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Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci

Abstract

We simultaneously investigated the genetic landscape of ankylosing spondylitis, Crohn's disease, psoriasis, primary sclerosing cholangitis and ulcerative colitis to investigate pleiotropy and the relationship between these clinically related diseases. Using high-density genotype data from more than 86,000 individuals of European ancestry, we identified 244 independent multidisease signals, including 27 new genome-wide significant susceptibility loci and 3 unreported shared risk loci. Complex pleiotropy was supported when contrasting multidisease signals with expression data sets from human, rat and mouse together with epigenetic and expressed enhancer profiles. The comorbidities among the five immune diseases were best explained by biological pleiotropy rather than heterogeneity (a subgroup of cases genetically identical to those with another disease, possibly owing to diagnostic misclassification, molecular subtypes or excessive comorbidity). In particular, the strong comorbidity between primary sclerosing cholangitis and inflammatory bowel disease is likely the result of a unique disease, which is genetically distinct from classical inflammatory bowel disease phenotypes.

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Figure 1: Discovery of 27 new genome-wide significant disease associations (Pdisease < 5 × 10−8) for ankylosing spondylitis, Crohn's disease, psoriasis, PSC and ulcerative colitis.
Figure 2: Heritability explained per risk variant for 244 independent multidisease association signals identified through cross-disease subset-based association meta-analysis.
Figure 3: Identification of drug-targeted genes in a core disease protein-protein interaction network.
Figure 4: Estimation of Immunochip-wide pleiotropy (excluding the MHC region) between the five diseases under study.

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Acknowledgements

We thank all patients with ankylosing spondylitis, Crohn's disease, PSC, psoriasis and ulcerative colitis, their families, healthy control individuals and clinicians for their participation in this study. We thank T. Wesse, T. Henke, S. Sedghpour Sabet, R. Vogler, G. Jacobs, I. Urbach, W. Albrecht, V. Pelkonen, K. Holm, H. Dahlen Sollid, B. Woldseth, J.A. Anmarkrud and L. Wenche Torbjørnsen for expert help. F. Braun, W. Kreisel, T. Berg and R. Günther are acknowledged for contributing German patients with PSC. B.A. Lie and the Norwegian Bone Marrow Donor Registry at Oslo University Hospital, Rikshospitalet, in Oslo and the Nord-Trøndelag Health Study (HUNT) are acknowledged for sharing the healthy Norwegian controls. This work was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (SysInflame grant 01ZX1306A). This project received infrastructure support from Deutsche Forschungsgemeinschaft (DFG) Excellence Cluster 306 'Inflammation at Interfaces' and the PopGen Biobank. A.F. receives an endowment professorship by the Foundation for Experimental Medicine (Zurich, Switzerland). The Estonian Genome Center at the University of Tartu (EGCUT) received targeted financing from Estonian Research Council grant IUT20-60, the Center of Excellence in Genomics (EXCEGEN) and the University of Tartu (SP1GVARENG). We acknowledge EGCUT technical personnel, especially V. Soo and S. Smit. Data analyses were carried out in part at the High-Performance Computing Center of the University of Tartu. We acknowledge support from the UK Department of Health via National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre awards to Guy's and St Thomas' National Health Service (NHS) Foundation Trust in partnership with King's College London and to Addenbrooke's Hospital in partnership with the University of Cambridge. The study was supported by the German Federal Ministry of Education and Research (BMBF), within the context of National Genome Research Network 2 (NGFN-2), National Genome Research Network plus (NGFNplus) and the Integrated Genome Research Network (IG) MooDS (grants 01GS08144 and 01GS08147). R.K.W. is supported by a VIDI grant (016.136.308) from the Netherlands Organization for Scientific Research (NWO). J.H. was supported by the Swedish Research Council (521-2011-2764). This work is supported in part by funding from the US NIH (1R01AR063759 (S.R.), 5U01GM092691-05 (S.R.), 1UH2AR067677-01 (S.R.), U19AI111224-01 (S.R.) and 1R01DK084960-05 (K.N.L.)) and Doris Duke Charitable Foundation grant 2013097. A.B.J. and S.B. acknowledge funding from the Novo Nordisk Foundation (grant NNF14CC0001) and the H2020 project MedBioinformatics (grant 634143). The study was supported by the Norwegian PSC Research Center. We thank G. Trynka for assistance in setting up GoShifter.

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D.E., L.J., S.L.S., A.C., J.B., B.H., Y.R.P., J.G.P., S.R., Y.W., T.E., H.-J.W., L.F., T.H.P., R.K.W., V.C., O.A.A., A.B.J., S.B. and A.M.D. performed statistical and computational analyses. M.H. performed computational analyses. T.F., A.M., M.D'A., J.H., W.L., F.D., A.J.F., A.H., S.S., U.M., B.D.J., K.N.L., R.C.T., S.W., M.W., E.E., J.T.E., J.N.W.N.B. and M.A.B. were involved in study subject recruitment and assembling phenotypic data. D.E. wrote the draft of the manuscript. D.E., D.P.M., T.H.K., J.C.B., M.P., M.A.B. and A.F. conceived, designed and managed the study. All authors reviewed, edited and approved the final manuscript.

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Correspondence to David Ellinghaus.

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A full list of members and affiliations appears in the Supplementary Note.

A full list of members and affiliations appears in the Supplementary Note.

A full list of members and affiliations appears in the Supplementary Note.

A full list of members and affiliations appears in the Supplementary Note.

Supplementary information

Supplementary Text and Figures

Supplementary Tables 1, 4 and 7–17, Supplementary Figures 1–3 and 7–17, and Supplementary Note. (PDF 4199 kb)

Supplementary Figure 4

Regional association plots for 244 independent association signals within 169 genome-wide significant non-MHC risk loci. (PDF 33785 kb)

Supplementary Figure 5

Synthesis-View plots showing the multidisease association signals for 244 independent association signals within 169 genome-wide significant non-MHC risk loci. (PDF 14842 kb)

Supplementary Figure 6

Pairwise comparisons of variance explained per risk variant between ankylosing spondylitis (AS), Crohn's disease (CD), psoriasis (PS), primary sclerosing cholangitis (PSC) and ulcerative colitis (UC) for a maximum of 244 independent signals from 169 risk loci. (PDF 382 kb)

Supplementary Table 2

Twenty-seven newly identified single-disease associations with genome-wide significance. (XLSX 25 kb)

Supplementary Table 3

Summary of 169 non-MHC genome-wide significant susceptibility loci. (XLSX 512 kb)

Supplementary Table 5

Functional in silico annotations of risk SNPs. (XLSX 1217 kb)

Supplementary Table 6

Analysis of cis-eQTL data from whole peripheral samples of 2,360 unrelated individuals. (XLSX 156 kb)

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Ellinghaus, D., Jostins, L., Spain, S. et al. Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci. Nat Genet 48, 510–518 (2016). https://doi.org/10.1038/ng.3528

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