Prospective functional classification of all possible missense variants in PPARG View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

Amit R. Majithia, Ben Tsuda, Maura Agostini, Keerthana Gnanapradeepan, Robert Rice, Gina Peloso, Kashyap A. Patel, Xiaolan Zhang, Marjoleine F. Broekema, Nick Patterson, Marc Duby, Ted Sharpe, Eric Kalkhoven, Evan D. Rosen, Inês Barroso, Sian Ellard, , Sekar Kathiresan, , Stephen O’Rahilly, , Krishna Chatterjee, Jose C. Florez, Tarjei Mikkelsen, David B. Savage, David Altshuler

ABSTRACT

Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty. For example, mutations in PPARG cause Mendelian lipodystrophy and increase risk of type 2 diabetes (T2D). Although approximately 1 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. 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. More... »

PAGES

1570-1575

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ng.3700

DOI

http://dx.doi.org/10.1038/ng.3700

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1028783527

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27749844


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