Stratification of Risk of Progression to Colectomy in Ulcerative Colitis using Measured and Predicted Gene Expression
Author:
Mo Angela, Nagpal Sini, Gettler Kyle, Haritunians Talin, Giri Mamta, Haberman Yael, Karns Rebekah, Prince Jarod, Arafat Dalia, Hsu Nai-Yun, Chuang Ling-Shiang, Argmann Carmen, Kasarskis Andrew, Suarez-Farinas Mayte, Gotman Nathan, Mengesha Emebet, Venkateswaran Suresh, Rufo Paul A., Baker Susan S., Sauer Cary G., Markowitz James, Pfefferkorn Marian D., Rosh Joel R., Boyle Brendan M., Mack David R., Baldassano Robert N., Shah Sapana, LeLeiko Neal S., Heyman Melvin B., Griffiths Anne M., Patel Ashish S., Noe Joshua D., Thomas Sonia Davis, Aronow Bruce J., Walters Thomas D., McGovern Dermot P. B., Hyams Jeffrey S., Kugathasan Subra, Cho Judy H., Denson Lee A., Gibson GregORCID
Abstract
SUMMARYAn important goal of clinical genomics is to be able to estimate the risk of adverse disease outcomes. Between 5% and 10% of ulcerative colitis (UC) patients require colectomy within five years of diagnosis, but polygenic risk scores (PRS) utilizing findings from GWAS are unable to provide meaningful prediction of this adverse status. By contrast, in Crohn’s disease, gene expression profiling of GWAS-significant genes does provide some stratification of risk of progression to complicated disease in the form of a Transcriptional Risk Score (TRS). Here we demonstrate that both measured (TRS) and polygenic predicted gene expression (PPTRS) identify UC patients at 5-fold elevated risk of colectomy with data from the PROTECT clinical trial and UK Biobank population cohort studies, independently replicated in an NIDDK-IBDGC dataset. Prediction of gene expression from relatively small transcriptome datasets can thus be used in conjunction with transcriptome-wide association studies to stratify risk of disease complications.
Publisher
Cold Spring Harbor Laboratory
Cited by
2 articles.
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