| Autor: |
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 D, Barroso, Inês, Ellard, Sian, UK Monogenic Diabetes Consortium, Kathiresan, Sekar, Myocardial Infarction Genetics Consortium, O'Rahilly, Stephen, UK Congenital Lipodystrophy Consortium, Chatterjee, Krishna, Florez, Jose C, Mikkelsen, Tarjei, Savage, David B, Altshuler, David |
| Přispěvatelé: |
Barroso, Ines [0000-0001-5800-4520], O'Rahilly, Stephen [0000-0003-2199-4449], Chatterjee, Krishna [0000-0002-2654-8854], Savage, David [0000-0002-7857-7032], Apollo - University of Cambridge Repository |
| Jazyk: |
angličtina |
| Rok vydání: |
2016 |
| Předmět: |
|
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
