The diversity of human leukocyte antigens (HLA) is critical for effective immune responses against pathogens and cancer. HLA class I molecules present endogenous antigens to eliminate infected or cancerous cells, while HLA class II molecules present exogenous antigens to helper CD4+ T-cells, stimulating antibody production. Polymorphisms in HLA genes, particularly in the peptide-binding cleft, create diverse antigen-binding affinities, suggesting evolutionary selection pressure to maintain diversity as a defense against pathogen adaptation.1 One mechanism by which HLA diversity is maintained is through heterozygote advantage2, where individuals with two different alleles at a genetic locus have higher fitness compared to those with two identical alleles. Particular attention has been focused on the role of HLA heterozygote advantage in colorectal cancer (CRC).3–5 Our prior study of 5,406 patients with CRC and 4,635 controls found that HLA class I and/or II alleles may be associated with higher tumor-infiltrating lymphocytes and reduced risk of CRC.4 Here, we expand on this work by analyzing 183,626 participants (84,907 CRC cases and 98,689 controls) from the International Colorectal Cancer GWAS Collaborative, including US-Europe-Australia (US-EU-AUS), UK-Europe (UK-EUR), and Asia (AS) (ST1). HLA class I and II alleles were imputed from germline genotype data, and the number of heterozygous genotypes at HLA class I (A, B, C) and HLA class II (DPB1, DQB1, DRB1) loci were quantified. Logistic regression estimated the risk of CRC, and Cox proportional hazards regression assessed overall survival (OS) and CRC-specific survival (CS) in 20,332 CRC cases (Supplementary Methods). To account for multiple hypothesis testing, we applied a Bonferroni correction, adjusting the statistical significance threshold to p<0.0063 (0.05/8 independent tests).
Our meta-analysis demonstrated that HLA heterozygosity is associated with significantly reduced CRC risk and longer survival. Compared to individuals with 0 or 1 heterozygous alleles across HLA class I and II loci, those with 2 to 5 heterozygotes had a 10% reduced odds of CRC (odds ratio (OR): 0.90, p=0.004), and those with all heterozygous genotypes at class I and II loci were at lower odds of CRC (OR: 0.89, p=0.002, Figure 1(A)). For HLA class I, individuals who carried 2 or 3 heterozygous genotypes were at 10% lower risk of CRC (2 heterozygotes: OR: 0.89, p=0.003; 3 heterozygotes: OR: 0.91, p=0.004, ST2). Among 20,322 CRC cases, a higher number of heterozygous genotypes was associated with better OS in a dose-response relationship (ptrend =0.008 for class II, ptrend =0.029 for class I/II combined; ST3). Interestingly, early stage (I and II) CRC cases with all 6 heterozygous loci exhibited a 41% lower risk of dying from CRC (hazard ratio (HR): 0.59, p=0.025, Figure 1(B)). However, this was not observed in patients with locally advanced or metastatic disease. While our primary finding for CRC risk remained statistically significant following multiple testing correction, the survival analysis p-values (0.008–0.025) did not meet this stringent threshold but are still strongly suggestive of an association.
Figure 1. Associations between HLA class I and II heterozygosity and CRC risk and outcome.
(A) HLA class I and II heterozygosity and CRC risk; (B) HLA class I and II heterozygosity and CRC-specific survival in patients with stage I and II disease. AS: Asia-based Consortium; UK-EUR: United Kingdom and Europe-based Consortium; US-EUR-AUS: United States, Europe and Australia-based Consortium.
