Physical activity and blood-based biomarkers of neurodegeneration in community dwelling Australians from ISLAND (Island Study Linking Ageing and Neurodegenerative Disease).

IF 4.4 Q1 CLINICAL NEUROLOGY

Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring Pub Date : 2025-08-17 eCollection Date: 2025-07-01 DOI:10.1002/dad2.70166

Eddy Roccati, Jessica Marie Collins, Michele Linda Callisaya, Jane Elizabeth Alty, Anna Elizabeth King, James John Rochfort Brady, James Clement Vickers

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引用次数: 0

Abstract

Introduction: Physical activity, a key modifiable risk factor for dementia, has been associated with biomarkers of neurodegeneration in the central nervous system, but less is known regarding blood-based biomarkers.

Methods: A total of 739 cognitively healthy participants (aged 50-83 years) from ISLAND (Island Study Linking Ageing and Neurodegenerative Disease) completed a battery of online surveys. Self-reported physical activity was assessed based on daily metabolic equivalent, and a blood sample was analyzed for serum neurofilament light chain, serum glial fibrillary acidic protein (GFAP), plasma phosphorylated tau, and genotyped for apolipoprotein E (APOE) ε4.

Results: Higher self-reported physical activity was significantly associated with lower log-transformed concentrations of GFAP (pg/mL, β = -0.022, P = 0.009) in fully adjusted generalized linear regression models. Subgroup analysis revealed this association was only significant in APOE ε4 non-carriers.

Discussion: This cross-sectional study provides novel evidence for the association of physical activity with blood-based biomarkers of neurodegeneration, and how APOE ε4 presence modifies this relationship.

Highlights: We looked at a large-scale (n = 739) community cohort of healthy Australians > 50 years of age.Physical activity (PA) levels were related to blood-based biomarkers of neurodegeneration.Higher PA was associated with lower serum glial fibrillary acidic protein (GFAP).Apolipoprotein E ε4 and PA intensity impacted this association.This novel finding provides a foundation for targeted physical activity interventions.

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来自岛屿的澳大利亚社区居民的身体活动和基于血液的神经变性生物标志物（连接衰老和神经退行性疾病的岛屿研究）。

体育活动是痴呆症的一个关键可改变的危险因素，与中枢神经系统神经退行性变的生物标志物有关，但对基于血液的生物标志物知之甚少。方法：来自ISLAND（连接衰老和神经退行性疾病的岛屿研究）的共有739名认知健康的参与者（50-83岁）完成了一系列在线调查。根据每日代谢当量评估自我报告的体力活动，分析血液样本的血清神经丝轻链、血清胶质纤维酸性蛋白（GFAP）、血浆磷酸化tau蛋白，并对载脂蛋白E (APOE) ε4进行基因分型。结果：在完全调整的广义线性回归模型中，较高的自我报告体力活动与较低的GFAP对数转化浓度（pg/mL, β = -0.022, P = 0.009）显著相关。亚组分析显示，这种关联仅在APOE ε4非携带者中显著。讨论：这项横断面研究为体力活动与基于血液的神经变性生物标志物之间的关联以及APOE ε4的存在如何改变这种关系提供了新的证据。重点：我们研究了一个大型（n = 739）社区队列的健康澳大利亚人在50岁。体力活动（PA）水平与基于血液的神经变性生物标志物有关。PA升高与血清胶质原纤维酸性蛋白（GFAP）降低相关。载脂蛋白E ε4和PA强度影响这种关联。这一新发现为有针对性的体育活动干预提供了基础。

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.