[en] <sec> <title>Background</title> <p>Crohn's Disease (CD) has a heterogeneous presentation, and is typically classified according to extent and location of disease. The genetic susceptibility to CD is well known and genome-wide association scans (GWAS) and meta-analysis thereof have identified over 30 susceptibility loci. Except for the association between ileal CD and <italic>NOD2</italic> mutations, efforts in trying to link CD genetics to clinical subphenotypes have not been very successful. We hypothesized that the large number of confirmed genetic variants enables (better) classification of CD patients.</p> </sec><sec> <title>Methodology/Principal Findings</title> <p>To look for genetic-based subgroups, genotyping results of 46 SNPs identified from CD GWAS were analyzed by Latent Class Analysis (LCA) in CD patients and in healthy controls. Six genetic-based subgroups were identified in CD patients, which were significantly different from the five subgroups found in healthy controls. The identified CD-specific clusters are therefore likely to contribute to disease behavior. We then looked at whether we could relate the genetic-based subgroups to the currently used clinical parameters. Although modest differences in prevalence of disease location and behavior could be observed among the CD clusters, Random Forest analysis showed that patients could not be allocated to one of the 6 genetic-based subgroups based on the typically used clinical parameters alone. This points to a poor relationship between the genetic-based subgroups and the used clinical subphenotypes.</p> </sec><sec> <title>Conclusions/Significance</title> <p>This approach serves as a first step to reclassify Crohn's disease. The used technique can be applied to other common complex diseases as well, and will help to complete patient characterization, in order to evolve towards personalized medicine.</p> </sec>
Disciplines :
Gastroenterology & hepatology
Author, co-author :
Cleynen, Isabelle
Mahachie John, Jestinah ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Bioinformatique
Henckaerts, Liesbet
Van Moerkercke, Wouter
Rutgeerts, Paul
Van Steen, Kristel ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Bioinformatique
Vermeire, Severine
Language :
English
Title :
Molecular Reclassification of Crohn's Disease by Cluster Analysis of Genetic Variants
Publication date :
2010
Journal title :
PLoS ONE
eISSN :
1932-6203
Publisher :
Public Library of Science, United States - California
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
Bibliography
Barrett JC, Hansoul S, Nicolae DL, Cho JH, Duerr RH, et al. (2008) Genomewide association defines more than 30 distinct susceptibility loci for Crohn's disease. Nat Genet 40: 955-962.
Vermeire S, Wild G, Kocher K, Cousineau J, Dufresne L, et al. (2002) CARD15 genetic variation in a Quebec population: prevalence, genotype-phenotype relationship, and haplotype structure. Am J Hum Genet 71: 74-83.
Hampe J, Grebe J, Nikolaus S, Solberg C, Croucher PJ, et al. (2002) Association of NOD2 (CARD 15) genotype with clinical course of Crohn's disease: a cohort study. Lancet 359: 1661-1665.
Cuthbert AP, Fisher SA, Mirza MM, King K, Hampe J, et al. (2002) The contribution of NOD2 gene mutations to the risk and site of disease in inflammatory bowel disease. Gastroenterology 122: 867-874.
Ahmad T, Armuzzi A, Bunce M, Mulcahy-Hawes K, Marshall SE, et al. (2002) The molecular classification of the clinical manifestations of Crohn's disease. Gastroenterology 122: 854-866.
Henckaerts L, Van Steen K, Verstreken I, Cleynen I, Franke A, et al. (2009) Genetic Risk Profiling And Prediction Of Disease Course In Crohn'S Disease Patients. Clin Gastroenterol Hepatol.
Silverberg MS, Satsangi J, Ahmad T, Arnott ID, Bernstein CN, et al. (2005) Toward an integrated clinical, molecular and serological classification of inflammatory bowel disease: Report of a Working Party of the 2005 Montreal World Congress of Gastroenterology. Can J Gastroenterol 19 Suppl A: 5-36.
Satsangi J, Silverberg MS, Vermeire S, Colombel JF (2006) The Montreal classification of inflammatory bowel disease: controversies, consensus, and implications. Gut 55: 749-753.
McLachlan G, Peel D (2000) Finite Mixture Models; Series W, editor. New York: John Wiley & Sons. 456 p.
Hunt L, Jorgensen M (1999) Mixture Model clustering using the MULTIMIX program. Aust N Z J Stat 41: 154-171.
Hunt L, Jorgensen M (2003) Mixture model clustering for mixed data with missing information. Computational Statistics & Data Analysis 41: 429-440.
Wang K, Zhang H, Kugathasan S, Annese V, Bradfield JP, et al. (2009) Diverse genome-wide association studies associate the IL12/IL23 pathway with Crohn Disease. Am J Hum Genet 84: 399-405.
McGovern DP, Rotter JI, Mei L, Haritunians T, Landers C, et al. (2009) Genetic epistasis of IL23/IL17 pathway genes in Crohn's disease. Inflamm Bowel Dis 15: 883-889.
Rioux JD, Xavier RJ, Taylor KD, Silverberg MS, Goyette P, et al. (2007) Genome-wide association study identifies new susceptibility loci for Crohn disease and implicates autophagy in disease pathogenesis. Nat Genet 39: 596-604.
Parkes M, Barrett JC, Prescott NJ, Tremelling M, Anderson CA, et al. (2007) Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility. Nat Genet 39: 830-832.
Hugot JP, Chamaillard M, Zouali H, Lesage S, Cezard JP, et al. (2001) Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn's disease. Nature 411: 599-603.
Ogura Y, Bonen DK, Inohara N, Nicolae DL, Chen FF, et al. (2001) A frameshift mutation in NOD2 associated with susceptibility to Crohn's disease. Nature 411: 603-606.
Duerr RH, Taylor KD, Brant SR, Rioux JD, Silverberg MS, et al. (2006) A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science 314: 1461-1463.
Weersma RK, Stokkers PC, van Bodegraven AA, van Hogezand RA, Verspaget HW, et al. (2009) Molecular prediction of disease risk and severity in a large Dutch Crohn's disease cohort. Gut 58: 388-395.
Vasiliauskas EA, Kam LY, Karp LC, Gaiennie J, Yang H, et al. (2000) Marker antibody expression stratifies Crohn's disease into immunologically homogeneous subgroups with distinct clinical characteristics. Gut 47: 487-496.
Mow WS, Vasiliauskas EA, Lin YC, Fleshner PR, Papadakis KA, et al. (2004) Association of antibody responses to microbial antigens and complications of small bowel Crohn's disease. Gastroenterology 126: 414-424.
This website uses cookies to improve user experience. Read more
Save & Close
Accept all
Decline all
Show detailsHide details
Cookie declaration
About cookies
Strictly necessary
Performance
Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies.
This cookie is used by Cookie-Script.com service to remember visitor cookie consent preferences. It is necessary for Cookie-Script.com cookie banner to work properly.
Performance cookies are used to see how visitors use the website, eg. analytics cookies. Those cookies cannot be used to directly identify a certain visitor.
Used to store the attribution information, the referrer initially used to visit the website
Cookies are small text files that are placed on your computer by websites that you visit. Websites use cookies to help users navigate efficiently and perform certain functions. Cookies that are required for the website to operate properly are allowed to be set without your permission. All other cookies need to be approved before they can be set in the browser.
You can change your consent to cookie usage at any time on our Privacy Policy page.