Clinical Variant Reclassification in Hereditary Disease Genetic Testing.

IF 10.5 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Yuya Kobayashi, Elaine Chen, Flavia M Facio, Hillery Metz, Sarah R Poll, Dan Swartzlander, Britt Johnson, Swaroop Aradhya
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引用次数: 0

Abstract

Importance: Because accurate and consistent classification of DNA sequence variants is fundamental to germline genetic testing, understanding patterns of initial variant classification (VC) and subsequent reclassification from large-scale, empirical data can help improve VC methods, promote equity among race, ethnicity, and ancestry (REA) groups, and provide insights to inform clinical practice.

Objectives: To measure the degree to which initial VCs met certainty thresholds set by professional guidelines and quantify the rates of, the factors associated with, and the impact of reclassification among more than 2 million variants.

Design, setting, and participants: This cohort study used clinical multigene panel and exome sequencing data from diagnostic testing for hereditary disorders, carrier screening, or preventive genetic screening from individuals for whom genetic testing was performed between January 1, 2015, and June 30, 2023.

Exposure: DNA variants were classified into 1 of 5 categories: benign, likely benign, variant of uncertain significance (VUS), likely pathogenic, or pathogenic.

Main outcomes and measures: The main outcomes were accuracy of classifications, rates and directions of reclassifications, evidence contributing to reclassifications, and their impact across different clinical areas and REA groups. One-way analysis of variance followed by post hoc pairwise Tukey honest significant difference tests were used to analyze differences among means, and pairwise Pearson χ2 tests with Bonferroni corrections were used to compare categorical variables among groups.

Results: The cohort comprised 3 272 035 individuals (median [range] age, 44 [0-89] years; 2 240 506 female [68.47%] and 1 030 729 male [31.50%]; 216 752 Black [6.62%]; 336 414 Hispanic [10.28%]; 1 804 273 White [55.14%]). Among 2 051 736 variants observed over 8 years in this cohort, 94 453 (4.60%) were reclassified. Some variants were reclassified more than once, resulting in 105 172 total reclassification events. The majority (64 752 events [61.65%]) were changes from VUS to either likely benign, benign, likely pathogenic, or pathogenic categories. An additional 37.66% of reclassifications (39 608 events) were gains in classification certainty to terminal categories (ie, likely benign to benign and likely pathogenic to pathogenic). Only a small fraction (663 events [0.63%]) moved toward less certainty, or very rarely (61 events [0.06%]) were classification reversals. When normalized by the number of individuals tested, VUS reclassification rates were higher among specific underrepresented REA populations (Ashkenazi Jewish, Asian, Black, Hispanic, Pacific Islander, and Sephardic Jewish). Approximately one-half of VUS reclassifications (37 074 of 64 840 events [57.18%]) resulted from improved use of data from computational modeling.

Conclusions and relevance: In this cohort study of individuals undergoing genetic testing, the empirically estimated accuracy of pathogenic, likely pathogenic, benign, and likely benign classifications exceeded the certainty thresholds set by current VC guidelines, suggesting the need to reevaluate definitions of these classifications. The relative contribution of various strategies to resolve VUS, including emerging machine learning-based computational methods, RNA analysis, and cascade family testing, provides useful insights that can be applied toward further improving VC methods, reducing the rate of VUS, and generating more definitive results for patients.

遗传病基因检测中的临床变异重新分类。
重要性:由于对 DNA 序列变异体进行准确一致的分类是种系遗传检测的基础,因此从大规模实证数据中了解初始变异体分类(VC)和后续重新分类的模式有助于改进 VC 方法,促进种族、民族和祖先(REA)群体之间的公平,并为临床实践提供启示:测量初始变异分类符合专业指南设定的确定性阈值的程度,并量化 200 多万个变异的重新分类率、相关因素及其影响:这项队列研究使用了临床多基因面板和外显子组测序数据,这些数据来自 2015 年 1 月 1 日至 2023 年 6 月 30 日期间进行基因检测的遗传性疾病诊断检测、携带者筛查或预防性基因筛查的个体:DNA变异分为5类中的一类:良性、可能良性、意义不确定的变异(VUS)、可能致病或致病:主要结果是分类的准确性、重新分类的比率和方向、导致重新分类的证据及其对不同临床领域和 REA 组的影响。采用单因素方差分析和Tukey事后成对显著性差异检验来分析平均值之间的差异,采用成对Pearson χ2检验和Bonferroni校正来比较组间的分类变量:组群包括 3 272 035 人(中位数[范围]年龄,44 [0-89] 岁;2 240 506 名女性[68.47%]和 1 030 729 名男性[31.50%];216 752 名黑人[6.62%];336 414 名西班牙裔[10.28%];1 804 273 名白人[55.14%])。在该队列 8 年中观察到的 2 051 736 个变异中,94 453 个(4.60%)被重新分类。有些变异体被重新分类了不止一次,因此总共发生了 105 172 次重新分类事件。其中大部分(64 752 例 [61.65%])是从 VUS 变为可能良性、良性、可能致病或致病类别。另有 37.66% 的重新分类(39 608 例)是将分类确定性提高到终末类别(即从可能良性变为良性,从可能致病变为致病)。只有一小部分(663 次[0.63%])的分类确定性降低,或极少数(61 次[0.06%])的分类颠倒。如果按受检人数进行归一化处理,在代表性不足的特定 REA 群体(阿什肯纳兹犹太人、亚裔、黑人、西班牙裔、太平洋岛民和塞法迪犹太人)中,VUS 重新分类率较高。约有二分之一的 VUS 重新分类(64 840 例事件中的 37 074 例[57.18%])是由于更好地利用了计算建模的数据:在这项对接受基因检测的个体进行的队列研究中,根据经验估计的致病、可能致病、良性和可能良性分类的准确性超过了现行 VC 指南设定的确定性阈值,这表明有必要重新评估这些分类的定义。解决 VUS 问题的各种策略(包括基于机器学习的新兴计算方法、RNA 分析和级联家族检测)的相对贡献提供了有用的见解,可用于进一步改进 VC 方法、降低 VUS 发生率并为患者提供更明确的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JAMA Network Open
JAMA Network Open Medicine-General Medicine
CiteScore
16.00
自引率
2.90%
发文量
2126
审稿时长
16 weeks
期刊介绍: JAMA Network Open, a member of the esteemed JAMA Network, stands as an international, peer-reviewed, open-access general medical journal.The publication is dedicated to disseminating research across various health disciplines and countries, encompassing clinical care, innovation in health care, health policy, and global health. JAMA Network Open caters to clinicians, investigators, and policymakers, providing a platform for valuable insights and advancements in the medical field. As part of the JAMA Network, a consortium of peer-reviewed general medical and specialty publications, JAMA Network Open contributes to the collective knowledge and understanding within the medical community.
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