{"title":"抑郁症缺乏和过度模式的神经活动差异:系统回顾和荟萃分析方案。","authors":"Liling Chen, Xinyu Jia, Jianjun Wang, Liling Li, Jianxiang Chen, Songjun Lin, Haotao Zheng, Xinbei Li, Xiude Qin, Lanying Liu, Hanqing Lyu","doi":"10.2196/68996","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Major depressive disorder (MDD) is a complex and heterogeneous condition. Current diagnosis relies on symptom-based assessments, leading to varied treatment responses. Data-driven approaches have attempted to identify MDD subtypes, but their clinical applicability remains limited. Traditional Chinese Medicine (TCM) provides a theory-driven classification system that categorizes MDD into syndrome subtypes of deficiency pattern and excess pattern, offering insights into the biological mechanisms and personalized treatment strategies.</p><p><strong>Objective: </strong>This systematic review and meta-analysis aims to identify potential neurobiological distinctions of TCM-based deficiency and excess patterns in MDD by examining differences in the brain activity by using various functional magnetic resonance imaging (fMRI) modalities, including resting-state and task-based fMRI, diffusion tensor imaging, and magnetic resonance spectroscopy.</p><p><strong>Methods: </strong>In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P), we will conduct a comprehensive search of 7 electronic databases (PubMed, Embase, Web of Science, Chinese Biological Medical Literature database, China National Knowledge Infrastructure, Chinese Wanfang database, and Chongqing VIP database) for studies published up to December 2024. Eligible studies will be screened by 2 independent reviewers based on predefined inclusion criteria, followed by data extraction and quality assessment. For the meta-analysis, resting-state fMRI studies will be analyzed in Montreal Neurological Institute space using Seed-based d Mapping-Permutation of Subject Images software (version 6.21), enabling a focused evaluation of brain activity differences in deficiency and excess MDD patterns.</p><p><strong>Results: </strong>The search and screening for the systematic literature review were completed in December 2024. This study relies on published, publicly accessible data. We found approximately 30 eligible studies in our preliminary search, suggesting that a quantitative meta-analysis is feasible. Data extraction, quality appraisal, and subsequent data synthesis will begin in September 2025. The review should be completed by December 2025, and the study results will be published in 2026.</p><p><strong>Conclusions: </strong>The results of this study may help to explain the neural mechanisms of depression's neurobiological subtypes from the perspective of TCM.</p><p><strong>Trial registration: </strong>PROSPERO CRD42023475178; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023475178.</p><p><strong>International registered report identifier (irrid): </strong>DERR1-10.2196/68996.</p>","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"14 ","pages":"e68996"},"PeriodicalIF":1.5000,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12491882/pdf/","citationCount":"0","resultStr":"{\"title\":\"Neural Activity Disparities in Deficiency and Excess Patterns of Depression: Protocol for a Systematic Review and Meta-Analysis.\",\"authors\":\"Liling Chen, Xinyu Jia, Jianjun Wang, Liling Li, Jianxiang Chen, Songjun Lin, Haotao Zheng, Xinbei Li, Xiude Qin, Lanying Liu, Hanqing Lyu\",\"doi\":\"10.2196/68996\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Major depressive disorder (MDD) is a complex and heterogeneous condition. 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Traditional Chinese Medicine (TCM) provides a theory-driven classification system that categorizes MDD into syndrome subtypes of deficiency pattern and excess pattern, offering insights into the biological mechanisms and personalized treatment strategies.</p><p><strong>Objective: </strong>This systematic review and meta-analysis aims to identify potential neurobiological distinctions of TCM-based deficiency and excess patterns in MDD by examining differences in the brain activity by using various functional magnetic resonance imaging (fMRI) modalities, including resting-state and task-based fMRI, diffusion tensor imaging, and magnetic resonance spectroscopy.