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利用1029名健康个体的全基因组数据了解印度遗传性乳腺癌的遗传流行病学。

Understanding the genetic epidemiology of hereditary breast cancer in India using whole genome data from 1029 healthy individuals.

作者信息

Vatsyayan Aastha, Mathur Prerika, Bhoyar Rahul C, Imran Mohamed, Senthivel Vigneshwar, Divakar Mohit Kumar, Mishra Anushree, Jolly Bani, Sivasubbu Sridhar, Scaria Vinod

机构信息

CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) Mathura Road, Delhi, 110025, India.

Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.

出版信息

Cancer Causes Control. 2025 Jul;36(7):673-682. doi: 10.1007/s10552-025-01974-9. Epub 2025 Mar 1.

DOI:10.1007/s10552-025-01974-9
PMID:40024972
Abstract

Breast cancer is the most highly reported cancer in India. Genetic testing could help tackle the increasing cancer burden by enabling carriers obtain early diagnosis through increased surveillance, and help guide treatment. However, accurate interpretation of variant pathogenicity must be established in a population-specific manner to ensure effective use of genetic testing. Here we query IndiGen data obtained from sequencing 1029 Indian individuals, and perform variant classification of all reported BRCA variants using gold-standard ACMG & AMP guidelines to establish disease epidemiology. To address the high number of VUS variants thus obtained, we further utilize the brca-NOVUS ML tool to obtain pathogenicity predictions in a manner close to ACMG guidelines at scale. Through the manual application of ACMG & AMP guidelines, we determined the genetic prevalence to be the following: 1 in 342 carriers of BRCA1, and 1 in 256 carriers of BRCA2 pathogenic/likely pathogenic variants bear a significant lifetime risk of developing breast / ovarian cancer in India. The high population prevalence and unique variant landscape emphasizes a need for population-scale studies of causative variants to enable effective screening. We advise cautious clinical interpretation, given incomplete penetrance and other complex factors that result in cancer disease. To the best of our knowledge, this is the first and most comprehensive population-scale genetic epidemiological study of BRCA-linked breast cancer variants reported from India.

摘要

乳腺癌是印度报告率最高的癌症。基因检测可以通过让携带者通过加强监测获得早期诊断,帮助应对不断增加的癌症负担,并有助于指导治疗。然而,必须以特定人群的方式建立对变异致病性的准确解读,以确保有效利用基因检测。在这里,我们查询了对1029名印度个体进行测序获得的IndiGen数据,并使用金标准的美国医学遗传学与基因组学学会(ACMG)和美国分子病理学会(AMP)指南对所有报告的BRCA变异进行变异分类,以确定疾病流行病学。为了解决由此获得的大量意义未明的变异(VUS),我们进一步利用brca-NOVUS机器学习工具大规模地以接近ACMG指南的方式获得致病性预测。通过手动应用ACMG和AMP指南,我们确定了印度的遗传患病率如下:每342名BRCA1携带者中有1人,每256名BRCA2致病性/可能致病性变异携带者中有1人在一生中患乳腺癌/卵巢癌的风险显著。高人群患病率和独特的变异情况强调了对致病变异进行人群规模研究以实现有效筛查的必要性。鉴于不完全外显率和导致癌症疾病的其他复杂因素,我们建议谨慎进行临床解读。据我们所知,这是印度首次也是最全面的关于BRCA相关乳腺癌变异的人群规模遗传流行病学研究。

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Asian Pac J Cancer Prev. 2024 Dec 1;25(12):4145-4151. doi: 10.31557/APJCP.2024.25.12.4145.
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WilsonGenAI a deep learning approach to classify pathogenic variants in Wilson Disease.WilsonGenAI:一种深度学习方法,用于分类肝豆状核变性中的致病性变异。
PLoS One. 2024 May 17;19(5):e0303787. doi: 10.1371/journal.pone.0303787. eCollection 2024.
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Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.
2022 年全球癌症统计数据:全球 185 个国家和地区 36 种癌症的发病率和死亡率全球估计数。
CA Cancer J Clin. 2024 May-Jun;74(3):229-263. doi: 10.3322/caac.21834. Epub 2024 Apr 4.
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Hereditary Cancer Syndromes: A Comprehensive Review with a Visual Tool.遗传性癌症综合征:全面综述及可视化工具
Genes (Basel). 2023 Apr 30;14(5):1025. doi: 10.3390/genes14051025.
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Cancer incidence estimates for 2022 & projection for 2025: Result from National Cancer Registry Programme, India.2022 年癌症发病估计数及 2025 年预测:印度国家癌症登记计划的结果。
Indian J Med Res. 2022 Oct-Nov;156(4&5):598-607. doi: 10.4103/ijmr.ijmr_1821_22.
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A database of 5305 healthy Korean individuals reveals genetic and clinical implications for an East Asian population.一个包含 5305 名健康韩国个体的数据库揭示了东亚人群的遗传和临床意义。
Exp Mol Med. 2022 Nov;54(11):1862-1871. doi: 10.1038/s12276-022-00871-4. Epub 2022 Nov 2.
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NAR Genom Bioinform. 2022 Feb 8;4(1):lqac005. doi: 10.1093/nargab/lqac005. eCollection 2022 Mar.
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