Association between Mitochondrial DNA Levels and Depression: A Systematic Review and Meta-Analysis

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Many studies have found that mitochondrial DNA(mtDNA) content changes in the peripheral blood or cerebrospinal fluid of patients with depression. Some investigators ask whether it has a clear association between mtDNA and depression. Thus, we conducted a meta-analysis to comprehensively assess the evidence for mtDNA's effect on depression. Methods PubMed, Embase, the Cochrane Library, the Web of Science, Wanfang Database, SINOMED, China Science and Technology Journal Databaseand China National Knowledge Infrastructure were searched up to 13 March 2023. RevMan (version 5.4) and Stata (version 16.0) software were used for meta-analysis. Besides, publication bias was assessed with funnel plots, Begg’s test and Egger’s test. Results A total of 1372 patients were included in this study, including 686 patients with depression and 686 healthy controls. A meta-analysis including eleven studies showed significantly higher mtDNA level in depression compared with healthy controls [standardised mean difference(SMD) = 0.42, 95% confidence intervals(CI): 0.16, 0.69]. Conclusions Our study demonstrates significantly higher mtDNA leveles in depression comparison to healthy controls. Registration number: PROSPERO CRD42023414285. depression mtDNA mitochondria meta-analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Depression is a heterogenous disorder with symptoms spanning multiple domains of emotion and behavior, including but not limited to, changes in mood, memory loss, anhedonia, insomnia, fatigue, decreased appetite and libido, and in severe cases, self-harm and suicide [ 1 ] . It is a serious threat to people's mental and physical health, and is the leading cause of disability worldwide [ 2 ] . Depression is common and frequently recurrent, with a global prevalence of 4.4% [ 3 ] . The lifetime prevalence rate of depression in China was 6.8%, among which major depression was 3.4% [ 4 ] . However, due to the increasing pressure of people's study, life and society, the incidence of depression increases year by year. About one third of patients go into remission after taking a selective serotonin reuptake inhibitor, only 25–27% remit after subsequent treatment with another antidepressant, and up to 40% will be treatment-resistant [ 5 ] . An important barrier to efective care for depression is inaccurate assessment and that people who are depressed are ofen not correctly diagnosed [ 6 ] . Currently, depression is evaluated on the basis of medical history, clinical symptoms, and specific evaluation scales, and there are no objective biomarkers for the diagnosis of depression [ 7 ] . Therefore, the search for biomarkers for effective diagnosis of depression is an urgent scientific problem to be solved. At present, the biological mechanisms of depression iremains elusive. Research on depression is no longer limited to classical hypotheses such as monoaminergic neurotransmitters and inflammatory mechanisms, but more and more attention is paid to the relationship between mitochondrial energy metabolism and depression. Depressed patients usually exhibit altered inflammatory markers, mitochondrial membrane depolarization, oxidized mtDNA, and thus high levels of both central and peripheral reactive oxygen species (ROS) [ 8 ] . Mitochondria are the “energy factories” of cells, maintaining cellular stability by regulating calcium homeostasis, participating in the production of ROS and mediating apoptosis. However, defective mitochondria increase mitochondrial ROS (mtROS) production and cell-free mtDNA release [ 9 ] . MtDNA is the genetic material of mitochondria, which can be involved in mediating mitochondrial energy metabolism by encoding many critical proteins for the assembly and activity of the mitochondrial respiratory complexs [ 10 ] . The mtDNA copy number could reflect the level of mtDNA damage; it is thought to be an indicator of mitochondrial function [ 11 ] . With growing evidence of mitochondrial dysfunction as a potential molecular alteration in depression. Therefore, we have performed a systematic review and meta-analysis investigating the current literature of all papers that measured mtDNA for depression. To our knowledge, this is the first study to include global data to describe the association between mtDNA and depression. 2. Methods 2.1 Study registration This systematic review and meta-analysis was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [ 12 ] . The review protocol was registered in PROSPERO, number CRD42023414285. 2.2 Literature search strategy We searched 4 English electronic databases and 4 Chinese literature databases for studies published from inception to March 13, 2023: PubMed, EMBASE, Cochrane Library, Web of Science, Wanfang database, SINOMED, VIP database and CNKI. And there was no restriction for language. The keywords used in our search strategy were (“mtDNA” OR “mitochondrial DNA”) AND ( “depression” OR “depressive disorder” ). To avoid missing any publications, we assessed the references of all the reviewed publications. This work was completed by two independent reviewers (WL and YZ) and, in cases where they had a disagreement, a third investigator (LZ) was asked for advice. Moreover, we screened the references of included papers, full texts, and bibliographies of all potential articles including relevant reviews and meta-analysis to identify additional eligible studies. 2.3 Inclusion and exclusion criteria The inclusion criteria were prespecified as follows: (a) the subjects were patients with depression; (b) cross-sectional, case–control or longitudinal study; (c) all studies reported mtDNA levels using mean (M), standard deviation (SD) and sample size; (d) all studies included both depressive patients (cases) and healthy participants (controls); and (e) if the same datasets were found in the search process, only the paper with more complete finding was included in our meta-analysis. Studies were excluded if any of the following criteria were observed: (a) duplications; (b) no measurement of mtDNA in humans; (c) no healthy controls group; (d) case reports, review articles, systematic reviews, meta-analyses, commentaries, editorials, or meeting abstracts; or (e) an in vivo or in vitro study. 2.4 Data extraction NoteExpress software was used for literature management. All data were extracted independently by two reviewers (WL and YZ), and disagreements were resolved by discussion, involving a third person (LZ) if necessary. Study information of included studies was recorded, including the first author, publication year, participant characteristics, sample size, sample source, region, mtDNA contents. 2.5 Quality assessment Two authors (YC and SW) independently assessed the risk of bias and methodological quality of the included studies using the Newcastle-Ottawa Scale (NOS), an evidence-based quality assessment tool for systematic reviews of prospective cohort studies [ 13 ] . There are 8 items on this scale. The maximum score of this scale is 9 points, and studies with a score ≥ 6 points are rated as high quality [ 14 ] . 