These findings are consistent with the hypothesis that HLA heterozygosity enhances immune surveillance by presenting a broader antigenic peptide repertoire to T cells. Prior studies revealed the complementary roles of HLA class I and II genotypes on the oncogenic mutational landscape and immunoediting during tumor development6,7, influencing both CD8+ and CD4+ T-cell responses. Our work explores the less-studied impact of germline HLA heterozygosity, which is distinct from the common somatic loss of heterozygosity. Analyzing germline HLA zygosity, rather than individual alleles, offers a key advantage in a multi-ethnic study, allowing examination of HLA variability across ancestry groups without the complexity of comparing highly population-specific alleles. Our prior analysis showed an association between HLA class I and II heterozygosity and higher levels of tumor-infiltrating lymphocytes4, suggesting a mechanistic role in CRC development. Furthermore, a study of esophagogastric adenocarcinoma demonstrated that germline HLA class I homozygosity reduced immunogenic peptide repertoires8, supporting HLA heterozygote advantage in enhancing immune surveillance against cancer.
Our analysis revealed a dose-response relationship between HLA heterozygosity and improved OS, but not CS. This suggests that HLA heterozygosity may influence OS through mechanisms beyond exclusively cancer-specific mortality. We found that patients with early-stage CRC and greater HLA class I and II heterozygosity exhibited significantly better CS, likely because increased HLA diversity allows the immune system to recognize and respond to a wider range of tumor antigens, especially when tumor burden is low. Conversely, advanced-stage CRC patients did not experience such benefit, possibly due to factors like somatic HLA loss, immune exhaustion, or reduced tumor infiltration. Notably, a different trend was observed in the Asian cohort, where HLA class I heterozygosity was associated with worse OS and CS. This finding may be influenced by the small sample size and variability in HLA allele frequencies specific to the Asian population. The Asian cohort’s limitation of including only male patients may further contribute to these differences. However, we cannot rule out that this observation is due to chance.
Despite robust statistical power, our study has limitations. Our findings, primarily from individuals of European and Asian ancestry, have limited generalizability. The lack of comprehensive treatment information, including immunotherapy, precluded analysis of the effect of HLA heterozygosity on treatment responses. Incomplete survival information for some datasets, especially AS, may also give rise to potential bias. A higher proportion of stage I/II cases also constrained our stage-specific results, highlighting the need for larger samples of advanced-stage patients to better understand the influence of HLA heterozygosity on outcomes.
Using the largest dataset of HLA genotypes from CRC patients across multiple continents, we unveil the important relationship between germline HLA diversity and both CRC risk and prognosis. Our findings demonstrate that increased HLA heterozygosity is associated with reduced CRC risk and potentially better clinical outcomes, particularly in early-stage patients. These results highlight potential for incorporating HLA diversity into polygenic risk scores and prognostic models to improve CRC risk prediction and prognostication. Future research should focus on understanding the mechanisms by which HLA diversity influences CRC development and progression to inform the targeted immunoprevention and immunotherapies that leverage this diversity to improve CRC outcomes.
Supplementary Material
Supplementary Table 1. Demographic and clinical characteristics of the study populations. AS: Asia-based consortium (ACCC); UK-EUR: United Kingdom and Europe-based consortium (COGENT); US-EUR-AUS: United States, Europe and Australia-based Consortia (GECCO, CCFR, and CORECT).
Supplementary Table 2. HLA class I and II heterozygosity and CRC risk.
Supplementary Table 3. HLA class I and II heterozygosity and five-year overall survival.
Acknowledgements
The Polyp Prevention Study Group would like to thank all of the study participants, investigators and staff. We extend our sincere thanks to the following funding and collaborative partners: the Association Anne de Bretagne Genetique and the Ligue Regionale Contre le Cancer (LRCC), the Swedish Low-Risk Colorectal Cancer Study Group, and the Maryland Cancer Registry (MCR) Cancer, Center for Cancer Prevention and Control, Maryland Department of Health, with funding from the State of Maryland and the Maryland Cigarette Restitution Fund. We further acknowledge the support for cancer registry data collection and availability provided by the Cooperative Agreement NU58DP006333, funded by the Centers for Disease Control and Prevention. It is important to note that the content of this publication is solely the responsibility of the authors and does not necessarily reflect the views or policies of the Centers for Disease Control and Prevention or the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US government. Additionally, we thank the COLON and NQplus investigators at Wageningen University & Research, and the involved clinicians in the participating hospitals. NSHDS investigators thank the Västerbotten Intervention Programme, the Northern Sweden MONICA study, the Section of Biobank and Registry Support at the Department of Public Health and Clinical Medicine, Umeå University, and Biobanken Norr at Region Västerbotten for providing data and samples. We also acknowledge the contribution from Biobank Sweden, supported by the Swedish Research Council.
