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一种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:在 和 中的应用。

A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants: application to and .

机构信息

Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.

Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.

出版信息

Hum Mutat. 2023;2023. doi: 10.1155/2023/9961341. Epub 2023 Sep 14.

DOI:10.1155/2023/9961341
PMID:38725546
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11080979/
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 analyses of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of and 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 to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in , and other high-risk genes with known penetrance.

摘要

通过临床遗传检测在疾病易感性基因中鉴定出大量的变体,其意义不确定(VUS)。根据美国医学遗传学与基因组学学院(ACMG)和分子病理学协会(AMP)的建议,病例对照数据集(PS4 标准)中的频率可以为其解释提供信息。我们提出了一种新的基于病例对照似然比的方法,该方法纳入了基因特异性年龄相关外显率。我们在模拟和真实数据集的分析中展示了该方法的实用性。在模拟数据分析中,似然比方法比其他方法更有效。为了分析,我们计算了来自乳腺癌协会联盟(BCAC)的病例对照数据集的似然比和 个变体,与逻辑回归结果进行了比较。更多的变体达到了支持致病性的证据,大量的变体有证据反对致病性——如果使用其他病例对照分析方法,这些结果将无法得到。与传统的病例对照方法相比,我们的新方法为分类罕见变体提供了更大的能力。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,用于在 和其他具有已知外显率的高危基因中实现该方法对罕见变体的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb3/11919184/d7be50cfcf2f/HUMU2023-9961341.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb3/11919184/53edde3dbd74/HUMU2023-9961341.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb3/11919184/d7be50cfcf2f/HUMU2023-9961341.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb3/11919184/53edde3dbd74/HUMU2023-9961341.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecb3/11919184/d7be50cfcf2f/HUMU2023-9961341.002.jpg

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