Liao Chung-Chih, Wu Shih-An, Lee Chun-I, Liao Ke-Ru, Li Jung-Miao
Department of Integrated Chinese and Western Medicine, Chung Shan Medical University Hospital, Taichung 40201, Taiwan.
School of Chinese Medicine, College of Chinese Medicine, China Medical University, Taichung 40402, Taiwan.
J Affect Disord. 2025 Aug 15;383:167-178. doi: 10.1016/j.jad.2025.04.161. Epub 2025 Apr 29.
Major depressive disorder (MDD) is a highly prevalent psychiatric disorder with complex genetic underpinnings. While genome-wide association studies (GWAS) have identified multiple risk loci, pinpointing causal genes within the human brain remains challenging, particularly given the regulatory complexity across different cell types.
We performed summary data-based MR (SMR) and Bayesian colocalization analyses by integrating bulk-tissue eQTL data from 888 individuals with single-cell eQTL datasets from 192 donors representing major brain cell types (excitatory and inhibitory neurons, astrocytes, microglia, oligodendrocytes, OPCs/COPs, endothelial cells, and pericytes). GWAS summary statistics for MDD (170,756 cases and 329,443 controls) were used to assess the causal impact of gene expression. Sensitivity analyses, including the heterogeneity in dependent instruments (HEIDI) test and Steiger filtering, ensured robust inference.
In bulk tissue analyses, five genes (BTN3A2, SLC12A5, AREL1, GMPPB, and ZNF660) emerged as having robust causal evidence for MDD, displaying consistent MR signals and strong colocalization. Cell type-specific analyses revealed additional candidate genes in excitatory neurons (FLOT1, AL450423.1), astrocytes (AL121821.1), and oligodendrocytes (YLPM1, COP1).
Our integrative approach reveals that causal gene expression profiles differ markedly between bulk-tissue and specific brain cell types, emphasizing cellular heterogeneity in MDD pathogenesis and informing precision therapeutic strategies. These findings underscore the necessity of considering cell type-specific gene regulation when developing therapeutic interventions for MDD.
重度抑郁症（MDD）是一种高度流行的精神疾病，具有复杂的遗传基础。虽然全基因组关联研究（GWAS）已经确定了多个风险位点，但在人类大脑中确定因果基因仍然具有挑战性，特别是考虑到不同细胞类型之间的调控复杂性。
我们通过整合来自888名个体的大量组织eQTL数据和来自192名供体的单细胞eQTL数据集（代表主要脑细胞类型，即兴奋性和抑制性神经元、星形胶质细胞、小胶质细胞、少突胶质细胞、少突胶质前体细胞/少突胶质祖细胞、内皮细胞和周细胞），进行了基于汇总数据的孟德尔随机化（SMR）和贝叶斯共定位分析。使用MDD的GWAS汇总统计数据（170,756例病例和329,443例对照）来评估基因表达的因果影响。敏感性分析，包括依赖工具的异质性（HEIDI）检验和Steiger过滤，确保了可靠的推断。
在大量组织分析中，五个基因（BTN3A2、SLC12A5、AREL1、GMPPB和ZNF660）出现了对MDD具有强有力因果证据的情况，显示出一致的MR信号和强共定位。细胞类型特异性分析揭示了兴奋性神经元（FLOT1、AL450423.1）、星形胶质细胞（AL121821.1）和少突胶质细胞（YLPM1、COP1）中的其他候选基因。
我们的综合方法表明，大量组织和特定脑细胞类型之间的因果基因表达谱存在显著差异，强调了MDD发病机制中的细胞异质性，并为精准治疗策略提供了信息。这些发现强调了在开发MDD治疗干预措施时考虑细胞类型特异性基因调控的必要性。