2.6 Data synthesis and statistical analysis All data were analyzed using Cochrane Collaboration software (Rev Man 5.4) and Stata (version 16.0). The effect size was estimated using the SMD, since the mtDNA concentrations were measured with different units of measurement (units/µL, copies/µL, C/µL and some articles didn’t mention units) in the analyzed reports. In addition, I 2 was used to test for heterogeneity amongst the studies. I 2 values of 0–25%, 26–50%, 51–75%, and 75–100% were classified as indicating no, low, moderate, and substantial heterogeneity, respectively [ 15 , 16 ] . In order to determine the source of heterogeneity, the subgroup analysis was performed according to the specimen type (plasma, or not plasma), detection method [quantitative reverse transcription polymerase chain reaction (qRT-PCR), quantitative polymerase chain reaction (qPCR) or real-time fluorescence polymerase chain reaction (rt-PCR)] and location (Asia, Europe, or North America) to identify potential sources of heterogeneity. We carried out sensitivity analyses in order to evaluate reliable results. Moreove, Egger’s test and Begg’s test were adopted to investigate publication bias. A z-score was used to evaluate effect sizes and a p-value of < 0.05 was considered as statistically significant. All statistical tests were two-tailed with 95% CI, and the significance level was set at P < 0.05. 2.7 Ethics. Because patient privacy was not involved in the present study, ethical approval was not required. 3. Results 3.1 Study selection The search of 8 databases identified 1104 articles for further evaluation (11 from CNKI, 2 from WANFANG, 0 from VIP, 4 from SINOMED, 559 from PubMed, 320 from Embase, 203 from the Web of Science, and 5 from the Cochrane Library), of which 65 were removed after reviewing due to duplicate records. After reading the titles and abstracts, 951 were excluded for various reasons. Finally, only ten studies [ 17 – 26 ] met our inclusion criteria after screening full texts. The flow diagram is found in Fig. 1 . 3.2 Study characteristics and quality assessment In total, ten articles (from 1997 to 2023) reported on 11 studies, including 686 patients with depression and 686 healthy controls. Most trials were performed in Asia (2 in China, 1 in Japan, and 1 in Korea) and Europe (2 in Sweden, 1 in Ireland, 1 in Germany). However, trials were also performed in North America(1 in the United States, 1 in Canada). The mtDNA levels were detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR), real-time fluorescence polymerase chain reaction (rt-PCR) or quantitative polymerase chain reaction (qPCR). The basic characteristics of the included literature are presented in Table 1 . For quality evaluation of the included studies, the NOS was used (Table 1 ), which revealed that the quality of most articles were relatively high. Only one study, Kato T et al [ 26 ] , presented with NOS score of five, due to lack of provided information. Table 1 Characteristics of studies included in the present meta-analysis ID First author Year location Sample size Specimen Detection Method Study quality Depression Controls 1 Karen M Ryan [ 17 ] 2023 Ireland 100 89 whole blood qRT-PCR 7 2 Emi Ampo [ 18 ] 2022 USA 9 16 Plasma qRT-PCR 7 3 Vanessa F Gonçalves [ 19 ] 2021 Canada 32 21 Plasma qRT-PCR 7 4 Johan Fernström [ 20 ] 2021 Sweden 47 11 Plasma qRT-PCR 7 5 Jae Kyung Chung [ 21 ] 2021 Republic of Korea 118 116 peripheral blood qPCR 7 6 Kerstin Kuffner [ 22 ] 2020 Germany 16 16 Skin Fibroblasts qRT-PCR 7 7a Daniel Lindqvist [ 23 ] 2018 Sweden 50 55 Plasma rt-PCR 7 7b Daniel Lindqvist [ 23 ] 2018 Sweden 50 55 PBMCs rt-PCR 7 8 Cheng Chen Chang [ 24 ] 2015 China 40 70 Leukocyte rt-PCR 6 9 Ying He [ 25 ] 2014 China 210 217 Leukocyte qPCR 6 10 Kato T [ 26 ] 1997 Japan 14 20 Leukocyte qPCR 5 3.3 MtDNA Levels in Depression There is a significant difference in mtDNA levels favouring a higher value in depression compared with healthy controls with a SMD of 0.42 (95% CI: 016, 0.69), and an overall effect of Z = 3.13 ( P < 0.05). Another important finding is that the heterogeneity is substantial (I 2 = 79%). The overall meta-analysis output is illustrated in Fig. 2 as a forest plot. 3.4 Subgroup analysis We performed subgroup analysis based on specimen type (plasma or not plasma), detection method (qRT-PCR, qPCR or rt-PCR) and location (Asia, Europe, or North America). According to the specimen type, there was a significant difference between depression and healthy controls in plasma (SMD = 0.54, P < 0.05), but not in other sample types (Fig. 3 A). Subgroup analysis of detection methods showed that compared with healthy people, there was a significant difference in patients with depression(SMD = 0.52, P < 0.05) using qRT-PCR (Fig. 3 B). In Europe (SMD = 0.46, P < 0.05) and North America (SMD = 0.79, P < 0.05), mtDNA levels were significantly higher in depression than in healthy controls, with no statistical difference in Asia (Fig. 3 C). 3.5 Publication bias analysis and sensitivity analysis There was no publication bias in our study according to Egger’s regression test ( P = 0.478) and Begg’s continuity corrected test ( P = 0.876). And we found no obvious asymmetry appeared in the funnel plot (Fig. 4 ). Sensitivity analysis was performed to assess whether the results of this meta-analysis were stable. The results showed no obvious effect after deleting the studies one by one, which suggested that our study results were stable and credible. 4. Discussion 4.1 Mitochondrial energy metabolism disorders are involved in depression Depression has become a serious threat to people's mental and physical health. It is one of the most significant public health problems facing the world today. Among the clinical manifestations of depression, in addition to loss of pleasure and cognitive impairment, the more prominent somatic hypokinetic symptoms are fatigue, insomnia, appetite loss and so on [ 27 ] . Hypodynamic symptoms in depressed patients coincide with insufficient mitochondrial ATP production. Therefore, some scholars have proposed that mitochondrial energy metabolism disorder is involved in the pathogenesis of depression [ 28 ] . Mitochondria, as the principal place of cellular energy metabolism and ROS generation, maintain the mass balance of mitochondria and ensure normal function through continuous biosynthesis, division, fusion and autophagy. Mitochondrial dysfunction includes reduced ATP synthesis, respiratory chain dysfunction, structural abnormalities and excessive occurrence of apoptosis [ 29 ] . Previous studies have shown that disruption of mitochondrial energy metabolism is common in chronic stress animal models and patients with depression [ 30 , 31 ] .When Gardner et al [ 32 ] studied the muscle tissue of depressed patients, they found that low ATP levels were closely associated with severe physical symptoms. In the hippocampus and gastrocnemius muscle of rats, chronic unpredictable mild stress (CUMS) reduced ATP content, Na/K-ATPase activity, respiratory chain complex I, III, and IV activities, and impaired mitochondrial ultrastructure [ 33 ] . Mitochondrial oxidative phosphorylation produces large amounts of ROS, and the resulting oxidative stress can lead to mitochondrial dysfunction [ 34 ] . Chen et al [ 35 ] used lipopolysaccharide to induce depression-like behavior in mice, and found that the generation of depression-like behavior was related to mitochondrial oxidative damage. In addition, yuan et al [ 33 ] found significantly more swollen mitochondria, disrupted cristae and broken mitochondrial membranes in hippocampus and gastrocnemius tissue of CUMS rats. It is well known that normal mitochondrial membrane potential (MMP) is a prerequisite for the formation of ATP through oxidative phosphoric acid acylation. The stability of MMP plays an important role in maintaining the normal physiological function of cells. Javani et al [ 36 ] found that MMP in the prefrontal cortex of depressed rats decreased, whereas mitochondrial transplantation improved it. Li et al [ 37 ] found ginsenoside Rg1 reduced microglial activation and mitochondrial dysfunction to alleviate depression-like behaviour via the GAS5/EZH2/SOCS3/NRF2 axis. In summary, mitochondrial dysfunction plays an significant role in the pathogenesis of depression, which may help to provide new perspectives on the diagnosis and treatment of depression. 