Key result
Polygenic risk scores significantly increased the variation explained in resting QTc beyond the 9-10% explained by clinical variables in individuals of European descent (P<0.001).
Why the study?
Does a polygenic risk score improve the prediction of resting QTc interval variation compared to clinical variables alone in diverse ancestry cohorts?
Population
4,158 participants from two real-world cohorts, including 3,735 of European ancestry and 423 of African…
Comparison
Polygenic risk scores for QT interval derived… vs Regression models using only clinical variables
Design
Cohort
Authors
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Supports PRS for QTc prediction in Europeans; leaves open utility across ancestries and clinical translation.
Cohort (n=4,158)
Does a polygenic risk score improve the prediction of resting QTc interval variation compared to clinical variables alone in diverse ancestry cohorts?
p-value: p=<0.001
Polygenic risk scores for QT interval improve prediction of resting QTc in individuals of European descent but not in those of African descent, highlighting the need for ancestry-specific genomic studies.
Rosenberg et al. (2017) conducted a cohort in QT interval variation (n=4,158). Polygenic risk scores (PGS) vs. Clinical variables (nongenetic factors) was evaluated on Variation explained in resting QTc (p=<0.001). Polygenic risk scores significantly increased the variation explained in resting QTc beyond the 9-10% explained by clinical variables in individuals of European descent (P<0.001).
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