Journal
NATURE GENETICS
Volume 48, Issue 12, Pages 1570-1575Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/ng.3700
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Funding
- National Institute of Diabetes and Digestive and Kidney Diseases [1K08DK102877-01, 1R01DK097768-01]
- NIH/Harvard Catalyst [1KL2TR001100-01]
- Broad Institute
- Wellcome Trust [095564, 107064]
- Medical Research Council [MC_UU_12012/5/B, MC_UU_12012/5] Funding Source: researchfish
- National Institute for Health Research [NF-SI-0514-10176, CL-2013-23-001, NF-SI-0507-10380, NF-SI-0513-10109] Funding Source: researchfish
- Wellcome Trust [110082/Z/15/Z] Funding Source: researchfish
- MRC [MC_UU_12012/5] Funding Source: UKRI
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Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty(1,2). For example, mutations in PPARG cause Mendelian lipodystrophy(3,4) and increase risk of type 2 diabetes (T2D)(5). Although approximately 1 in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPAR gamma variants, we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single-amino acid substitutions. We developed a pooled functional assay in human macrophages, experimentally evaluated all protein variants, and used the experimental data to train a variant classifier by supervised machine learning. When applied to 55 new missense variants identified in population-based and clinical sequencing, the classifier annotated 6 variants as pathogenic; these were subsequently validated by single variant assays. Saturation mutagenesis and prospective experimental characterization can support immediate diagnostic interpretation of newly discovered missense variants in disease-related genes.
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