Introduction

Heart diseases (HDs) are the leading cause of death worldwide, with the majority of fatalities, approximately 80%, occurring in low- to middle-income countries. If current trends continue, it is projected that by 2030, cardiovascular diseases will claim the lives of about 23.6 million individuals, predominantly through heart attacks and strokes1, 2. Ischemic HD is recognized as a significant threat in the 21 century3, also known as coronary artery disease (CAD) or coronary HD. A large number of individuals with CAD live with chronic disabilities and impaired quality of life4.

One of the most significant risk factors associated with HD is a family history of HD5. The increase in HD risk due to family history can be attributed to shared genetic, environmental, and lifestyle factors. The importance of genetics becomes more apparent with the early onset of HD in the family and the number of family members affected6. It is believed that an imbalance between pro- and anti-inflammatory activities plays a crucial role in the development of atherosclerosis7. Inflammation contributes to the early stages of HD, and therefore, may drive the progression of this disease8, 9.

CAD is the primary cause of deaths related to cardiovascular issues10, and atherosclerosis is the most common reason for CAD, which is a longstanding inflammatory condition of the arterial walls that arises from an inappropriate inflammatory response and an imbalance in lipid metabolism11. A multitude of evidence, including both clinical trials and experimental studies, collectively indicates that inflammation is integral to all phases of atherosclerosis development9, 12, 13.

Several signaling pathways have been reported and linked to CAD pathogenesis14, 15, 16, 17. Cytokines, which are part of the extracellular signaling proteins, are secreted by both immune and non-immune cells, including cells of the vascular endothelium18. Increased levels of inflammatory cytokines in the plasma have been documented in patients with CAD, especially in those with unstable disease conditions10. Conversely, the presence of anti-inflammatory mediators is less well documented. Interleukin-10 (IL-10) is a potent anti-inflammatory cytokine that plays a vital and often indispensable role in warding off inflammatory and autoimmune conditions19, 20, 21, 22. The gene for human IL-10 is located on chromosome 1, specifically at the juncture of regions 1q31 and 1q3223. IL-10 can reduce the likelihood of atherosclerosis development and improve the progression of atherosclerosis and vascular complications24. Studies have documented the role of plasma/serum IL-10 levels in CAD patients but with varying and contradictory results25, 26, 27. The interactions of IL-10 are complex and can vary depending on the specific context and conditions28, 29, 30.

To our knowledge, this topic has not been the subject of a meta-analysis. Therefore, the goal of this meta-analysis was to assess the levels of IL-10 in the blood of patients with CAD to obtain better and more accurate results and to identify the possible reasons for these discrepancies between the results of individual studies. Another aim was to understand the pathogenesis, protein-protein interactions (PPI), and patient-specific factors as research gaps.

Methods

Statistical Analyses

The Review Manager 5.3 (RevMan 5.3, The Cochrane Collaboration, Oxford, UK) software was utilized to calculate effect sizes, providing the standardized mean difference (SMD) and a 95% confidence interval (CI) for IL-10 levels in the blood of CAD cases and controls. The Z-test determined the significance of the pooled SMD, considering a two-sided p-value of less than 0.05 significant. If heterogeneity was significant, indicated by a Pheterogeneity value of less than 0.1 and an I2 value greater than 50%, a random-effects model56 was used. Conversely, a fixed-effect model57 wad used in cases of insignificant heterogeneity.

Subgroup analysis, random meta-regression analysis, and sensitivity analysis ("one-study-removed" and "cumulative" analyses) were performed using the Comprehensive Meta-Analysis version 2.0 (CMA 2.0; Biostat Inc., Englewood, NJ, USA). Publication bias was assessed using Egger's58 and Begg’s tests59, with a 2-sided p < 0.10 indicating the presence of publication bias.

The NCSS 2021 version 21.0.2 (NCSS, Kaysville, UT, USA) software generated two plots (Radial and L'Abbé plots). The Radial, or Galbraith, plot displays the z-statistic60, and the L’Abbé plot illustrates event rates in cases compared to control groups61, 62, with a p-value less than 0.05 indicating statistically significant heterogeneity.

Trial Sequential Analysis (TSA) was conducted using TSA software (version 0.9.5.10 beta) (Copenhagen Trial Unit, Centre for Clinical Intervention Research, Rigshospitalet, Copenhagen, Denmark)63. The required information size (RIS) was calculated with an alpha risk of 5%, a beta risk of 20%, and a two-sided boundary type. The studies were considered to have included sufficient cases if the Z-curve intersected the RIS line, adhered to the boundary line, or entered the futility area. Otherwise, additional information and further studies were deemed necessary.

Functional interactions between examined genes were studied using the STRING software, a protein-protein interaction network tool accessed at https://string-db.org/ (accessed on 5 August 2023)64. Interaction settings were limited to "" and required an interaction score threshold of more than 0.900. In the resulting networks, proteins are represented by nodes, and interactions are indicated by edges. STRING was used to identify potential interactions between differentially expressed genes (DEGs) in various tissues, with KEGG analysis obtained from the STRING software.

