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描述表达量性特征位点 (eQTLs),DNA甲基化量性特征位点 (mQTLs) 和乳腺癌风险变体之间的关系

Peh Joo Ho^1,2,3, Alexis Khng¹, Benita Kiat-Tee Tan^4,5,6

¹Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore 138672, Singapore.

|June 19, 2024

概括

使用乳腺癌风险功能变异的新多基因风险评分 (PRS) 与已建立的GWAS PRS相比,没有改善预测. 已建立的GWAS PRS在识别乳腺癌病例方面表现出卓越的区分能力.

科学领域:

遗传学是一个遗传学.
癌症研究癌症研究
流行病学流行病学

背景情况:

多基因风险评分 (PRS) 对于评估对复杂疾病的遗传倾向至关重要.
识别功能性遗传变异可能会改进PRS,以改善疾病风险预测.
乳腺癌仍然是一个重大的全球健康问题,需要在风险分层方面取得进展.

研究的目的:

为了评估乳腺癌风险的功能遗传变异衍生的新型PRS.
为了比较这个功能性PRS的预测性能与标准的313个变异的全基因组关联研究 (GWAS) PRS.
为了确定是否结合功能变体可以提高乳腺癌风险预测的准确性.

主要方法:

总结基于数据的门德尔随机化 (SMR) 和依赖仪器的异质性 (HEIDI) 用于识别与基因表达和甲基化相关的风险变异.
使用SMR识别的变体构建了一个功能性的PRS.
功能性PRS和313种GWAS PRS在病例控制和前性队列中进行了比较.

主要成果:

149种变体显示了与乳腺癌风险的类关系.
功能性PRS的区分能力 (AUC:0.540) 比GWAS的PRS (AUC:0.609) 的区分能力更低.
结合功能和GWAS PRS变体并没有超过单独GWAS PRS的预测性能.

结论:

确定了与乳腺癌风险相关的潜在功能变异.
这些功能变体的纳入并没有显著提高已建立的GWAS PRS的预测准确性.
在这种情况下,标准GWAS PRS仍然是一个更有效的工具来预测乳腺癌风险.

关键词:

KCNN4 在线播放这是一个SMR.乳腺癌的风险乳腺癌的风险我们的eQTL是eQTL.遗传风险评分遗传风险评分 mQTLTL 是一个很好的方法.甲基化处理的方法

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