https://orcid.org/0000-0003-1838-9010
Figures
Abstract
Objective
This study aimed to assess the correlation between the circulating cell-free mitochondria DNA and inflammation factors in noninfectious disease by meta-analysis of data from eligible studies.
Materials and methods
Through a comprehensive searching of pubmed, embase, web of science, cochrane from establishment of the database to October 31, 2022, studies were selected that investigated the association of circulating cell free mitochondria DNA with inflammatory factors in non-infectious diseases. Studies that met the inclusion criteria and were published in English or Chinese were included. Data of each correlation coefficients were extracted from the paper and 95% confidence intervals were calculated. Sensitivity and heterogeneity tests were carried out for each data.
Results
A total of 660 articles were retrieved and 22 were included in this meta-analysis, including 2600 patients. A fixed effects model was employed to examine ISS and IL-8, others were analyzed using random effects models. The correlation coefficient between mtDNA and ISS score was 0.37 (95%CI = [0.232;0.494]), p<0.0001, heterogeneity I2 = 46%, p = 0.11). The correlation coefficients between mtDNA and inflammatory factors are as follows: TNFα, 0.405 [(95%CI = [0.253;0.538], p<0.0001, heterogeneity I2 = 77%, p = 0.0001]. IL-6, 0.469 [(95%CI = [0.296;0.612]), p = 0.0001, heterogeneity I2 = 93%, p<0.0001]. CRP, 0.333[(95%CI = [0.149;0.494]), p = 0.005, heterogeneity I2 = 85%, p<0.0001]. IL-8, 0.343[(95%CI = [0.233;0.524]), p = 0.001, heterogeneity I2 = 50%, p = 0.09]. PCT, 0.333 [(95%CI = [0.06;0.64]), p = 0.09,heterogeneity I2 = 64%,p = 0.06]. There were no significant publication bias for TNFα, IL-6 and CRP.
Citation: Zhou M, Zhang H, Xu X, Chen H, Qi B (2024) Association between circulating cell-free mitochondrial DNA and inflammation factors in noninfectious diseases: A systematic review. PLoS ONE 19(1): e0289338. https://doi.org/10.1371/journal.pone.0289338
Editor: Wisit Kaewput, Phramongkutklao College of Medicine, THAILAND
Received: August 16, 2022; Accepted: July 18, 2023; Published: January 19, 2024
Copyright: © 2024 Zhou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Non-infectious diseases such as acute trauma and surgery often lead to tissue damage and inflammatory responses. These diseases can activate neutrophils, impaired endothelial cell function through releasing proteolytic enzyme, oxygen free radical [1]. These reaction increases the permeability of capillaries and extensive infiltration of inflammatory cells, then develop into systemic inflammatory response syndrome, and further to impair organ function, eventually result in multiple organ dysfunction [2]. How to assess severtiy of noninfectious inflammatory response caused by non-infectious diseases is an urgent clinical problem to be solved.
According to recent study, acute trauma and surgery results in cell membranes rapture, following the contents of cell spill out onto extracellular milieu. Massive release of DAMP (damage associated molecular patterns) damages adjacent cells, causing more cell necrosis and releasing more DAMP [3]. Mitochondrial DAMP released into circulate was identified by cellular surface receptor and triggered a serious inflammation responds [4]. Mitochondria DNA is a common DAMP and has ability to active multiple immune cells, such as monocytes, macrophages, and then induce release of IL-6, TNFα, IL-1, which result in system inflammation [5, 6]. After mtDNA is recognized by TLR9, interaction of TLR9 and Myd88 activate MAPK and NFƙB, leading to produce proinflammation factors such as IL-1, IL-6 and TNFα [7]. MtDNA activates NLRP3 recruited by mitochondria,then induce the production of caspase-1,which produce active IL-1β through cleaving inactive pro-IL-1β and promote IL-18 expression [8]. MtDNA induce IFN expression by activating cGAS-STING-TBK1 pathway [9]. Plasma mitochondrial DNA (mtDNA) level in trauma patients was prominent higher than non-trauma patients. The level of mtDNA in patients who developed Systemic inflammatory response syndrome (SIRS) was significantly higher than that in non-SIRS patients [10]. Although experimental and clinical studies have shown that mtDNA concentration is associated with inflammatory responses, the relationship between mtDNA concentration and inflammatory factors remains unclear.
Several studies have shown that the content of mtDNA in plasma is positive correlated with the expression of IL-6, TNFα. Other studies have shown that DNA is negatively or no correlated with inflammatory factors. So, the result remains controversial [11, 12]. In addition, the inflammatory response caused by infection also increase the expression of IL-1, IL-6 and other inflammatory factors through interaction of PAMP and TLR [13].
Therefore, in order to avoid the interference of infection, we performed this meta-analysis in order to uncover the correlation between plasma mtDNA and inflammation factors in noninfectious diseases, such as acute trauma, surgery, AMI, dialysis, diabetes.
