利用病例对照数据进行罕见序列变异临床分类的似然比方法:应用于BRCA1和BRCA2

IF 3.3 2区 医学 Q2 GENETICS & HEREDITY
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
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引用次数: 0

摘要

通过临床基因检测发现的大量疾病易感基因变异具有不确定的意义(VUS)。根据美国医学遗传学和基因组学学院(ACMG)和分子病理学协会(AMP)的建议,病例对照数据集中的频率(PS4标准)可以为其解释提供依据。我们提出了一种新的基于病例对照似然比的方法,该方法结合了基因特异性年龄相关外显率。我们演示了该方法在模拟和真实数据集分析中的实用性。在模拟数据的分析中,似然比方法比其他方法更强大。对来自乳腺癌协会协会(BCAC)的BRCA1和BRCA2变异病例对照数据集计算似然比,并与logistic回归结果进行比较。大量的变异得到了有利于致病性的证据,而大量的变异有不利于致病性的证据——这些发现是使用其他病例对照分析方法无法得到的。与传统的病例对照方法相比,我们的新方法对罕见变异的分类能力更强。作为ENIGMA分析工作组的一项倡议,我们提供了用户友好的脚本和预格式化的Excel计算器,用于实现BRCA1, BRCA2和其他已知外显率的高风险基因的罕见变异方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Likelihood Ratio Approach for Utilizing Case-Control Data in the Clinical Classification of Rare Sequence Variants: Application to BRCA1 and BRCA2
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.
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来源期刊
Human Mutation
Human Mutation 医学-遗传学
CiteScore
8.40
自引率
5.10%
发文量
190
审稿时长
2 months
期刊介绍: Human Mutation is a peer-reviewed journal that offers publication of original Research Articles, Methods, Mutation Updates, Reviews, Database Articles, Rapid Communications, and Letters on broad aspects of mutation research in humans. Reports of novel DNA variations and their phenotypic consequences, reports of SNPs demonstrated as valuable for genomic analysis, descriptions of new molecular detection methods, and novel approaches to clinical diagnosis are welcomed. Novel reports of gene organization at the genomic level, reported in the context of mutation investigation, may be considered. The journal provides a unique forum for the exchange of ideas, methods, and applications of interest to molecular, human, and medical geneticists in academic, industrial, and clinical research settings worldwide.
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