Systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for major depressive disorder

doi:10.12307/2026.212

Abstract

Abstract: BACKGROUND: The occurrence of major depressive disorder is typically associated with genetic and environmental factors. Currently, the diagnosis of major depressive disorder mainly relies on clinical interviews and symptom assessments, lacking clear and reproducible biological markers. This can lead to misdiagnosis and missed diagnoses, delaying the timing of treatment.
OBJECTIVE: To identify druggable genes that may act as potential therapeutic targets for major depressive disorder by conducting comprehensive genome-wide Mendelian randomization analysis.
METHODS: By integrating expression quantitative trait locus (eQTL) data and protein quantitative trait locus (pQTL) data from pharmacologically actionable genes with genome-wide association study (GWAS) data on major depressive disorder (including 177 377 cases and 445 321 controls), Mendelian randomization analysis was conducted to identify druggable genes that have a causal relationship with major depressive disorder. Additionally, enrichment analysis, protein-protein interaction network construction, drug target identification, and molecular docking simulations were performed to further explore potential therapeutic strategies.
RESULTS AND CONCLUSION: A total of 4 394 druggable genes were analyzed, and 21 druggable genes considerably associated with major depressive disorder were identified. Bayesian colocalization analysis indicated that BTN3A3 (butyrophilin subfamily 3 member A3), CISD1 (CDGSH iron sulfur domain 1), and PSMB4 (proteasome subunit beta type 4) had approximate Bayesian factor-based hypothesis 4 posterior probabilities (H4.abf) > 0.5, supporting the possibility of shared causal variations. Gene Ontology (GO) enrichment analysis revealed that these genes were mainly involved in several functional pathways related to major depression, including "antigen processing and presentation," "protein degradation and processing," "mitochondrial outer membrane," and "immune receptor activity." Protein-protein interaction network analysis showed a moderate degree of connectivity among the identified genes (21 nodes and 14 edges). Drug target identification highlighted gemcitabine (CID 60750), fucose (CID 17106), and isocorydine (CID 2826) as major candidate compounds, which were strongly associated with several key genes. Molecular docking analysis revealed stable drug-protein interactions, with isocorydine exhibiting the most stable binding energy with BTN3A3 (-52.74 kJ/mol). Furthermore, the combination of Mendelian randomization with genomics and structural biology analysis methods provides valuable decision-making support for target prioritization and drug repurposing, offering new ideas and directions for the efficient utilization of basic research resources and drug development for major depressive disorder.

Key words: drug target genes, major depressive disorder, druggable genes, colocalization analyses, Mendelian randomization, therapeutic targets

CLC Number:

Zhou Menghan, Liu Shuning, Jiang Tao, Sun Zhuangzhuang, Cao Lingling, Su Xin, Yu Cheng, Guo Junpeng. Systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for major depressive disorder[J]. Chinese Journal of Tissue Engineering Research, 2026, 30(22): 5886-5896.

