Searching for Genotype-Phenotype Structure: Using Hierarchical Log-Linear Models in Crohn Disease

• Published in: American journal of human genetics 2009-02, Vol.84 (2), p.178-187
• Main Authors: Chapman, Juliet M., Onnie, Clive M., Prescott, Natalie J., Fisher, Sheila A., Mansfield, John C., Mathew, Christopher G., Lewis, Cathryn M., Verzilli, Claudio J., Whittaker, John C.
• Format: Article
• Language: English
• Subjects: Bayesian analysis; Biological and medical sciences; Computer Simulation; Crohn Disease - genetics; Crohn Disease - pathology; Crohn's disease; Fundamental and applied biological sciences. Psychology; Gastroenterology. Liver. Pancreas. Abdomen; General aspects. Genetic counseling; Genes; Genetic diversity; Genetics; Genetics of eukaryotes. Biological and molecular evolution; Genotype; Genotype & phenotype; Humans; Intestine, Small - anatomy & histology; Medical genetics; Medical sciences; Models, Genetic; Models, Statistical; Molecular and cellular biology; Mutation; Other diseases. Semiology; Phenotype; Poisson Distribution; Probability; Reproducibility of Results; Severity of Illness Index; Stomach. Duodenum. Small intestine. Colon. Rectum. Anus
• ISSN: 0002-9297; 1537-6605
• DOI: 10.1016/j.ajhg.2008.12.015

There has been considerable recent success in the detection of gene-disease associations. We consider here the development of tools that facilitate the more detailed characterization of the effect of a genetic variant on disease. We replace the simplistic classification of individuals according to a single binary disease indicator with classification according to a number of subphenotypes. This more accurately reflects the underlying biological complexity of the disease process, but it poses additional analytical difficulties. Notably, the subphenotypes that make up a particular disease are typically highly associated, and it becomes difficult to distinguish which genes might be causing which subphenotypes. Such problems arise in many complex diseases. Here, we concentrate on an application to Crohn disease (CD). We consider this problem as one of model selection based upon log-linear models, fitted in a Bayesian framework via reversible-jump Metropolis-Hastings approach. We evaluate the performance of our suggested approach with a simple simulation study and then apply the method to a real data example in CD, revealing a sparse disease structure. Most notably, the associated NOD2.908G→R mutation appears to be directly related to more severe disease behaviors, whereas the other two associated NOD2 variants, 1007L→FS and 702R→W, are more generally related to disease in the small bowel (ileum and jejenum). The ATG16L1.300T→A variant appears to be directly associated with only disease of the small bowel.