Bermudez Camilo, Syrjanen Jeremy A, Stricker Nikki H, Algeciras-Schimnich Alicia, Kouri Naomi, Kremers Walter K, Petersen Ronald C, Jack Clifford R, Knopman David S, Dickson Dennis W, Rothberg Darren M, Moloney Christina M, Boon Baayla D C, Nguyen Aivi T, Reichard R Ross, Murray Melissa E, Mielke Michelle M, Vemuri Prashanthi, Graff-Radford Jonathan
Department of Neurology, Mayo Clinic, Rochester, MN, USA.
Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
J Prev Alzheimers Dis. 2025 Sep;12(8):100224. doi: 10.1016/j.tjpad.2025.100224. Epub 2025 Jun 11.
Plasma biomarkers for Alzheimer's disease and neurodegeneration have shown accurate prediction of underlying neuropathology. However, chronic cardiovascular risk factors such as diabetes and hypertension are associated with plasma biomarker levels and can influence the accurate prediction of underlying neuropathologic changes.
To understand the interaction between plasma biomarkers of Alzheimer's disease and neurodegeneration with cardiovascular risk factors in relation to neuropathologic change in a heterogenous population to ascertain a more accurate utilization of these biomarkers.
Retrospective, case-control study.
Population-based, Olmstead county, Minnesota, USA.
Three-hundred and fifty-one participants (aged 87.4 ± 7.5 years) with brain autopsy and antemortem plasma biomarker testing.
Plasma biomarker testing for Aβ42/40, p-tau181, GFAP, and NfL using Quanterix Simoa assays. Cardiovascular risk factors were quantified by a composite score of cardiovascular metabolic conditions (CMC) consisting of a binary history of diabetes, congestive heart failure, stroke, coronary artery disease, atrial fibrillation, hypertension, or dyslipidemia. Plasma biomarkers and cardiovascular metabolic conditions score were Z-scored and neuropathologic scales were binarized into high and low categories. Outcomes included elevated microvascular (Kalaria) and macrovascular (Strozyk) neuropathologic scales as well as Alzheimer's disease neuropathologic change (ADNC), Thal phase, Braak stage, and neuritic plaque score. Multivariate logistic regression models incorporated interaction terms between plasma biomarkers and CMC while controlling for age, sex, cognitive impairment, and BMI.
We observed that at higher cardiovascular metabolic conditions score, the association between GFAP and overall ADNC (OR = 0.61 [0.42, 0.89]), Thal phase (OR = 0.48 [0.33, 0.71]), and Braak Stage (OR = 0.56 [0.37, 0.84]), became weaker, while the association with Strozyk score (OR = 1.65 [1.11, 2.46]) was stronger with higher CMC. Meanwhile, at higher CMC Aβ42/40 became more strongly negative with high Braak stage (OR = 0.63 [0.47, 0.85]), neuritic plaque score (OR 0.70 [0.52, 0.95]), Kalaria score (OR = 0.71 [0.57, 0.88]), and Strozyk score (OR = 0.60 [0.43, 0.83]). The association between p-tau181 and Thal phase (OR = 1.43 [1.00, 2.04]) was stronger at higher CMC while the association between p-tau181 and Strozyk score (OR = 0.47 [0.31, 0.71]) was weaker at higher CMC. There was no interaction between NfL and CMC score for any metric of neuropathologic change.
Understanding how cardiovascular risk factors can modulate plasma biomarkers is important for their interpretation with respect to underlying pathology and their clinical application in screening, diagnosis, and prognosis of neurodegenerative diseases.
阿尔茨海默病和神经退行性变的血浆生物标志物已显示出对潜在神经病理学的准确预测。然而，糖尿病和高血压等慢性心血管危险因素与血浆生物标志物水平相关，并可能影响对潜在神经病理变化的准确预测。
了解阿尔茨海默病和神经退行性变的血浆生物标志物与心血管危险因素之间的相互作用，以及与异质性人群神经病理变化的关系，以确定这些生物标志物更准确的应用。
回顾性病例对照研究。
美国明尼苏达州奥尔姆斯特德县基于人群的研究。
351名参与者（年龄87.4±7.5岁），进行了脑尸检和生前血浆生物标志物检测。
使用Quanterix Simoa分析方法对Aβ42/40、p-tau181、GFAP和NfL进行血浆生物标志物检测。通过心血管代谢状况（CMC）综合评分对心血管危险因素进行量化，该评分由糖尿病、充血性心力衰竭、中风、冠状动脉疾病、心房颤动、高血压或血脂异常的二元病史组成。对血浆生物标志物和心血管代谢状况评分进行Z评分，并将神经病理量表分为高、低两类。结果包括微血管（卡拉里亚）和大血管（斯特罗齐克）神经病理量表升高，以及阿尔茨海默病神经病理变化（ADNC）、塔尔阶段、布拉克阶段和神经炎性斑块评分。多变量逻辑回归模型纳入了血浆生物标志物与CMC之间的交互项，同时控制了年龄、性别、认知障碍和体重指数。
我们观察到，在心血管代谢状况评分较高时，GFAP与总体ADNC（比值比=0.61[0.42,0.89]）、塔尔阶段（比值比=0.48[0.33,0.71]）和布拉克阶段（比值比=0.56[0.37,0.84]）之间的关联变弱，而与斯特罗齐克评分（比值比=1.65[1.11,2.46]）的关联在CMC较高时更强。同时，在CMC较高时，Aβ42/40与高布拉克阶段（比值比=0.63[0.47,0.85]）、神经炎性斑块评分（比值比0.70[0.52,0.95]）、卡拉里亚评分（比值比=0.71[0.57,0.88]）和斯特罗齐克评分（比值比=0.60[0.43,0.83]）之间的负相关性更强。在CMC较高时p-tau181与塔尔阶段（比值比=1.43[1.00,2.04]）之间的关联更强，而在CMC较高时p-tau181与斯特罗齐克评分（比值比=0.47[0.31,0.71]）之间的关联较弱。对于任何神经病理变化指标，NfL与CMC评分之间均无相互作用。
了解心血管危险因素如何调节血浆生物标志物对于其在潜在病理学解释以及神经退行性疾病筛查、诊断和预后的临床应用方面都很重要。
