Multi-omics analysis reveals cell-specific neuronal dysfunction and predictive proteomic markers in major depressive disorder, highlighting potential therapeutic and diagnostic targets.
Major Depressive Disorder (MDD) is a complex psychiatric condition characterized by neuronal and functional disruptions in the dorsolateral prefrontal cortex (dlPFC). We integrated MDD-associated multi-omics data, including two single-cell RNA sequencing (scRNA-seq) datasets, GWAS summary data, and depression-related proteomic data from UK Biobank. We identified 273 MDD-associated eQTL, while the single-cell disease-relevance score (scDRS) algorithm revealed that excitatory neurons, inhibitory neurons, and oligodendrocyte precursor cells (OPCs) are significantly associated with MDD. Non-negative matrix factorization (NMF) identified four meta-programs (MPs) in excitatory and inhibitory neurons, reflecting functional impairments related to synaptic plasticity, neuronal connectivity, and epigenetic regulation. Differentiation trajectory analysis revealed distinct pathological states of neuronal subtypes. We identified CXCL14 + inhibitory neurons and investigated their role in stress perception and intercellular communication. Plasma proteomics data validated 33 risk genes, five of which encoded proteins predictive of patient survival in CoxBoost regression models. These findings provide a comprehensive understanding of the cellular and molecular underpinnings of MDD, offering potential diagnostic and therapeutic targets and advancing the development of precision medicine approaches for MDD.
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Zhang et al. (2025) studied this question.
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