Transcriptomic analysis of ileal tissue from Crohn's disease patients identifies extracellular matrix genes that distinguish individuals by age at diagnosis

Physiol Genomics. 2020 Oct 1;52(10):478-484. doi: 10.1152/physiolgenomics.00062.2020. Epub 2020 Aug 31.

Abstract

Crohn's disease (CD) is a debilitating gastrointestinal (GI) disorder that can impact the entirety of the GI tract. While substantial progress has been made in the medical management of CD, it remains incurable, frequently relapses, and is a significant financial and medical burden. The pathophysiology of CD is not well understood, but it is thought to arise in genetically susceptible individuals upon an environmental insult. Further elucidation of the disease etiology promises to expose additional therapeutic avenues, with the hope of reducing the burden of CD. One approach to understanding disease pathophysiology is to identify clinically relevant molecular disease subsets by using transcriptomics. In this report, we use hierarchical clustering of the ileal transcriptomes of 34 patients and identify two CD subsets. Clinically, these clusters differed in the age of the patients at CD diagnosis, suggesting that age of onset affects disease pathophysiology. The clusters were segregated by three major gene ontology categories: developmental processes, ion homeostasis, and the immune response. Of the genes constituting the immune system category, expression of extracellular matrix-associated genes, COL4A1, S100A9, ADAMTS2, SERPINE1, and FCN1, exhibits the strongest correlation with an individual's age at CD diagnosis. Together these findings demonstrate that transcriptional profiling is a powerful approach to subclassify CD patients.

Keywords: Crohn’s disease; RNA sequencing; extracellular matrix; inflammation; transcriptome.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Crohn Disease / diagnosis
  • Crohn Disease / epidemiology
  • Crohn Disease / genetics*
  • Crohn Disease / metabolism*
  • Extracellular Matrix / metabolism*
  • Female
  • Gene Expression Profiling
  • Genetic Predisposition to Disease
  • Humans
  • Ileum / metabolism*
  • Male
  • Middle Aged
  • Pennsylvania / epidemiology
  • RNA-Seq
  • Transcriptome*
  • Young Adult