Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
PLoS Genet. 2022 Sep 1;18(9):e1010294. doi: 10.1371/journal.pgen.1010294. eCollection 2022 Sep.
For Alzheimer's disease-a leading cause of dementia and global morbidity-improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer's disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer's disease comprised of 7.1 million common DNA variants. We noted a 7.3-fold (95% CI 4.8 to 11.0; p < 0.001) gradient in risk across deciles of the score among 288,289 middle-aged participants of the UK Biobank study. In cross-sectional analyses stratified by age, minimal differences in risk of Alzheimer's disease and performance on a digit recall test were present according to polygenic score decile at age 50 years, but significant gradients emerged by age 65. Similarly, among 30,541 participants of the Mass General Brigham Biobank, we again noted no significant differences in Alzheimer's disease diagnosis at younger ages across deciles of the score, but for those over 65 years we noted an odds ratio of 2.0 (95% CI 1.3 to 3.2; p = 0.002) in the top versus bottom decile of the polygenic score. To understand the proteomic signature of inherited risk, we performed aptamer-based profiling in 636 blood donors (mean age 43 years) with very high or low polygenic scores. In addition to the well-known apolipoprotein E biomarker, this analysis identified 27 additional proteins, several of which have known roles related to disease pathogenesis. Differences in protein concentrations were consistent even among the youngest subset of blood donors (mean age 33 years). Of these 28 proteins, 7 of the 8 proteins with concentrations available were similarly associated with the polygenic score in participants of the Multi-Ethnic Study of Atherosclerosis. These data highlight the potential for a DNA-based score to identify high-risk individuals during the prolonged presymptomatic phase of Alzheimer's disease and to enable biomarker discovery based on profiling of young individuals in the extremes of the score distribution.
对于阿尔茨海默病——一种主要的痴呆症和全球发病原因——提高对无症状高风险个体的识别和新的循环生物标志物的识别是关键的公共卫生需求。在这里，我们检验了这样一个假设，即阿尔茨海默病风险的多基因预测因子将确定一部分人群具有更高的临床诊断痴呆、亚临床神经认知功能障碍和不同的循环蛋白质组特征的风险。我们使用最近全基因组关联研究的汇总关联统计数据，首先开发了一个由 710 万个常见 DNA 变体组成的阿尔茨海默病多基因预测因子。我们注意到，在 UK Biobank 研究的 288289 名中年参与者中，评分的十分位数跨越风险呈 7.3 倍（95%CI 4.8 至 11.0；p < 0.001）梯度。在按年龄分层的横断面分析中，根据 50 岁时多基因评分的十分位数，阿尔茨海默病的风险和数字回忆测试的表现差异极小，但到 65 岁时出现显著梯度。同样，在 Mass General Brigham Biobank 的 30541 名参与者中，我们再次注意到在评分的十分位数中，在年龄较轻的情况下，阿尔茨海默病的诊断没有显著差异，但对于 65 岁以上的人，我们注意到多基因评分的最高与最低十分位数之间的比值为 2.0（95%CI 1.3 至 3.2；p = 0.002）。为了了解遗传风险的蛋白质组特征，我们在 636 名血液供体（平均年龄 43 岁）中进行了基于适配子的蛋白质组分析，这些供体的多基因评分非常高或非常低。除了众所周知的载脂蛋白 E 生物标志物外，该分析还确定了另外 27 种蛋白质，其中一些具有与疾病发病机制相关的已知作用。即使在血液供体中年龄最小的亚组（平均年龄 33 岁）中，蛋白质浓度的差异也保持一致。在这 28 种蛋白质中，在动脉粥样硬化多民族研究参与者中，有 8 种蛋白质的浓度可用，其中 7 种与多基因评分呈类似相关性。这些数据突出了基于 DNA 的评分在阿尔茨海默病无症状的长期前期阶段识别高危个体的潜力，并能够基于评分分布极端的年轻人的蛋白质组分析来发现生物标志物。
