Abstract
Genome-wide association studies (GWASs) have identified hundreds of loci associated with Crohn’s disease (CD). However, as with all complex diseases, robust identification of the genes dysregulated by noncoding variants typically driving GWAS discoveries has been challenging. Here, to complement GWASs and better define actionable biological targets, we analyzed sequence data from more than 30,000 patients with CD and 80,000 population controls. We directly implicate ten genes in general onset CD for the first time to our knowledge via association to coding variation, four of which lie within established CD GWAS loci. In nine instances, a single coding variant is significantly associated, and in the tenth, ATG4C, we see additionally a significantly increased burden of very rare coding variants in CD cases. In addition to reiterating the central role of innate and adaptive immune cells as well as autophagy in CD pathogenesis, these newly associated genes highlight the emerging role of mesenchymal cells in the development and maintenance of intestinal inflammation.
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Data availability
We describe all datasets in the manuscript or its Supplementary Information. Genome Reference Consortium Human Build 38 can be accessed at https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.40/. Sequence data used in this study have been made publicly available in dbGaP Study Accession: phs001642.v1.p1, Center for Common Disease Genomics (CCDG), Autoimmune: Inflammatory Bowel Disease (IBD) Exomes and Genomes (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001642.v1.p1). The summary statistics of Nextera and Twist meta-analysis have been deposited on GitHub (https://github.com/iibdgc/Crohn-s-Disease-WES-meta) (https://doi.org/10.5281/zenodo.6564928). This research has been conducted using the UK Biobank Resource and controls made publicly available by dbGaP (phs001000.v1.p1, phs000806.v1.p1, Myocardial Infarction Genetics Consortium (MIGen); phs000401.v1.p1, NHLBI GO-ESP Project; phs000298.v4.p3, Autism Sequencing Consortium (ASC); phs000572.v8.p4, Alzheimer’s Disease Sequencing Project (ADSP); phs001489.v1.p1, Epi25 Consortium; phs001095.v1.p1, T2D-GENES) as well as additional controls from the 1000 Genomes Project, the Epi25 Collaborative, UK-Ireland Collaborators (A. McQuillin, D. Blackwood, A. McIntosh), and collaborators A. Pulver, H. Ostrer, D. Chung, M. Hiltunen and A. Palotie (H2000 and SUPER cohorts) (Supplementary Table 1).
Code availability
The software and code used are described throughout the Methods and can be found at https://github.com/iibdgc/Crohn-s-Disease-WES-meta (https://doi.org/10.5281/zenodo.6564928).
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Acknowledgements
We thank all of the principal investigators, local staff from individual cohorts and all of the patients who kindly donated samples used in the study for making possible this global collaboration and resource to advance IBD genetics research. This research was funded in whole, or in part, by the US National Institutes of Health grants no. U54HG003067 and no. 5UM1HG008895, the Wellcome Trust grants no. 206194 and no. 108413/A/15/D, and The Leona M. & Harry B. Helmsley Charitable Trust grant no. 2015PG-IBD001. We thank the Broad Institute Genomics Platform for genomic data generation efforts and the Stanley Center for Psychiatric Research at the Broad Institute for supporting control sample aggregation. M.A.R. is in part supported by the NHGRI of the NIH under award no. R01HG010140 and an NIH Center for Multi- and Trans-ethnic Mapping of Mendelian and Complex Diseases grant (no. 5U01HG009080). H.H. acknowledges support from NIDDK grant no. K01DK114379, grant no. P30DK043351 and the Stanley Center for Psychiatric Research. H.S.W. receives philanthropic support from Martin Schlaff, James Brooks and the B. Hasso Family Foundation. H.H.U. and A. Sazonovs. are supported by the NIHR Oxford Biomedical Research Centre and by The Leona M. and Harry B. Helmsley Charitable Trust. A.P. is in part supported by the Academy of Finland Centre of Excellence in Complex Disease Genetics grants no. 312074 and no. 336824. Individual studies contributing to this meta-analysis acknowledge support from NIH grants no. DK062431, no. DK062432, no. DK087694, no. K23DK117054, no. R01DK111843, no. P01DK094779, no. R01HG010140, no. 5U01HG009080 and no. DK062420, and NIDDK grants no. P01DK046763, no. U01DK062413 and no. R01DK104844.