Results

Pooled Analysis for All Studies

As Figure 2 shows, the pooled SMD for 85 studies reporting CAD patients was 0.33 (95%CI: ˗ 0.12, 0.78; = 0.15; I = 98%). Based on the result, the two groups (patients with CAD and controls) did not exhibit a significant difference in blood IL-10 levels.

Publication Bias

Figure 3 indicates funnel plots of blood IL-10 levels in controls compared to CAD patients. With regards to blood IL-10 levels, the -values of tests were Egger’s: 0.274 and Begg’s: 0.128 for the CAD patients compared to controls. Publication bias was not observed.

Trial Sequential Analysis

Figure 4 presents the outcome of the TSA for blood IL-10 levels in CAD patients versus controls. The data indicates that there are ample cases for comparing blood IL-10 levels in CAD patients and controls.

Radial and L'Abbé plots

The results of both radial and L'Abbé plots for blood IL-10 levels in the CAD patients versus the controls are identified in Figure 5 and Figure 6, respectively. The radial plot indicated that one possible cause of heterogeneity in the initial analysis could be outliers. Also, the L'Abbé plot shows evidence of high heterogeneity ( < 0.001).

IL-10/STAT3/SOCS3 axis and PPI interaction

Figure 7 shows the IL-10/STAT3 pathway and its role in suppressing inflammation. IL-10 activates STAT3, and the IL-10/STAT3 axis can have a powerful anti-inflammatory property65 and its role can be crucial in limiting undesirable immune reactions. It is possible that this axis could play a role in regulating inflammation in the context of CAD17. SOCS3 plays a role in the mechanism by which IL-10 modulates inflammation and acts as a feedback inhibitor of the JAK/STAT pathway. Further research would be needed to determine the exact role of the IL-10/STAT3/SOCS3 axis in CAD. The STRING PPI interaction contains 5 nodes with 10 edges with the highest confidence (0.900). The average node degree was 4 and the PPI enrichment -value was 6.73e. In addition, the KEGG suggested a network analysis for the JAK-STAT signaling pathway based on 5 nodes entered into STRING (Figure 8).

Discussion

Coronary artery disease (CAD), a prevalent cardiovascular condition, is characterized by the buildup of plaque within the coronary artery walls, leading to reduced blood flow to the heart muscle66. Our main findings showed no difference in the blood levels of IL-10 between the CAD patients and the controls. The analyses reported that factors such as ethnicity, blood sample type (serum or plasma), sample size, and publication year could affect the pooled results.

Limited knowledge exists regarding the function of anti-inflammatory cytokines in CAD. IL-10, an anti-inflammatory cytokine that effectively inhibits immune responses, is produced by T and B cells, monocytes, and macrophages67. It suppresses pro-inflammatory cytokines and has a broad range of anti-inflammatory capabilities, including the inhibition of early pro-inflammatory transcription factors, which consequently reduces cytokine production68.

, IL-10 plays a crucial role in diminishing lesion growth and preventing the advancement of atherosclerosis69, 70, as well as in modulating the immune response to atherosclerosis, a major contributor to CAD71. However, in clinical settings, the role of IL-10 in patients with CAD has yielded inconsistent results25, 26, 33, despite numerous studies investigating the relationship between IL-10 and CAD25, 27, 40.

One study suggested that CAD patients of both sexes who smoked and consumed alcohol had lower levels of IL-1042, while another demonstrated that CAD patients with low serum iron had significantly higher levels of IL-10 compared to normal controls or CAD patients with normal/high serum iron36. The current meta-analysis suggested that factors such as ethnicity, blood sample, sample size, and publication year could significantly influence the pooled results. Therefore, CAD progression and development may be influenced by several factors, and future studies should examine the effect of each factor individually to identify the most significant influences. According to one study, there was no significant correlation between serum IL-10 levels in CAD patients and factors such as smoking, hypertension, diabetes, obesity, and dyslipidemia72. The findings suggest that certain risk factors for CAD, such as dietary habits (e.g., low intake of fruits and vegetables, high intake of saturated fats), smoking, physical inactivity, and obesity, may reduce IL-10 levels and increase inflammation in the body73, 74, 75, 76, thus contributing to the disease's development. Understanding the underlying mechanisms of these associations may assist in identifying new preventive and therapeutic strategies for CAD.

IL-10 has been shown to suppress the generation of pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α) and IL-1β, which are key contributors to the formation of atherosclerotic plaques68, 77. Additionally, IL-10 has been found to promote the survival of endothelial cells that line the inner surfaces of blood vessels and prevent their apoptosis, thereby reducing the risk of plaque formation78, 79.