4.2 MtDNA, mitochondrial energy metabolism disorder and depression In addition to the above mentioned ATP synthesis, oxygen free radical generation and MMP changes, the study on the molecular level of mitochondrial energy metabolism also includes the changes of mtDNA levels. As the genetic material of mitochondria, mtDNA is the most frequently measured biomarker for mitochondrial dysfunction [ 38 ] . However, there is no univocal explanation for mtDNA levels, and either a decrease or an increase in mtDNA levels may indicate mitochondrial dysfunction [ 39 ] . MtDNA copies number (mtDNAcn) is an effective indicator of a cellular ability to generate ATP by mitochondrial oxidative phosphorylation [ 40 ] . Thus, it is possible to indirectly assess mitochondrial function by measuring mtDNA levels. A study suggests that higher mtDNAcn may represent a marker of poor mitochondrial health or mitochondrial allostatic load, which might explain the findings of higher mtDNAcn in relation to depression [ 41 ] . On the one hand, oxidative stress leads to altered mitochondrial membrane permeability, which can elicit increased mtDNAs release [ 18 ] . On the other hand, upon mitochondrial stress and defective mitophagy, mtDNAs can be released out of mitochondria and can cause inflammation [ 42 ] . What's more, mitochondrial dysfunction may contribute to depression by promoting oxidative stress and inflammation [ 43 ] . A study concerning cell-free mtDNA suggests that its elevated copy number may be associated with depression and suicide attempts [ 44 ] . Cai et al [ 45 ] pioneered the discovery that major depressive disorder was associated with greater amount of mtDNA in leukocytes from saliva samples and blood. Meanwhile, they found that mitochondrial function is altered in tissues with increased mtDNA [ 45 ] . Therefore, mtDNA is a plausible biomarker candidate for further investigation of its role in depression. 4.3 Discussion of meta-analysis results With the above information in mind, we provided a comprehensive assessment to enrich our understandings of altered mtDNA content in depression. In this study, we have focused on the association between mtDNA levels and depression by carrying out a systematic review and meta-analysis of 11 eligible studies. Our study conducted in 686 depressive patients and 686 healthy controls showed that depressed people had higher levels of mtDNA compared to healthy people (SMD = 0.42, 95% CI: 016, 0.69). However, the published literature has reported conflicting findings. Four studies [ 17 , 19 , 21 , 23 ] found higher mtDNA levels for persons with depression compared with healthy controls. In contrast, seven [ 18 , 20 , 22 , 23 , 25 , 26 ] studies found no significant difference between depressed patients and healthy controls. However, the overall results showed that depressed patients had higher mtDNA than healthy individuals. We consider that the discrepancies reported in the above studies could be related to the different age span, detection method, tissue types ,the diversity in ethnicity and so on. Heterogeneity was noted in this meta-analysis. As a result, we observed significant heterogeneity through subgroup analysis by specimen type, detection method and location. The range of mtDNAcn may be affected by different methods used for DNA isolation and extraction [ 46 ] . Moreover, mtDNA is heterogeneous, which is influenced by different environmental and genetic contexts [ 47 ] . Alternatively, in different individuals, some tissues require more or less mtDNAcn than others to maintain normal function, so the amount of mtDNAcn in different tissues or organs is different [ 38 ] . Consequently, more research would be required to determine the most appropriate sample (plasma or other samples) and the best detection method to test mtDNA. Next, funnel plot, Begg’s test and Egger’s test suggested that no obvious publication bias in this study. Finally, we performed a sensitivity analysis, which showed that the results were stable and reliable. Most of the studies included were cross-sectional in design. Therefore, future studies will need to be initiated to design more longitudinal studies to identify mtDNA levels as a biomarker for predicting depression. 4.4 Strengths and limitations To our knowledge, we conducted the first systematic review and meta-analysis of mtDNA level with a specific focus on depression. Our study found that the levels of mtDNA in patients with depression are significantly higher than in healthy controls. At the same time, our article illustrates the link between mitochondrial dysfunction and depression. Nonetheless, there were some limitations. First, the interpretation of our study might be limited by heterogeneity, although this is a frequent phenomenon in many meta-analysis. Second, although we used SMD to estimate the effect size, the inconsistency in biomarker units, as well as different methods of analysis of the same type of biomarkers could affect the statistical conclusions drawn from this meta-analysis. Third, our study did not explore all the variables that affect mtDNA levels, such as the environment and concomitant diseases. Finally, numerical information provided in some studies was not sufficient to carry out meta-analysis, so we did not include them. It could have an impact on the results. 5. Conclusion In conclusion, here, we report a systematic review and meta-analysis suggesting mtDNA concentrations in patients with depression were higher than healthy controls. Thus, it is plausible to infer that higher mtDNA levels are associated with depression. However, more high-quality and large-scale studies are required for further analysis. Declarations Funding This work was supported by National Natural Science Foundation of China (No.U21A20401). Availability of data and materials The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors. Author contributions WL: research design, conceptualization, writing (original draft). LZ: review and editing. YZ and YC: data management, data analysis. WL and SW: methodology, software application. RG: project administration and funding acquisition. All authors contributed to and have approved the final version of the manuscript. Competing interests All authors declared no competing interests. Acknowledgements We thank Dr. Lingqun Zhu and Dr. Rongjuan Guo for providing professional guidance on an earlier draft of this manuscript and funding this study. Ethics approval and consent to participate (Not applicable) Consent for publication (Not applicable) References Tartt AN, Mariani MB, Hen R, Mann JJ, Boldrini M. Dysregulation of adult hippocampal neuroplasticity in major depression: pathogenesis and therapeutic implications. Mol Psychiatry 2022 Jun;27(6):2689–99. doi: 10.1038/s41380-022-01520-y . Friedrich MJ. Depression Is the Leading Cause of Disability Around the World. JAMA. 2017 Apr 18;317(15):1517. doi: 10.1001/jama.2017.3826 . Marwaha S, Palmer E, Suppes T, Cons E, Young AH, Upthegrove R. Novel and emerging treatments for major depression. Lancet. 2023 Jan;14(10371):141–53. 10.1016/S0140-6736(22)02080-3 . Epub 2022 Dec 16. Huang Y, Wang Y, Wang H et al. 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Front Med (Lausanne). 