Luckett Emma S, Abakkouy Yasmina, Lorenzini Luigi, Collij Lyduine E, Garcia David Vallez, Visser Pieter Jelle, den Braber Anouk, Ritchie Craig, Boada Mercè, Genius Patricia, Vilor-Tejedor Natàlia, Gispert Juan Domingo, Vandenberghe Rik, Barkhof Frederik, Cleynen Isabelle
Department of Radiology and Nuclear Medicine, Amsterdam UMC location VUmc, Amsterdam, the Netherlands.
Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands.
Alzheimers Dement. 2025 Sep;21(9):e70376. doi: 10.1002/alz.70376.
We sought to harmonize genotype data from the predementia AMYPAD (Amyloid Imaging to Prevent Alzheimer's Disease) Consortium, compute polygenic risk scores (PRS), and determine their association with global amyloid deposition.
Genetic data from five AMYPAD parent cohorts were harmonized, and PRS were computed for Alzheimer's disease (AD) susceptibility, cerebrospinal fluid (CSF) amyloid beta (Aβ)42, and CSF phosphorylated tau181. Cross-sectional amyloid (Centiloid [CL]) burden was available for all participants, and regression models determined if PRS were associated with CL burden.
After harmonization, data for 867 participants showed that high CL burden was most strongly predicted by CSF Aβ42 PRS compared to traditional AD susceptibility PRS.
This work emphasizes the importance of data harmonization and pooling of cohorts for large-powered studies. Findings suggest a genetic predisposition to amyloid pathology that may predispose individuals early in the AD continuum. This validates the potential use of PRS in clinical (trial) settings as a non-invasive tool to assess AD risk.
We developed a robust harmonization pipeline for multi-cohort genotype array data. Cerebrospinal fluid amyloid beta (Aβ)-specific polygenic risk scores (PRS) more strongly predicted global Aβ positron emission tomography burden than other PRS. Results suggest a strong genetic predisposition to early Aβ pathology. This work highlights the need for robust data harmonization and data pooling. This work also validates the potential use of PRS as a non-invasive tool to assess Alzheimer's disease risk.
我们试图整合来自痴呆前阶段的AMYPAD（淀粉样蛋白成像预防阿尔茨海默病）联盟的基因型数据，计算多基因风险评分（PRS），并确定它们与整体淀粉样蛋白沉积的关联。
对五个AMYPAD亲本队列的遗传数据进行整合，并计算阿尔茨海默病（AD）易感性、脑脊液（CSF）淀粉样β蛋白（Aβ）42和CSF磷酸化tau181的PRS。所有参与者都有横断面淀粉样蛋白（百分离度[CL]）负担数据，回归模型用于确定PRS是否与CL负担相关。
整合后，867名参与者的数据显示，与传统的AD易感性PRS相比，CSF Aβ42 PRS对高CL负担的预测能力最强。
这项工作强调了数据整合和队列汇集对于大型研究的重要性。研究结果表明存在淀粉样蛋白病理的遗传易感性，这可能使个体在AD连续病程的早期就具有易感性。这验证了PRS在临床（试验）环境中作为评估AD风险的非侵入性工具的潜在用途。
我们为多队列基因型阵列数据开发了一个强大的整合流程。脑脊液淀粉样β蛋白（Aβ）特异性多基因风险评分（PRS）比其他PRS更能强烈预测整体Aβ正电子发射断层扫描负担。结果表明早期Aβ病理存在很强的遗传易感性。这项工作强调了进行强大的数据整合和数据汇集的必要性。这项工作还验证了PRS作为评估阿尔茨海默病风险的非侵入性工具的潜在用途。
