Progress and challenges in exploring the pathogenesis of depressive disorders via RNA sequencing
TL;DR
Current evidence indicates that immune-inflammatory activation, impaired synaptic plasticity, and mitochondrial energy metabolism dysfunction constitute shared core pathological mechanisms across these disorders, validating classical pathogenic hypotheses at the molecular level.
Abstract
Depressive disorders (DD) are highly heterogeneous psychiatric illnesses. Their complex pathogenesis, coupled with suboptimal response rates to current clinical treatments, poses significant challenges to global mental health. High-throughput RNA sequencing (RNA-seq) has emerged as a powerful tool for dissecting the molecular mechanisms of DD at the transcriptomic level. This paper reviews recent advances utilizing bulk RNA-seq, single-cell RNA-seq (scRNA-seq), and single-nucleus RNA-seq (snRNA-seq) to explore the pathogenesis of major depressive disorder (MDD), perinatal depression (PND), perimenopausal depression (PMD), and post-stroke depression (PSD). Current evidence indicates that immune-inflammatory activation, impaired synaptic plasticity, and mitochondrial energy metabolism dysfunction constitute shared core pathological mechanisms across these disorders, validating classical pathogenic hypotheses at the molecular level. Furthermore, distinct clinical subtypes exhibit significant transcriptomic heterogeneity; for instance, MDD shows marked sexual dimorphism and immunophenotypic characteristics. Specific molecular pathways also distinguish different DD categories: PND and PMD mainly involve imbalances in neuroendocrine–immune interaction networks driven by hormonal fluctuations, whereas PSD is characterized by the interaction between innate immune responses and autophagy flux impairment. Although RNA-seq has significantly advanced our understanding of DD, challenges such as restricted sample sources, high data heterogeneity, and insufficient clinical translation remain. Future research should prioritize single-cell and spatial transcriptomics to resolve tissue heterogeneity, promote multi-omics integration to construct causal regulatory networks, and strengthen cross-species comparative studies. These efforts will accelerate the development of precision diagnosis and personalized treatment strategies.