Stratification of Risk of Progression to Colectomy in Ulcerative Colitis using Measured and Predicted Gene Expression

Angela Mo; Sini Nagpal; Kyle Gettler; Talin Haritunians; Mamta Giri; Yael Haberman; Rebekah A. Karns; Jarod Prince; Dalia Arafat; Nai-Yun Hsu; Ling-shiang F. Chuang; Carmen Argmann; Andrew Kasarskis; Mayte Suárez‐Fariñas; Nathan Gotman; Emebet Mengesha; Suresh Venkateswaran; Paul A. Rufo; Susan S. Baker; Cary G. Sauer; James F. Markowitz; Marian D. Pfefferkorn; Joel R. Rosh; Brendan M. Boyle; David R. Mack; Robert N. Baldassano; Sapana Shah; Neal S. LeLeiko; Melvin B. Heyman; Anne Marie Griffiths

doi:10.1101/2021.04.02.438187

GeneticsbioRxivApr 2, 2021

Preprint

Stratification of Risk of Progression to Colectomy in Ulcerative Colitis using Measured and Predicted Gene Expression

Angela Mo, Sini Nagpal iD, Kyle Gettler iD, Talin Haritunians iD, Mamta Giri iD, Yael Haberman iD, Rebekah A. Karns iD, Jarod Prince, Dalia Arafat iD, Nai-Yun Hsu iD, Ling-shiang F. Chuang iD, Carmen Argmann iD, Andrew Kasarskis iD, Mayte Suárez‐Fariñas iD, Nathan Gotman, Emebet Mengesha iD, Suresh Venkateswaran iD, Paul A. Rufo iD, Susan S. Baker iD, Cary G. Sauer, James F. Markowitz iD, Marian D. Pfefferkorn, Joel R. Rosh iD, Brendan M. Boyle, David R. Mack iD, , Greg C. Gibson iD

Abstract

An 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 Crohns 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.

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