在结直肠癌风险预测中的多重多基因评分方法
Shangqing Joyce Jiang1,2, Minta Thomas2, Elisabeth A Rosenthal3
1University of Washington, Seattle, WA, USA.
Scientific reports
|October 31, 2025
概括
多重多基因评分 (MPS) 方法,包括其他疾病的多基因风险评分,显著改善结直肠癌 (CRC) 风险预测. 这种方法增强了预测模型,为个性化CRC风险评估提供了有希望的进步.
科学领域:
- 遗传学 是一个遗传学.
- 流行病学 流行病学
- 机器学习 机器学习
背景情况:
- 多基因风险评分 (PRS) 越来越多地用于疾病风险预测.
- 多重多基因评分 (MPS) 方法整合了来自各种特征的PRS,以潜在地提高预测准确性.
- 结肠直肠癌 (CRC) 风险预测可以从改进的建模策略中受益.
研究的目的:
- 评估MPS方法在改善结直肠癌 (CRC) 风险预测方面的有效性.
- 为了确定最具预测性的非CRC PRS,将其纳入MPS模型.
- 评估MPS在与现有的CRC风险预测模型相结合时的性能提升.
主要方法:
- 利用来自31,257例CRC病例和33,408例对照的个人级数据来选择预测性非CRCPRS.
- 使用机器学习 (ML) 模型从PGS目录中识别337个重要的非CRC PRS.
- 在独立的GERA队列中验证了MPS模型,使用接收器操作曲线 (AUC) 下的面积来评估性能.
主要成果:
- 该ML模型成功识别了337个与CRC风险相关的非CRCPRS.
- 结合MPS显著改善了CRC风险预测模型AUC,当与已知的CRC-PRS.loci相结合时,AUC提高了0.017.
- 当MPS与全基因组CRC-PRS (0.005) 和两种CRC-PRS类型 (0.004) 结合使用时,观察到进一步的AUC改善.
结论:
- 该MPS方法显示了改进和增强结直肠癌 (CRC) 风险预测模型的巨大潜力.
- 整合其他特征的PRS为提高复杂疾病风险评估的准确性提供了有价值的策略.
- 这项研究强调了多基因风险预测CRC和其他疾病未来进步的途径.
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