2022 Dec;14:9:1011819. 10.3389/fmed.2022.1011819 . Picard M. Blood mitochondrial DNA copy number: What are we counting? Mitochondrion. 2021 Sep;60:1–11. doi: 10.1016/j.mito.2021.06.010 . Epub 2021 Jun 19. St John JC. Mitochondrial DNA copy number and replication in reprogramming and differentiation. Semin Cell Dev Biol. 2016 Apr;52:93–101. 10.1016/j.semcdb.2016.01.028 . Epub 2016 Jan 28. Verhoeven JE, Révész D, Picard M, Epel EE, Wolkowitz OM, Matthews KA, Penninx BWJH, Puterman E. Depression, telomeres and mitochondrial DNA: between- and within-person associations from a 10-year longitudinal study. Mol Psychiatry 2018 Apr;23(4):850–7. doi: 10.1038/mp.2017.48 . Epub 2017 Mar 28. Picca A, Calvani R, Coelho-Junior HJ, Marzetti E. Cell Death and Inflammation: The Role of Mitochondria in Health and Disease. Cells. 2021 Mar 3;10(3):537. doi: 10.3390/cells10030537 . PMID: 33802550; PMCID: PMC7998762. Raison CL, Borisov AS, Majer M, Drake DF, Pagnoni G, Woolwine BJ, Vogt GJ, Massung B, Miller AH. Activation of central nervous system inflammatory pathways by interferon-alpha: relationship to monoamines and depression. Biol Psychiatry 2009 Feb 15;65(4):296–303. doi: 10.1016/j.biopsych.2008.08.010. Epub 2008 Sep 18. Lindqvist D, Fernström J, Grudet C, Ljunggren L, Träskman-Bendz L, Ohlsson L, Westrin Ã. Increased plasma levels of circulating cell-free mitochondrial DNA in suicide attempters: associations with HPA-axis hyperactivity. Transl Psychiatry. 2016 Dec 6;6(12):e971. doi: 10.1038/tp.2016.236 . Cai N, Chang S, Li Y et al. Molecular signatures of major depression. Curr Biol. 2015 May 4;25(9):1146-56. doi: 10.1016/j.cub.2015.03.008 . Epub 2015 Apr 23. Fazzini F, Schöpf B, Blatzer M, Coassin S, Hicks AA, Kronenberg F, Fendt L. Plasmid-normalized quantification of relative mitochondrial DNA copy number. Sci Rep 2018 Oct 18;8(1):15347. doi: 10.1038/s41598-018-33684-5 . Pereira CV, Gitschlag BL, Patel MR. Cellular mechanisms of mtDNA heteroplasmy dynamics. Crit Rev Biochem Mol Biol. 2021 Oct;56(5):510–25. Epub 2021 Jun 13. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 22 Nov, 2023 Read the published version in BMC Psychiatry → Version 1 posted Editorial decision: Major revision 28 Sep, 2023 Reviews received at journal 24 Sep, 2023 Reviewers agreed at journal 20 Sep, 2023 Reviews received at journal 23 Aug, 2023 Reviewers agreed at journal 13 Aug, 2023 Reviewers invited by journal 11 Aug, 2023 Editor assigned by journal 11 Aug, 2023 Editor invited by journal 05 Jul, 2023 Submission checks completed at journal 05 Jul, 2023 First submitted to journal 27 May, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2990380","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":215878431,"identity":"3b411038-4196-43af-834b-97a18ed1ff3d","order_by":0,"name":"Wenhui Li","email":"","orcid":"","institution":"Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wenhui","middleName":"","lastName":"Li","suffix":""},{"id":215878433,"identity":"b56c99a4-9bfa-4baa-a4ef-c79b425a4b57","order_by":1,"name":"Lingqun Zhu","email":"","orcid":"","institution":"Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing Key Laboratory of Dongzhimen Hospital, Beijing University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lingqun","middleName":"","lastName":"Zhu","suffix":""},{"id":215878434,"identity":"de9c1dd5-5e56-41c4-9ffd-9d6812c17856","order_by":2,"name":"Yi Chen","email":"","orcid":"","institution":"Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Chen","suffix":""},{"id":215878436,"identity":"cf895f6b-50aa-4e6e-b94e-177574b762e1","order_by":3,"name":"Yudi Zhuo","email":"","orcid":"","institution":"Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yudi","middleName":"","lastName":"Zhuo","suffix":""},{"id":215878437,"identity":"6dcf63a5-5514-4645-97b6-2a9457eb01e7","order_by":4,"name":"Shurun Wan","email":"","orcid":"","institution":"Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shurun","middleName":"","lastName":"Wan","suffix":""},{"id":215878439,"identity":"55023a1b-e8ce-45c6-9e4c-697a1aa0793b","order_by":5,"name":"Rongjuan Guo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDCCwwdgLBCjQkJOnqCWYwnIWs5YGBs2EK8FCBjbKhIZDuBQCQN8x9ivSXzcY5Mn73jG8HPhPIkExgbmh49u4NEieYynTHLGs7RiwwNnjKVnbpPIY2dgMzbOwaPF4H5PmjTPgcOJGxvOGEjzbpMoZmzgYZPGq+UYD1yL8W/eORKJDQcIamE/BtYyn+GMmTRvAxFagH5htpxxIC1xA8OxMmueYxLGhs0E/AIMsYc3PhywSZw/4/Dm2zw1dXLy7M0PH+PTwsDAYwBx4Y0DUAFmvMpBgP0BmJLvbyCodBSMglEwCkYoAAACCVEhfYn37QAAAABJRU5ErkJggg==","orcid":"","institution":"Dongfang Hospital Affiliated to Beijing University of Chinese Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Rongjuan","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2023-05-28 02:14:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2990380/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2990380/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12888-023-05358-8","type":"published","date":"2023-11-22T15:00:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":39855170,"identity":"b8dd81e8-9bc7-4a42-bcf6-b0e826079dd0","added_by":"auto","created_at":"2023-07-11 14:06:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":134587,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram of study selection\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2990380/v1/aa6c8f37ca19204dc787a822.png"},{"id":39855169,"identity":"1f099d47-e2e7-44f8-b5ff-f586ba3a857d","added_by":"auto","created_at":"2023-07-11 14:06:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":20068,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot output of meta-analysis with all ten articles of mtDNA in depression, composed of eleven comparisons.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-2990380/v1/c285942e9734801879ea7d8a.png"},{"id":39855171,"identity":"88b15c4f-0383-4244-8abc-25fcf2211c41","added_by":"auto","created_at":"2023-07-11 14:06:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":886622,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A). Subgroup analysis according to the specimen type.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(B). Subgroup analysis according to the detection method.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(C). Subgroup analysis according to the location.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"F3.png","url":"https://assets-eu.researchsquare.com/files/rs-2990380/v1/bb4b31a8569911271d501875.png"},{"id":39855172,"identity":"76a65188-5dea-4d9e-bd97-7b1f7f319574","added_by":"auto","created_at":"2023-07-11 14:06:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5462,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunnel plot of the studies included in the meta-analysis relevant to depression.