使用多基因分数和机器学习在深度表型样本中预测酒精使用障碍的寻求治疗状态
Zeal Jinwala1, ReJoyce Green2, Yousef Khan3
1Crescenz VA Medical Center, Philadelphia, PA 19104, United States; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, United States.
Drug and alcohol dependence
|July 22, 2025
概括
很少有酒精使用障碍 (AUD) 的个人寻求治疗. 这项研究发现,虽然临床因素预测寻求治疗,但遗传风险评分 (PGS) 在患有AUD的年轻人中更有影响力.
科学领域:
- 遗传学 遗传学 是一个
- 精神病学是一个精神病学.
- 公共卫生 公共卫生
背景情况:
- 酒精使用障碍 (AUD) 影响了许多人,但很少有人接受治疗.
- 寻求治疗的预测因素包括饮酒模式,心理问题和物质依赖.
- 通过多基因分数 (PGS) 测量的遗传倾向在寻求AUD治疗中的作用仍未得到充分研究.
研究的目的:
- 研究临床表型和多基因分数 (PGS) 对寻求酒精使用障碍 (AUD) 治疗的预测价值.
- 检查遗传风险如何影响寻求治疗的不同祖先群体和年龄人口统计数据.
主要方法:
- 利用了9103名被诊断患有DSM-IV AUD的人的深度表型样本.
- 采用随机森林模型,根据91种临床表型预测寻求治疗的情况.
- 计算了欧洲 (EUR) 和非洲 (AFR) 祖先群体的AUD PGS,并将它们整合到预测模型中,按年龄分层 (<40和≥40).
主要成果:
- 临床因素,如多年的酒精使用,心理问题,精神病诊断和心脏病是寻求治疗的重要预测因素.
- 纳入AUD PGS并没有显著提高祖先群体的预测准确性 (欧元:准确率77.6%,AFR:准确率75.1%).
- 多基因分数 (PGS) 在年轻人中成为更重要的预测因素 (欧元:第8位为<40;第34位为≥40;AFR:第70位为<40;第78位为≥40).
结论:
- 临床特征仍然是寻求酒精使用障碍 (AUD) 治疗的主要预测因素.
- 多基因分数 (PGS) 在一般AUD人口中为寻求治疗提供了有限的额外预测能力.
- 正如PGS所指出的,遗传风险在预测AUD年轻人寻求治疗方面发挥着更重要的作用.
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