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Single-cell eQTL and Mendelian randomization analyses of shared genetic architecture in major depressive disorder and
Jing Ren1, Bin Dong1, Xiaofen Li1
1School of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, Jinzhong, 030619, China; Shanxi Key Laboratory of Traditional Chinese Medicine Processing, Shanxi University of Chinese Medicine, Jinzhong, 030619, China; Shanxi University of Chinese Medicine, Key Research Laboratory of Processing and Innovation in Traditional Chinese Medicinal Materials, Jinzhong, 030619, China; Traditional Chinese Medicine Processing Technology Inheritance Base (Shanxi University of Chinese Medicine), Jinzhong, 030619, China.
Abstract:
Schizophrenia (SCZ) and major depressive disorder (MDD) are severe psychiatric disorders with substantial shared genetic liability and frequent clinical co-occurrence, yet their shared cell type-specific genetic mechanisms remain unclear. We integrated single-cell expression quantitative trait locus (sc-eQTL) data from eight major brain cell types with large-scale genome-wide association study (GWAS) summary statistics for SCZ and MDD. Cell type-specific genetically regulated gene expression was evaluated using Mendelian randomization (MR) and Bayesian colocalization analyses, followed by validation in independent single-cell RNA sequencing datasets and functional characterization using virtual gene knockout and phenome-wide association study (PheWAS) analyses. Integrative analyses prioritized three shared candidate genes, ZSCAN31, BTN3A2, and YLPM1, all showing strong colocalization support (PP·H4 > 0.8). Single-cell transcriptomic validation supported distinct cell type-specific patterns, with ZSCAN31 enriched in astrocytes and endothelial cells, BTN3A2 in microglia, and YLPM1 in oligodendrocytes. Virtual knockout of YLPM1 suggested perturbation of neurodevelopment-related pathways in SCZ and synaptic signaling pathways in MDD. These findings provide a cell type-resolved view of shared genetic architecture between SCZ and MDD and highlight candidate genes for further mechanistic and translational investigation.