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A combined polygenic score of 21,293 rare and 22 common variants improves diabetes diagnosis based on hemoglobin A1C levels.

Peter DornbosRyan KoestererAndrew RuttenburgTrang NguyenJoanne B Colenull nullAaron LeongJames B MeigsJose C FlorezJerome I RotterMiriam S UdlerJason Flannick
Published in: Nature genetics (2022)
Polygenic scores (PGSs) combine the effects of common genetic variants 1,2 to predict risk or treatment strategies for complex diseases 3-7 . 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) diagnosis 7-10 . 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.
Keyphrases
  • copy number
  • type diabetes
  • genome wide
  • gene expression
  • mass spectrometry
  • adipose tissue
  • skeletal muscle
  • genome wide analysis