Abstract
To further resolve the genetic architecture of the inflammatory bowel diseases ulcerative colitis and Crohn's disease, we sequenced the whole genomes of 4,280 patients at low coverage and compared them to 3,652 previously sequenced population controls across 73.5 million variants. We then imputed from these sequences into new and existing genome-wide association study cohorts and tested for association at ∼12 million variants in a total of 16,432 cases and 18,843 controls. We discovered a 0.6% frequency missense variant in ADCY7 that doubles the risk of ulcerative colitis. Despite good statistical power, we did not identify any other new low-frequency risk variants and found that such variants explained little heritability. We detected a burden of very rare, damaging missense variants in known Crohn's disease risk genes, suggesting that more comprehensive sequencing studies will continue to improve understanding of the biology of complex diseases.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Liu, J.Z. et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat. Genet. 47, 979–986 (2015).
Parkes, M. et al. Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility. Nat. Genet. 39, 830–832 (2007).
Yamazaki, K. et al. A genome-wide association study identifies 2 susceptibility loci for Crohn's disease in a Japanese population. Gastroenterology 144, 781–788 (2013).
Anderson, C.A. et al. Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47. Nat. Genet. 43, 246–252 (2011).
Kenny, E.E. et al. A genome-wide scan of Ashkenazi Jewish Crohn's disease suggests novel susceptibility loci. PLoS Genet. 8, e1002559 (2012).
Julià, A. et al. A genome-wide association study identifies a novel locus at 6q22.1 associated with ulcerative colitis. Hum. Mol. Genet. 23, 6927–6934 (2014).
Yang, S.-K. et al. Genome-wide association study of Crohn's disease in Koreans revealed three new susceptibility loci and common attributes of genetic susceptibility across ethnic populations. Gut 63, 80–87 (2014).
Ellinghaus, D. 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).
Manolio, T.A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009).
Zuk, O. et al. Searching for missing heritability: designing rare variant association studies. Proc. Natl. Acad. Sci. USA 111, E455–E464 (2014).
Rivas, M.A. et al. Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease. Nat. Genet. 43, 1066–1073 (2011).
Beaudoin, M. et al. Deep resequencing of GWAS loci identifies rare variants in CARD9, IL23R and RNF186 that are associated with ulcerative colitis. PLoS Genet. 9, e1003723 (2013).
Hunt, K.A. et al. Negligible impact of rare autoimmune-locus coding-region variants on missing heritability. Nature 498, 232–235 (2013).
Prescott, N.J. et al. Pooled sequencing of 531 genes in inflammatory bowel disease identifies an associated rare variant in BTNL2 and implicates other immune related genes. PLoS Genet. 11, e1004955 (2015).
Do, R. et al. Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. Nature 518, 102–106 (2015).
De Rubeis, S. et al. Synaptic, transcriptional and chromatin genes disrupted in autism. Nature 515, 209–215 (2014).
Singh, T. et al. Rare loss-of-function variants in SETD1A are associated with schizophrenia and developmental disorders. Nat. Neurosci. 19, 571–577 (2016).
Huang, H. et al. Association mapping of inflammatory bowel disease loci to single variant resolution. Preprint at bioRxiv http://dx.doi.org/10.1101/028688 (2015).
Farh, K.K.-H. et al. Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature 518, 337–343 (2015).
Li, Y., Sidore, C., Kang, H.M., Boehnke, M. & Abecasis, G.R. Low-coverage sequencing: implications for design of complex trait association studies. Genome Res. 21, 940–951 (2011).
CONVERGE Consortium. Sparse whole-genome sequencing identifies two loci for major depressive disorder. Nature 523, 588–591 (2015).
Danjou, F. et al. Genome-wide association analyses based on whole-genome sequencing in Sardinia provide insights into regulation of hemoglobin levels. Nat. Genet. 47, 1264–1271 (2015).
UK10K Consortium. The UK10K project identifies rare variants in health and disease. Nature 526, 82–90 (2015).
McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
Browning, B.L. & Browning, S.R. Improving the accuracy and efficiency of identity-by-descent detection in population data. Genetics 194, 459–471 (2013).
Handsaker, R.E. et al. Large multiallelic copy number variations in humans. Nat. Genet. 47, 296–303 (2015).
Fuchsberger, C. et al. The genetic architecture of type 2 diabetes. Nature 536, 41–47 (2016).
McCarthy, S. et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279–1283 (2016).
Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).
Barrett, J.C. et al. Genome-wide association study of ulcerative colitis identifies three new susceptibility loci, including the HNF4A region. Nat. Genet. 41, 1330–1334 (2009).
