Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn's disease

For most immune-mediated diseases, the main determinant of patient well-being is not the diagnosis itself but instead the course that the disease takes over time (prognosis). Prognosis may vary substantially between patients for reasons that are poorly understood. Familial studies support a genetic contribution to prognosis, but little evidence has been found for a proposed association between prognosis and the burden of susceptibility variants. To better characterize how genetic variation influences disease prognosis, we performed a within-cases genome-wide association study in two cohorts of patients with Crohn's disease. We identified four genome-wide significant loci, none of which showed any association with disease susceptibility. Conversely, the aggregated effect of all 170 disease susceptibility loci was not associated with disease prognosis. Together, these data suggest that the genetic contribution to prognosis in Crohn's disease is largely independent of the contribution to disease susceptibility and point to a biology of prognosis that could provide new therapeutic opportunities.

[1]  Tom R. Gaunt,et al.  LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis , 2016, bioRxiv.

[2]  M. Brown,et al.  Multiple Sclerosis Susceptibility-Associated SNPs Do Not Influence Disease Severity Measures in a Cohort of Australian MS Patients , 2010, PloS one.

[3]  C. Vallot,et al.  Erosion of X Chromosome Inactivation in Human Pluripotent Cells Initiates with XACT Coating and Depends on a Specific Heterochromatin Landscape. , 2015, Cell Stem Cell.

[4]  C. Franceschi,et al.  Genes involved in immune response/inflammation, IGF1/insulin pathway and response to oxidative stress play a major role in the genetics of human longevity: the lesson of centenarians , 2005, Mechanisms of Ageing and Development.

[5]  A. Zeileis,et al.  Regression Models for Count Data in R , 2008 .

[6]  D. Altshuler,et al.  A map of human genome variation from population-scale sequencing , 2010, Nature.

[7]  B Bass,et al.  The natural history of multiple sclerosis: a geographically based study. I. Clinical course and disability. , 1989, Brain : a journal of neurology.

[8]  D. Clayton,et al.  Multiple sclerosis in sibling pairs: an analysis of 250 families , 2001, Journal of neurology, neurosurgery, and psychiatry.

[9]  K. Liao,et al.  Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset , 2011, PloS one.

[10]  Judy H. Cho,et al.  Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations , 2015, Nature Genetics.

[11]  R. Xavier,et al.  Differential Effect of Genetic Burden on Disease Phenotypes in Crohn's Disease and Ulcerative Colitis: Analysis of a North American Cohort , 2014, The American Journal of Gastroenterology.

[12]  T. Pincus.  Long-term outcomes in rheumatoid arthritis. , 1995, British journal of rheumatology.

[13]  P. Gregersen,et al.  Clustering of disease features within 512 multicase rheumatoid arthritis families. , 2004, Arthritis and rheumatism.

[14]  T. Ørntoft,et al.  Identification of expressed and conserved human noncoding RNAs , 2014, RNA.

[15]  C. Morimoto,et al.  The cellular basis for lack of antibody response to hepatitis B vaccine in humans , 1991, The Journal of experimental medicine.

[16]  Inês Barroso,et al.  Meta-analysis and imputation refines the association of 15q25 with smoking quantity , 2010, Nature Genetics.

[17]  Samir A. Shah,et al.  Risk of early surgery for Crohn's disease: implications for early treatment strategies , 2003, American Journal of Gastroenterology.

[18]  A. Goris,et al.  Burden of risk variants correlates with phenotype of multiple sclerosis , 2015, Multiple sclerosis.

[19]  Tariq Ahmad,et al.  Meta-analysis and imputation refines the association of 15q25 with smoking quantity , 2010, Nature Genetics.

[20]  J. Satsangi,et al.  Clinical patterns of familial inflammatory bowel disease. , 1996, Gut.

[21]  Jon Wakefield,et al.  A Bayesian measure of the probability of false discovery in genetic epidemiology studies. , 2007, American journal of human genetics.

[22]  M. Todaro,et al.  T-cell activation in HLA-B8, DR3-positive individuals. Early antigen expression defect in vitro. , 1995, Human immunology.

[23]  O. Delaneau,et al.  Supplementary Information for ‘ Improved whole chromosome phasing for disease and population genetic studies ’ , 2012 .

