Abstract

A major challenge in inflammatory bowel disease (IBD) is the integration of diverse IBD data sets to construct predictive models of IBD. We present a predictive model of the immune component of IBD that informs causal relationships among loci previously linked to IBD through genome-wide association studies (GWAS) using functional and regulatory annotations that relate to the cells, tissues, and pathophysiology of IBD. Our model consists of individual networks constructed using molecular data generated from intestinal samples isolated from three populations of patients with IBD at different stages of disease. We performed key driver analysis to identify genes predicted to modulate network regulatory states associated with IBD, prioritizing and prospectively validating 12 of the top key drivers experimentally. This validated key driver set not only introduces new regulators of processes central to IBD but also provides the integrated circuits of genetic, molecular, and clinical traits that can be directly queried to interrogate and refine the regulatory framework defining IBD.

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References

  1. 1.

    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).

  2. 2.

    et al. Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119–124 (2012).

  3. 3.

    et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn's disease susceptibility loci. Nat. Genet. 42, 1118–1125 (2010).

  4. 4.

    et al. A genome-wide scan of Ashkenazi Jewish Crohn's disease suggests novel susceptibility loci. PLoS Genet. 8, e1002559 (2012).

  5. 5.

    et al. Estimation and partitioning of (co)heritability of inflammatory bowel disease from GWAS and Immunochip data. Hum. Mol. Genet. 23, 4710–4720 (2014).

  6. 6.

    , & Genetics and pathogenesis of inflammatory bowel disease. Nature 474, 307–317 (2011).

  7. 7.

    et al. Variations in DNA elucidate molecular networks that cause disease. Nature 452, 429–435 (2008).

  8. 8.

    et al. Genetics of gene expression and its effect on disease. Nature 452, 423–428 (2008).

  9. 9.

    et al. Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers. Mol. Syst. Biol. 8, 594 (2012).

  10. 10.

    et al. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease. Cell 153, 707–720 (2013).

  11. 11.

    et al. Pediatric Crohn disease patients exhibit specific ileal transcriptome and microbiome signature. J. Clin. Invest. 124, 3617–3633 (2014).

  12. 12.

    et al. Ustekinumab induction and maintenance therapy in refractory Crohn's disease. N. Engl. J. Med. 367, 1519–1528 (2012).

  13. 13.

    et al. Variants in TRIM22 that affect NOD2 signaling are associated with very-early-onset inflammatory bowel disease. Gastroenterology 150, 1196–1207 (2016).

  14. 14.

    , , & Unraveling the genetics of autoimmunity. Cell 140, 791–797 (2010).

  15. 15.

    et al. Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature 518, 337–343 (2015).

  16. 16.

    Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).

  17. 17.

    et al. A point mutation in the murine Hem1 gene reveals an essential role for Hematopoietic protein 1 in lymphopoiesis and innate immunity. J. Exp. Med. 205, 2899–2913 (2008).

  18. 18.

    et al. Essential role of Elmo1 in Dock2-dependent lymphocyte migration. J. Immunol. 192, 6062–6070 (2014).

  19. 19.

    et al. Allograft inflammatory factor-1 stimulates chemokine production and induces chemotaxis in human peripheral blood mononuclear cells. Biochem. Biophys. Res. Commun. 448, 287–291 (2014).

  20. 20.

    et al. Inherited DOCK2 deficiency in patients with early-onset invasive infections. N. Engl. J. Med. 372, 2409–2422 (2015).

  21. 21.

    et al. The Rac activator DOCK2 regulates natural killer cell–mediated cytotoxicity in mice through the lytic synapse formation. Blood 122, 386–393 (2013).

  22. 22.

    et al. Selective control of type I IFN induction by the Rac activator DOCK2 during TLR-mediated plasmacytoid dendritic cell activation. J. Exp. Med. 207, 721–730 (2010).

  23. 23.

    et al. DOCK2 and DOCK5 act additively in neutrophils to regulate chemotaxis, superoxide production, and extracellular trap formation. J. Immunol. 193, 5660–5667 (2014).

  24. 24.

    et al. DOCK2 regulates Rac activation and cytoskeletal reorganization through interaction with ELMO1. Blood 102, 2948–2950 (2003).

  25. 25.

    , & Role of AIF-1 in the regulation of inflammatory activation and diverse disease processes. Cell. Immunol. 284, 75–83 (2013).

  26. 26.

    et al. Haematopoietic cell–specific CDM family protein DOCK2 is essential for lymphocyte migration. Nature 412, 826–831 (2001).

  27. 27.

    , , , & Autoimmune disease classification by inverse association with SNP alleles. PLoS Genet. 5, e1000792 (2009).

  28. 28.

    et al. G protein signaling modulator-3 inhibits the inflammasome activity of NLRP3. J. Biol. Chem. 289, 33245–33257 (2014).