Figures/Tables 6

可能性(图2)。 2.4 显著基因功能分析对21个潜在靶点进行GO富集分析，可以看出这些候选基因主要涉及“抗原加工与呈递”“蛋白质降解与加工”“线粒体外膜”“免疫受体活性”等多个与重度抑郁相关的功能通路(图3)。具体而言，生物过程中，“抗原加工与呈递”和“蛋白质水解过程”显著富集，提示候选基因可能调控重度抑郁症患者的免疫激活状态与细胞应激反应，在抗原呈递过程在该过程中可能发挥促进作用[35]；细胞成分中，多个候选基因富集于“线粒体外膜”与“蛋白酶体复合体”，线粒体功能异常被认为是抑郁症的重要发病机制之一，尤其在中枢神经系统中能量代谢不稳可影响神经递质合成与神经元可塑性[36]，说明它们可能参与调控细胞能量代谢和蛋白质稳态，与慢性应激诱导下的能量障碍、线粒体功能紊乱及突触结构异常密切相关；分子功能中，富集项如“免疫受体活性”与“结合酶调节活性”提示候选基因可能通过调节免疫通路信号的识别与转导，免疫受体在细胞识别炎症信号并介导跨膜信息传导中扮演关键角色，说明它们可能与慢性疼痛或慢性低度炎症密切相关[37]。为深入探究这些可成药基因在抑郁症中潜在的治疗机制，进一步进行了KEGG通路分析。结果显示，重度抑郁相关的显著可成药基因主要集中于免疫调控、代谢应答和信号转导相关的关键通路。例如，“抗原加工与呈递”和“T细胞受体信号通路”均与重度抑郁症中常见的免疫激活及外周炎症反应密切相关。慢性应激状态下，外周免疫系统活化和T细胞功能失衡可通过炎症因子影响中枢神经系统功能，导致情绪调节失衡。“鞘磷脂信号通路”和“AMP依赖的蛋白激酶信号通路”与能量代谢和细胞存活密切相关。研究表明，鞘磷脂代谢失衡与神经元膜结构损伤和凋亡有关，而AMP依赖的蛋白激酶作为能量代谢调控的核心分子，可影响神经元可塑性、突触传递和应激反应，在抑郁症模型中已被证实是潜在的抗抑郁药物靶点[38]。另外，其他通路如“催产素信号”则直接与情绪调控、社会行为和压力反应相关，催产素水平下降已在多项抑郁症临床研究中观察到[39]，提示该调节通路可能在重度抑郁治疗中具有潜力(图4)。 2.5 靶蛋白的蛋白质-蛋白质相互作用网络利用STRING数据库构建了包含这 21个药物靶基因的蛋白质-蛋白质相互作用网络，如图5所示。该网络包含代表蛋白质的 21个节点和代表相互作用的14条边，网络的局部聚类系数为 0.508，表明所鉴定蛋白间存在中等程度的连通性。 BTN3A3、PSMB4与CISD1在网络中具有较多的直接互作伙伴，处于互作网络的中心区域，提示这些蛋白可能为调控抑郁症关键路径的“中枢节点”。其中，PSMB4作为蛋白酶体20S核心粒子的组成部分，广泛参与细胞内蛋白降解，与神经免疫调节密切相关[40]。CISD1则与线粒体铁代谢调控有关，在调节神经元氧化应激反应中可能发挥重要作用[41]。这些关键蛋白在网络中的突出位置，提示其可能在重度抑郁的发病机制中处于核心调控地位，为靶向干预提供了理论依据。 2.6 药物富集结果利用药物特征基因集数据库鉴定潜在的治疗化合物，根据关联基因的数量筛选出前5位候选药物作为潜在的治疗药物(表2)。值得注意的是，吉西他滨(CID 60750)、岩藻糖(CID 17106)和异古柯碱(CID 2826)的结果最为突出，它们分别与BTN3A3、PSMB4和CISD1相关联，并与大多数已鉴定的可成药基因存在联系，表明它们具有调节重度抑郁症相关生物学通路的潜力。 2.7 候选药物的分子对接分析分子对接的结合能计算揭示了5个稳定的药物-蛋白质相互作用(表3)，每次相互作用产生结合能，结合能越低，结合效果越好、亲和力越高。对接结果的可视化分别为结合全景图与局部细节图，突出了参与结合的关键氨基酸残基以及氢键长度(图6)。其中，BTN3A3表现出最低的结合能(-52.74 kJ/mol)，表明它具有高度稳定的结合亲和力及潜在的治疗相关性。在BTN3A3-异古柯碱对接模型中，异古柯碱通过2个氢键与残基Ser76和Glu112形成稳定连接，同时形成疏水作用网络覆盖Val80与Ile115，有助于稳定其构象[42]；在CISD1-岩藻糖对接模型中，通过极性相互作用与残基Asn39和Tyr42形成稳定键合，提示该位点可能为药物敏感结构域[43]；在PSMB4-吉西他滨对接模型中，吉西他滨通过氢键与Thr20和Gln26结"

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