Euesden Jack, Ali Muhammad, Robins Chloe, Surendran Praveen, Gormley Padhraig, Pulford David, Cruchaga Carlos
Biostatistics, GSK Pharma R&D, Stevenage, Hertfordshire, United Kingdom.
Washington University School of Medicine, NeuroGenomics and Informatics Center, St. Louis, MO, United States of America.
PLoS One. 2025 Jan 9;20(1):e0310977. doi: 10.1371/journal.pone.0310977. eCollection 2025.
Case-only designs in longitudinal cohorts are a valuable resource for identifying disease-relevant genes, pathways, and novel targets influencing disease progression. This is particularly relevant in Alzheimer's disease (AD), where longitudinal cohorts measure disease "progression," defined by rate of cognitive decline. Few of the identified drug targets for AD have been clinically tractable, and phenotypic heterogeneity is an obstacle to both clinical research and basic science. In four cohorts (n = 7241), we performed genome-wide association studies (GWAS) and Mendelian randomization (MR) to discover novel targets associated with progression and assess causal relationships. We tested opportunities for patient stratification by deriving polygenic risk scores (PRS) for AD risk and severity and tested the value of these scores in predicting progression. Genome-wide association studies identified no loci associated with progression at genome-wide significance (α = 5×10-8); MR analyses provided no significant evidence of an association between cognitive decline in AD patients and protein levels in brain, cerebrospinal fluid (CSF), and plasma. Polygenic risk scores for AD risk did not reliably stratify fast from slow progressors; however, a deeper investigation found that APOE ε4 status predicts amyloid-β and tau positive versus negative patients (odds ratio for an additional APOE ε4 allele = 5.78 [95% confidence interval: 3.76-8.89], P<0.001) when restricting to a subset of patients with available CSF biomarker data. These results provided no evidence for large-effect, common-variant loci involved in the rate of memory decline, suggesting that patient stratification based on common genetic risk factors for progression may have limited utility. Where clinically relevant biomarkers suggest diagnostic heterogeneity, there is evidence that a priori identified genetic risk factors may have value in patient stratification. Mendelian randomization was less tractable due to the lack of large-effect loci, and future analyses with increased samples sizes are needed to replicate and validate our results.
纵向队列中的病例对照设计是识别与疾病相关的基因、通路以及影响疾病进展的新靶点的宝贵资源。这在阿尔茨海默病（AD）中尤为重要，纵向队列通过认知衰退率来衡量疾病“进展”。已确定的AD药物靶点中很少有临床上易于处理的，而且表型异质性对临床研究和基础科学都是一个障碍。在四个队列（n = 7241）中，我们进行了全基因组关联研究（GWAS）和孟德尔随机化（MR），以发现与疾病进展相关的新靶点并评估因果关系。我们通过推导AD风险和严重程度的多基因风险评分（PRS）来测试患者分层的机会，并测试这些评分在预测疾病进展中的价值。全基因组关联研究未发现与全基因组显著性水平（α = 5×10-8）的疾病进展相关的位点；MR分析未提供AD患者认知衰退与脑、脑脊液（CSF）和血浆中蛋白质水平之间存在关联的显著证据。AD风险的多基因风险评分不能可靠地区分疾病进展快与慢的患者；然而，更深入的研究发现，当仅限于有可用CSF生物标志物数据的患者亚组时，APOE ε4状态可预测淀粉样β蛋白和tau蛋白阳性与阴性患者（额外一个APOE ε4等位基因的优势比 = 5.78 [95%置信区间：3.76 - 8.89]，P<0.001）。这些结果没有为参与记忆衰退速率的大效应常见变异位点提供证据，这表明基于常见遗传风险因素进行患者分层可能效用有限。在临床相关生物标志物表明诊断异质性的情况下，有证据表明预先确定的遗传风险因素可能在患者分层中具有价值。由于缺乏大效应位点，孟德尔随机化较难处理，需要增加样本量进行未来分析以重复和验证我们的结果。