  29. 29.

    et al. Allograft inflammatory factor-1 (AIF-1) is crucial for the survival and pro-inflammatory activity of macrophages. Int. Immunol. 17, 1391–1397 (2005).

  30. 30.

    , , & Allograft inflammatory factor-1 and its immune regulation. Autoimmunity 40, 95–102 (2007).

  31. 31.

    et al. Characterizing the genetic basis of innate immune response in TLR4-activated human monocytes. Nat. Commun. 5, 5236 (2014).

  32. 32.

    et al. The Dok-3/Grb2 protein signal module attenuates Lyn kinase-dependent activation of Syk kinase in B cell antigen receptor microclusters. J. Biol. Chem. 288, 2303–2313 (2013).

  33. 33.

    , & Dok-3 plays a nonredundant role in negative regulation of B-cell activation. Blood 110, 259–266 (2007).

  34. 34.

    , , & Adaptor protein DOK3 promotes plasma cell differentiation by regulating the expression of programmed cell death 1 ligands. Proc. Natl. Acad. Sci. USA 111, 11431–11436 (2014).

  35. 35.

    , & DOK3 negatively regulates LPS responses and endotoxin tolerance. PLoS One 7, e39967 (2012).

  36. 36.

    & The role of macrophages and dendritic cells in the initiation of inflammation in IBD. Inflamm. Bowel Dis. 20, 166–175 (2014).

  37. 37.

    et al. Microbiota-dependent crosstalk between macrophages and ILC3 promotes intestinal homeostasis. Science 343, 1249288 (2014).

  38. 38.

    et al. Activation of T cell death-associated gene 8 regulates the cytokine production of T cells and macrophages in vitro. Eur. J. Pharmacol. 683, 325–331 (2012).

  39. 39.

    et al. GBP5 promotes NLRP3 inflammasome assembly and immunity in mammals. Science 336, 481–485 (2012).

  40. 40.

    et al. Lineage-specific enhancers activate self-renewal genes in macrophages and embryonic stem cells. Science 351, aad5510 (2016).

  41. 41.

    et al. Regulation of the formyl peptide receptor 1 (FPR1) gene in primary human macrophages. PLoS One 7, e50195 (2012).

  42. 42.

    et al. Receptor signaling lymphocyte-activation molecule family 1 (Slamf1) regulates membrane fusion and NADPH oxidase 2 (NOX2) activity by recruiting a Beclin-1/Vps34/ultraviolet radiation resistance-associated gene (UVRAG) complex. J. Biol. Chem. 287, 18359–18365 (2012).

  43. 43.

    et al. A20 restricts ubiquitination of pro-interleukin-1β protein complexes and suppresses NLRP3 inflammasome activity. Immunity 42, 55–67 (2015).

  44. 44.

    , , , & LAPTM5 protein is a positive regulator of proinflammatory signaling pathways in macrophages. J. Biol. Chem. 287, 27691–27702 (2012).

  45. 45.

    et al. Infliximab for the treatment of fistulas in patients with Crohn's disease. N. Engl. J. Med. 340, 1398–1405 (1999).

  46. 46.

    Treatment of Crohn's disease with anti-IL-6 receptor antibody. J. Gastroenterol. 40 (Suppl. 16), 32–34 (2005).

  47. 47.

    et al. Significance of IL-1RA polymorphism in Iranian patients with inflammatory bowel disease. Dig. Dis. Sci. 60, 1389–1395 (2015).

  48. 48.

    et al. Anti-IP-10 antibody (BMS-936557) for ulcerative colitis: a phase II randomised study. Gut 63, 442–450 (2014).

  49. 49.

    et al. Comprehensive intestinal T helper cell profiling reveals specific accumulation of IFN-γ+IL-17+ coproducing CD4+ T cells in active inflammatory bowel disease. Inflamm. Bowel Dis. 20, 2321–2329 (2014).

  50. 50.

    , , , & Th17 cells give rise to Th1 cells that are required for the pathogenesis of colitis. Proc. Natl. Acad. Sci. USA 112, 7061–7066 (2015).

  51. 51.

    et al. Interleukin 23 production by intestinal CD103+CD11b+ dendritic cells in response to bacterial flagellin enhances mucosal innate immune defense. Immunity 36, 276–287 (2012).

  52. 52.

    , & Intestinal CD103+ dendritic cells: master regulators of tolerance? Trends Immunol. 32, 412–419 (2011).

  53. 53.

    et al. G-protein signaling modulator-3, a gene linked to autoimmune diseases, regulates monocyte function and its deficiency protects from inflammatory arthritis. Mol. Immunol. 54, 193–198 (2013).

  54. 54.