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-2990380/v1/62d48c4c79f49d95b769acfe.png"},{"id":47146200,"identity":"1919d982-33f8-4d3b-8284-f113c218949f","added_by":"auto","created_at":"2023-11-27 15:03:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1027052,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2990380/v1/16e8910f-9feb-41e9-a80f-b55e777eda9c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between Mitochondrial DNA Levels and Depression: A Systematic Review and Meta-Analysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDepression is a heterogenous disorder with symptoms spanning multiple domains of emotion and behavior, including but not limited to, changes in mood, memory loss, anhedonia, insomnia, fatigue, decreased appetite and libido, and in severe cases, self-harm and suicide\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. It is a serious threat to people\u0026apos;s mental and physical health, and is the leading cause of disability worldwide\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Depression is common and frequently recurrent, with a global prevalence of 4.4%\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. The lifetime prevalence rate of depression in China was 6.8%, among which major depression was 3.4%\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. However, due to the increasing pressure of people\u0026apos;s study, life and society, the incidence of depression increases year by year. About one third of patients go into remission after taking a selective serotonin reuptake inhibitor, only 25\u0026ndash;27% remit after subsequent treatment with another antidepressant, and up to 40% will be treatment-resistant\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. An important barrier to efective care for depression is inaccurate assessment and that people who are depressed are ofen not correctly diagnosed\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Currently, depression is evaluated on the basis of medical history, clinical symptoms, and specific evaluation scales, and there are no objective biomarkers for the diagnosis of depression\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Therefore, the search for biomarkers for effective diagnosis of depression is an urgent scientific problem to be solved.\u003c/p\u003e\n\u003cp\u003eAt present, the biological mechanisms of depression iremains elusive. Research on depression is no longer limited to classical hypotheses such as monoaminergic neurotransmitters and inflammatory mechanisms, but more and more attention is paid to the relationship between mitochondrial energy metabolism and depression. Depressed patients usually exhibit altered inflammatory markers, mitochondrial membrane depolarization, oxidized mtDNA, and thus high levels of both central and peripheral reactive oxygen species (ROS)\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Mitochondria are the \u0026ldquo;energy factories\u0026rdquo; of cells, maintaining cellular stability by regulating calcium homeostasis, participating in the production of ROS and mediating apoptosis. However, defective mitochondria increase mitochondrial ROS (mtROS) production and cell-free mtDNA release\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. MtDNA is the genetic material of mitochondria, which can be involved in mediating mitochondrial energy metabolism by encoding many critical proteins for the assembly and activity of the mitochondrial respiratory complexs\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. The mtDNA copy number could reflect the level of mtDNA damage; it is thought to be an indicator of mitochondrial function\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWith growing evidence of mitochondrial dysfunction as a potential molecular alteration in depression. Therefore, we have performed a systematic review and meta-analysis investigating the current literature of all papers that measured mtDNA for depression. To our knowledge, this is the first study to include global data to describe the association between mtDNA and depression.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study registration\u003c/h2\u003e \u003cp\u003eThis systematic review and meta-analysis was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. The review protocol was registered in PROSPERO, number CRD42023414285.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Literature search strategy\u003c/h2\u003e \u003cp\u003eWe searched 4 English electronic databases and 4 Chinese literature databases for studies published from inception to March 13, 2023: PubMed, EMBASE, Cochrane Library, Web of Science, Wanfang database, SINOMED, VIP database and CNKI. And there was no restriction for language. The keywords used in our search strategy were (\u0026ldquo;mtDNA\u0026rdquo; OR \u0026ldquo;mitochondrial DNA\u0026rdquo;) AND ( \u0026ldquo;depression\u0026rdquo; OR \u0026ldquo;depressive disorder\u0026rdquo; ). To avoid missing any publications, we assessed the references of all the reviewed publications. This work was completed by two independent reviewers (WL and YZ) and, in cases where they had a disagreement, a third investigator (LZ) was asked for advice. Moreover, we screened the references of included papers, full texts, and bibliographies of all potential articles including relevant reviews and meta-analysis to identify additional eligible studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Inclusion and exclusion criteria\u003c/h2\u003e \u003cp\u003eThe inclusion criteria were prespecified as follows: (a) the subjects were patients with depression; (b) cross-sectional, case\u0026ndash;control or longitudinal study; (c) all studies reported mtDNA levels using mean (M), standard deviation (SD) and sample size; (d) all studies included both depressive patients (cases) and healthy participants (controls); and (e) if the same datasets were found in the search process, only the paper with more complete finding was included in our meta-analysis.\u003c/p\u003e \u003cp\u003eStudies were excluded if any of the following criteria were observed: (a) duplications; (b) no measurement of mtDNA in humans; (c) no healthy controls group; (d) case reports, review articles, systematic reviews, meta-analyses, commentaries, editorials, or meeting abstracts; or (e) an in vivo or in vitro study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data extraction\u003c/h2\u003e \u003cp\u003eNoteExpress software was used for literature management. All data were extracted independently by two reviewers (WL and YZ), and disagreements were resolved by discussion, involving a third person (LZ) if necessary. Study information of included studies was recorded, including the first author, publication year, participant characteristics, sample size, sample source, region, mtDNA contents.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Quality assessment\u003c/h2\u003e \u003cp\u003eTwo authors (YC and SW) independently assessed the risk of bias and methodological quality of the included studies using the Newcastle-Ottawa Scale (NOS), an evidence-based quality assessment tool for systematic reviews of prospective cohort studies\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. There are 8 items on this scale. The maximum score of this scale is 9 points, and studies with a score\u0026thinsp;\u0026ge;\u0026thinsp;6 points are rated as high quality\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Data synthesis and statistical analysis\u003c/h2\u003e \u003cp\u003eAll data were analyzed using Cochrane Collaboration software (Rev Man 5.4) and Stata (version 16.0). The effect size was estimated using the SMD, since the mtDNA concentrations were measured with different units of measurement (units/\u0026micro;L, copies/\u0026micro;L, C/\u0026micro;L and some articles didn\u0026rsquo;t mention units) in the analyzed reports. In addition, I\u003csup\u003e2\u003c/sup\u003e was used to test for heterogeneity amongst the studies. I\u003csup\u003e2\u003c/sup\u003e values of 0\u0026ndash;25%, 26\u0026ndash;50%, 51\u0026ndash;75%, and 75\u0026ndash;100% were classified as indicating no, low, moderate, and substantial heterogeneity, respectively\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. In order to determine the source of heterogeneity, the subgroup analysis was performed according to the specimen type (plasma, or not plasma), detection method [quantitative reverse transcription polymerase chain reaction (qRT-PCR), quantitative polymerase chain reaction (qPCR) or real-time fluorescence polymerase chain reaction (rt-PCR)] and location (Asia, Europe, or North America) to identify potential sources of heterogeneity. We carried out sensitivity analyses in order to evaluate reliable results. Moreove, Egger\u0026rsquo;s test and Begg\u0026rsquo;s test were adopted to investigate publication bias. A z-score was used to evaluate effect sizes and a p-value of \u0026lt;\u0026thinsp;0.05 was considered as statistically significant. All statistical tests were two-tailed with 95% CI, and the significance level was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.7 Ethics.