[24]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[25]  J. Hugot,et al.  Genotype/Phenotype Analyses for 53 Crohn’s Disease Associated Genetic Polymorphisms , 2012, PloS one.

[26]  P. Munkholm,et al.  Changes in Clinical Characteristics, Course, and Prognosis of Inflammatory Bowel Disease during the Last 5 Decades: A Population‐Based Study from Copenhagen, Denmark , 2007, Inflammatory bowel diseases.

[27]  Tariq Ahmad,et al.  Human SNP Links Differential Outcomes in Inflammatory and Infectious Disease to a FOXO3-Regulated Pathway , 2013, Cell.

[28]  M. Daly,et al.  Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology , 2011, PLoS genetics.

[29]  J. González,et al.  Genetic factors conferring an increased susceptibility to develop Crohn's disease also influence disease phenotype: results from the IBDchip European Project , 2012, Gut.

[30]  P. Donnelly,et al.  A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies , 2009, PLoS genetics.

[31]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[32]  Y. Okada,et al.  Do Genetic Susceptibility Variants Associate with Disease Severity in Early Active Rheumatoid Arthritis? , 2015, The Journal of Rheumatology.

[33]  C. Caruso,et al.  HLA‐B8,DR3 PHENOTYPE AND LYMPHOCYTE RESPONSES TO PHYTOHAEMAGGLUTININ , 1990, Journal of immunogenetics.

[34]  Xinli Hu,et al.  SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci , 2014, Bioinform..

[35]  David C. Wilson,et al.  Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease , 2012, Nature.

[36]  A. Morris,et al.  Data quality control in genetic case-control association studies , 2010, Nature Protocols.

[37]  Paul A. Lyons,et al.  T cell exhaustion, costimulation and clinical outcome in autoimmunity and infection , 2015, Nature.

[38]  Yurii S. Aulchenko,et al.  PredictABEL: an R package for the assessment of risk prediction models , 2011, European Journal of Epidemiology.

[39]  M. Daly,et al.  An Atlas of Genetic Correlations across Human Diseases and Traits , 2015, Nature Genetics.

[40]  Jeanine J. Houwing-Duistermaat,et al.  Power of Selective Genotyping in Genetic Association Analyses of Quantitative Traits , 2000, Behavior genetics.

[41]  C. Wijmenga,et al.  Molecular prediction of disease risk and severity in a large Dutch Crohn’s disease cohort , 2008, Gut.

[42]  Cole Trapnell,et al.  Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. , 2010, Nature biotechnology.

[43]  Alexander T. Dilthey,et al.  Multi-Population Classical HLA Type Imputation , 2013, PLoS Comput. Biol..

[44]  Thomas R. Gingeras,et al.  STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..

[45]  Tom R. Gaunt,et al.  The UK10K project identifies rare variants in health and disease , 2016 .

[46]  H. Hakonarson,et al.  Large sample size, wide variant spectrum, and advanced machine-learning technique boost risk prediction for inflammatory bowel disease. , 2013, American journal of human genetics.

[47]  Tom C Freeman,et al.  An expression atlas of human primary cells: inference of gene function from coexpression networks , 2013, BMC Genomics.

[48]  Hailiang Huang,et al.  High density mapping of the MHC identifies a shared role for HLA-DRB1*01:03 in inflammatory bowel diseases and heterozygous advantage in ulcerative colitis , 2014, Nature Genetics.

[49]  M. Färkkilä,et al.  CARD15/NOD2 gene variants are associated with familially occurring and complicated forms of Crohn’s disease , 2003, Gut.

[50]  Lars Alfredsson,et al.  Extended Report , 2010 .

[51]  Ross M. Fraser,et al.  A General Approach for Haplotype Phasing across the Full Spectrum of Relatedness , 2014, PLoS genetics.

[52]  Tariq Ahmad,et al.  Inherited determinants of Crohn's disease and ulcerative colitis phenotypes: a genetic association study , 2016, The Lancet.

[53]  A. Ziegler,et al.  Cochran-Armitage Test versus Logistic Regression in the Analysis of Genetic Association Studies , 2011, Human Heredity.