发现与ARIC绝经后妇女乳腺癌发病率相关的血浆蛋白

Maria-Eleni Syleouni, Corinne E Joshu, Josef Coresh, Marc J Gunter, Kenneth R Butler, David J Couper, Marcela Guevara, Jiayun Lu, Anna Prizment, Elio Riboli, Meng Ru, Yahya Mahamat Saleh, Karl Smith-Byrne, Mehrnoosh Soori, Kala Visvanathan, Vernon A Burk, Ziqiao Wang, Nilanjan Chatterjee, Sabine Rohrmann, Elizabeth A Platz
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We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox regression adjusting for risk factors, and applied the Benjamini-Hochberg method to control false discovery. We determined whether the statistically significant proteins were confirmed in a case-cohort study within the European Prospective Investigation into Cancer and Nutrition (EPIC). Results After median follow-up of 23.3 years, 340 of 4,403 women had an incident breast cancer. Two proteins were statistically significantly associated after p-value adjustment per doubling, the HR of breast cancer was 1.45 (95% CI: 1.23-1.70, p = 7.47*10−6, padjusted=0.0370) for protein LEG1 homolog and 2.52 (95% CI: 1.66-3.83, p = 1.50*10−5, padjusted=0.0371) for ADP-dependent glucokinase. Results were consistent in a lagged analysis and among both Black (28.1%) and White women. 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摘要

血浆蛋白质组学数据可用于发现乳腺癌危险因素之外的生物标志物。需要在不同人群中使用大规模平台进行发现。方法:在社区动脉粥样硬化风险研究中,我们对绝经后妇女的4712种血浆蛋白和乳腺癌风险进行了前瞻性队列分析。用SomaScan®5K法测定蛋白质含量。病例主要从州癌症登记处确定。我们使用Cox回归对风险因素进行校正,估计风险比(hr)和95%置信区间(ci),并应用Benjamini-Hochberg方法控制错误发现。我们在欧洲癌症与营养前瞻性调查(EPIC)的一项病例队列研究中确定了这些具有统计学意义的蛋白质是否得到证实。结果中位随访23.3年后,4403名女性中有340人发生了乳腺癌。经p值调整后,两种蛋白的乳腺癌风险比均有统计学意义,LEG1同源蛋白的乳腺癌风险比为1.45 (95% CI: 1.23-1.70, p = 7.47*10−6,p校正=0.0370),adp依赖性葡萄糖激酶的乳腺癌风险比为2.52 (95% CI: 1.66-3.83, p = 1.50*10−5,p校正=0.0371)。在滞后分析中,黑人(28.1%)和白人女性的结果是一致的。在EPIC中,两种关联均得到证实(蛋白LEG1同源物,HR = 1.24, 95% CI 1.14-1.35, p = 9.79*10−7,adp依赖性葡萄糖激酶,HR = 1.13, 95% CI 1.03-1.23, p = 0.01)。结论:我们确定了两种血浆蛋白与绝经后妇女患乳腺癌的长期风险增加有关;两者在一个独立队列中得到证实。如果进一步验证,这些血浆蛋白生物标志物可以考虑在当前的风险分层工具中使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discovering plasma proteins associated with breast cancer incidence in post-menopausal women in ARIC
Background Plasma proteomic data can be used to discover breast cancer risk biomarkers beyond established risk factors. Discovery using a large-scale platform in a diverse population is needed. Methods We investigated 4,712 plasma proteins and breast cancer risk among post-menopausal women in a prospective cohort analysis in the Atherosclerosis Risk in Communities study. Proteins were measured by SomaScan® 5K Assay. Incident cases were ascertained primarily from state cancer registries. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox regression adjusting for risk factors, and applied the Benjamini-Hochberg method to control false discovery. We determined whether the statistically significant proteins were confirmed in a case-cohort study within the European Prospective Investigation into Cancer and Nutrition (EPIC). Results After median follow-up of 23.3 years, 340 of 4,403 women had an incident breast cancer. Two proteins were statistically significantly associated after p-value adjustment per doubling, the HR of breast cancer was 1.45 (95% CI: 1.23-1.70, p = 7.47*10−6, padjusted=0.0370) for protein LEG1 homolog and 2.52 (95% CI: 1.66-3.83, p = 1.50*10−5, padjusted=0.0371) for ADP-dependent glucokinase. Results were consistent in a lagged analysis and among both Black (28.1%) and White women. In EPIC, both associations were confirmed (protein LEG1 homolog, HR = 1.24, 95% CI 1.14-1.35, p = 9.79*10−7, ADP-dependent glucokinase, HR = 1.13, 95% CI 1.03-1.23, p = .01). Conclusion We identified two plasma proteins associated with increased breast cancer risk over the longer-term in post-menopausal women; both were confirmed in an independent cohort. If further validated, these plasma protein biomarkers could be considered for utility in current risk stratification tools.
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