The gene-regulatory landscape of the brain is highly dynamic in health and disease, coordinating a menagerie of biological processes across distinct cell types. Here, we present a multi-omic single-nucleus study of 191,890 nuclei in late-stage Alzheimer’s disease (AD), accessible through our web portal, profiling chromatin accessibility and gene expression in the same biological samples and uncovering vast cellular heterogeneity. We identified cell-type-specific, disease-associated candidate cis-regulatory elements and their candidate target genes, including an oligodendrocyte-associated regulatory module containing links to APOE and CLU. We describe cis-regulatory relationships in specific cell types at a subset of AD risk loci defined by genome-wide association studies, demonstrating the utility of this multi-omic single-nucleus approach. Trajectory analysis of glial populations identified disease-relevant transcription factors, such as SREBF1, and their regulatory targets. Finally, we introduce single-nucleus consensus weighted gene coexpression analysis, a coexpression network analysis strategy robust to sparse single-cell data, and perform a systems-level analysis of the AD transcriptome.

大脑的基因调控景观在健康和疾病中是高度动态的，协调不同细胞类型的一系列生物过程。在这里，我们提出了一项针对晚期阿尔茨海默病 (AD) 191,890 个细胞核的多组学单核研究，可通过我们的门户网站进行访问，分析同一生物样本中的染色质可及性和基因表达，并揭示巨大的细胞异质性。我们鉴定了细胞类型特异性、与疾病相关的候选顺式调节元件及其候选靶基因，包括包含APOE和CLU链接的少突胶质细胞相关调节模块。我们描述了由全基因组关联研究定义的 AD 风险位点子集中特定细胞类型中的顺式调节关系，证明了这种多组学单核方法的实用性。神经胶质细胞群的轨迹分析确定了与疾病相关的转录因子，例如 SREBF1 及其调控靶点。最后，我们介绍了单核一致性加权基因共表达分析，这是一种对稀疏单细胞数据具有鲁棒性的共表达网络分析策略，并对 AD 转录组进行系统级分析。