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Majithia, Amit R.

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Majithia

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Amit R.

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Majithia, Amit R.

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Author's Publications: search.filters.isAuthorOfPublication.8fa5153b-624b-4af6-bca4-44f35d7b7523

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    Prospective functional classification of all possible missense variants in PPARG
    (2016) Majithia, Amit R.; Tsuda, Ben; Agostini, Maura; Gnanapradeepan, Keerthana; Rice, Robert; Peloso, Gina; Patel, Kashyap A.; Zhang, Xiaolan; Broekema, Marjoleine F.; Patterson, Nick; Duby, Marc; Sharpe, Ted; Kalkhoven, Eric; Rosen, Evan; Barroso, Inês; Ellard, Sian; Kathiresan, Sekar; O’Rahilly, Stephen; Chatterjee, Krishna; Florez, Jose; Mikkelsen, Tarjei; Savage, David B.; Altshuler, David
    Abstract Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty1,2. For example, mutations in PPARG cause Mendelian lipodystrophy3,4 and increase risk of type 2 diabetes (T2D)5. While approximately one in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ 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 (http://miter.broadinstitute.org). When applied to 55 novel missense variants identified in population-based and clinical sequencing, the classifier annotated six 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.