Center for Human Development, University of California, San Diego, USA.
Department of Neuroscience, University of California, San Diego, USA.
Brain. 2020 Jul 1;143(7):2272-2280. doi: 10.1093/brain/awaa164.
Sex differences in the manifestations of Alzheimer's disease are under intense investigation. Despite the emerging importance of polygenic predictions for Alzheimer's disease, sex-dependent polygenic effects have not been demonstrated. Here, using a sex crossover analysis, we show that sex-dependent autosomal genetic effects on Alzheimer's disease can be revealed by characterizing disease progress via the hazard function. We first performed sex-stratified genome-wide associations, and then applied derived sex-dependent weights to two independent cohorts. Relative to sex-mismatched scores, sex-matched polygenic hazard scores showed significantly stronger associations with age-at-disease-onset, clinical progression, amyloid deposition, neurofibrillary tangles, and composite neuropathological scores, independent of apolipoprotein E. Models without using hazard weights, i.e. polygenic risk scores, showed lower predictive power than polygenic hazard scores with no evidence for sex differences. Our results indicate that revealing sex-dependent genetic architecture requires the consideration of temporal processes of Alzheimer's disease. This has strong implications not only for the genetic underpinning of Alzheimer's disease but also for how we estimate sex-dependent polygenic effects for clinical use.
性别在阿尔茨海默病表现中的差异正在受到深入研究。尽管多基因预测对阿尔茨海默病的重要性日益凸显，但尚未证明性别依赖性多基因效应。在这里，我们使用性别交叉分析表明，可以通过危害函数来描述疾病进展，从而揭示与阿尔茨海默病相关的、依赖于性别的常染色体遗传效应。我们首先进行了性别分层的全基因组关联分析，然后将衍生的性别依赖性权重应用于两个独立的队列。与性别不匹配的评分相比，性别匹配的多基因危害评分与发病年龄、临床进展、淀粉样蛋白沉积、神经原纤维缠结和综合神经病理学评分的相关性显著更强，与载脂蛋白 E 无关。不使用危害权重（即多基因风险评分）的模型比没有性别差异证据的多基因危害评分具有更低的预测能力。我们的结果表明，揭示依赖于性别的遗传结构需要考虑阿尔茨海默病的时间进程。这不仅对阿尔茨海默病的遗传基础具有重要意义，而且对我们如何估计用于临床的依赖于性别的多基因效应也具有重要意义。
