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基于虚拟生成的酒精数据进行食道癌症风险的个性化预测
Oswald Ndi Nfor1, Pei-Ming Huang2,3, Ming-Fang Wu4,5
1Department of Public Health, Institute of Public Health, Chung Shan Medical University, No.110, Sec.1, Jianguo North Road, Taichung, 40201, Taiwan.
Journal of translational medicine
|March 29, 2025
概括
个性化食道癌症风险可以通过将遗传数据与AI模拟的酒精消费相结合来预测. 戒酒显著降低了高风险个体的风险.
科学领域:
- 遗传学和流行病学
- 医疗保健中的人工智能
- 癌症研究 癌症研究
背景情况:
- 食道癌 (EC) 是一个全球性的健康问题,受遗传学和生活方式的影响,尤其是酒精消费.
- 高度饮酒的地区面临着来自欧盟的重大公共卫生挑战.
- 了解多因素病因对于EC预防至关重要.
研究的目的:
- 开发一个针对食道癌的个性化风险预测模型.
- 整合基因多态 (rs671,rs1229984) 与人工智能生成的酒精消费数据.
- 在不同的酒精消费场景下评估风险概况.
主要方法:
- 分析了来自台湾生物库的86,845名个人 (763名EC患者) 的数据.
- 采用了八种机器学习模型,包括Ensemble,Random Forest和SVM.
- 利用虚拟生成酒精消费数据进行风险评估.
主要成果:
- 基因型rs671=AG和rs1229984=CC的个体显示出最高的EC概率 (0.2041-0.9181).
- 在高风险基因型中,禁酒降低了16.29-49.58%的风险.
- 集团模型实现了高性能 (AUC=0.9577,灵敏度=0.9211).
结论:
- 整合虚拟生成的酒精数据增强了个性化的EC风险评估.
- 结合遗传和生活方式因素的个性化风险模型至关重要.
- 酒精戒断为遗传倾向的个体提供了显著的风险降低.
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