Detecting time-varying genetic effects in Alzheimer's disease using a longitudinal genome-wide association studies model.

IF 4 Q1 CLINICAL NEUROLOGY

Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring Pub Date : 2024-06-07 eCollection Date: 2024-04-01 DOI:10.1002/dad2.12597

Xiaowei Zhuang, Gang Xu, Amei Amei, Dietmar Cordes, Zuoheng Wang, Edwin C Oh

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引用次数: 0

Abstract

Introduction: The development and progression of Alzheimer's disease (AD) is a complex process, during which genetic influences on phenotypes may also change. Incorporating longitudinal phenotypes in genome-wide association studies (GWAS) could unmask these genetic loci.

Methods: We conducted a longitudinal GWAS using a varying coefficient test to identify age-dependent single nucleotide polymorphisms (SNPs) in AD. Data from 1877 Alzheimer's Neuroimaging Data Initiative participants, including impairment status and amyloid positron emission tomography (PET) scan standardized uptake value ratio (SUVR) scores, were analyzed using a retrospective varying coefficient mixed model association test (RVMMAT).

Results: RVMMAT identified 244 SNPs with significant time-varying effects on AD impairment status, with 12 SNPs on chromosome 19 validated using National Alzheimer's Coordinating Center data. Age-stratified analyses showed these SNPs' effects peaked between 70 and 80 years. Additionally, 73 SNPs were linked to longitudinal amyloid accumulation changes. Pathway analyses implicated immune and neuroinflammation-related disruptions.

Discussion: Our findings demonstrate that longitudinal GWAS models can uncover time-varying genetic signals in AD.

Highlights: Identify time-varying genetic effects using a longitudinal GWAS model in AD.Illustrate age-dependent genetic effects on both diagnoses and amyloid accumulation.Replicate time-varying effect of APOE in a second dataset.

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利用纵向全基因组关联研究模型检测阿尔茨海默病的时变遗传效应。

简介阿尔茨海默病（AD）的发生和发展是一个复杂的过程，在这一过程中，基因对表型的影响也可能发生变化。将纵向表型纳入全基因组关联研究（GWAS）可揭示这些遗传位点：我们采用变化系数检验法进行了一项纵向 GWAS 研究，以确定与年龄相关的 AD 单核苷酸多态性（SNPs）。我们使用回顾性变化系数混合模型关联检验（RVMMAT）分析了1877名阿尔茨海默氏症神经影像数据倡议参与者的数据，包括损伤状态和淀粉样蛋白正电子发射断层扫描（PET）扫描标准化摄取值比（SUVR）得分：结果：RVMMAT发现了244个对AD损伤状态有显著时变影响的SNPs，其中12个SNPs是通过国家阿尔茨海默氏症协调中心的数据验证的19号染色体上的SNPs。年龄分层分析显示，这些SNPs的影响在70至80岁之间达到峰值。此外，73 个 SNP 与纵向淀粉样蛋白累积变化有关。通路分析显示与免疫和神经炎症相关的干扰有关：讨论：我们的研究结果表明，纵向 GWAS 模型可以发现 AD 中的时变遗传信号：在第二个数据集中复制 APOE 的时变效应。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring Medicine-Psychiatry and Mental Health

CiteScore

7.80

自引率

7.50%

发文量

101

审稿时长

8 weeks

期刊介绍： Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.