\u003c/b\u003e Because patient privacy was not involved in the present study, ethical approval was not required.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Study selection\u003c/h2\u003e \u003cp\u003eThe search of 8 databases identified 1104 articles for further evaluation (11 from CNKI, 2 from WANFANG, 0 from VIP, 4 from SINOMED, 559 from PubMed, 320 from Embase, 203 from the Web of Science, and 5 from the Cochrane Library), of which 65 were removed after reviewing due to duplicate records. After reading the titles and abstracts, 951 were excluded for various reasons. Finally, only ten studies\u003csup\u003e[\u003cspan additionalcitationids=\"CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e met our inclusion criteria after screening full texts. The flow diagram is found in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Study characteristics and quality assessment\u003c/h2\u003e \u003cp\u003eIn total, ten articles (from 1997 to 2023) reported on 11 studies, including 686 patients with depression and 686 healthy controls. Most trials were performed in Asia (2 in China, 1 in Japan, and 1 in Korea) and Europe (2 in Sweden, 1 in Ireland, 1 in Germany). However, trials were also performed in North America(1 in the United States, 1 in Canada). The mtDNA levels were detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR), real-time fluorescence polymerase chain reaction (rt-PCR) or quantitative polymerase chain reaction (qPCR). The basic characteristics of the included literature are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. For quality evaluation of the included studies, the NOS was used (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), which revealed that the quality of most articles were relatively high. Only one study, Kato T et al\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e, presented with NOS score of five, due to lack of provided information.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of studies included in the present meta-analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFirst author\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003elocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eSample size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecimen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDetection Method\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003cp\u003equality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaren M Ryan\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIreland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ewhole blood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eqRT-PCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmi Ampo\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePlasma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eqRT-PCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVanessa F Gon\u0026ccedil;alves\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCanada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePlasma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eqRT-PCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJohan Fernstr\u0026ouml;m\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSweden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePlasma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eqRT-PCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJae Kyung Chung\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRepublic of Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eperipheral blood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eqPCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKerstin Kuffner\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSkin Fibroblasts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eqRT-PCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDaniel Lindqvist\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSweden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePlasma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ert-PCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDaniel Lindqvist\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSweden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePBMCs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ert-PCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCheng Chen Chang\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeukocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ert-PCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYing He\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeukocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eqPCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKato T\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeukocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eqPCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 MtDNA Levels in Depression\u003c/h2\u003e \u003cp\u003eThere is a significant difference in mtDNA levels favouring a higher value in depression compared with healthy controls with a SMD of 0.42 (95% CI: 016, 0.69), and an overall effect of Z\u0026thinsp;=\u0026thinsp;3.13 ( \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Another important finding is that the heterogeneity is substantial (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;79%). The overall meta-analysis output is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e as a forest plot.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Subgroup analysis\u003c/h2\u003e \u003cp\u003eWe performed subgroup analysis based on specimen type (plasma or not plasma), detection method (qRT-PCR, qPCR or rt-PCR) and location (Asia, Europe, or North America). According to the specimen type, there was a significant difference between depression and healthy controls in plasma (SMD\u0026thinsp;=\u0026thinsp;0.54, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but not in other sample types (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Subgroup analysis of detection methods showed that compared with healthy people, there was a significant difference in patients with depression(SMD\u0026thinsp;=\u0026thinsp;0.52, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) using qRT-PCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In Europe (SMD\u0026thinsp;=\u0026thinsp;0.46, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and North America (SMD\u0026thinsp;=\u0026thinsp;0.79, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), mtDNA levels were significantly higher in depression than in healthy controls, with no statistical difference in Asia (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Publication bias analysis and sensitivity analysis\u003c/h2\u003e \u003cp\u003eThere was no publication bias in our study according to Egger\u0026rsquo;s regression test (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.478) and Begg\u0026rsquo;s continuity corrected test (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.876). And we found no obvious asymmetry appeared in the funnel plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sensitivity analysis was performed to assess whether the results of this meta-analysis were stable. The results showed no obvious effect after deleting the studies one by one, which suggested that our study results were stable and credible.