Abstract
Microglial cells are key players in maintaining brain homeostasis and responding to pathological conditions. Their multifaceted roles in health and disease have garnered significant attention in the context of neurodegeneration. In recent years, single-cell transcriptomic techniques have provided unprecedented insights into microglial heterogeneity, revealing distinct subpopulations and gene expression patterns associated with neuroprotection or neurotoxicity. Here, we dissect the transcriptomic landscape of microglia by leveraging human single-nuclei RNA sequencing datasets from multiple neurodegenerative conditions, including Amyotrophic Lateral Sclerosis, frontotemporal dementia, Alzheimer's disease, aging, and Parkinson's disease. This integrative analysis identifies distinct microglial subpopulations, reflecting functional heterogeneity across diseases and reveals a shared cross-disease microglial transcriptional program associated with inflammatory and neurodegenerative processes. Using a machine learning framework, we further demonstrate that this transcriptional program enables robust discrimination between neurodegenerative and control samples. Experimental validation in primary microglia isolated from a mouse model of Niemann-Pick disease type C, also known as juvenile Alzheimer's disease, supports the conservation of key components of this program and highlights Spp1 as a biomarker of disease-associated microglia states. Overall, this study provides an improved portrait of microglia transcriptional remodeling across neurodegenerative disorders and offers a framework for identifying conserved molecular features that may inform therapeutic strategies aimed at modulating microglial activity to mitigate disease progression and foster neuroprotection.