Microglial, Inflammatory and Omics Markers of Cerebral Small Vessel Disease in the CHARGE Consortium

脑小血管病（SVD）是临床痴呆的一个重要的，潜在的可变因素。 最近的数据表明，痴呆症的年龄特异性发病率可能正在下降，部分原因是更好的治疗。 血管风险因素的管理，为痴呆症预防试验提供了紧迫性，但一个主要障碍是 缺乏用于追踪SVD发作和进展的循环生物标志物。脑MRI成像标志物 是SVD当前的黄金标准，但对于重复评估来说过于昂贵和繁琐。 最近的遗传学研究，包括来自基因组流行病学中心脏和衰老研究的队列 （CHARGE）财团的研究表明，小胶质细胞炎症和星形胶质细胞与SVD和痴呆的生物学有关。 我们建议测量小胶质细胞炎症的两种循环生物标志物（sCD-14和YKL-40）和一种 星形胶质细胞损伤标志物（GFAP）在约17，000人（包括4000名少数民族参与者，6000名>2 MRI）。 具体而言，我们将（1）检查新生物标志物与（a）先前收集的 MRI定义的SVD（白色高信号、腔隙性梗死和脑微出血），以及在人群中 年龄在70岁以下，早期、临床前SVD的敏感MRI指标，如弥散各向异性分数， 加权成像、局部皮质变薄和血管周围空间;（B）先前收集的测量 认知功能;和（c）SVD（痴呆和中风）的神经认知和血管后果。 我们将使用孟德尔随机化框架和现有的遗传数据来研究因果关系 新型生物标志物与MRI、神经认知和临床结果之间的关系。 (2)我们将评估新的生物标志物对（a）血管风险的增量预测效用 因子概况，例如卒中风险预测评分;（B）在先前测量的一组 SVD的“候选”生物标志物包括CRP、IL 6、TNF-α、纤维蛋白原、BNP、尿白蛋白、tHcy、ST 2， GDF 15、TnI、BDNF、VEGF、MMP-9、β-淀粉样蛋白、clusterin和APOE，以及（c）我们将鉴定一种吝啬的 一组生物标志物，最好地预测SVD的存在和认知能力下降，中风和痴呆的风险。 (3)我们将（a）在独立样本中验证目标2中开发的预测模型，（B）扩展 生物学关联，并通过无假设探索改善临床预测模型， 多维组学（全基因组、GWAS、表观遗传学和基因表达）和（c）研究 增加风险模型的预测价值，这些模型结合了联合收割机的遗传、表观遗传、转录组信息， 仅考虑危险因素和血清生物标志物信息。 总之，我们建议利用广泛的可用数据来识别和验证一种新的循环 神经胶质细胞功能障碍的生物标志物谱，这将提高我们对SVD生物学的理解，并有助于 预测SVD及其相关不良神经学结局。

Cerebral Small Vessel Disease (SVD) is an important, potentially modifiable factor for clinical dementia. Recent data suggest that the age-specific incidence of dementia may be decreasing, partly as a result of better management of vascular risk factors, lending urgency to dementia prevention trials but a major impediment is the absence of circulating biomarkers for tracking onset and progression of SVD. Brain MRI imaging markers are the current gold standard for SVD but are too expensive and burdensome for repeated assessments. Recent genetic studies, including from the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) consortium, implicate microglial inflammation and astroglia in the biology of SVD and dementia. We propose to measure 2 circulating biomarkers of microglial inflammation (sCD-14 and YKL-40) and a marker of astroglial injury (GFAP) in ~17,000 persons (including 4000 minority participants, 6000 with >2 MRI) across 5 CHARGE population-based cohorts. Specifcally, we will (1) examine the association of the novel biomarkers with (a) previously collected MRI-defined SVD (white matter hyperintensities, lacunar infarcts and cerebral microbleeds), and in persons under age 70, sensitive MRI measures of early, preclinical SVD such as fractional anisotropy on diffusion- weighted imaging, regional cortical thinning and perivascular spaces; (b) previously collected measures of cognitive function; and (c) neurocognitive and vascular consequences of SVD (dementia and stroke). We will use a Mendelian Randomization framework and existing genetic data to examine causal relationships between the novel biomarkers and MRI, neurocognitive, and clinical outcomes. (2) We will assess the incremental predictive utility of the novel biomarkers over (a) vascular risk factor profiles such as the Framingham Stroke Risk Prediction score; (b) over a panel of previously measured `candidate' biomarkers for SVD including CRP, IL6, TNF-alpha, fibrinogen, BNP, urine albumin, tHcy, ST2, GDF15, TnI, BDNF, VEGF, MMP-9, beta-amyloid, clusterin and APOE and (c) we will identify a parsimonious set of biomarkers that best predict presence of SVD and risk of cognitive decline, stroke and dementia. (3) We will (a) validate the prediction models developed in Aim 2 in independent samples, (b) extend the biological associations and improve clinical prediction models through hypothesis-free exploration of multi-dimensional omics (whole genome, GWAS, epigenetic and gene expression) and (c) investigate the added predictive value of risk models that combine genetic, epigenetic, transcriptomic information over models that consider only risk factor and serum biomarker information. In summary we propose to leverage extensive available data to identify and validate a novel circulating biomarker profile of glial cell dysfunction that will improve our understanding of SVD biology and help in the prediction of SVD and its associated adverse neurological outcomes.