Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction.
Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction.
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DOI：
10.1016/j.ajhg.2022.09.006
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发表时间：
2022-10-06
影响因子：
9.8
通讯作者：
中科院分区：
文献类型：
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已知的乳腺癌易感基因中的罕见致病性变异和已知的常见易感性变异不能完全解释乳腺癌的家族聚集性。为了研究残余家族聚集的合理遗传模型，我们研究了通过基于人群的先证者确定的17，425个家庭，其中86%通过基因组测序筛查BRCA 1，BRCA 2，PALB 2，CHEK 2，ATM和TP 53的致病性变体。我们进行了复杂的分离分析，并拟合遗传模型，其中乳腺癌的发病率取决于已知的易感基因和其他未识别的主基因和正态分布的多基因成分的影响。在20-29岁年龄段，由这6个基因解释的家族变异比例为46%，此后随年龄的增长而稳步下降。考虑这些基因后，剩余家族方差的最佳拟合模型包括一个隐性风险成分，其组合基因型频率为1.7%（95%CI：0.3%-5.4%），80岁的患病率为69%（95%CI：38%-95%），这可能反映了多个变异体以隐性方式起作用的联合效应，多基因方差为1.27（95%CI：0.94%-1.65），不随年龄变化。在20-29岁时，隐性风险成分解释的剩余家族方差的比例为40%，此后随年龄的增长而下降。该模型预测的年龄特异性家族相对风险与大型流行病学研究观察到的一致。这一发现对识别新的乳腺癌易感基因和改善疾病风险预测的策略具有重要意义，特别是在年轻时。一项基于人群的大型家族研究，采用基因组测序数据，研究了在考虑已知易感基因后解释残留乳腺癌家族聚集的遗传模型。这些结果可能对识别新的乳腺癌易感基因和改善疾病风险预测的策略有影响，特别是在年轻时。
Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20–29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%–5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%–95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%–1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20–29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age. A large population-based family study, with gene-panel sequencing data, investigated the genetic models that explain the residual breast cancer familial aggregation after considering known susceptibility genes. The results may have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.
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DOI：
10.1016/s1470-2045(21)00580-5
发表时间：
2021-12
期刊：
The Lancet. Oncology
影响因子：
--
作者：
de Andrade KC;Khincha PP;Hatton JN;Frone MN;Wegman-Ostrosky T;Mai PL;Best AF;Savage SA
通讯作者：
Savage SA
影响因子：
120.7
作者：
Kuchenbaecker, Karoline B.;Hopper, John L.;Antoniou, Antonis C.
通讯作者：
Antoniou, Antonis C.
影响因子：
8.8
作者：
通讯作者：
--
影响因子：
8.8
作者：
Antoniou, A. C.;Cunningham, A. P.;Peto, J.;Evans, D. G.;Lalloo, F.;Narod, S. A.;Risch, H. A.;Eyfjord, J. E.;Hopper, J. L.;Southey, M. C.;Olsson, H.;Johannsson, O.;Borg, A.;Passini, B.;Radice, P.;Manoukian, S.;Eccles, D. M.;Tang, N.;Olah, E.;Anton-Culver, H.;Warner, E.;Lubinski, J.;Gronwald, J.;Gorski, B.;Tryggvadottir, L.;Syrjakoski, K.;Kallioniemi, O-P;Eerola, H.;Nevanlinna, H.;Pharoah, P. D. P.;Easton, D. F.
通讯作者：
Easton, D. F.
影响因子：
9.8
作者：
Cui, JS;Antoniou, AC;Hopper, JL
通讯作者：
Hopper, JL