</p><p><strong>Methods: </strong>In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P), we will conduct a comprehensive search of 7 electronic databases (PubMed, Embase, Web of Science, Chinese Biological Medical Literature database, China National Knowledge Infrastructure, Chinese Wanfang database, and Chongqing VIP database) for studies published up to December 2024. Eligible studies will be screened by 2 independent reviewers based on predefined inclusion criteria, followed by data extraction and quality assessment. For the meta-analysis, resting-state fMRI studies will be analyzed in Montreal Neurological Institute space using Seed-based d Mapping-Permutation of Subject Images software (version 6.21), enabling a focused evaluation of brain activity differences in deficiency and excess MDD patterns.</p><p><strong>Results: </strong>The search and screening for the systematic literature review were completed in December 2024. This study relies on published, publicly accessible data. We found approximately 30 eligible studies in our preliminary search, suggesting that a quantitative meta-analysis is feasible. Data extraction, quality appraisal, and subsequent data synthesis will begin in September 2025. 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引用次数: 0
摘要
背景:重度抑郁障碍(MDD)是一种复杂的异质性疾病。目前的诊断依赖于基于症状的评估,导致不同的治疗反应。数据驱动的方法试图识别重度抑郁症亚型,但其临床适用性仍然有限。中医提供了一个理论驱动的分类系统,将重度抑郁症分为虚证型和虚证型两种亚型,为了解其生物学机制和个性化治疗策略提供了新的思路。目的:本系统综述和meta分析旨在通过使用各种功能磁共振成像(fMRI)模式(包括静息状态和任务型fMRI、弥散张量成像和磁共振波谱)检查脑活动的差异,确定MDD中基于tcm的缺乏和过量模式的潜在神经生物学差异。方法:根据系统评价和meta分析方案首选报告项目(PRISMA-P),我们将全面检索截至2024年12月发表的7个电子数据库(PubMed、Embase、Web of Science、中国生物医学文献数据库、中国国家知识基础设施、中国万方数据库和重庆VIP数据库)。符合条件的研究将由2名独立审稿人根据预先确定的纳入标准筛选,然后进行数据提取和质量评估。为了进行荟萃分析,静息状态fMRI研究将在蒙特利尔神经学研究所空间中使用基于种子的受试者图像映射-排列软件(版本6.21)进行分析,从而能够集中评估缺乏和过度MDD模式的大脑活动差异。结果:系统文献综述的检索和筛选于2024年12月完成。这项研究依赖于公开发布的数据。在我们的初步研究中,我们发现了大约30个符合条件的研究,这表明定量荟萃分析是可行的。数据提取、质量评估和随后的数据综合将于2025年9月开始。评审工作将于2025年12月完成,研究结果将于2026年公布。结论:本研究结果有助于从中医角度解释抑郁症神经生物学亚型的神经机制。试验注册:PROSPERO CRD42023475178;https://www.crd.york.ac.uk/PROSPERO/view/CRD42023475178.International注册报告标识符(irrid): DERR1-10.2196/68996。
Neural Activity Disparities in Deficiency and Excess Patterns of Depression: Protocol for a Systematic Review and Meta-Analysis.
Background: Major depressive disorder (MDD) is a complex and heterogeneous condition. Current diagnosis relies on symptom-based assessments, leading to varied treatment responses. Data-driven approaches have attempted to identify MDD subtypes, but their clinical applicability remains limited. Traditional Chinese Medicine (TCM) provides a theory-driven classification system that categorizes MDD into syndrome subtypes of deficiency pattern and excess pattern, offering insights into the biological mechanisms and personalized treatment strategies.
Objective: This systematic review and meta-analysis aims to identify potential neurobiological distinctions of TCM-based deficiency and excess patterns in MDD by examining differences in the brain activity by using various functional magnetic resonance imaging (fMRI) modalities, including resting-state and task-based fMRI, diffusion tensor imaging, and magnetic resonance spectroscopy.
Methods: In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P), we will conduct a comprehensive search of 7 electronic databases (PubMed, Embase, Web of Science, Chinese Biological Medical Literature database, China National Knowledge Infrastructure, Chinese Wanfang database, and Chongqing VIP database) for studies published up to December 2024. Eligible studies will be screened by 2 independent reviewers based on predefined inclusion criteria, followed by data extraction and quality assessment. For the meta-analysis, resting-state fMRI studies will be analyzed in Montreal Neurological Institute space using Seed-based d Mapping-Permutation of Subject Images software (version 6.21), enabling a focused evaluation of brain activity differences in deficiency and excess MDD patterns.
Results: The search and screening for the systematic literature review were completed in December 2024. This study relies on published, publicly accessible data. We found approximately 30 eligible studies in our preliminary search, suggesting that a quantitative meta-analysis is feasible. Data extraction, quality appraisal, and subsequent data synthesis will begin in September 2025. The review should be completed by December 2025, and the study results will be published in 2026.
Conclusions: The results of this study may help to explain the neural mechanisms of depression's neurobiological subtypes from the perspective of TCM.