNA sequences defined for known HLA alleles (24), we encoded all variable amino acid positions within the coding regions of the HLA genes in each of the previously HLA-typed 2767 individuals in the T1DGC reference panel, and we used this data set to impute the amino acids in the cases and controls (4). Among a total of 372 polymorphic amino acid positions in class I and II HLA proteins, 286 are biallelic like a typical nonsynonymous coding SNP. The remaining 86 positions accommodate more than two amino acids; position 97 is the most diverse in HLA-B with six possible amino acids observed in European populations.

After imputing these amino acids in the European sample, we used logistic regression to test all positions for association with host control (fig. S6 and table S6). Notably, position 97 in HLA-B was more significant (omnibus P = 4 × 10⁻⁴⁵) than any single SNP in the GWAS, and three amino acid positions (67, 70, and 97), all in HLA-B, showed much stronger associations than any single classical HLA allele, including B*57:01 (Fig. 3A). Moreover, allelic variants at these positions were associated with substantial frequency differences between cases and controls (Fig. 3B). These results indicate that the effect of HLA-B on disease outcome could be mediated, at least in part, by these positions. These three amino acid positions are located in the peptide binding groove, which suggests that conformational differences in peptide presentation at these sites contribute to the protective or susceptible nature of the various HLA-B allotypes. Although both innate and adaptive mechanisms could be at play, the hypothesis that HLA affects peptide presentation and subsequent T cell functionality is supported by experimental data showing substantial functional differences between CTL targeting identical epitopes but restricted by different HLA alleles (25).

Fig. 3

Associations at amino acids in HLA-B in the European sample. (A) Association results for all variable amino acid positions, as calculated by the omnibus test. Colors denote conventional pocket positions. P values for significant classical HLA-B alleles (more ...)

We next performed stepwise regression modeling and identified six residues as independent markers associated with durable control of HIV. These include Arg⁹⁷, Cys⁶⁷, Gly⁶², and Glu⁶³, all in HLA-B; Ser⁷⁷ in HLA-A; and Met³⁰⁴ in HLA-C, which collectively explain 20% of the observed variance (similar to the variance explained by the seven classical HLA alleles described above). With the exception of Met³⁰⁴ in the transmembrane domain of HLA-C, these residues are all located in the MHC class I peptide binding groove, again suggesting that the binding pocket—and, by inference, the conformational presentation of class I-restricted epitopes—plays a key role in host control.

Having identified these amino acid positions as strong candidates to account for the SNP and HLA association signals in this study, we next investigated their effects on protection or risk, revealing allelic variants at these positions linked to both extremes (Table 2). HLA-B position 97 (omnibus P = 4 × 10⁻⁴⁵), located at the base of the C pocket, has important conformational properties for peptide binding (26). Position 97 has six allelic variants: Protective haplotypes B*57:01, B*27:05, and B*14 are uniquely defined by Val⁹⁷ (3% frequency in controls), Asn⁹⁷ (4%) and Trp⁹⁷ (3%), respectively; the other amino acids at this position (Ser, Thr, Arg) segregate on a diverse set of haplotypes. Ser⁹⁷ (27% frequency) lies on risk haplotypes Cw*07, B*07, and others, where-as Thr⁹⁷ (11%) lies on protective B*52 (and others). Arg⁹⁷ is the most common amino acid (51%) and is carried by risk allele B*35, among others. The importance of this amino acid position to host control is underscored by conditional analyses revealing significance when we adjust incrementally for Val⁹⁷ (omnibus test for position 97, P = 3 × 10⁻²⁰), Asn⁹⁷ (P = 2 × 10⁻⁹), and Trp⁹⁷ (P = 7 × 10⁻⁵). Thus, at a single position within the peptide binding groove (position 97, C-pocket), discrete amino acids are associated with opposite disease outcomes, even after controlling for B*57 and B*27, alleles associated with host control.

Table 2

Haplotypes defined by the four independent SNPs, classical HLA alleles, and amino acids associated with host control in the European sample. Haplotypes are ordered by the estimated odds ratio, where the most common haplotype was taken as reference (OR (more ...)

