Project 461468

Single-cell, high-throughput characterization of the depressed brain

461468

Single-cell, high-throughput characterization of the depressed brain

$1,323,450
Project Information
Study Type: Unclear
Research Theme: Biomedical
Institution & Funding
Principal Investigator(s): Turecki, Gustavo X
Co-Investigator(s): Li, Yue; Nagy, Corina
Institution: CIUSSS de l'Ouest-de-l'Ile-de-Montréal-Douglas Hospital
CIHR Institute: Neurosciences, Mental Health and Addiction
Program: Project Grant
Peer Review Committee: Behavioural Sciences - B: Clinical Behavioural Sciences
Competition Year: 2022
Term: 5 yrs 0 mth
Abstract Summary

While there is strong evidence supporting the role of the anterior cingulate cortex, basolateral amygdala, and the hippocampus (ACC, BLA, HIPP) as a key neural network regulating mood, and therefore central to the pathophysiology of major depressive disorder (MDD), much remains unknown, including which gene pathways and which specific cell types play a primary causal role mediating alterations in this circuit, and what cell-type connections, within and between these regions, are particularly altered in depressive states. The proposed project is a large-scale, systematic investigation in the ACC, BLA, and HIPP to interrogate the transcriptome at single-nucleus resolution to identify, at the single-cell level changes in gene expression profiles associated with MDD. The proposed research is innovative because it is the first large-scale investigation of the ACC-BLA-HIPP circuit in humans and will represent the largest single-cell transcriptional resource of the human brain. This research is significant because it will greatly advance our understanding of the cellular and molecular pathways involved in mood regulation and MDD. Through a better understanding of the mechanisms of depressive illness, we may be one step closer to developing novel treatment strategies and personalize interventions.

No special research characteristics identified

This project does not include any of the advanced research characteristics tracked in our database.

Keywords
Depression Eqtls Human Post-Mortem Brain Tissues Machine Learning Mood Regulation Single-Cell Transcriptomics