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H.H., C.A.A. and M.J.D. designed and supervised the study. C.R.S., H.H., C.A.A. and M.J.D. were responsible for project management. A. Sazonovs, G.R.V., K.Y., B.A., A.D., T.G., D.G., V.I., J.T.K., D.L.R., M. Solomonson, M.A.R., H.H., C.A.A. and M.J.D. performed data analysis. M.T.A., T.A., M.A., A.N.A., G.A., A. Baras, A. Beecham, A. Bitton, J.C.B., N.B., L.B., C.N.B., B.B., A.C., D.C., I.C., J. Cho, J. Cosnes, D.J.C., O.M.D., L.W.D., N.D., M.D., E.E., L.F., M. Farkkila, M. Ferreira, W.F., D.F., M. Georges, M. Giri, K.G., B.G., S.G., P.G., E.H., T.H., G.A.H., M. Hiltunen, M. Hoeppner, J.E.H., P.I., C.J., J. Kelsen, J. Kupcinskas, H.K., B.S.K., K.K., J.T.K., S.K., C.A.L., M.L., C. Lévesque, C. Liefferinckx, A.P.L., J.D.L., B.-S.L., E.L., J.M., S.M., J.L.M., E.M., M.M., P.M., C.J.M., R.D.N., S.O., D.T.O., B.O., H.O., A.P., J. Paquette, J. Pekow, I.P., M.J.P., C.Y.P., N. Pontikos, N. Prescott, A.E.P., S.R., P. Saavalainen, P. Seksik, B.S., R.B.S., E.R.S., S.S., L.P.S., A.W.S., R.S., S.Z.S., M.S.S., A. Simmons, J.S., H. Sokol, H. Somineni, D.S., S.T., D.T., H.H.U., A.E.V., S. Vermeire, S. Verstockt, M.D.V., H.S.W., J.Y., R.H.D., A.F., S.R.B., R.K.W., M.P., R.J.X., J.D.R. and D.P.B.M. were responsible for recruitment, clinical phenotyping, analysis and/or leadership of a contributing study. S.D. and S.B.G. performed sequencing technology development. A. Sazonovs, C.R.S., G.R.V., K.Y., S.R.B., J.D.R., D.P.B.M., H.H., C.A.A. and M.J.D. wrote the manuscript.
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A. Baras., M. Ferreira., J.E.H. and D.S are current or former employees and/or stockholders of Regeneron Genetics Center or Regeneron Pharmaceuticals. M.A. is consulting for or part of the advisory board for AbbVie Inc., Bellatrix Pharmaceuticals, Bristol Myers Squibb, Eli Lilly Pharmaceuticals, Gilead, Janssen Ortho, LLC, and Prometheus Biosciences; and teaching, lecturing or speaking at Alimentiv, Arena Pharmaceuticals, Janssen, Prime CME, Takeda Pharmaceuticals. A.B. is an employee of Regeneron and owns stock in Regeneron. O.M.D. has served in the IBD fellowship funding committee for Pfizer and has a funded research project by Pfizer. H.K. receives grant funding from Takeda and Pfizer and has received consulting fees from Takeda. A.P. is a member of Astra Zenecas Genomics Advisory Board. M.A.R. is on the SAB of 54gene and has advised BioMarin, Third Rock Ventures, MazeTx and Related Sciences. G.A.H. is an employee of Takeda, former employee of AbbVie and owns stock in Takeda and AbbVie. C.A.L. reports grants from Genentech, grants and personal fees from Janssen, grants and personal fees from Takeda, grants from AbbVie, personal fees from Ferring, grants from Eli Lilly, grants from Pfizer, grants from Roche, grants from UCB Biopharma, grants from Sanofi Aventis, grants from Biogen IDEC, grants from Orion OYJ, personal fees from Dr Falk Pharma and grants from AstraZeneca, outside the submitted work. H.H.U. reports research collaboration or consultancy with Janssen, Eli Lilly, UCB Pharma, Celgene, MiroBio, OMass and Mestag. D.P.B.M. has consulted for Takeda, Boehringer Ingelheim, Palatin Technologies, Bridge Biotherapeutics, Pfizer and Gilead. M.P. received an unrestricted research grant from Pfizer UK and speaker fees from Janssen. P.I. received lecture fees from AbbVie, BMS, Celgene, Celltrion, Falk Pharma, Ferring, Galapagos, Gilead, MSD, Janssen, Pfizer, Takeda, Tillotts, Sapphire Medical, Sandoz, Shire and Warner Chilcott; financial support for research from Celltrion, MSD, Pfizer and Takeda; advisory fees from AbbVie, Arena, Boehringer Ingelheim, BMS, Celgene, Celltrion, Genentech, Gilead, Hospira, Janssen, Lilly, MSD, Pfizer, Pharmacosmos, Prometheus, Roche, Sandoz, Samsung Bioepis, Takeda, Topivert, VH2, Vifor Pharma and Warner Chilcott. Cedars-Sinai and D.P.B.M. have financial interests in Prometheus Biosciences, a company which has access to the data and specimens in Cedars-Sinais MIRIAD Biobank (including the Cedars-Sinai data and specimens used in this study) and seeks to develop commercial products. H.H. has received consultancy fees from Ono Pharmaceutical and honoraria from Xian Janssen Pharmaceutical. C.A.A. has received consultancy fees from Genomics plc and BridgeBio Inc. and lecture fees from GSK. M.J.D. is a founder of Maze Therapeutics. The remaining authors declare no competing interests.
