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Polygenic Risk Scores May Improve IBD Risk Prediction

For every population in BioMe biobank, combining risk scores from distinct ancestral populations improved risk prediction for IBD

woman holding her stomach

MONDAY, Jan. 4, 2021 (HealthDay News) -- Risk scores from multiethnic populations improve risk prediction for inflammatory bowel disease (IBD), according to a study published online Dec. 24 in Gastroenterology.

Kyle Gettler, Ph.D., from the Icahn School of Medicine at Mount Sinai in New York City, and colleagues examined the effects of common and rare IBD variants on disease prediction and pathophysiology using exome-sequence and single-nucleotide polymorphism array data from 29,358 individuals in the multiethnic BioMe biobank. Polygenic risk scores (PRS) were calculated from European, African American, and Ashkenazi Jewish reference case-control studies; all three datasets were used to run a meta-genomewide association study. PRS were then combined to examine which combination of scores best predicted IBD status.

The researchers found that for every population in BioMe, combining risk scores based on association data from distinct ancestral populations improved IBD prediction; among individuals of European ancestry in the U.K. Biobank, prediction was significantly improved. For non-Europeans, lower predictive power was observed, partly due to lower African IBD case-control reference sizes. Associations for two very early-onset IBD genes, ADAM17 and LRBA, were replicated, with high dominant model penetrance in BioMe. There was an association for autosomal, recessive LRBA risk alleles with severe, early-onset autoimmunity.

"The ability to accurately predict genetic disease risk in individuals across ancestries is a critical avenue that may positively affect patient outcomes, as early interventions and even preventive measures are being considered and developed," a coauthor said in a statement. "These findings support a need for greater genetic diversity, including more data on African American populations, to enhance disease risk predictions and reduce health disparities for all populations."

One author disclosed financial ties to the biotechnology industry.

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