Title: Single-cell meta-analysis uncovers shared and distinct gene-regulatory signatures in disorders of the human brain
Abstract: In recent years biotechnological and algorithmic advances in single-cell genomics have led to discoveries in the gene-regulatory landscapes of many human diseases, including disorders of the human brain such as Alzheimer’s Disease. In this study we jointly analyze multiple disorders in a single-cell transcriptomics meta-analysis of the human brain to identify shared and distinct gene regulatory signatures of disease. We constructed an integrated cell atlas encompassing nine independent datasets and over 500,000 cells, including both neurodegenerative and neuropsychiatric disorders. We identified a wide array of neuronal and glial cell types, as well as rare sub-populations that were not well characterized in the original studies due to their small population sizes. As a preliminary analysis of this cross-disorder cell atlas, we performed differential gene expression and co-expression network analysis in the oligodendrocyte lineage. Based on our preliminary results, we expect that further analysis of this dataset and incorporation of additional datasets will elucidate shared molecular phenotypes of multiple disorders across each major cell clade thereby identifying candidate regulators of disease and will serve as a valuable compendium of high-resolution data for the broader neurobiology community.