Grant Support
This research was supported by several funding sources. CET received support from L70 CA284301, T32 CA094880, and T32 CA009168. JRH was supported by R21CA230486, and HY by F99CA284261. DA and SIB received funding from the intramural Research Program of the Division of Cancer Epidemiology and Genetics, NCI, NIH. ELB’s work was supported by R01CA059005 and R01CA098286. SB acknowledges funding from the Hospital Clinical Research Program (PHRC-BRD09/C) from the University Hospital Center of Nantes (CHU deNantes), the Regional Council of Pays de la Loire, and the Groupement des Entreprises Francaises dans la Lutte contre le Cancer (GEFLUC). RCG and RKP received support from U01CA167551. TOK was supported by P30 DK 034987, R01 CA66635, and U01CA093344. LLM acknowledges funding from U01 CA164973, R01 CA60987, R01 CA74806, U01 CA167551. HJL received support from P30CA014089. AL was supported by the Swedish Research Council (2019–01441), the Swedish Cancer Society (21 1443 Pj), and the Cancer Research Funds of Radiumhemmet (221223). SO’s research is supported by grants from the USA National Institutes of Health (R01 CA248857), the Cancer Research UK Grand Challenge Award (C10674 / A27140), and the American Cancer Society Clinical Research Professor Award (CRP-24–1185864-01-PROF). RP reports that some data were derived from the Ohio Colorectal Cancer Prevention Initiative (OCCPI), supported by a grant from Pelotonia, an annual cycling event in Columbus, Ohio that supports cancer research at The Ohio State University Comprehensive Cancer Center – James Cancer Hospital and Solove Research Institute. The OCCPI was also supported in part by grant P30 CA016058, National Cancer Institute, Bethesda, MD. EAP’s CLUE II funding was provided by the National Cancer Institute (U01 CA086308, Early Detection Research Network; P30 CA006973), National Institute on Aging (U01 AG018033), and the American Institute for Cancer Research. RES received support from U01 CA152753. CYU acknowledges the American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study-II cohort. FJBvD’s COLON study was sponsored by Wereld Kanker Onderzoek Fonds, including funds from grant 2014/1179 as part of the World Cancer Research Fund International Regular Grant Programme, by Alpe d’Huzes and the Dutch Cancer Society (UM 2012–5653, UW 2013–5927, UW2015–7946), and by TRANSCAN (JTC2012-MetaboCCC, JTC2013-FOCUS). VV’s work was supported by the Czech Science Foundation (21–04607X), and the National Institute for Cancer Research (Programme EXCELES, ID Project No. LX22NPO5102), funded by the European Union – Next Generation EU. AW’s SMC-COSM cohorts are part of the Swedish Infrastructure for Medical Population-based Life-course and Environmental Research (SIMPLER), funded by the Swedish Research Council under the grant no 2017–00644 and 2021–00160, and received support from the Swedish Cancer Foundation (grant CF 20 0864). VM acknowledges support from the Spanish Association Against Cancer (AECC) Scientific Foundation (GCTRA18022MORE) and the Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP). MGD was supported by Cancer Research UK Programme Grant DRCPGM\100012 and Cancer Research UK Centre Grant CTRQQR-2021\100006. WZ received funding from R01 CA188214. RH was supported by the Wellcome Trust (214388) and Cancer Research UK (C1298/A8362). SBG acknowledges funding from NIH R01 CA263318, NIH R01 CA197350, NIH R01 CA81488, U19 CA014089, and generous gifts from the Gilbert Foundation, David and Karen Leff, and Daniel and Maryann Fong.
