饮食摄入量 门德尔随机化:对仪器选择和强大的推理方法的评估和开发
Kristen J Sutton1, Julie Gervis2,3, Moomal Jatoi1
1Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA.
medRxiv : the preprint server for health sciences
|July 16, 2025
概括
关于饮食和健康的门德尔随机化 (MR) 研究需要仔细的基因仪器 (GI) 治疗. 精制地理标志物可以更好地检测饮食与生物标志物的联系,但饮食与疾病的关联需要像MR-CAUSE这样的先进方法来解释混.
科学领域:
- 遗传学和流行病学
- 营养科学 营养科学
- 生物统计学 生物统计学
背景情况:
- 门德尔随机化 (MR) 用于推断饮食摄入量与健康结果之间的因果关系.
- 目前的MR方法经常使用所有全基因组显著 (GWS) 变异,可能引入间接效应的偏差.
研究的目的:
- 评估有关饮食MR的当前文献,并确定共同的方法.
- 评估传统MR技术在检测已确定的饮食与健康关系方面的有效性.
- 开发和测试改进遗传仪器 (GI) 的方法,以更好地估计直接的饮食影响.
主要方法:
- 通过PubMed发现的饮食MR研究的文献综述.
- 实证测试常规的两样MR与GWS变体在六个阳性对照中的饮食与健康关系.
- 胃肠道精炼技术的开发和应用:基于全现象关联研究 (PheWAS) 的过和多变量MR (MVMR).
主要成果:
- 传统的MR与GWSGI在检测预期的饮食健康关联方面取得了有限的成功.
- 胃肠道过改善了饮食-生物标志物对的检测,但不是饮食-疾病对.
- MR-CAUSE确定了饮食与疾病的关联 (CVD上的白色与全谷物面包),并突出了身体组成特征的混.
结论:
- 对于饮食暴露的MR的广泛使用,由于不一致的发现和潜在的混,需要谨慎.
- 对遗传仪器进行深思熟虑的理对于减少偏见和准确评估饮食对健康的因果关系至关重要.
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