Serum Biomarkers Identify Patients Who Will Develop Inflammatory Bowel Diseases Up to 5 Years Before Diagnosis

      Background & Aims

      Biomarkers are needed to identify patients at risk for development of inflammatory bowel diseases. We aimed to identify serum biomarkers of Crohn’s disease and ulcerative colitis that can be detected and quantified before diagnosis.


      We obtained serum samples from patients archived before a diagnosis of Crohn’s disease (n = 200) or ulcerative colitis (n = 199), as well as from 200 healthy individuals (controls), collected from 1998 through 2013 as part of the US Defense Medical Surveillance System. We measured levels of antibodies against microbes (anti–Saccharomyces cerevisiae IgA or IgG, anti–Escherichia coli outer membrane porin C, anti-CBir1, anti-flagellin 2, anti-flagellin X, and perinuclear anti-neutrophil cytoplasmic antibodies) and 1129 proteins in each sample. We then used functional principal component analysis to derive the time-varying trajectory for each marker, which then was used in a multivariate model to predict disease status. Predictive performances at different prediagnosis timepoints were evaluated using area under the receiver operating characteristic curves (AUROCs). Biological pathways that were up-regulated in serum from patients with Crohn’s disease were identified based on changes in protein abundance at different time periods preceding diagnosis.


      We identified a panel of 51 protein biomarkers that were predictive of Crohn’s disease within 5 years with an AUROC of 0.76 and a diagnosis within 1 year with an AUROC of 0.87. Based on the proteins included in the panel, imminent development of CD was associated with changes in the complement cascade, lysosomes, innate immune response, and glycosaminoglycan metabolism. Serum antibodies and proteins identified patients who received a diagnosis of ulcerative colitis within 5 years with an AUROC of only 0.56 and within 1 year with an AUROC of 0.72.


      We identified a panel of serum antibodies and proteins that were predictive of patients who will receive a diagnosis of Crohn’s disease within 5 years with high accuracy. By contrast we did not identify biomarkers associated with future diagnosis of ulcerative colitis.


      Abbreviations used in this paper:

      APCS (serum amyloid P component), ASCA (anti–Saccharomyces cerevisiae antibodies), CD (Crohn’s disease), CRP (C-reactive protein), DMSS (Defense Medical Surveillance System), DoDSR (US Department of Defense Serum Repository), HC (healthy control), IBD (inflammatory bowel disease), ICD-9 (International Classification of Diseases, Ninth Revision), IL (interleukin), KEGG (Kyoto Encyclopedia of Genes and Genomes), LASSO (least absolute shrinkage and selection operatory), pANCA (perinuclear anti–neutrophil cytoplasmic antibodies), PREDICTS (Proteomic Evaluation and Discovery in an IBD Cohort of Tri-service Subjects), UC (ulcerative colitis)
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        • Ng S.C.
        • Shi H.Y.
        • Hamidi N.
        • et al.
        Worldwide incidence and prevalence of inflammatory bowel disease in the 21st century: a systematic review of population-based studies.
        Lancet. 2018; 390: 2769-2778
        • Kaplan G.G.
        The global burden of IBD: from 2015 to 2025.
        Nat Rev Gastroenterol Hepatol. 2015; 12: 720-727
        • Torres J.
        • Boyapati R.K.
        • Kennedy N.A.
        • et al.
        Systematic review of effects of withdrawal of immunomodulators or biologic agents from patients with inflammatory bowel disease.
        Gastroenterology. 2015; 149: 1716-1730
        • Torres J.
        • Burisch J.
        • Riddle M.
        • et al.
        Preclinical disease and preventive strategies in IBD: perspectives, challenges and opportunities.
        Gut. 2016; 65: 1061-1069
        • Choung R.S.
        • Princen F.
        • Stockfisch T.P.
        • et al.
        Serologic microbial associated markers can predict Crohn’s disease behaviour years before disease diagnosis.
        Aliment Pharmacol Ther. 2016; 43: 1300-1310
        • Porter C.K.
        • Riddle M.S.
        • Gutierrez R.L.
        • et al.
        Cohort profile of the PRoteomic Evaluation and Discovery in an IBD Cohort of Tri-service Subjects (PREDICTS) study: rationale, organization, design, and baseline characteristics.
        Contemp Clin Trials Comm. 2019; 14: 100345
        • Rubertone M.V.
        • Brundage J.F.
        The Defense Medical Surveillance System and the Department of Defense serum repository: glimpses of the future of public health surveillance.
        Am J Public Health. 2002; 92: 1900-1904
        • Gold L.
        • Walker J.J.
        • Wilcox S.K.
        • Williams S.
        Advances in human proteomics at high scale with the SOMAscan proteomics platform.
        N Biotechnol. 2012; 29: 543-549
        • James G.M.
        • Hastie T.J.
        • Sugar C.A.
        Principal component models for sparse functional data.
        Biometrika. 2000; 87: 587-602
        • Yao F.
        • Müller H.-G.
        • Wang J.-L.
        Functional data analysis for sparse longitudinal data.
        J Am Stat Assoc. 2005; 100: 577-590
        • Peng J.
        • Paul D.
        A geometric approach to maximum likelihood estimation of the functional principal components from sparse longitudinal data.
        J Comput Graph Stat. 2009; 18: 995-1015
        • Feng Z.Z.
        • Yang X.
        • Subedi S.
        • McNicholas P.D.
        The LASSO and sparse least square regression methods for SNP selection in predicting quantitative traits.
        IEEE/ACM Trans Comput Biol Bioinform. 2012; 9: 629-636
        • Breiman L.
        Random forests.
        Mach Learn. 2001; 45: 5-32
        • Porter C.K.
        • Welsh M.
        • Riddle M.S.
        • et al.
        Epidemiology of inflammatory bowel disease among participants of the Millennium Cohort: incidence, deployment-related risk factors, and antecedent episodes of infectious gastroenteritis.
        Aliment Pharmacol Ther. 2017; 45: 1115-1127
        • Betteridge J.D.
        • Armbruster S.P.
        • Maydonovitch C.
        • Veerappan G.R.
        Inflammatory bowel disease prevalence by age, gender, race, and geographic location in the U.S. military health care population.
        Inflamm Bowel Dis. 2013; 19: 1421-1427
        • Liberzon A.
        • Subramanian A.
        • Pinchback R.
        • et al.
        Molecular signatures database (MSigDB) 3.0.
        Bioinformatics. 2011; 27: 1739-1740
        • Subramanian A.
        • Tamayo P.
        • Mootha V.K.
        • et al.
        Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.
        Proc Natl Acad Sci U S A. 2005; 102: 15545-15550
        • Kohavi R.
        A study of cross-validation and bootstrap for accuracy estimation and model selection.
        Proceedings of the 14th International Joint Conference on Artificial Intelligence. 2. Morgan Kaufmann, Montreal, Canada1995: 1137-1143
        • Israeli E.
        • Grotto I.
        • Gilburd B.
        • et al.
        Anti-Saccharomyces cerevisiae and antineutrophil cytoplasmic antibodies as predictors of inflammatory bowel disease.
        Gut. 2005; 54: 1232-1236
        • van Schaik F.D.M.
        • Oldenburg B.
        • Hart A.R.
        • et al.
        Serological markers predict inflammatory bowel disease years before the diagnosis.
        Gut. 2013; 62: 683-688
        • Lochhead P.
        • Khalili H.
        • Ananthakrishnan A.N.
        • et al.
        Association between circulating levels of C-reactive protein and interleukin-6 and risk of inflammatory bowel disease.
        Clin Gastroenterol Hepatol. 2016; 14: 818-824
        • Landers C.J.
        • Cohavy O.
        • Misra R.
        • et al.
        Selected loss of tolerance evidenced by Crohn’s disease-associated immune responses to auto- and microbial antigens.
        Gastroenterology. 2002; 123: 689-699
        • Lodes M.J.
        • Cong Y.
        • Elson C.O.
        • et al.
        Bacterial flagellin is a dominant antigen in Crohn disease.
        J Clin Invest. 2004; 113: 1296-1306
        • Wang Z.Z.
        • Shi K.
        • Peng J.
        Serologic testing of a panel of five antibodies in inflammatory bowel diseases: diagnostic value and correlation with disease phenotype.
        Biomed Rep. 2017; 6: 401-410
        • Danese S.
        • Fiorino G.
        • Peyrin-Biroulet L.
        Early intervention in Crohn’s disease: towards disease modification trials.
        Gut. 2017; 66: 2179-2187
        • Cadwell K.
        • Liu J.Y.
        • Brown S.L.
        • et al.
        A key role for autophagy and the autophagy gene Atg16l1 in mouse and human intestinal Paneth cells.
        Nature. 2008; 456: 259-263
        • Dias A.M.
        • Pereira M.S.
        • Padrao N.A.
        • et al.
        Glycans as critical regulators of gut immunity in homeostasis and disease.
        Cell Immunol. 2018; 333: 9-18
        • Simurina M.
        • de Haan N.
        • Vuckovic F.
        • et al.
        Glycosylation of immunoglobulin G associates with clinical features of inflammatory bowel diseases.
        Gastroenterology. 2018; 154: 1320-1333
        • Heybeli C.
        The complement system and inflammatory bowel disease.
        Inflamm Bowel Dis. 2016; 22: E22
        • Nguyen V.Q.
        • Jiang D.
        • Hoffman S.N.
        • et al.
        Impact of diagnostic delay and associated factors on clinical outcomes in a U.S. inflammatory bowel disease cohort.
        Inflamm Bowel Dis. 2017; 23: 1825-1831