International Colorectal Cancer GWAS Collaborative includes
Jeroen R Huyghe1, Hang Yin1,2, Ceres Fernandez-Rozadilla3,4,5, Minta Thomas1, Li Hsu1,6, Demetrius Albanes7, Elizabeth L. Barry8, Sonja I. Berndt7, Stéphane Bézieau9, D. Timothy Bishop10, Hermann Brenner11,12, Daniel D. Buchanan13,14,15, Andrew T. Chan16,17,18,19,20, Marcia Cruz-Correa21,22,23, Jane C. Figueiredo24, Manuela Gago-Dominguez25, Robert C. Grant26, Andrea Gsur27, Marc J. Gunter28,29, Jochen Hampe30, Michael Hoffmeister11, Mark A. Jenkins31,32, Temitope O. Keku33, Loic Le Marchand34, Flavio Lebjkowicz35, Heinz-Josef Lenz36, Li Li37,38, Annika Lindblom39,40, Robert J. MacInnis41,42, Marilena Melas43, Aaron L. Meyers44,45,46, Kenneth Offit47,48,49, Shuji Ogino19,20,50,51, Rish K. Pai52, Rachel Pearlman53, Andrew J. Pellatt54, Elizabeth A. Platz55,56, Chenxu Qu43, Robert E. Schoen57, Cornelia M. Ulrich58, Caroline Y. Um59, Franzel J.B. van Duijnhoven60, Bethany Van Guelpen61,62, Veronika Vymetalkova63,64, Christopher P. Walker65, Emily White1,66, Alicja Wolk67, Michael O. Woods68, Anna H. Wu69, Amanda Phipps1,68, Gad Rennert70, Victor Moreno71,72,73,74, Malcolm G. Dunlop75, Ian Tomlinson76, Ulrike Peters1,68, Wei Zheng77, Richard Houlston78
1 Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA,
2 Institute for Public Health Genetics, University of Washington, Seattle, Washington, USA,
3 Cancer Predisposition and Biomarkers Lab, Instituto de Investigacion Sanitaria de Santiago, Santiago de Compostela, Spain,
4 Genomic Medicine Group, University of Santiago de Compostela, Santiago de Compostela, Spain,
5 Galician Public Foundation for Genomic Medicine, Santiago de Compostela, Spain,
6 Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington, USA,
7 Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA,
8 Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA,
9 Service de Génétique Médicale, Centre Hospitalier Universitaire (CHU) Nantes, Nantes, France,
10 Leeds Institute of Medical Research, University of Leeds, Leeds, UK,
11 Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany,
12 German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany,
13 Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, VIC, Australia,
14 Genomic Medicine and Family Cancer Clinic, The Royal Melbourne Hospital, Parkville, VIC, Australia,
15 University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria, Australia,
16 Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA,
17 Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA,
18 Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA,
19 Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA,
20 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA,
21 Comprehensive Cancer Center, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico 00936, USA,
22 Pan American Center for Oncology Trials, San Juan, Puerto Rico 00907,
23 Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA,
24 Cedars-Sinai Cancer Institute, Los Angeles, California, USA,
25 Fundación Gallega de Instituto de Investigación de Santiago (FIDIS), Grupo de Genética y Epidemiología del Cáncer, Complejo Hospitalario Univ. Santiago, SERGAS, Spain,
26 Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada,
27 Center for Cancer Research, Medical University of Vienna, Vienna, Austria,
28 Cancer Epidemiology and Prevention Research Unit, School of Public Health, Imperial College, London, United Kingdom,
29 Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France,
30 Department of Medicine I, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany,
31 University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, VIC, 3010, Australia,
32 Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, VIC, 3053, Australia,
33 Center for Gastrointestinal Biology and Disease, University of North Carolina, Chapel Hill, North Carolina, USA,
34 University of Hawaii Cancer Center, Honolulu, Hawaii, USA,
35 Department of Community Medicine and Epidemiology, Carmel Medical Center, Haifa, Israel,
36 Department of Medicine, University of Southern California, Los Angeles, California, USA,
37 Department of Family Medicine, University of Virginia, Charlottesville, Virginia, USA,
