Single-cell multi-region transcriptional and epigenomic dissection of VCID.

摘要 阿尔茨海默病(AD)和AD相关痴呆(ADRD)是导致死亡、发病率和 患者及其亲人的医疗费用，由于人口老龄化，缺乏预测性诊断， 缺乏有效的治疗或预防措施。血管对认知损害和痴呆的贡献 (VCID)是AD和ADRD的关键因素，并通过各种脑血管病变表现出来， 包括动脉粥样硬化、微梗塞和小血管中风。VCID包括脑部小血管疾病 (CSVD)、脑淀粉样血管病(CAA)和单基因家族性CSVD(CADASIL、脑 常染色体显性遗传性动脉病伴皮质下梗塞和白质脑病)。了解 VCID的机制和驱动因素将使新的生物标志物和治疗方法成为可能，类似于 解决心脏病中的心血管疾病和高血压问题。要了解细胞机制 在跨大脑区域、细胞类型、病理和分子通路的VCID基础上，我们进行了高度的 两个样本死后中枢神经系统中表观基因组和转录改变的分辨率分析 散发性和遗传性VCID患者。目的1：我们对单核RNA测序和DNA进行了分析 可访问性(SnATAC-seq)，以创建VCID跨诊断、大脑的转录和表观基因组图谱 区域、细胞类型、性别和个体。目标2：我们创建了一份SVD相关基因变化的图谱， 模块、途径和细胞与细胞的相互作用。目标3：我们预测候选驱动基因、调节器和 使用跨时间和遗传模型的因果关系分析的路径，我们验证了我们的结果 试验性地使用成像研究。我们研究的成功实施将描绘出与临床相关的 散发性和遗传性VCID的生物标记物和治疗学，使我们能够剖析它们的共同 和不同的分子回路，横跨四个受影响的中枢神经系统区域和其中所有主要细胞类型，以及 捕捉到前所未有的复杂程度，并实现丰富的计算比较。数据集 生成的和计算的分析将为解决紧迫的医疗问题提供宝贵的见解 需要VCID，它们的时间、区域和细胞类型特定的变化，可以帮助指导新的 治疗学。

Abstract Alzheimer’s disease (AD) and AD-related dementias (ADRDs) are major drivers of mortality, morbidity, and health care costs for patients and their loved ones, due to the aging population, lack of predictive diagnosis, and lack of effective treatments or prevention. Vascular contributions to cognitive impairment and dementia (VCIDs) are key contributors to AD and ADRDs and manifest through diverse cerebrovascular lesions, including atherosclerosis, microinfarcts, and small vessel strokes. VCIDs include cerebral small vessel disease (CSVD), cerebral amyloid angiopathy (CAA), and a monogenic familial form of CSVD (CADASIL, Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy). Understanding the mechanisms and drivers of VCID will enable new biomarkers and therapeutics, similar to the success of addressing cardiovascular disease and hypertension in heart disease. To understand the cellular mechanisms underlying VCID across brain regions, cell types, pathology, and molecular pathways, we perform high- resolution profiling of epigenomic and transcriptional alterations in post-mortem CNS samples from both sporadic and genetic VCID patients. Aim 1: We profile single-nucleus RNA-sequencing (snRNA-seq) and DNA accessibility (snATAC-seq) to create a transcriptional and epigenomic atlas of VCID across diagnoses, brain regions, cell types, sexes, and individuals. Aim 2: We create an atlas of SVD-associated changes in genes, modules, pathways, and cell-cell interactions. Aim 3: We predict candidate driver genes, regulators, and pathways using causality analyses across temporal and genetic models, and we validate our results experimentally using imaging studies. The successful execution of our studies will delineate clinically-relevant VCID biomarkers and therapeutics across sporadic and genetic VCID, enabling us to dissect their common and distinct molecular circuits, across four affected CNS region and all major cell types within them, and capturing an unprecedented level of complexity and enabling rich computational comparisons. The datasets generated and the computational analyses will provide invaluable insights for addressing the pressing medical need of VCIDs, their temporal, region-specific, and cell-type-specific changes, which can help guide new therapeutics.