    , & Hem-1: putting the “WAVE” into actin polymerization during an immune response. FEBS Lett. 584, 4923–4932 (2010).

  55. 55.

    , , & Rac attack: modulation of the small GTPase Rac in inflammatory bowel disease and thiopurine therapy. Mol. Diagn. Ther. 20, 551–557 (2016).

  56. 56.

    et al. Single nucleotide polymorphisms that increase expression of the guanosine triphosphatase RAC1 are associated with ulcerative colitis. Gastroenterology 141, 633–641 (2011).

  57. 57.

    et al. DOK3 is required for IFN-β production by enabling TRAF3/TBK1 complex formation and IRF3 activation. J. Immunol. 193, 840–848 (2014).

  58. 58.

    et al. An evolutionary analysis of RAC2 identifies haplotypes associated with human autoimmune diseases. Mol. Biol. Evol. 28, 3319–3329 (2011).

  59. 59.

    et al. Rac2-deficiency leads to exacerbated and protracted colitis in response to Citrobacter rodentium infection. PLoS One 8, e61629 (2013).

  60. 60.

    et al. NADPH oxidase complex and IBD candidate gene studies: identification of a rare variant in NCF2 that results in reduced binding to RAC2. Gut 61, 1028–1035 (2012).

  61. 61.

    et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

  62. 62.

    , & featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

  63. 63.

    et al. RNA-SeQC: RNA-seq metrics for quality control and process optimization. Bioinformatics 28, 1530–1532 (2012).

  64. 64.

    et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

  65. 65.

    et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

  66. 66.

    et al. An integrative genomics approach to the reconstruction of gene networks in segregating populations. Cytogenet. Genome Res. 105, 363–374 (2004).

  67. 67.

    et al. Increasing the power to detect causal associations by combining genotypic and expression data in segregating populations. PLOS Comput. Biol. 3, e69 (2007).

  68. 68.

    et al. Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks. Nat. Genet. 40, 854–861 (2008).

  69. 69.

    et al. Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation. PLoS Biol. 10, e1001301 (2012).

  70. 70.

    et al. Hem-1 complexes are essential for Rac activation, actin polymerization, and myosin regulation during neutrophil chemotaxis. PLoS Biol. 4, e38 (2006).

  71. 71.

    , , , & An actin-based wave generator organizes cell motility. PLoS Biol. 5, e221 (2007).

  72. 72.

    et al. JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles. Nucleic Acids Res. 44, D110–D115 (2016).

  73. 73.

    , & Genetic inactivation of the allograft inflammatory factor-1 locus. Genesis 51, 734–740 (2013).

  74. 74.

    et al. RORγt and commensal microflora are required for the differentiation of mucosal interleukin 22–producing NKp46+ cells. Nat. Immunol. 10, 83–91 (2009).

  75. 75.

    et al. The orphan nuclear receptor RORγt directs the differentiation program of proinflammatory IL-17+ T helper cells. Cell 126, 1121–1133 (2006).

  76. 76.

    , , & Chemically induced mouse models of intestinal inflammation. Nat. Protoc. 2, 541–546 (2007).

  77. 77.

    , , , & Phenotypically distinct subsets of CD4+ T cells induce or protect from chronic intestinal inflammation in C. B-17 scid mice. Int. Immunol. 5, 1461–1471 (1993).

  78. 78.

    & Time Series Analysis and Its Applications (Springer, 2000).

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Acknowledgements

We acknowledge P. Chinnasamy for backcrossing of Aif1−/− mice; E. Esplugues; K. Saulnier from Charles River Laboratories; S. Graham, J. Mena, and G. Lyng from Biomodels; K. Amin from Qiagen; E. Venturini and the New York Genome Center; M. Mahajan, Y. Kasai, and the Genome Core at Mount Sinai; H. Thomas; R. Ng; the Pathology Department and the Histology core at MSH; and Sinai Innovations. This work was supported in part through the computational resources and staff expertise provided by the Department of Scientific Computing at the Icahn School of Medicine at Mount Sinai. This work was funded by the Schadt laboratory at the Icahn Institute for Genomics and Multi-scale Biology, Icahn School of Medicine at Mount Sinai (NewYork). This work was partially funded by NIH/NIA grant R01AG046170 (to E.E.S. and B.Z.), a component of the AMP-AD Target Discovery and Preclinical Validation Project, the Rheumatology Research Foundation (to T.K.T.), the Leading Advanced Projects for Medical Innovation (LEAP; to Y.F.) from the Japan Agency for Medical Research and Development (AMED), U01HG008451 (to J.Z.), NIH R01HL128066 (to N.S.), and RO1 AI092093 and R21 AI109020 (to B.M.I.).

