{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T15:25:04Z","timestamp":1784647504146,"version":"3.55.0"},"reference-count":39,"publisher":"American Physiological Society","issue":"8","funder":[{"DOI":"10.13039\/100019687","name":"Hamad Bin Khalifa University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100019687","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.physiology.org"],"crossmark-restriction":true},"short-container-title":["Physiological Genomics"],"published-print":{"date-parts":[[2023,8,1]]},"abstract":"<jats:p> Identification of novel BRCA1 variants outpaces their clinical annotation which highlights the importance of developing accurate computational methods for risk assessment. Therefore our aim was to develop a BRCA1-specific machine learning model to predict the pathogenicity of all types of BRCA1 variants and to apply this model and our previous BRCA2-specific model to assess BRCA variants of uncertain significance (VUS) among Qatari patients with breast cancer. We developed an XGBoost model that utilizes variant information such as position frequency and consequence as well as prediction scores from numerous in silico tools. We trained and tested the model with BRCA1 variants that were reviewed and classified by the Evidence-Based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium. In addition we tested the model\u2019s performance on an independent set of missense variants of uncertain significance with experimentally determined functional scores. The model performed excellently in predicting the pathogenicity of ENIGMA-classified variants (accuracy: 99.9%) and in predicting the functional consequence of the independent set of missense variants (accuracy: 93.4%). Moreover it predicted 2 115 potentially pathogenic variants among the 31 058 unreviewed BRCA1 variants in the BRCA exchange database. Using two BRCA-specific models we did not identify any pathogenic BRCA1 variants among those found in patients in Qatar but predicted four potentially pathogenic BRCA2 variants, which could be prioritized for functional validation. <\/jats:p>","DOI":"10.1152\/physiolgenomics.00033.2023","type":"journal-article","created":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T12:09:26Z","timestamp":1687176566000},"page":"315-323","update-policy":"https:\/\/doi.org\/10.1152\/aps-crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["<i>BRCA1<\/i>-specific machine learning model predicts variant pathogenicity with high accuracy"],"prefix":"10.1152","volume":"55","author":[{"given":"Mohannad","family":"Khandakji","sequence":"first","affiliation":[{"name":"Division of Genomics and Translational Biomedicine, College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar"},{"name":"Hamad Dental Center, Hamad Medical Corporation, Doha, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hind Hassan Ahmed","family":"Habish","sequence":"additional","affiliation":[{"name":"National Center for Cancer Care and Research, Hamad Medical Corporation, Doha, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nawal Bakheet Salem","family":"Abdulla","sequence":"additional","affiliation":[{"name":"National Center for Cancer Care and Research, Hamad Medical Corporation, Doha, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sitti Apsa Albani","family":"Kusasi","sequence":"additional","affiliation":[{"name":"National Center for Cancer Care and Research, Hamad Medical Corporation, Doha, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nema Mahmoud Ghobashy","family":"Abdou","sequence":"additional","affiliation":[{"name":"National Center for Cancer Care and Research, Hamad Medical Corporation, Doha, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hajer Mahmoud M. A.","family":"Al-Mulla","sequence":"additional","affiliation":[{"name":"National Center for Cancer Care and Research, Hamad Medical Corporation, Doha, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reem Jawad A. A.","family":"Al Sulaiman","sequence":"additional","affiliation":[{"name":"National Center for Cancer Care and Research, Hamad Medical Corporation, Doha, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Salha M.","family":"Bu Jassoum","sequence":"additional","affiliation":[{"name":"National Center for Cancer Care and Research, Hamad Medical Corporation, Doha, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3429-3094","authenticated-orcid":false,"given":"Borbala","family":"Mifsud","sequence":"additional","affiliation":[{"name":"Division of Genomics and Translational Biomedicine, College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar"},{"name":"William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"24","reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1349-7006.2004.tb02195.x"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1016\/s1097-2765(00)80276-2"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1093\/carcin\/bgq069"},{"key":"B4","volume-title":"GeneReviews","author":"Petrucelli N","year":"1993"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1086\/375033"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2007.55-a"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1136\/jmedgenet-2013-101974"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2005.03.6772"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1086\/301749"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1415979111"},{"key":"B11","first-page":"741","volume":"8","author":"Hopper JL","year":"1999","journal-title":"Cancer Epidemiol Biomarkers Prev"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1158\/1078-0432.CCR-07-4436"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2407-8-155"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2017.7112"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.3390\/cancers13092192"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1054\/bjoc.2000.1407"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1186\/s13073-019-0691-1"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1097\/01.gim.0000151155.36470.ff"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2018.2140"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1002\/mgg3.534"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.5281\/zenodo.1040670"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.4172\/1948-5956.1000442"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1093\/annonc\/mdv278"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-018-4986-5"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1038\/gim.2015.30"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1002\/humu.21628"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1002\/humu.21627"},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2016.03.024"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.1038\/s41523-020-0159-x"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-016-0974-4"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.1002\/humu.21517"},{"key":"B34","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2022.982930"},{"key":"B35","doi-asserted-by":"crossref","unstructured":"Chen T, Guestrin C. Xgboost: a scalable tree boosting system. KDD \u203216: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Francisco, CA, August 2016, p. 785\u2013794. doi:10.1145\/2939672.2939785.","DOI":"10.1145\/2939672.2939785"},{"key":"B36","doi-asserted-by":"publisher","DOI":"10.1158\/1078-0432.CCR-20-0255"},{"key":"B37","doi-asserted-by":"publisher","DOI":"10.1038\/s41436-019-0740-6"},{"key":"B38","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti1109"},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.1038\/s41436-018-0018-4"},{"key":"B40","doi-asserted-by":"publisher","DOI":"10.1007\/s12282-019-00951-w"},{"key":"B41","doi-asserted-by":"publisher","DOI":"10.3802\/jgo.2020.31.e83"}],"container-title":["Physiological Genomics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.physiology.org\/doi\/pdf\/10.1152\/physiolgenomics.00033.2023","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,18]],"date-time":"2023-07-18T15:14:17Z","timestamp":1689693257000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.physiology.org\/doi\/10.1152\/physiolgenomics.00033.2023"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,1]]},"references-count":39,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2023,8,1]]}},"alternative-id":["10.1152\/physiolgenomics.00033.2023"],"URL":"https:\/\/doi.org\/10.1152\/physiolgenomics.00033.2023","relation":{},"ISSN":["1094-8341","1531-2267"],"issn-type":[{"value":"1094-8341","type":"print"},{"value":"1531-2267","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,1]]},"assertion":[{"value":"2023-04-18","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-05-22","order":1,"name":"revised","label":"Revised","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-06-09","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-07-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}