Materials and methods
The present meta-analysis was reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement [14].
Inclusion criteria
If article met the following criteria, it was selected for inclusion: ① the study subject were patients; ② the disease studied was non-infectious; ③ the outcome was the relationship between circulating mtDNA level and inflammatory factors, such as TNF-α, IL-6, IL-1β, C-reactive protein (CRP), IL-8, procalcitonin (PCT), NFƙB, and Injury Severity Score (ISS); ④ the article was published in a peer-reviewed scientific journal as a full paper; ⑤ prospective, retrospectively and cross-section studies
Exclusion criteria
The articles were excluded according to following criteria: ① The research subjects were animals or cell; ② The same set of data was published repeatedly; ③ The articles not provide the data of correlation coefficient and number of cases and data was not available after contacting the author; ③ The full articles were unavailable. ④ reviews, case reports, abstracts of meetings and comments.
Literature research
The following databases were searched by two independent observer from establishment of the database to October 31, 2022: Pubmed, Embase, Cochrane library, Web of Science, Cochrane Library and China National Knowledge Infrastructure (CNKI). The searching terms included “mtDNA” OR “mitochondria DNA” OR “mitochrondria deoxyribonucleic acid” And “TNFα” OR “IL-6” OR “IL-1β” OR “ISS” OR “CRP” OR “PCT” OR “NFƙB”. The language of published articles is limited to Chinese and English. Articles searched in databases were published prior to and including October 2022. All retrieved articles were manually crosscheck for titles and abstracts, and full-text inspection followed according to selection criteria.
Evaluation of literature quality
The included studies were independently scaned by two observers (MZ and Hr Ch) using the The Agency for Healthcare Research and Quality. The useful data extracted from each study based on a table, included the following: authors, the nation of origin, the year of publication, the number of the patients, Pearson or Spearman correlation coefficient (r). Disagreements between the two reviewers were resolved by a majority opinion after a third reviewer (Bw Qi) assessed all involved items.
Extraction of data
After selected by reading abstract, included articles were independently evaluated by two investigators, and data were extracted base on a standardized form. The variables included: first author, publication year, study design, study period, geographic region, r value and total sample size. The correlation coefficient between mtDNA and inflammation factors, such as TNF-α, IL-6, CRP, IL-8, PCT, IL-10, IL-1, lactate and ISS score were recorded detail. If the data provided by the article is incomplete, contact the author to obtain complete data.
Pearson correlation coefficients published in article were converted into Spearman correlation coefficients [15]. Fisher’s transformation, changing Spearman correlation coefficients to a Z-score, was used to compare [16].
Statistical analysis
After suitable transformation, the corresponding data from each study was combined with a random effect model [17].
Statistical heterogeneity was assessed by the chi-square test on Q statistic, which was quantified by the I-square values, assuming that I-square values 50 were nominally assigned as moderate estimates [18]. The fixed-effect model was used after no significant heterogeneity was monitored. To investigate potential sources of heterogeneity, stratified analyses was performed to find any possible sources. Sensitivity analysis was also performed by excluding each study at a time to assess whether one or more studies influenced the overall results. Publication bias was assessed first by visually inspecting the distribution of observed studies on a funnel plot [19]. And P ≤0.05 was indicated the presence of statistically significant.
Results
Results of literature retrieval and screening
A total of 660 articles were retrieved by searching databases. 460 irrelevant articles were eliminated by reading abstracts due to duplications (n = 124), non-revelance(n = 336). 105 articles of review were excluded. 5 articles were excluded for which full text cannot be obtained. 10 articles that trauma combined with infection, 54 articles with inconsistent outcome, 4 animal experiments were excluded by reading the full text. In the end, a total of 22 papers were included (19 in English, 3 in Chinese; Fig 1). The basic information of the included literature was summarized in Table 1. All literatures were scored using The Agency for Healthcare Research and Quality (Table 2). The quality of the literature is acceptable.
Correlation between mtDNA and inflammation factors
After a heterogeneity test, there were no notable heterogeneity among ISS score and IL-8, so fixed effects model was used for meta-analysis. The results showed that plasma mtDNA was moderately positive correlation with ISS score (r = 0.37(0.232, 0.494))(Fig 2) and IL-8 (r = 0.343(0.133, 0.524)) (Fig 3). After heterogeneity test, we found there was great heterogeneity among TNFα (Fig 4), IL-6 (Fig 5), CRP (Fig 6) and PCT (Fig 7), so the random effects model was used. The results of funnel plot showed no evidence of obvious publication bias of TNFα (Fig 8) and IL-6 (Fig 9), and p value of egger’s test for TNFα, IL-6 and CRP was 0.225, 0.349 and 0.631, respectively. Plasma mtDNA was moderately positive correlation with TNFα (Fig 2), IL-6(Fig 9) and CRP(Fig 6). There was no correlation between plasma mtDNA and PCT (p = 0.09) (Fig 7). (The results of meta analysis were summarized in Table 3)
The GRADE quality of evidence for TNFα, IL-6 and CRP were judged to be high, ISS and IL-8 were judged to be moderate. GRADE evidence quality was summarized in Table 4.
