多omics孟德尔随机化整合GWAS,eQTL和mQTL数据确定了与乳腺癌相关的基因
Zhihao Zhang1, Tian Fang2, Lanlan Chen3
1Breast Center, Department of General Surgery, West China Hospital, Sichuan University No. 37 Guo Xue Alley, Chengdu 610041, Sichuan, P. R. China.
American journal of cancer research
|April 9, 2024
概括
这项研究确定了两种关键基因,ATG10和RCCD1,与乳腺癌 (BC) 风险相关,使用多omics门德尔随机化. 这些发现提高了对BC机制和潜在治疗点的理解.
科学领域:
- 遗传学 遗传学 是一个
- 在瘤学瘤学.
- 生物信息学是一种生物信息学.
背景情况:
- 乳腺癌 (BC) 是一个重要的全球妇女健康问题.
- 结核病的潜在生物机制尚未完全理解.
- 识别影响BC风险的遗传因素对于开发有效治疗方法至关重要.
研究的目的:
- 为了确定与乳腺癌风险因果相关的基因.
- 用多omics数据分析已识别的基因的病理生理机制.
- 通过外部数据集验证已识别的基因.
主要方法:
- 使用基于总结数据的门德尔随机化 (MR).
- 从血液和乳腺组织中分析了表达量的特征位点 (eQTL).
- 综合了全基因组关联研究 (GWAS) 数据,eQTL和甲基化QTL (mQTL).
主要成果:
- 两种基因,ATG10和RCCD1,在血液和乳腺组织分析中都显示出与BC风险的显著关联.
- 结果在独立的BCAC和FinnGen队列中得到了一致的验证.
- 多组体MR分析证实了ATG10和RCCD1.1的单核酸多态 (SNP) 信号的关联.
结论:
- ATG10和RCCD1被确定为可能与乳腺癌相关的优先基因.
- 这些发现有助于更好地了解BC病变的发生.
- 这些已识别的基因可能会成为针对乳腺癌的新型治疗策略的潜在目标.
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