Genetic predictors of medically refractory ulcerative colitis
โ Scribed by Talin Haritunians; Kent D. Taylor; Stephan R. Targan; Marla Dubinsky; Andrew Ippoliti; Soonil Kwon; Xiuqing Guo; Gil Y. Melmed; Dror Berel; Emebet Mengesha; Bruce M. Psaty; Nicole L. Glazer; Eric A. Vasiliauskas; Jerome I. Rotter; Phillip R. Fleshner; Dermot P.B. McGovern
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- English
- Weight
- 426 KB
- Volume
- 16
- Category
- Article
- ISSN
- 1078-0998
No coin nor oath required. For personal study only.
โฆ Synopsis
Background: Acute severe ulcerative colitis (UC) remains a significant clinical challenge and the ability to predict, at an early stage, those individuals at risk of colectomy for medically refractory UC (MR-UC) would be a major clinical advance. The aim of this study was to use a genome-wide association study (GWAS) in a well-characterized cohort of UC patients to identify genetic variation that contributes to MR-UC.
Methods: A GWAS comparing 324 MR-UC patients with 537 non-MR-UC patients was analyzed using logistic regression and Cox proportional hazards methods. In addition, the MR-UC patients were compared with 2601 healthy controls.
Results: MR-UC was associated with more extensive disease (P ยผ 2.7 ร 10 ร6 ) and a positive family history of UC (P ยผ 0.004). A risk score based on the combination of 46 single nucleotide polymorphisms (SNPs) associated with MR-UC explained 48% of the variance for colectomy risk in our cohort. Risk scores divided into quarters showed the risk of colectomy to be 0%, 17%, 74%, and 100% in the four groups. Comparison of the MR-UC subjects with healthy controls confirmed the contribution of the major histocompatibility complex to severe UC (peak association: rs17207986, P ยผ 1.4 ร 10 ร16 ) and provided genome-wide suggestive association at the TNFSF15 (TL1A) locus (peak association: rs11554257, P ยผ 1.4 ร 10 ร6 ).
Conclusions: A SNP-based risk scoring system, identified here by GWAS analyses, may provide a useful adjunct to clinical parameters for predicting the natural history of UC. Furthermore, discovery of genetic processes underlying disease severity may help to identify pathways for novel therapeutic intervention in severe UC.
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