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      Validation of Polygenic Scores for QT Interval in Clinical Populations

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          Abstract

          Background

          Polygenic risk scores (PGS) enable rapid estimation of genome-wide susceptibility for traits, which may be useful in clinical settings, such as prediction of QT interval. In this study, we sought to validate PGS for QT interval in two ‘real-world’ cohorts of European and African ancestry.

          Methods and Results

          2915 participants of European (EA) and 366 of African ancestry (AA) in the MGH Cardiology and Metabolic Patient (CAMP) study were genotyped on a genome-wide array and imputed to the 1000 Genomes reference panel. An additional 820 EA and 57 AA participants in the Partners Biobank were genotyped and used for validation. PGS were created for each individual using effect estimates from association tests with QT interval obtained from prior genome-wide association studies (GWAS), with variants selected based from multiple significance thresholds in the original study. In regression models, clinical variables explained ∼9-10% of total variation in resting QTc in EA individuals, and ∼12-18% in AA individuals. The PGS significantly increased variation explained at most significance thresholds (p<0.001), with a trend toward increased variation explained at more stringent p value cut-points in the CAMP EA cohort (p < 0.05). In AA individuals, PGS provided no improvement in variation explained at any significance threshold.

          Conclusions

          For individuals of European descent, PGS provided a significant increase in variation in QT interval explained compared to a model with only non-genetic factors at nearly every significance level. There was no apparent benefit gained by relaxing the significance threshold from conventional genome-wide significance (p<5×10 -8).

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          Author and article information

          Journal
          101489144
          35623
          Circ Cardiovasc Genet
          Circ Cardiovasc Genet
          Circulation. Cardiovascular genetics
          1942-325X
          1942-3268
          13 September 2017
          October 2017
          01 October 2018
          : 10
          : 5
          : e001724
          Affiliations
          [1 ]University of Colorado School of Medicine, Aurora, CO
          [2 ]Massachusetts General Hospital, Boston, MA
          [3 ]Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA
          Author notes
          Correspondence: Michael Rosenberg, Division of Cardiology, University of Colorado, Anschutz Medical Campus, 12631 E. 17 th Avenue, Mail Stop B130, Aurora, CO 80045, Tel: 303-724-8391, Fax: 303-724-2094, michael.a.rosenberg@ 123456ucdenver.edu
          Article
          PMC5679734 PMC5679734 5679734 nihpa905670
          10.1161/CIRCGENETICS.117.001724
          5679734
          28986454
          65dbe012-7078-4e66-a8a8-7220bfdae1b3
          History
          Categories
          Article

          prediction,epidemiology,bioinformatics,genetics,repolarization

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