Prioritizing Crohn’s disease genes by integrating association signals with gene expression implicates monocyte subsets

Autor: Judy H. Cho, Ephraim Kenigsberg, Wallace Crandall, Ling-Shiang Chuang, Subra Kugathasan, Clara Abraham, Lee A. Denson, Joshua D. Noe, Nai Yun Hsu, Anne M. Griffiths, Jeffrey S. Hyams, Kyle Gettler, Mamta Giri, Richard Kellermayer, Jerome Martin, David R. Mack, Gabriel E. Hoffman
Rok vydání: 2019
Předmět:
Zdroj: Genes & Immunity. 20:577-588
ISSN: 1476-5470
1466-4879
Popis: Genome-wide association studies have identified ~170 loci associated with Crohn's disease (CD) and defining which genes drive these association signals is a major challenge. The primary aim of this study was to define which CD locus genes are most likely to be disease related. We developed a gene prioritization regression model (GPRM) by integrating complementary mRNA expression datasets, including bulk RNA-Seq from the terminal ileum of 302 newly diagnosed, untreated CD patients and controls, and in stimulated monocytes. Transcriptome-wide association and co-expression network analyses were performed on the ileal RNA-Seq datasets, identifying 40 genome-wide significant genes. Co-expression network analysis identified a single gene module, which was substantially enriched for CD locus genes and most highly expressed in monocytes. By including expression-based and epigenetic information, we refined likely CD genes to 2.5 prioritized genes per locus from an average of 7.8 total genes. We validated our model structure using cross-validation and our prioritization results by protein-association network analyses, which demonstrated significantly higher CD gene interactions for prioritized compared with non-prioritized genes. Although individual datasets cannot convey all of the information relevant to a disease, combining data from multiple relevant expression-based datasets improves prediction of disease genes and helps to further understanding of disease pathogenesis.
Databáze: OpenAIRE
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