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Extended data
Extended Data Fig. 1 Overview of the study design.
We utilized a logistic mixed-model for the association analysis, followed by meta-analyses to combine multiple cohorts. Multiple cohorts serve the purpose of replication. Two large cohorts at Broad Institute of different exome capture platforms were used to discover candidate variants (Nextera WES and Twist WES). Two independent cohorts at Sanger (Sanger WGS and Sanger WES) and one Kiel/Regeneron cohort (Regeneron WES) were used to replicate the findings.
Extended Data Fig. 2 Quality control procedures applied in the Broad sequencing pipeline.
We show as an example the quality control steps performed on variants and subjects from the Broad sequencing platform. Quality controls performed on data from other platforms follow a similar plan and are described in Methods. Quality control steps using external information from gnomAD were colored green. Thresholds and details can be found in Methods.
Extended Data Fig. 3 QQ plots for Nextera and Twist discovery cohorts.
Only QC passed variants with minor allele frequency in NFE between 0.0001 and 0.10 were included. a, all variants. b, non-synonymous variants. c, synonymous variants. In a and b, the y axis is capped at -log10 p = 30 while the top four variants (three in NOD2 and one in IL23R) have -log10 p > 100. In c, to remove the synonymous variants that tag causal non-synonymous variants and artifacts through LD, we removed loci hosting large-effect coding variants (IL23R, NOD2, LRRK2, TYK2, ATG16L1, SLC39A8, PTGER4, IRGM, CARD9), implicated by variants removed in the heterogeneous test (AHNAK2, LILRA), and with long range LD (MHC).
Extended Data Fig. 4 Power to detect single variant associations.
We performed a series of power calculations using the methodology described by Johnson and Abecasis (2017). Our initial ‘exome-wide scan’ (two cohorts) had fewer samples and a more lenient significance threshold than subsequent meta-analysis (five cohorts). However, both analyses had similar power to detect true associations at their respective significance levels. Our single-variant association analyses did not have the power to uncover association to variants with a MAF = 0.0001 and below (unless the variant has a very strong effect, for example 0.76 power at OR = 8). Similarly, the exome-wide scan had limited power to detect association to variants with a MAF = 0.001 and OR < 2, but was well-powered above these thresholds. a, Power of the exome-wide scan analysis b, Power of the meta-analysis. c, Power to detect single-variant associations at different minor allele frequencies at α = 0.0002 (‘scan’; dashed lines) and 3 ×10-7 (‘meta’; solid lines) and assuming Crohn’s disease population prevalence of 276 in 100,000, and an additive effect model.
Extended Data Fig. 5 Relation to known IBD associations.
Numbers in brackets are the number of variants assigned to the categories out of the 45 exome-wide significant variants.
Extended Data Fig. 6 WES variants from this study implicating known IBD loci.
a-c: a novel CD variant implicating TAGAP. d-g: CD variants tagging fine-mapped IBD associations in LRRK2. a and d, P-value for variants from the fine-mapping study5. b and e, PIP from fine-mapping. c, f and g, P-value for variants from this study. Open circle indicating LD information is missing. LD calculated between the plotted variant and the best variant in b for panel c, and variants with best PIP in credible sets 1 and 2 (panel e) respectively for panels f and g.
Extended Data Fig. 7 Nextera and Twist callset population assignment.
Principal components for a, c, before removing non-European samples for Twist and Nextera respectively. b, d, after removing non-European samples for Twist and Nextera respectively. Principal components generated from the 1000 Genome Project Phase III data and different colors stand for different continental / superpopulations. Study subjects (black dots) were projected onto principal components.
Supplementary information
Supplementary Information
Details of individuals participating in IBD cohorts. Supplementary acknowledgments of participating consortia and programs.
Supplementary Tables
Supplementary Tables 1–8.
Supplementary Data 1
Principal components for subjects in the Nextera and Twist cohorts. Cases and controls are plotted as on the first two principal components for exome-wide significant CD variants. Carriers of the minor alleles are highlighted for cases and controls, respectively.
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Sazonovs, A., Stevens, C.R., Venkataraman, G.R. et al. Large-scale sequencing identifies multiple genes and rare variants associated with Crohn’s disease susceptibility. Nat Genet 54, 1275–1283 (2022). https://doi.org/10.1038/s41588-022-01156-2
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DOI: https://doi.org/10.1038/s41588-022-01156-2