38 UVA Comprehensive Cancer, University of Virginia, Charlottesville, Virginia, USA,
39 Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden,
40 Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden,
41 Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia,
42 Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia,
43 Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA,
44 Centre for Genomic Cancer Medicine, Victorian Comprehensive Cancer Centre, University of Melbourne, Victoria, Australia,
45 Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Victoria, Australia,
46 Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Victoria, Australia,
47 Clinical Genetics Service, Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York, USA,
48 Department of Medicine, Weill Cornell Medical College, New York, New York, USA,
49 Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA,
50 Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA,
51 Institute of Science Tokyo, Tokyo, Japan,
52 Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, Arizona, USA,
53 Division of Human Genetics, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio, USA,
54 Intermountain Health, Salt Lake City, Utah, USA,
55 Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA,
56 Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, Maryland, USA,
57 Departments of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA,
58 Huntsman Cancer Institute and Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA,
59 Department of Population Science, American Cancer Society, Atlanta, Georgia, USA,
60 Division of Human Nutrition and Health, Wageningen University & Research, Wageningen, The Netherlands,
61 Department of Diagnostics and Intervention, Oncology Unit, Umeå University, Umeå, Sweden,
62 Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden,
63 Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czech Republic,
64 Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, Prague, Czech Republic,
65 Department of Medical Oncology & Therapeutics Research and Center for Precision Medicine, City of Hope National Medical Center, Duarte, California, USA,
66 Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA,
67 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden,
68] Memorial University of Newfoundland, Division of Biomedical Sciences, St. John’s, Canada,
69 University of Southern California, Population and Public Health Sciences, Los Angeles, California, USA,
70 B. Rappaport Faculty of Medicine, Technion and the Association for Promotion of Research in Precision Medicine (APRPM), Haifa, Israel,
71 Catalan Institute of Oncology (ICO), Hospitalet de Llobregat, Barcelona, Spain,
72 ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Barcelona, Spain,
73 Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Spain,
74 Department of Clinical Sciences, Faculty of Medicine and Health Sciences and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona, Barcelona, Spain,
75 Colon Cancer Genetics Group, Cancer Research UK Scotland Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK,
76 Department of Oncology, University of Oxford, Oxford, UK,
77 Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA,
78 Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK,
Footnotes
Conflict of Interest
M Cruz-Correa reports research contracts from BMS, Merck, Genentech, AstraZeneca, Natera, Abbvie, Huyabio, Jannsen, Incyte, Revolution Medicine, Pfizer, Astellas. RC Grant reports a graduate scholarship from Pfizer, and consulting/advisory roles for Astrazeneca, Tempus, Eisai, Incyte, Knight Therapeutics, Guardant Health, and Ipsen. U Peters reports consulting with AbbVie, and her husband holds individual stocks in Amazon, ARM Holdings PLC, BioNTech, BYD Company Limited, Crowdstrike Holdings Inc, CureVac, Google/Alphabet, Microsoft Corp, NVIDIA Corp, and Stellantis. SB Gruber is a co-founder of Brogent International LLC (equity unrelated to this work) and reports research grant support from Abbvie, Astra-Zeneca, Eisai, HaloDx, Invitae, and Johnson & Johnson, also all unrelated to this work. All other authors declare no conflicts of interest.