Durbin, R. Efficient haplotype matching and storage using the positional Burrows–Wheeler transform (PBWT). Bioinformatics 30, 1266–1272 (2014).
de Lange, K.M. et al. Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease. Nat. Genet. http://dx.doi.org/10.1038/ng.3760 (2017).
Li, Y.R. et al. Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases. Nat. Med. 21, 1018–1027 (2015).
Dahle, M.K., Myhre, A.E., Aasen, A.O. & Wang, J.E. Effects of forskolin on Kupffer cell production of interleukin-10 and tumor necrosis factor α differ from those of endogenous adenylyl cyclase activators: possible role for adenylyl cyclase 9. Infect. Immun. 73, 7290–7296 (2005).
Duan, B. et al. Distinct roles of adenylyl cyclase VII in regulating the immune responses in mice. J. Immunol. 185, 335–344 (2010).
Jiang, L.I., Sternweis, P.C. & Wang, J.E. Zymosan activates protein kinase A via adenylyl cyclase VII to modulate innate immune responses during inflammation. Mol. Immunol. 54, 14–22 (2013).
Risøe, P.K. et al. Higher TNFα responses in young males compared to females are associated with attenuation of monocyte adenylyl cyclase expression. Hum. Immunol. 76, 427–430 (2015).
Pierre, S., Eschenhagen, T., Geisslinger, G. & Scholich, K. Capturing adenylyl cyclases as potential drug targets. Nat. Rev. Drug Discov. 8, 321–335 (2009).
Bhatia, G. et al. Subtle stratification confounds estimates of heritability from rare variants. Preprint at bioRxiv http://dx.doi.org/10.1101/048181 (2016).
Yang, J., Lee, S.H., Goddard, M.E. & Visscher, P.M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).
Chen, G.-B. et al. Estimation and partitioning of (co)heritability of inflammatory bowel disease from GWAS and Immunochip data. Hum. Mol. Genet. 23, 4710–4720 (2014).
Purcell, S.M. et al. A polygenic burden of rare disruptive mutations in schizophrenia. Nature 506, 185–190 (2014).
Derkach, A. et al. Association analysis using next-generation sequence data from publicly available control groups: the robust variance score statistic. Bioinformatics 30, 2179–2188 (2014).
Andersson, R. et al. An atlas of active enhancers across human cell types and tissues. Nature 507, 455–461 (2014).
Zimmerman, N.P., Kumar, S.N., Turner, J.R. & Dwinell, M.B. Cyclic AMP dysregulates intestinal epithelial cell restitution through PKA and RhoA. Inflamm. Bowel Dis. 18, 1081–1091 (2012).
Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).
Genovese, G. et al. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat. Neurosci. 19, 1433–1441 (2016).
Jostins, L. et al. Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119–124 (2012).
Hinrichs, A.S. et al. The UCSC Genome Browser Database: update 2006. Nucleic Acids Res. 34, D590–D598 (2006).
Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
Marchini, J. & Howie, B. Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 11, 499–511 (2010).
Speed, D. & Balding, D.J. MultiBLUP: improved SNP-based prediction for complex traits. Genome Res. 24, 1550–1557 (2014).
Acknowledgements
We thank all individuals who contributed samples to the study. This work was co-funded by the Wellcome Trust (098051) and the Medical Research Council, UK (MR/J00314X/1). Case collections were supported by Crohn's and Colitis UK. K.M.d.L., L.M., Y.L., C.A.L., C.A.A. and J.C.B. are supported by the Wellcome Trust (098051; 093885/Z/10/Z). K.M.d.L. is supported by a Woolf Fisher Trust scholarship. C.A.L. is a clinical lecturer funded by the NIHR. H.U. is supported by the Crohn's and Colitis Foundation of America (CCFA) and the Leona M. and Harry B. Helmsley Charitable Trust. We acknowledge support from the UK Department of Health via NIHR comprehensive Biomedical Research Centre awards to Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London and to Addenbrooke's Hospital, Cambridge, in partnership with the University of Cambridge, and the BRC to the Oxford IBD cohort study, University of Oxford. This research was also supported by the NIHR Newcastle Biomedical Research Centre. The UK Household Longitudinal Study is led by the Institute for Social and Economic Research at the University of Essex and funded by the Economic and Social Research Council. The survey was conducted by NatCen, and the genome-wide scan data were analyzed and deposited by the Wellcome Trust Sanger Institute. Information on how to access the data can be found on the Understanding Society website. We are grateful for genotyping data from the British Society for Surgery of the Hand Genetics of Dupuytren's Disease consortium and L. Southam for assistance with genotype intensities. This research has been conducted using the UK Biobank Resource.
