1. A combined polygenic score of 21,293 rare and 22 common variants improves diabetes diagnosis based on hemoglobin A1C levels
- Author
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Dornbos, Peter, Koesterer, Ryan, Ruttenburg, Andrew, Nguyen, Trang, Cole, Joanne B, Leong, Aaron, Meigs, James B, Florez, Jose C, Rotter, Jerome I, Udler, Miriam S, and Flannick, Jason
- Subjects
Biological Sciences ,Genetics ,Precision Medicine ,Diabetes ,2.1 Biological and endogenous factors ,Metabolic and endocrine ,Good Health and Well Being ,Humans ,Multifactorial Inheritance ,Glycated Hemoglobin ,Diabetes Mellitus ,Type 2 ,Genome-Wide Association Study ,AMP-T2D-GENES Consortium ,Medical and Health Sciences ,Developmental Biology ,Agricultural biotechnology ,Bioinformatics and computational biology - Abstract
Polygenic scores (PGSs) combine the effects of common genetic variants1,2 to predict risk or treatment strategies for complex diseases3-7. Adding rare variation to PGSs has largely unknown benefits and is methodically challenging. Here, we developed a method for constructing rare variant PGSs and applied it to calculate genetically modified hemoglobin A1C thresholds for type 2 diabetes (T2D) diagnosis7-10. The resultant rare variant PGS is highly polygenic (21,293 variants across 154 genes), depends on ultra-rare variants (72.7% observed in fewer than three people) and identifies significantly more undiagnosed T2D cases than expected by chance (odds ratio = 2.71; P = 1.51 × 10-6). A PGS combining common and rare variants is expected to identify 4.9 million misdiagnosed T2D cases in the United States-nearly 1.5-fold more than the common variant PGS alone. These results provide a method for constructing complex trait PGSs from rare variants and suggest that rare variants will augment common variants in precision medicine approaches for common disease.
- Published
- 2022