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Mitochondrial energy metabolism disorders are involved in depression\u003c/h2\u003e \u003cp\u003eDepression has become a serious threat to people's mental and physical health. It is one of the most significant public health problems facing the world today. Among the clinical manifestations of depression, in addition to loss of pleasure and cognitive impairment, the more prominent somatic hypokinetic symptoms are fatigue, insomnia, appetite loss and so on\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Hypodynamic symptoms in depressed patients coincide with insufficient mitochondrial ATP production. Therefore, some scholars have proposed that mitochondrial energy metabolism disorder is involved in the pathogenesis of depression\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Mitochondria, as the principal place of cellular energy metabolism and ROS generation, maintain the mass balance of mitochondria and ensure normal function through continuous biosynthesis, division, fusion and autophagy. Mitochondrial dysfunction includes reduced ATP synthesis, respiratory chain dysfunction, structural abnormalities and excessive occurrence of apoptosis\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Previous studies have shown that disruption of mitochondrial energy metabolism is common in chronic stress animal models and patients with depression\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e.When Gardner et al\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003estudied the muscle tissue of depressed patients, they found that low ATP levels were closely associated with severe physical symptoms. In the hippocampus and gastrocnemius muscle of rats, chronic unpredictable mild stress (CUMS) reduced ATP content, Na/K-ATPase activity, respiratory chain complex I, III, and IV activities, and impaired mitochondrial ultrastructure\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. Mitochondrial oxidative phosphorylation produces large amounts of ROS, and the resulting oxidative stress can lead to mitochondrial dysfunction\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. Chen et al\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e used lipopolysaccharide to induce depression-like behavior in mice, and found that the generation of depression-like behavior was related to mitochondrial oxidative damage. In addition, yuan et al\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e found significantly more swollen mitochondria, disrupted cristae and broken mitochondrial membranes in hippocampus and gastrocnemius tissue of CUMS rats. It is well known that normal mitochondrial membrane potential (MMP) is a prerequisite for the formation of ATP through oxidative phosphoric acid acylation. The stability of MMP plays an important role in maintaining the normal physiological function of cells. Javani et al\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e found that MMP in the prefrontal cortex of depressed rats decreased, whereas mitochondrial transplantation improved it. Li et al\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e found ginsenoside Rg1 reduced microglial activation and mitochondrial dysfunction to alleviate depression-like behaviour via the GAS5/EZH2/SOCS3/NRF2 axis. In summary, mitochondrial dysfunction plays an significant role in the pathogenesis of depression, which may help to provide new perspectives on the diagnosis and treatment of depression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 MtDNA, mitochondrial energy metabolism disorder and depression\u003c/h2\u003e \u003cp\u003eIn addition to the above mentioned ATP synthesis, oxygen free radical generation and MMP changes, the study on the molecular level of mitochondrial energy metabolism also includes the changes of mtDNA levels. As the genetic material of mitochondria, mtDNA is the most frequently measured biomarker for mitochondrial dysfunction\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. However, there is no univocal explanation for mtDNA levels, and either a decrease or an increase in mtDNA levels may indicate mitochondrial dysfunction\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. MtDNA copies number (mtDNAcn) is an effective indicator of a cellular ability to generate ATP by mitochondrial oxidative phosphorylation\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e. Thus, it is possible to indirectly assess mitochondrial function by measuring mtDNA levels. A study suggests that higher mtDNAcn may represent a marker of poor mitochondrial health or mitochondrial allostatic load, which might explain the findings of higher mtDNAcn in relation to depression\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e. On the one hand, oxidative stress leads to altered mitochondrial membrane permeability, which can elicit increased mtDNAs release\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. On the other hand, upon mitochondrial stress and defective mitophagy, mtDNAs can be released out of mitochondria and can cause inflammation\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. What's more, mitochondrial dysfunction may contribute to depression by promoting oxidative stress and inflammation\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e. A study concerning cell-free mtDNA suggests that its elevated copy number may be associated with depression and suicide attempts\u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e. Cai et al\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003epioneered the discovery that major depressive disorder was associated with greater amount of mtDNA in leukocytes from saliva samples and blood. Meanwhile, they found that mitochondrial function is altered in tissues with increased mtDNA\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e. Therefore, mtDNA is a plausible biomarker candidate for further investigation of its role in depression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Discussion of meta-analysis results\u003c/h2\u003e \u003cp\u003eWith the above information in mind, we provided a comprehensive assessment to enrich our understandings of altered mtDNA content in depression. In this study, we have focused on the association between mtDNA levels and depression by carrying out a systematic review and meta-analysis of 11 eligible studies. Our study conducted in 686 depressive patients and 686 healthy controls showed that depressed people had higher levels of mtDNA compared to healthy people (SMD\u0026thinsp;=\u0026thinsp;0.42, 95% CI: 016, 0.69). However, the published literature has reported conflicting findings. Four studies\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e found higher mtDNA levels for persons with depression compared with healthy controls. In contrast, seven\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e studies found no significant difference between depressed patients and healthy controls. However, the overall results showed that depressed patients had higher mtDNA than healthy individuals. We consider that the discrepancies reported in the above studies could be related to the different age span, detection method, tissue types ,the diversity in ethnicity and so on. Heterogeneity was noted in this meta-analysis. As a result, we observed significant heterogeneity through subgroup analysis by specimen type, detection method and location. The range of mtDNAcn may be affected by different methods used for DNA isolation and extraction \u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e. Moreover, mtDNA is heterogeneous, which is influenced by different environmental and genetic contexts\u003csup\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e. Alternatively, in different individuals, some tissues require more or less mtDNAcn than others to maintain normal function, so the amount of mtDNAcn in different tissues or organs is different\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. Consequently, more research would be required to determine the most appropriate sample (plasma or other samples) and the best detection method to test mtDNA. Next, funnel plot, Begg\u0026rsquo;s test and Egger\u0026rsquo;s test suggested that no obvious publication bias in this study. Finally, we performed a sensitivity analysis, which showed that the results were stable and reliable. Most of the studies included were cross-sectional in design. Therefore, future studies will need to be initiated to design more longitudinal studies to identify mtDNA levels as a biomarker for predicting depression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Strengths and limitations\u003c/h2\u003e \u003cp\u003eTo our knowledge, we conducted the first systematic review and meta-analysis of mtDNA level with a specific focus on depression. Our study found that the levels of mtDNA in patients with depression are significantly higher than in healthy controls. At the same time, our article illustrates the link between mitochondrial dysfunction and depression. Nonetheless, there were some limitations. First, the interpretation of our study might be limited by heterogeneity, although this is a frequent phenomenon in many meta-analysis. Second, although we used SMD to estimate the effect size, the inconsistency in biomarker units, as well as different methods of analysis of the same type of biomarkers could affect the statistical conclusions drawn from this meta-analysis. Third, our study did not explore all the variables that affect mtDNA levels, such as the environment and concomitant diseases. Finally, numerical information provided in some studies was not sufficient to carry out meta-analysis, so we did not include them. It could have an impact on the results.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, here, we report a systematic review and meta-analysis suggesting mtDNA concentrations in patients with depression were higher than healthy controls. Thus, it is plausible to infer that higher mtDNA levels are associated with depression. However, more high-quality and large-scale studies are required for further analysis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by National Natural Science Foundation of China (No.U21A20401).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;\u003c/strong\u003eWL:\u0026nbsp;research design, conceptualization, writing (original draft). LZ: review and editing. YZ and YC: data management, data analysis. WL and SW:\u0026nbsp;methodology, software application.\u0026nbsp;RG:\u0026nbsp;project administration and funding acquisition.\u0026nbsp;All authors contributed to and have approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declared no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Dr. Lingqun Zhu and Dr. Rongjuan Guo for providing professional guidance on an earlier draft of this manuscript and funding this study.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u0026nbsp;(Not applicable)\u003c/p\u003e\n\u003cp\u003eConsent for publication (Not applicable)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTartt AN, Mariani MB, Hen R, Mann JJ, Boldrini M. 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Epub 2021 Jun 13.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"depression, mtDNA, mitochondria, meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-2990380/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2990380/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDisturbances in energy metabolism due to mitochondrial dysfunction have emerged as one of the important cause in the pathogenesis of depression. Many studies have found that mitochondrial DNA(mtDNA) content changes in the peripheral blood or cerebrospinal fluid of patients with depression. Some investigators ask whether it has a clear association between mtDNA and depression. Thus, we conducted a meta-analysis to comprehensively assess the evidence for mtDNA's effect on depression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePubMed, Embase, the Cochrane Library, the Web of Science, Wanfang Database, SINOMED, China Science and Technology Journal Databaseand China National Knowledge Infrastructure were searched up to 13 March 2023. RevMan (version 5.4) and Stata (version 16.0) software were used for meta-analysis. Besides, publication bias was assessed with funnel plots, Begg’s test and Egger’s test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 1372 patients were included in this study, including 686 patients with depression and 686 healthy controls. A meta-analysis including eleven studies showed significantly higher mtDNA level in depression compared with healthy controls [standardised mean difference(SMD) = 0.42, 95% confidence intervals(CI): 0.16, 0.69].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study demonstrates significantly higher mtDNA leveles in depression comparison to healthy controls.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegistration number: \u003c/strong\u003ePROSPERO CRD42023414285.\u003c/p\u003e","manuscriptTitle":"Association between Mitochondrial DNA Levels and Depression: A Systematic Review and Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-07-11 14:06:07","doi":"10.21203/rs.3.rs-2990380/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-09-28T08:33:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-09-25T00:45:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4aa6d0da-7642-418f-9e91-faf4885e32e3","date":"2023-09-20T12:33:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-08-24T02:35:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"cc092611-ffe5-4a44-a68a-c021960dc0f8","date":"2023-08-14T01:23:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-08-11T19:23:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-08-11T16:58:53+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-07-05T08:13:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-07-05T08:10:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2023-05-28T02:07:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"01c187c1-4d6d-4aff-8418-74980bbe5c96","owner":[],"postedDate":"July 11th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-11-27T15:02:11+00:00","versionOfRecord":{"articleIdentity":"rs-2990380","link":"https://doi.org/10.1186/s12888-023-05358-8","journal":{"identity":"bmc-psychiatry","isVorOnly":false,"title":"BMC Psychiatry"},"publishedOn":"2023-11-22 15:00:36","publishedOnDateReadable":"November 22nd, 2023"},"versionCreatedAt":"2023-07-11 14:06:07","video":"","vorDoi":"10.1186/s12888-023-05358-8","vorDoiUrl":"https://doi.org/10.1186/s12888-023-05358-8","workflowStages":[]},"version":"v1","identity":"rs-2990380","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2990380","identity":"rs-2990380","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}