Scientists reveal how distinct brain cells contribute to Alzheimer’s progression, unlocking new insights for developing personalized treatments and improving the accuracy of diagnosis across disease stages. Study: Integrated multimodal cell atlas of Alzheimer’s disease . Image Credit: illustrissima / Shutterstock In a recent study published in the journal Nature Neuroscience , researchers combined single-nucleus RNA sequencing (snRNA-seq), spatial genomics, single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq), multiomics, and preexisting reference atlases to evaluate the molecular and cellular alterations in the middle temporal gyrus (MTG) across the spectrum of Alzheimer's disease (AD) progression.
They further used quantitative neuropathology in conjunction with a machine learning model to devise a patient-specific pseudoprogression score (CPS), a continuous metric that orders donors along a neuropathological continuum. Study findings revealed the presence of two distinct major disease phases (early/slow and late/exponential), each with unique cell physiology. A small subset of donors in the study also exhibited a third ‘terminal’ disease phase characterized by more severe pathology.
Notably, the paper provides a framework for integrating previously confounding lines of evidence, allowing for cross-validation of Alzheimer's disease observations across studies, thereby increasing the robustness and consistency of study findings acros.