Discussions
Correlation analysis results on mtDNA and inflammation
The purpose of this Meta analysis study was to reveal the correlation between circulating mtDNA content and inflammatory response induced by non-infectious diseases. We excluded inflammatory responses caused by infection, because infection resulted in severe inflammatory responses through other pathways, which would affect the accuracy of the results. The results of this study showed that mtDNA content was correlated with ISS score, TNF-α, IL-6, CRP and IL-8 content, but not with PCT content. This study provides evidence for mtDNA as a molecular marker for predicting inflammation.
When cells are damaged and mitochondria are destroyed, mtDNA is released into the blood. After trauma, compared with non-MODS patients, patients with MODS had significantly higher blood mtDNA concentrations [41]. The content of mtDNA in trauma patients was higher than that in normal control group at before operation, during operation and 3 days after operation. At the same time, the concentration of mtDNA in patients who developed SIRS was significantly higher than that in patients without SIRS. The concentration of mtDNA was correlated with SIRS [10, 42]. Animal experimental studies on hip fractures in rats showed that the concentration of mtDNA increased significantly after surgery, and its concentration was significantly correlated with inflammatory factors IL-10 and TNF-α [43]. The above studies showed that after trauma or surgery, a large amount of mtDNA is released into the blood. And plasma mtDNA levels correlate with injury and disease severity. The results of this study also showed that the circulating mtDNA levels was positively moderate correlated with the score of ISS. This results indicate that circulating mtDNA was positively correlated with the severity of trauma.
Studies have shown that mtDNA promotes TNFα expression. During intestinal ischemia-reperfusion injury, MtDNA-STING signaling pathway promotes intestinal endothelial cell necrosis; in addition, mtDNA promotes the expression of IFN and TNF-α to induce intestinal necrosis [44]. Timmermans et al. [45] study have shown that there were no relationship between mtDNA and TNFα, IL-6, IL-8 in sepsis shock patients. Plasma mtDNA was positive correlation with TNFα in diabetes patients by multiple linear regression [46]. The present meta analysis have confirmed that plasma mtDNA is moderate positive correlation with TNFα.
Zhang et al. showed that in trauma patients with sepsis, mtDNA was negatively correlated with organ function, and was negatively correlated with both IL-6 and IL-10 [47]. In a study of kidney damage caused by SIRS, the results showed that the level of mtDNA in SIRS patients was significantly higher than that in non-SIRS patients. But there was no correlation between mtDNA and IL-6 and IL-8 [9]. Bao et al study showed that plasma mtDNA was strong positive correlation with IL-6 and strong negative correlation with IL-10 in rat hip fracture [48]. Puskarich et al. [11] study showed that plasma mtDNA was negative correlation with IL-6 and IL-10 in sepsis and sepsis shock patients. In diabetes, plasma mtDNA was moderate positive correlation with IL-6 [46]. The above studies indicate that the correlation between mtDNA and IL-6 is uncertain. This study have confirmed that plasma mtDNA is positive correlation with IL-6 in noninfectious disease.
Studies have shown that mtDNA is associated with CRP expression in infectious disease. Results of Huang et al. study showed that plasma mtDNA was significantly positively correlated with CRP in acute respiratory distress syndrome [49]. However, studies have showed that plasma mtDNA was no correlation with CRP in sepsis patients [50]. This meta-analysis showed that in non-infectious diseases, the expression of plasma mtDNA is correlated with the expression of CRP.
Heterogeneity
The results suggest that TNFα, IL-6 and CRP have distinct heterogeneity, so we analyze the reasons for the heterogeneity. First, the diseases included in the studies were diverse and lacked similarity. Because this study is mainly aimed at non-infectious diseases, the types of diseases include fractures, trauma, surgery, myocardial infarction, hemodialysis and other diseases. The bigger the difference in diseases, the larger the difference in heterogeneity. Second, the quality of the original research was inconsistent. The AHRQ score of the included literature were mostly 5 to 7 points, and the overall quality was not high, resulting in high heterogeneity. Third, different data processing methods also bring some heterogeneity
Limitations
This meta analysis comes with several limitations. Firstly, the sample size of each included study was small. Except for Fan2020, where the number of cases is 962, the number of cases in the other studies ranges from 17 to 107, which may weaken the reliability of the conclusions. Secondly, In the original research, some articles only give conclusions, and do not provide original data or correlation coefficients, so they cannot be included, which may lead to publication bias. Thirdly, this meta analysis has not been registered online, which may lead to potential bias.
In conclusion,although there are some limitations of this study, the current evidence shows that mtDNA is related to the degree of trauma and the expression of inflammatory factors CRP, IL-6, TNF-α, and IL-8 and play an important role in the inflammatory response. Future research is need to identify clinical value of mtDNA for indicating inflammatory response.
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