Author information
Authors and Affiliations
Contributions
Y.L., K.M.d.L., L.J., L.M., J.C.B. and C.A.A. performed statistical analysis. Y.L., K.M.d.L., L.J., L.M., J.C.L., C.A.L., E.G.S., J.R., M. Pollard, S.N. and S.M. processed the data. T.A., C.E., N.A.K., A.H., C.H., J.C.M., J.C.L., C.M., W.G.N., J.S., A.S., M.T., H.U., D.C.W., N.J.P., C.W.L., M. Parkes and C.G.M. contributed samples and/or materials. Y.L., K.M.d.L., L.M., J.C.L., M. Parkes, C.A.L., N.A.K., J.C.B. and C.A.A. wrote the manuscript. All authors read and approved the final version of the manuscript. J.C.M., M. Parkes, C.W.L., T.A., N.J.P., J.C.B. and C.A.A. conceived and designed experiments.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Integrated supplementary information
Supplementary Figure 2 Genotypic accuracy of sequencing data.
Dosage r2 plots for determining sequencing quality when compared against other genotyping data. The x axis is minor allele frequency calculated based on sequencing samples, and the y axis is correlation between dosages for sequencing and genotype data sets. Numbers in parentheses are the number of individuals with both types of data.
Supplementary Figure 3 Biallelic SNV discovery rate compared to the 1000 Genomes Project Phase 3 European panel.
Percentage of biallelic SNVs in all autosomal regions that are shared by the IBD sequencing set and 1000 Genomes Project (1000GP) Phase 3 European panel (503 individuals). Left, percentage of IBD sequencing SNVs that are also found in 1000GP; right, variants identified in the 1000GP set that are also in the IBD sequencing cohort. MAFs on the left were calculated based on SNVs discovered in the IBD sequencing project, and MAFs on the right were calculated based on the 1000GP set. Different lines represent SNVs in different quality control stages of the analysis.
Supplementary Figure 4 Number of copy number variants called per cohort.
Average number of calls per individual per site, across different copy number variant (CNV) lengths. UK10K controls (6×) are shown in yellow, Crohn’s disease cases (4×) are shown in red, and ulcerative colitis cases (2×) are shown in blue.
Supplementary Figure 5 Quantile–quantile plots of genome-wide association studies for variants with MAF ≥ 0.1% in the sequencing data set.
λ1,000 values are reported for ulcerative colitis, Crohn’s disease and inflammatory bowel disease analyses. Gray shapes show the 95% confidence interval.
Supplementary Figure 6 Cluster plots for rs78534766.
(a–c) Cluster plots are shown for rs78534766 for the GWAS3 (a), replication (b) and UK Biobank (c) samples that passed quality control. SNP genotypes have been assigned based on cluster formation in scatterplots of normalized allele intensities X and Y. Each circle represents one individual’s genotype. Blue and red clouds correspond to homozygote genotypes for the SNP (CC/AA), green clouds correspond to the heterozygote genotype (CA) and gray clouds correspond to undetermined genotype.
Supplementary Figure 8 Distribution of INFO scores by cohort, across a range of minor allele frequencies.
(a) INFO scores calculated using genotype probabilities generated directly from the SAMtools Genotype Quality (GQ) field. (b) INFO scores calculated using genotype probabilities after imputation improvement using BEAGLE.
Supplementary Figure 10 Principal-component analysis of the sequencing samples.
IBD samples are plotted with 11 different HapMap 3 populations.
Supplementary Figure 11 Effect of read depth on sensitivity and specificity across the allele frequency spectrum (UC (2×) CD (4×), controls (6×)).
(a–c) Top, full distribution of variant counts per individual at singletons (observed once in the data set) (a), doubletons (observed twice) (b) and variants with a MAF of 5% (c). (d) Plot showing the median of each distribution across a range of MAF values.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–11, Supplementary Tables 1–17 and Supplementary Note (PDF 3457 kb)
Rights and permissions
About this article
Cite this article
Luo, Y., de Lange, K., Jostins, L. et al. Exploring the genetic architecture of inflammatory bowel disease by whole-genome sequencing identifies association at ADCY7. Nat Genet 49, 186–192 (2017). https://doi.org/10.1038/ng.3761
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/ng.3761
This article is cited by
-
Tipping the balance in autoimmunity: are regulatory t cells the cause, the cure, or both?
Molecular and Cellular Pediatrics (2024)
-
The relationship between extreme inter-individual variation in macrophage gene expression and genetic susceptibility to inflammatory bowel disease
Human Genetics (2024)
-
Polygenic risk score for ulcerative colitis predicts immune checkpoint inhibitor-mediated colitis
Nature Communications (2024)
-
Dietary L-Tryptophan consumption determines the number of colonic regulatory T cells and susceptibility to colitis via GPR15
Nature Communications (2023)
-
Interaction between mitochondria and microbiota modulating cellular metabolism in inflammatory bowel disease
Journal of Molecular Medicine (2023)