Maria Zanti, Denise G. O'Mahony, Michael T. Parsons, Hongyan Li, Joe Dennis, Kristiina Aittomäkkiki, Irene L. Andrulis, Hoda Anton-Culver, Kristan J. Aronson, Annelie Augustinsson, Heiko Becher, Stig E. Bojesen, Manjeet K. Bolla, Hermann Brenner, Melissa A. Brown, Saundra S. Buys, Federico Canzian, Sandrine M. Caputo, Jose E. Castelao, Jenny Chang-Claude, None GC-HBOC study Collaborators, Kamila Czene, Mary B. Daly, Arcangela De Nicolo, Peter Devilee, Thilo Dörk, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Christoph Engel, D. Gareth Evans, Peter A. Fasching, Manuela Gago-Dominguez, Montserrat García-Closas, José A. García-Sáenz, Aleksandra Gentry-Maharaj, Willemina R. R. Geurts - Giele, Graham G. Giles, Gord Glendon, Mark S. Goldberg, Encarna B. Gómez Garcia, Melanie Güendert, Pascal Guénel, Eric Hahnen, Christopher A. Haiman, Per Hall, Ute Hamann, Elaine F. Harkness, Frans B. L. Hogervorst, Antoinette Hollestelle, Reiner Hoppe, John L. Hopper, Claude Houdayer, Richard S. Houlston, Anthony Howell, None ABCTB Investigators, Milena Jakimovska, Anna Jakubowska, Helena Jernström, Esther M. John, Rudolf Kaaks, Cari M. Kitahara, Stella Koutros, Peter Kraft, Vessela N. Kristensen, James V. Lacey, Diether Lambrechts, Melanie Léoné, Annika Lindblom, Jan Lubiński, Michael Lush, Arto Mannermaa, Mehdi Manoochehri, Siranoush Manoukian, Sara Margolin, Maria Elena Martinez, Usha Menon, Roger L. Milne, Alvaro N. Monteiro, Rachel A. Murphy, Susan L. Neuhausen, Heli Nevanlinna, William G. Newman, Kenneth Offit, Sue K. Park, Paul James, Paolo Peterlongo, Julian Peto, Dijana Plaseska-Karanfilska, Kevin Punie, Paolo Radice, Muhammad U. Rashid, Gad Rennert, Atocha Romero, Efraim H. Rosenberg, Emmanouil Saloustros, Dale P. Sandler, Marjanka K. Schmidt, Rita K. Schmutzler, Xiao-Ou Shu
{"title":"A Likelihood Ratio Approach for Utilizing Case-Control Data in the Clinical Classification of Rare Sequence Variants: Application to BRCA1 and BRCA2","authors":"Maria Zanti, Denise G. O'Mahony, Michael T. Parsons, Hongyan Li, Joe Dennis, Kristiina Aittomäkkiki, Irene L. Andrulis, Hoda Anton-Culver, Kristan J. Aronson, Annelie Augustinsson, Heiko Becher, Stig E. Bojesen, Manjeet K. Bolla, Hermann Brenner, Melissa A. Brown, Saundra S. Buys, Federico Canzian, Sandrine M. Caputo, Jose E. Castelao, Jenny Chang-Claude, None GC-HBOC study Collaborators, Kamila Czene, Mary B. Daly, Arcangela De Nicolo, Peter Devilee, Thilo Dörk, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Christoph Engel, D. Gareth Evans, Peter A. Fasching, Manuela Gago-Dominguez, Montserrat García-Closas, José A. García-Sáenz, Aleksandra Gentry-Maharaj, Willemina R. R. Geurts - Giele, Graham G. Giles, Gord Glendon, Mark S. Goldberg, Encarna B. Gómez Garcia, Melanie Güendert, Pascal Guénel, Eric Hahnen, Christopher A. Haiman, Per Hall, Ute Hamann, Elaine F. Harkness, Frans B. L. Hogervorst, Antoinette Hollestelle, Reiner Hoppe, John L. Hopper, Claude Houdayer, Richard S. Houlston, Anthony Howell, None ABCTB Investigators, Milena Jakimovska, Anna Jakubowska, Helena Jernström, Esther M. John, Rudolf Kaaks, Cari M. Kitahara, Stella Koutros, Peter Kraft, Vessela N. Kristensen, James V. Lacey, Diether Lambrechts, Melanie Léoné, Annika Lindblom, Jan Lubiński, Michael Lush, Arto Mannermaa, Mehdi Manoochehri, Siranoush Manoukian, Sara Margolin, Maria Elena Martinez, Usha Menon, Roger L. Milne, Alvaro N. Monteiro, Rachel A. Murphy, Susan L. Neuhausen, Heli Nevanlinna, William G. Newman, Kenneth Offit, Sue K. Park, Paul James, Paolo Peterlongo, Julian Peto, Dijana Plaseska-Karanfilska, Kevin Punie, Paolo Radice, Muhammad U. Rashid, Gad Rennert, Atocha Romero, Efraim H. Rosenberg, Emmanouil Saloustros, Dale P. Sandler, Marjanka K. Schmidt, Rita K. Schmutzler, Xiao-Ou Shu","doi":"10.1155/2023/9961341","DOIUrl":null,"url":null,"abstract":"A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity—findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2023/9961341","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity—findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.