We also found similar discordant associations for alleles at positions 67, 63, and 62 (Table 2), all of which line the α1 helix along the peptide binding groove and help shape the B-pocket (Fig. 4). At position 67 (omnibus P = 2 × 10⁻⁴²), risk haplotypes B*35 and B*07 carry aromatic residues Phe⁶⁷ and Tyr⁶⁷, respectively, whereas protective B*57:01, B*27:05, and B*14 alleles carry sulfur-containing residues Met⁶⁷ or Cys⁶⁷. Position 62 (P = 5 × 10⁻²⁷) is biallelic (Arg/Gly) with the Gly⁶² allele segregating with protective alleles B*57:01 and B*58 (<1% frequency, OR = 1.7, P = 0.2). Adjacent position 63 (P = 9 × 10⁻¹⁶) is also biallelic (Glu/Asn) with Glu⁶³ appearing in complete LD (D’ = 1) with B*57:01, B*27:05, and B*52. In contrast, at this position the risk alleles B*07 (14% frequency, OR = 0.5, P = 1 × 10⁻⁷) and B*35 both carry Asn⁶³. Position 70 (omnibus P = 3 × 10⁻³⁹) accommodates four alleles that are tightly coupled with positions 67 and 97: Ser⁷⁰ appears exclusively with Met⁶⁷ (which defines B*57 and B*58), Gln⁷⁰ with Tyr⁶⁷, and Lys⁷⁰ with Asn⁹⁷ (B*27). Hence, these data create a consistent and parsimonious model that can explain the associations of classical HLA-B alleles by specific amino acids lining the binding groove (and residues tightly coupled to them), which are expected to have an impact on the three-dimensional structure of the peptide-MHC complex.

Fig. 4

Three-dimensional ribbon representation of the HLA-B protein based on Protein Data Bank entry 2bvp (30), highlighting amino acid positions 62, 63, 67, 70, and 97 lining the peptide binding pocket. The peptide backbone of the epitope is also displayed. (more ...)

To further investigate the role of individual amino acid positions in HLA-B, we implemented a permutation procedure to assess how consistent the above observations are with a null model in which there is no relation between amino acids at a particular position and host control (4). The results of this procedure provided evidence that multiple amino acid positions in the peptide binding groove are indeed associated with host control (table S7), including positions 62, 63, 67, 70, and 97, thus providing a structural basis for the effect of HLA-B on host control (Fig. 4).

Within HLA-A position 77, which lies on the α helix contributing to the F-pocket, we identified a weaker but still significant association (omnibus P = 3 × 10⁻⁶). Ser⁷⁷ (6% frequency, OR = 2.0, P = 2 × 10⁻⁶) is carried by only two HLA-A alleles (joint r² = 1): A*25 (2.4% frequency, OR = 2.6, P = 1 × 10⁻⁵) and A*32 (3.2%, OR = 1.6, P = 0.02). Given its location and earlier association evidence for the A10 supertype (27), HLA-A could play a role in host control, although the evidence is not as strong as for HLA-B.

The signals within HLA-C are less straight-forward to interpret. Position 304 is a biallelic variant (Val/Met) located in the transmembrane domain (Met³⁰⁴, 28% frequency, OR = 2.3, P = 7 × 10⁻²³). Met³⁰⁴ is in moderate LD (r² = 0.5) with rs9264942, which is known to be associated with HLA-C expression levels (28). Addition of this SNP to a multivariate model of all six amino acids is marginally significant (P = 0.013) but eliminates the effect of Met³⁰⁴ (P = 0.06). Similarly, addition of rs9264942 to a multivariate model of all seven independent classical HLA alleles is also significant (P = 2 × 10⁻⁴) but eliminates the effect of Cw*07 (P = 0.08). These observations make it difficult to determine the extent to which epitope presentation in the HLA-C peptide binding pocket is important for host control. Thus, rs9264942 could be a proxy for not only many protective and risk HLA alleles (predominantly at HLA-B), but also for an independent effect on HLA-C gene expression, differentially affecting the response to HIV (29).

We next evaluated associations for the SNPs in the MHC, classical HLA alleles, and amino acids in a second independent cohort of untreated HIV-infected persons from Switzerland (fig. S7 and tables S8 and S9) (4), in whom virus load set point was measured as a quantitative trait. Allelic variants at positions 67, 70, and 97 were also associated with highly significant differences in virus load set point in this second cohort (Fig. 3C). The effect estimates of all variable amino acids in HLA-B (r² > 0.9) and, to a lesser degree, those in HLA-C (r² > 0.8) in that cohort are in excellent agreement (figs. S8 and S9). As before, position 97 in HLA-B is the most significant association (omnibus P = 1 × 10⁻¹³). The HLA-A associations (A*25 or Ser⁷⁷) did not replicate, which reduces the likelihood that HLA-A plays a major role in host control.

