Heiskanen Marja A, Mykkänen Juha, Pahkala Katja, Juonala Markus, Kähönen Mika, Lehtimäki Terho, Laitinen Tomi P, Jokinen Eero, Tossavainen Päivi, Linko-Parvinen Anna, Pallari Hanna-Mari, Blennow Kaj, Zetterberg Henrik, Viikari Jorma, Raitakari Olli, Rovio Suvi P
Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland; Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.
Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland; Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.
Lancet Healthy Longev. 2025 Jun;6(6):100717. doi: 10.1016/j.lanhl.2025.100717.
Blood-based biomarkers (BBM) of neurodegenerative diseases are emerging as cost-effective tools in the differential diagnostics of Alzheimer's disease and other dementias. Scarce data exist about factors explaining BBM variation in population-based cohorts, and their intergenerational associations are unknown. This study aimed to characterise BBM distributions among a population-based cohort, investigate the association of a wide array of factors with BBM both in midlife and old age, and investigate intergenerational associations of BBM.
We measured BBM detecting amyloid β and tau pathologies, including amyloid β42, amyloid β40, and phosphorylated Tau (pTau)-217, as well as glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) in the multigenerational Young Finns Study participants (n=1237, age 41-56 years) and their parents (n=814, age 59-90 years) using the Quanterix Simoa HD-X analyser. Standard statistical methods were used to examine the associations between BBM and age, sex, genetic factors, a plethora of cardiometabolic markers, liver and kidney function, and lifestyle factors, as well as their intergenerational associations.
Increased age was associated with adverse BBM concentrations. Of the various investigated factors, the most robust associations towards adverse BBM concentration were found for APOE ε4 carrier status among parents (amyloid β42:40 ratio, pTau-217, and GFAP) and high serum creatinine concentration in both generations (pTau-217, GFAP, and NfL). Several factors related to glucose metabolism and dyslipidaemia were negatively associated with all BBM, but adjusting for BMI diluted many of these associations. Statistically significant intergenerational correlations ranged from 0·20 to 0·33 and were mostly observed between mothers and offspring in pTau-217, GFAP, and NfL. No intergenerational correlations existed in amyloid β42:40 ratio.
We identified several factors that might influence BBM concentrations, parental transmission being one of them. For reliable use of BBM in clinical practice, it is important to identify which factors directly link to amyloid β and tau pathology and which factors influence BBM concentrations due to other physiological processes.
Research Council of Finland, Social Insurance Institution of Finland, Competitive State Research Financing of the Expert Responsibility area of the Kuopio, Tampere and Turku University Hospitals, Juho Vainio Foundation, Paavo Nurmi Foundation, Finnish Foundation for Cardiovascular Research, Finnish Cultural Foundation, The Sigrid Juselius Foundation, Tampere Tuberculosis Foundation, Emil Aaltonen Foundation, Yrjö Jahnsson Foundation, Signe and Ane Gyllenberg Foundation, Jenny and Antti Wihuri Foundation, Diabetes Research Foundation of the Finnish Diabetes Association, EU Horizon 2020, European Research Council, Tampere University Hospital Supporting Foundation, Finnish Society of Clinical Chemistry, the Jane and Aatos Erkko Foundation, and the Finnish Brain Foundation.
神经退行性疾病的血液生物标志物正成为阿尔茨海默病和其他痴呆症鉴别诊断中具有成本效益的工具。关于基于人群队列中解释血液生物标志物变异的因素的数据稀缺,且它们的代际关联尚不清楚。本研究旨在描述基于人群队列中的血液生物标志物分布,调查中年和老年时一系列因素与血液生物标志物的关联,并研究血液生物标志物的代际关联。
我们在多代芬兰青年研究参与者(n = 1237,年龄41 - 56岁)及其父母(n = 814,年龄59 - 90岁)中,使用Quanterix Simoa HD - X分析仪测量了检测淀粉样β蛋白和tau蛋白病变的血液生物标志物,包括淀粉样β42、淀粉样β40和磷酸化Tau(pTau)- 217,以及胶质纤维酸性蛋白(GFAP)和神经丝轻链(NfL)。使用标准统计方法检查血液生物标志物与年龄、性别、遗传因素、大量心脏代谢标志物、肝肾功能和生活方式因素之间的关联,以及它们的代际关联。
年龄增加与不良血液生物标志物浓度相关。在各种研究因素中,父母中APOE ε4携带者状态(淀粉样β42:40比值、pTau - 217和GFAP)以及两代人中高血清肌酐浓度与不良血液生物标志物浓度的关联最为显著。一些与葡萄糖代谢和血脂异常相关的因素与所有血液生物标志物均呈负相关,但调整体重指数后,其中许多关联被削弱。具有统计学意义的代际相关性范围为0.20至0.33,主要在母亲与后代的pTau - 217、GFAP和NfL中观察到。淀粉样β42:40比值不存在代际相关性。
我们确定了几个可能影响血液生物标志物浓度的因素,父母遗传是其中之一。为了在临床实践中可靠地使用血液生物标志物,重要的是确定哪些因素直接与淀粉样β蛋白和tau蛋白病变相关,以及哪些因素由于其他生理过程影响血液生物标志物浓度。
芬兰研究理事会、芬兰社会保险机构、库奥皮奥、坦佩雷和图尔库大学医院专家责任领域的竞争性国家研究资金、尤霍·瓦伊尼奥基金会、帕沃·努尔米基金会、芬兰心血管研究基金会、芬兰文化基金会、西格丽德·尤西利厄斯基金会、坦佩雷结核病基金会、埃米尔·阿尔托宁基金会、约尔约·亚恩松基金会、西格内和阿内·吉伦伯格基金会、珍妮和安蒂·维胡里基金会、芬兰糖尿病协会糖尿病研究基金会、欧盟地平线2020、欧洲研究理事会、坦佩雷大学医院支持基金会、芬兰临床化学学会、简和阿托斯·埃尔科基金会以及芬兰脑基金会。