Human microglial state dynamics in Alzheimer’s disease progression - Sun, Na; Victor, Matheus B.; Park, Yongjin P.; Xiong, Xushen; Scannail, Aine Ni; Leary, Noelle; Prosper, Shaniah; Viswanathan, Soujanya; Luna, Xochitl; Boix, Carles A.; James, Benjamin T.; Tanigawa, Yosuke; et al. (Cell, 2023)
Altered microglial states affect neuroinflammation, neurodegeneration, and disease but remain poorly understood. Here, we report 194,000 single-nucleus microglial transcriptomes and epigenomes across 443 human subjects and diverse Alzheimer’s disease (AD) pathological phenotypes. We annotate 12 microglial transcriptional states, including AD-dysregulated homeostatic, inflammatory, and lipid-processing states. We identify 1,542 AD-differentially-expressed genes, including both microglia-state-specific and disease-stage-specific alterations. By integrating epigenomic, transcriptomic, and motif information, we infer upstream regulators of microglial cell states, gene-regulatory networks, enhancer-gene links, and transcription-factor-driven microglial state transitions. We demonstrate that ectopic expression of our predicted homeostatic-state activators induces homeostatic features in human iPSC-derived microglia-like cells, while inhibiting activators of inflammation can block inflammatory progression. Lastly, we pinpoint the expression of AD-risk genes in microglial states and differential expression of AD-risk genes and their regulators during AD progression. Overall, we provide insights underlying microglial states, including state-specific and AD-stage-specific microglial alterations at unprecedented resolution. [Display omitted] •Single-nucleus transcriptomes and epigenomes of human microglia•Microglia state-specific and disease-stage-specific profile in Alzheimer’s disease•Chromatin accessibility poorly captured microglia transcriptional state diversity•Transcription factor networks regulate microglial states and their transitions Microglia states showing Alzheimer’s disease (AD)-risk-gene expression and AD-progression-associated expression differences were identified from the microglial transcriptome and epigenomes from the 443 human subjects spanning brain regions and diverse clinical and pathological states. Computational framework and functional studies using iPSC-derived microglia defined the diversity of microglial states across disease, the disease-stage changes of gene expression, and the regulatory network that governs microglial state transitions during the progression of AD.