In the African American sample (fig. S10), the most significant HLA allele association was observed for two-digit B*57 (OR = 5.1, P = 1.7 × 10⁻²¹) and four-digit B*57:03 (OR = 5.1, P = 2.8 × 10⁻¹⁷; tables S10 and S11), consistent with previous studies (11-13). Position 97 in HLA-B (omnibus P = 2 × 10⁻²⁵) is again the most significant amino acid (table S12). The consistency of these results demonstrates that imputation and association testing at amino acid resolution in multiple ethnicities can resolve disparate SNP associations in the MHC and help with fine-mapping of classical HLA associations.

Altogether, these results link the major genetic impact of host control of HIV-1 to specific amino acids involved in the presentation of viral peptides on infected cells. Moreover, they reconcile previously reported SNP and HLA associations with host control and lack of control to specific amino acid positions within the MHC class I peptide binding groove. Although variation in the entire HLA protein is involved in the differential response to HIV across HLA allotypes, the major genetic effects are condensed to the positions highlighted in this study, indicating a structural basis for the HLA association with disease progression that is probably mediated by the conformation of the peptide within the class I binding groove. The most significant residue, position 97 in the floor of the peptide binding groove of HLA-B, is associated with the extremes of viral load, depending on the expressed amino acid. This residue has been shown to have important conformational properties that affect epitope-contacting residues within the binding groove (26, 30) and has also been implicated in HLA protein folding and cell-surface expression (31).

Although the main focus of this study was on common sequence variation, it remains an open question as to the role of variants outside the MHC and the contribution of epistatic effects and epigenetic regulation. Additional factors also contribute to immune control of HIV, including fitness-altering mutations, immuno-regulatory networks, T cell help, thymic selection, and innate effector mechanisms such as killer cell immunoglobulin-like receptor recognition (23), some of which are influenced by the peptide-HLA class I complex. However, the combination and location of the significant amino acids defined here are most consistent with the genetic associations observed being modulated by HLA class I restricted CD8⁺ T cells. These results implicate the nature of the HLA-viral peptide interaction as the major genetic factor modulating durable control of HIV infection and provide the basis for future studies of the impact of HLA-peptide conformation on immune cell induction and function.

Supplementary Material

Supplementary data

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Acknowledgments

This work was made possible through a generous donation from the Mark and Lisa Schwartz Foundation and a subsequent award from the Collaboration for AIDS Vaccine Discovery of the Bill and Melinda Gates Foundation. This work was also supported in part by the Harvard University Center for AIDS Research (grant P-30-AI060354); University of California San Francisco (UCSF) Center for AIDS Research (grant P-30 AI27763); UCSF Clinical and Translational Science Institute (grant UL1 RR024131); Center for AIDS Research Network of Integrated Clinical Systems (grant R24 AI067039); and NIH grants AI28568 and AI030914 (B.D.W.); AI087145 and K24AI069994 (S.G.D.); AI069513, AI34835, AI069432, AI069423, AI069477, AI069501, AI069474, AI069428, AI69467, AI069415, Al32782, AI27661, AI25859, AI28568, AI30914, AI069495, AI069471, AI069532, AI069452, AI069450, AI069556, AI069484, AI069472, AI34853, AI069465, AI069511, AI38844, AI069424, AI069434, AI46370, AI68634, AI069502, AI069419, AI068636, and RR024975 (AIDS Clinical Trials Group); and AI077505 and MH071205 (D.W.H.). The Swiss HIV Cohort Study is supported by the Swiss National Science Foundation (SNF grants 33CSC0-108787 and 310000-110012). S. Ripke acknowledges support from NIH/National Institute of Mental Health (grant MH085520). This project has been funded in whole or in part with funds from National Cancer Institute/NIH (grant HHSN261200800001E to M. Carrington). The content of this publication does not necessarily reflect the views or policies of the U.S. Department of Health and Human Services, nor does the mention of trade names, commercial products, or organizations imply endorsement by the U.S. government. This research was supported in part by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research.

Footnotes

Supporting Online Material

www.sciencemag.org/cgi/content/full/science.1195271/DC1

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33. Single-letter abbreviations for the amino acid residues referred to in Table 2 are as follows: Glu E, Phe F, Gly G, Lys K, Met M, Asn N, Gln Q, Arg R, Ser S, Val V, Trp W, Tyr Y