CrediT Authorship Contributions
Ya-Yu Tsai, PhD, MS (Conceptualization: Lead; Data Curation: Supporting; Formal Analysis: Lead; Methodology: Lead; Project Administration: Lead; Writing- original draft: Lead; Writing -review and editing: Lead)
Claire E. Thomas, PhD, MPH (Conceptualization: Lead, Formal Analysis: Equal; Methodology: Equal; Writing- review and editing: Supporting)
Philip Law, PhD (Formal Analysis: Equal; Writing- review and editing: Supporting)
Zhishan Chen (Formal Analysis: Equal; Writing- review and editing: Supporting)
Stephen B. Gruber, MD, PhD (Conceptualization: Lead; Data Curation: Supporting; Formal Analysis: Supporting; Funding Acquisition: Lead; Methodology: Lead; Project Administration: Lead; Resources: Lead; Overall Supervision: Supporting; Writing -review and editing: Supporting)
Stephanie L. Schmit, PhD, MPH (Conceptualization: Lead; Data Curation: Supporting; Formal Analysis: Supporting; Methodology: Lead; Project Administration: Lead; Resources: Supporting; Overall Supervision: Lead; Writing -review and editing: Lead)
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Data Transparency Statement
Summary statistics for the full set of Asian and European genome-wide association studies are available through the GWAS catalog (GCST90129505). Individual-level genotype data are available via dbGaP (phs001415.v1.p1, phs001315.v1.p1, phs001078.v1.p1, phs001903.v1.p1, phs001856.v1.p1 and phs001045.v1.p1 for CCFR, CORECT, CORSA_2 and GECCO), the European Genome-phenome Archive (accession numbers EGAS00001005412 for NSCCG, EGAS00001005421 for COIN), UK Biobank (http://www.ukbiobank.ac.uk), and THL Biobank (for Finnish data). Access to the remaining individual-level data require application through oversight committees or specific contacts, as detailed for CCFR (www.coloncfr/collaboration.org), QUASAR2, SCOT, CORGI (LP1), Scotland Phase 1, Scotland Phase 2, SOCCS, DACHS, Croatia (access.crc.gwas.data@outlook.com), CORSA_1 (gecco@fredhutch.org), Generation Scotland controls (access@generationscotland.org), and Asian cohorts (Aichi1, Aichi2, Korea and Shanghai cohorts; see https://swhs-smhs.app.vumc.org/ or contact Dr. Zheng at wei.zheng@vanderbilt.edu). Germline genotype data are available in dbGAP for the MECC study (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001045.v1.p1; https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001856.v1.p1; https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001903.v1.p1).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Table 1. Demographic and clinical characteristics of the study populations. AS: Asia-based consortium (ACCC); UK-EUR: United Kingdom and Europe-based consortium (COGENT); US-EUR-AUS: United States, Europe and Australia-based Consortia (GECCO, CCFR, and CORECT).
Supplementary Table 2. HLA class I and II heterozygosity and CRC risk.
Supplementary Table 3. HLA class I and II heterozygosity and five-year overall survival.
Data Availability Statement
Summary statistics for the full set of Asian and European genome-wide association studies are available through the GWAS catalog (GCST90129505). Individual-level genotype data are available via dbGaP (phs001415.v1.p1, phs001315.v1.p1, phs001078.v1.p1, phs001903.v1.p1, phs001856.v1.p1 and phs001045.v1.p1 for CCFR, CORECT, CORSA_2 and GECCO), the European Genome-phenome Archive (accession numbers EGAS00001005412 for NSCCG, EGAS00001005421 for COIN), UK Biobank (http://www.ukbiobank.ac.uk), and THL Biobank (for Finnish data). Access to the remaining individual-level data require application through oversight committees or specific contacts, as detailed for CCFR (www.coloncfr/collaboration.org), QUASAR2, SCOT, CORGI (LP1), Scotland Phase 1, Scotland Phase 2, SOCCS, DACHS, Croatia (access.crc.gwas.data@outlook.com), CORSA_1 (gecco@fredhutch.org), Generation Scotland controls (access@generationscotland.org), and Asian cohorts (Aichi1, Aichi2, Korea and Shanghai cohorts; see https://swhs-smhs.app.vumc.org/ or contact Dr. Zheng at wei.zheng@vanderbilt.edu). Germline genotype data are available in dbGAP for the MECC study (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001045.v1.p1; https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001856.v1.p1; https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001903.v1.p1).