Assessment of multi-population polygenic risk scores for lipid traits in African Americans

Author:

Drouet Domenica E.1,Liu Shiying2,Crawford Dana C.234

Affiliation:

1. Department of Medicine, Case Western Reserve University, Cleveland, OH, United States of America

2. Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States of America

3. Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States of America

4. Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, United States of America

Abstract

Polygenic risk scores (PRS) based on genome-wide discoveries are promising predictors or classifiers of disease development, severity, and/or progression for common clinical outcomes. A major limitation of most risk scores is the paucity of genome-wide discoveries in diverse populations, prompting an emphasis to generate these needed data for trans-population and population-specific PRS construction. Given diverse genome-wide discoveries are just now being completed, there has been little opportunity for PRS to be evaluated in diverse populations independent from the discovery efforts. To fill this gap, we leverage here summary data from a recent genome-wide discovery study of lipid traits (HDL-C, LDL-C, triglycerides, and total cholesterol) conducted in diverse populations represented by African Americans, Hispanics, Asians, Native Hawaiians, Native Americans, and others by the Population Architecture using Genomics and Epidemiology (PAGE) Study. We constructed lipid trait PRS using PAGE Study published genetic variants and weights in an independent African American adult patient population linked to de-identified electronic health records and genotypes from the Illumina Metabochip (n = 3,254). Using multi-population lipid trait PRS, we assessed levels of association for their respective lipid traits, clinical outcomes (cardiovascular disease and type 2 diabetes), and common clinical labs. While none of the multi-population PRS were strongly associated with the tested trait or outcome, PRSLDL-Cwas nominally associated with cardiovascular disease. These data demonstrate the complexity in applying PRS to real-world clinical data even when data from multiple populations are available.

Funder

The National Human Genome Research Institute

The CWRU Cleveland Institute for Computational Biology

The National Center for Advancing Translational Sciences

The Heart, Lung and Blood Summer Research Program

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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