Deciphering the neural mechanisms of miR-134 in major depressive disorder with population-based and person-specific imaging transcriptomic techniques

Abstract

MiR-134 has emerged as a potential molecular biomarker for the detection and management of major depressive disorder (MDD). Nevertheless, the specific effects of miR-134 as a regulatory element on brain function and its implications for the clinical presentation of MDD are not yet fully understood. In order to investigate the potential neural mechanisms that contribute to the relationship between miR-134 and MDD, we employed a parallel two-stage cross-scale multi-omics approach. This involved utilizing the anterior cingulate cortex (ACC) functional connectivity as a means to connect microscopic molecular structures with macroscopic brain function in two separate cohorts: the MDD-I dataset (56 MDD patients and 51 healthy controls) and the MDD-II dataset (57 MDD patients and 52 healthy controls). We found a stable ACC functional dysconnectivity pattern of MDD and established the hierarchical cross-scale association from molecular organizations of miR-134 target genes to macroscopic brain functional dysconnectivity and associated behavior, as revealed by population-based analysis. Additionally, our person-specific imaging transcriptomic study revealed that individual exosomal miR-134 expression levels impact on individual clinical symptoms of MDD by modulating ACC-related functional dysconnectivity. Together, our findings provide compelling evidence of the correlation between miR-134 and depression across multi scales within the gene-brain-behavior context.

Keywords: Biomarkers; Major depressive disorder (MDD); Multi-omics; Two-stage cross-scale imaging transcriptomic analyses; miR-134.