Multi-Omics Reveals Dysregulated Neurotransmitter Systems in Aging and CNS Disorders.

Abstract

The neurotransmitter system (NTS) composed of neurotransmitter receptors and transporters is associated with a variety of diseases and disorders. The identification of disease-associated NTS features is important for understanding disease mechanisms and for prioritizing potential therapeutic targets. The differences in the composition of NTS in aging and different diseases are not well understood. Here, we show how to integrate multi-omics data at scale, including single-cell and spatial transcriptomic, to identify disease-associated NTS. By integrating, annotating, and analyzing 368 publicly available single-nucleus RNA sequencing (snRNA-seq) datasets from 17 cohort studies, we created a snRNA-seq dataset for the prefrontal cortex (PFC) of the human brain. The resulting dataset included > 1 million cells covering healthy individuals throughout the life course after birth and eight common neuropsychiatric disorders. We comprehensively describe the cellular heterogeneity of NTS in aging and disease, and resolve the relationship between age or sex and disease-associated NTS. A module composed of NTS and their regulatory genes was constructed and showed disease-associated discriminatory signal, with supportive validation from protein-level and external datasets. In order to screen NTS networks that can simulate disease brain tissue, we conducted a comparative analysis of five disease-related cerebral organoids and found partial similarity between patient-derived organoids and parental brain tissues. Our work provides a multi-disease cell atlas based on large-scale snRNA-seq data and analyses the disease and sex heterogeneity of NTS, which provides new insights into the mechanisms of multiple CNS diseases and sheds light on disease precision therapy against NTS.