Zhang Yuxin, Liao Xiaoyu, Zhang Dahe, Xu Qingyu, Bu Lingtong, Shen Pei, Zheng Jisi, Yang Chi
Department of Oral Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China; Shanghai Key Laboratory of Orthopedic Implants, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Department of Rehabilitation Medicine, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China.
Int Dent J. 2025 Aug 4;75(5):100934. doi: 10.1016/j.identj.2025.100934.
Temporomandibular disorder (TMD) is the most common maxillofacial musculoskeletal disease involving various conditions such as chewing muscle disorders, disc displacement and osteoarthritis. However, its intricate pathogenesis remains unclear. Herein, by integrating evidence at the blood, tissue and cell levels, we aimed to investigate the association of cell death-related genes with TMD and predict potential target drugs.
Summary-level data on methylation, expression and protein abundance levels of cell death-related genes were used to identify drug-targeted genes at the blood level. FUSION tool was employed to identify and validate associations at the tissue level. Single-cell analysis was utilised to determine whether TMD-associated cell death genes exhibited higher expression in specific cell types. Drug prediction and molecular docking was used to confirm drug-related effects of TMD-associated cell death genes.
Integrating the overlapping results of summary-data-based Mendelian randomisation of mQTL, eQTL and pQTL at the blood level with Bayesian co-localisation analysis, 3 cell death-related genes were identified as causally associated with TMD: TIE1 (Tier 1), IFI16 (Tier 1) and GATM (Tier 2). Based on tissue-level FUSION analysis, we validated the specific effects of TIE1 and GATM genes in muscle-skeletal histology. Meanwhile, single-cell data were utilised to further analyse the cell type-specific enrichment of the 3 target genes in TMD. Finally, drug prediction and molecular docking identified 5 pharmacokinetic associations of 3 TMD-associated cell death genes.
Based on multilevel evidence of the blood, tissue and cell, we found that cell death-related genes TIE1, IFI16 and GATM were associated with TMD risk and predict potential target drugs such as fostamatinib. This study further elucidates the critical role of cell death-related molecules and drugs in TMD.
颞下颌关节紊乱病（TMD）是最常见的颌面肌肉骨骼疾病，涉及多种情况，如咀嚼肌紊乱、盘状移位和骨关节炎。然而，其复杂的发病机制仍不清楚。在此，通过整合血液、组织和细胞水平的证据，我们旨在研究细胞死亡相关基因与TMD的关联，并预测潜在的靶向药物。
利用细胞死亡相关基因的甲基化、表达和蛋白质丰度水平的汇总数据，在血液水平上鉴定药物靶向基因。采用FUSION工具在组织水平上鉴定和验证关联。利用单细胞分析来确定TMD相关的细胞死亡基因是否在特定细胞类型中表现出更高的表达。使用药物预测和分子对接来确认TMD相关细胞死亡基因的药物相关效应。
将基于汇总数据的血液水平上的mQTL、eQTL和pQTL的孟德尔随机化的重叠结果与贝叶斯共定位分析相结合，确定了3个与TMD因果相关的细胞死亡相关基因：TIE1（一级）、IFI16（一级）和GATM（二级）。基于组织水平的FUSION分析，我们验证了TIE1和GATM基因在肌肉骨骼组织学中的特定作用。同时，利用单细胞数据进一步分析了这3个靶基因在TMD中的细胞类型特异性富集。最后，药物预测和分子对接确定了3个TMD相关细胞死亡基因的5种药代动力学关联。
基于血液、组织和细胞的多水平证据，我们发现细胞死亡相关基因TIE1、IFI16和GATM与TMD风险相关，并预测了潜在的靶向药物，如福斯替尼。本研究进一步阐明了细胞死亡相关分子和药物在TMD中的关键作用。
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