Development and validation of genome-wide polygenic risk scores for predicting breast cancer incidence in Japanese females: a population-based case-cohort study
Development and validation of genome-wide polygenic risk scores for predicting breast cancer incidence in Japanese females: a population-based case-cohort study
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用于预测日本女性乳腺癌发病率的全基因组多基因风险评分的开发和验证：基于人群的病例队列研究
DOI：
10.1007/s10549-022-06843-6
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发表时间：
2022
影响因子：
3.8
通讯作者：
for the Japan Public Health Center-based Prospective
中科院分区：
文献类型：
--
作者：
Ohbe Hiroyuki;Hachiya Tsuyoshi;Yamaji Taiki;Nakano Shiori;Miyamoto Yoshihisa;Sutoh Yoichi;Otsuka-Yamasaki Yayoi;Shimizu Atsushi;Yasunaga Hideo;Sawada Norie;Inoue Manami;Tsugane Shoichiro;Iwasaki Motoki;for the Japan Public Health Center-based Prospective
本研究旨在建立预测日本女性乳腺癌事件的祖先特异性多基因风险评分(PRSS)，并在纵向队列研究中对其进行验证。方法使用公开的日本和欧洲女性乳腺癌全基因组关联研究的汇总统计数据，分别使用修剪和阈值(P + T)和不同参数的LDpred方法开发了31个候选的全基因组风险评分(PRSS)。在候选的PRS模型中，根据Harrell的C-统计量的最大预测能力，使用病例队列数据集(63例乳腺癌病例和2213名日本女性亚队列，平均随访11.9年)选择了最佳模型。在另一个独立的病例队列数据集中(260例乳腺癌病例和7,845个日本女性亚群，平均随访16.9年)，对每个衍生的GWA的最佳PR进行了评估。结果对于涉及46,861个单核苷酸多态(SNP；P + T方法，PT= 0.05，R2= 0.2)的最佳PR模型，在评估数据集中，Harrell的C统计量为0.598 ± 0.018。与最低的女性相比，年龄调整后的乳腺癌风险比是2.47(95%可信区间，1.64-3.70)。与使用欧洲血统的GWA相比，使用日本血统的GWA构建的乳腺癌预测模型对日本女性乳腺癌的预测效果更好(哈瑞尔的C-统计量为0.598比0.586)。结论本研究开发了日本女性的乳腺癌预测模型，并证明了该模型在乳腺癌风险分层中的有效性。
PurposeThis study aimed to develop an ancestry-specific polygenic risk scores (PRSs) for the prediction of breast cancer events in Japanese females and validate it in a longitudinal cohort study.MethodsUsing publicly available summary statistics of female breast cancer genome-wide association study (GWAS) of Japanese and European ancestries, we, respectively, developed 31 candidate genome-wide PRSs using pruning and thresholding (P + T) and LDpred methods with varying parameters. Among the candidate PRS models, the best model was selected using a case-cohort dataset (63 breast cancer cases and 2213 sub-cohorts of Japanese females during a median follow-up of 11.9 years) according to the maximal predictive ability by Harrell’s C-statistics. The best-performing PRS for each derivation GWAS was evaluated in another independent case-cohort dataset (260 breast cancer cases and 7845 sub-cohorts of Japanese females during a median follow-up of 16.9 years).ResultsFor the best PRS model involving 46,861 single nucleotide polymorphisms (SNPs; P + T method withPT= 0.05 andR2= 0.2) derived from Japanese-ancestry GWAS, the Harrell’s C-statistic was 0.598 ± 0.018 in the evaluation dataset. The age-adjusted hazard ratio for breast cancer in females with the highest PRS quintile compared with those in the lowest PRS quintile was 2.47 (95% confidence intervals, 1.64–3.70). The PRS constructed using Japanese-ancestry GWAS demonstrated better predictive performance for breast cancer in Japanese females than that using European-ancestry GWAS (Harrell’s C-statistics 0.598 versus 0.586).ConclusionThis study developed a breast cancer PRS for Japanese females and demonstrated the usefulness of the PRS for breast cancer risk stratification.
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影响因子：
30.8
作者：
Bulik-Sullivan, Brendan K.;Loh, Po-Ru;Finucane, Hilary K.;Ripke, Stephan;Yang, Jian;Patterson, Nick;Daly, Mark J.;Price, Alkes L.;Neale, Benjamin M.
通讯作者：
Neale, Benjamin M.
影响因子：
10.3
作者：
Shieh, Yiwey;Eklund, Martin;Tice, Jeffrey A.
通讯作者：
Tice, Jeffrey A.
影响因子：
10.3
作者：
Vachon, Celine M.;Pankratz, V. Shane;Couch, Fergus J.
通讯作者：
Couch, Fergus J.
影响因子：
3.8
作者：
Hsieh, Yi-Chen;Tu, Shih-Hsin;Chiou, Hung-Yi
通讯作者：
Chiou, Hung-Yi
影响因子：
9.8
作者：
Sham, PC;Cherny, SS;Hewitt, JK
通讯作者：
Hewitt, JK