Author information

Affiliations

  1. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Lauren A Peters
    • , Won-min Song
    • , Sean R Llewellyn
    • , Antonio Di Narzo
    • , Brian A Kidd
    • , Yongzhong Zhao
    • , Khader Shameer
    • , Riccardo Miotto
    • , Bojan Losic
    • , Eunjee Lee
    • , Minghui Wang
    • , Jeremiah J Faith
    • , Andrew Kasarskis
    • , Carmen Argmann
    • , Ke Hao
    • , Panos Roussos
    • , Jun Zhu
    • , Bin Zhang
    •  & Eric E Schadt
  2. Icahn Institute of Genomics and Multi-scale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Lauren A Peters
    • , Won-min Song
    • , Sean R Llewellyn
    • , Antonio Di Narzo
    • , Brian A Kidd
    • , Yongzhong Zhao
    • , Khader Shameer
    • , Riccardo Miotto
    • , Bojan Losic
    • , Hardik Shah
    • , Eunjee Lee
    • , Minghui Wang
    • , Jeremiah J Faith
    • , Andrew Kasarskis
    • , Carmen Argmann
    • , Ke Hao
    • , Panos Roussos
    • , Jun Zhu
    • , Bin Zhang
    •  & Eric E Schadt
  3. Sema4, a Mount Sinai venture, Stamford, Connecticut, USA.

    • Lauren A Peters
    • , Jun Zhu
    •  & Eric E Schadt
  4. Janssen Research and Development, LLC., Spring House, Pennsylvania, USA.

    • Jacqueline Perrigoue
    • , Eric M Neiman
    • , Shannon E Telesco
    • , Aleksandar Stojmirovic
    • , Jocelyn Sendecki
    • , Carrie Brodmerkel
    • , Mark Curran
    • , Anuk Das
    • , Joshua R Friedman
    •  & Radu Dobrin
  5. Department of Immunology, University of Toronto, Toronto, Ontario, Canada.

    • Arthur Mortha
  6. Department of Oncological Sciences, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Arthur Mortha
  7. Department of Pathology and Cell Biology, Columbia University Medical Center, New York, New York, USA.

    • Alina Iuga
  8. Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Sean R Llewellyn
  9. The Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Sean R Llewellyn
    • , Jeremiah J Faith
    •  & Lloyd F Mayer
  10. Institute for Next-Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Riccardo Miotto
  11. Division of Immunogenetics, Department of Immunobiology and Neuroscience, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan.

    • Yoshinori Fukui
  12. University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA.

    • Mary Beth Humphrey
  13. Department of Comparative Medicine, University of Washington, Seattle, Washington, USA.

    • Brian M Iritani
  14. Department of Medicine (Cardiovascular Division), Albert Einstein College of Medicine, Bronx, New York, USA.

    • Nicholas Sibinga
  15. Thurston Arthritis Research Center and Department of Medicine, Division of Rheumatology, Allergy, and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

    • Teresa K Tarrant
  16. Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

    • Teresa K Tarrant
  17. Bristol-Myers Squibb, Research & Development, Pennington, New Jersey, USA.

    • Radu Dobrin
  18. Division of Clinical Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Lloyd F Mayer

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Contributions

L.A.P. and E.E.S. conceived of, designed, managed, and performed all analysis in the study. J.P. and E.M.N. performed macrophage knockdown experiments. W.-m.S. performed network enrichments. A.M. performed flow cytometry. A.I. performed histological scoring of mouse tissue, and S.R.L. and L.A.P. performed adoptive T cell transfer colitis experiments. L.A.P. designed and managed DSS experiments, A.D.N. and K.H. performed polygenic risk score and variant calling, A.D.N., K.H., and P.R. performed CRE SNP enrichments, B.A.K. generated differential expression signatures, Y.Z. generated clinical correlations, A.S. performed cell enrichments, J.S., S.E.T., W.-m.S., and Y.Z. performed statistical analysis on macrophage experiments, K.S., R.M., P.R., and L.A.P. constructed the eQTL database, B.L. and H.S. performed RNA-seq analysis, E.L. performed transcription factor analysis, M.W. and C.A. provided visualization tools, C.B., M.C., A.D., J.R.F., J.P., and L.F.M. provided patient population guidance, Y.F., M.B.H., B.M.I., N.S., and T.K.T. provided reagents and guidance, A.K., C.A., and J.J.F. provided project support, J.Z. constructed Bayesian networks, B.Z. constructed coexpression networks, and L.A.P. and E.E.S. wrote the manuscript. C.A., B.Z., J.P., J.R.F., and R.D. provided critical review of the manuscript.

Competing interests

J.P., E.M.N., A.S., J.S., S.E.T., C.B., M.C., A.D., J.R.F., and R.D. were employees of Janssen during the time this work was completed.

Corresponding author

Correspondence to Eric E Schadt.

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