Various studies have indicated that increased IL-10 levels in the bloodstream could signal ongoing systemic inflammation in CAD patients27, 33, 40, while other studies noted that in human coronary disease, IL-10 is present and associated with diminished signs of inflammation71, 80. The available evidence suggests that IL-10 plays a protective role against CAD by modulating the inflammatory response and promoting endothelial cell survival. Nonetheless, additional studies are needed to fully comprehend the mechanisms underlying the relationship between IL-10 and CAD.

Research has established that CAD is associated with a continuous inflammatory response81. STAT3 has been identified as a crucial molecule in IL-10's operation, with its activation necessary for the cytokine's anti-inflammatory effects82, 83. Furthermore, evidence suggests that SOCS3 plays a role in how IL-10 modulates inflammation17, 84. Acting as a feedback inhibitor of the JAK/STAT pathway, SOCS3 is crucial in preventing STAT3 activation, cytokine signaling, and the expression of inflammatory genes in immune cells such as macrophages and microglia85. One study found that IL-10 increased SOCS3 expression in cultured cardiomyocytes17. With regards to protein-protein interactions between IL-10, STAT3, and SOCS3, evidence supports that both STAT3 and SOCS3 are involved in IL-10's regulation of inflammation. Additionally, the KEGG analysis reported several biomarkers.

The effects of statins on IL-10 levels in CAD patients versus controls have varied across studies39. One trial reported that statin therapy did not affect IL-10 mRNA expression in patients with CAD86, while another study confirmed this for serum IL-10 levels87. Our meta-analysis included a few studies that involved cases with statin therapy; thus, we were unable to analyze data related to the effect of statins on IL-10 levels comprehensively. Future research should investigate the impact of statins on IL-10 levels in CAD patients. The meta-regression identified the publication year as a confounding factor in the pooled result, indicating possible significant differences in the therapeutic approach to CAD patients over time.

The significant limitations of this meta-analysis include heterogeneity among the studies, limited case count in some analyses, and the lack of patient-level data; diverse criteria for study inclusion, such as varying definitions of CAD, which could introduce bias; different patient populations; and varying methodologies. Additionally, the study mentions factors such as statin therapy that could influence IL-10 levels in CAD patients, but these confounding variables were not fully explored in the analysis. The quality assessment of the included studies was conducted by a single author, which may introduce subjective bias. A more systematic and independent quality assessment process could enhance the reliability of the results. While no evidence of publication bias was found, it is possible that studies with significant results may have been more likely to be published, leading to an over representation of certain findings in the meta-analysis. However, the strengths of the meta-analysis include the absence of publication bias, the high quality of most included studies, and the consistency of the combined results.

Conclusions

According to this systematic review and meta-analysis, no significant difference was observed in blood IL-10 levels between CAD patients and controls, suggesting that IL-10 may not serve as a reliable biomarker for CAD. The analysis included a sufficient number of cases for robust comparison, highlighting the complex and multifactorial nature of CAD. Further research is needed to better understand the role of inflammation and specific inflammatory markers in the development of CAD. Future studies should include larger sample sizes and explore the interaction of IL-10 with other proteins to enhance our understanding of CAD's pathogenesis and identify potential therapeutic targets. This study underscores the importance of continued research efforts to improve our comprehension of the mechanisms and risk factors involved in CAD.

This meta-analysis is clinically significant as it informs clinicians and researchers that IL-10 levels may not be useful for diagnosing or predicting CAD. It highlights the complex and multifactorial nature of CAD, indicating that many factors, not just IL-10, contribute to the disease's development. This insight is vital for clinicians when diagnosing and treating CAD.

Abbreviations

CAD - Coronary Artery Disease, CI - Confidence Interval, CK - Creatine Kinase, CO - Control, DEGs - Differentially Expressed Genes, ECG - Electrocardiographic/Electrocardiography, HDs - Heart Diseases, IL-10 - Interleukin-10, JAK - Janus Kinase, KEGG - Kyoto Encyclopedia of Genes and Genomes, NR - Not Reported, NOS - Newcastle-Ottawa Scale, PECO - Population, Exposure, Comparator, Outcome, PPI - Protein-Protein Interactions, PRISMA - Preferred Reporting Items for Systematic Reviews and Meta-Analyses, PROSPERO - International Prospective Register of Systematic Reviews, RIS - Required Information Size, SD - Standard Deviation, SE - Standard Error, SMD - Standardized Mean Difference, SOCS3 - Suppressor of Cytokine Signaling 3, STAT3 - Signal Transducer and Activator of Transcription 3, TNF-α - Tumor Necrosis Factor-Alpha, TSA - Trial Sequential Analysis

Acknowledgments

None.

Author’s contributions

Conceptualization, R.H.M.; methodology, M.S.; software, M.S.; validation, R.H.M., and N.S.; formal analysis, M.S.; investigation, M.R. and M.S.; resources, M.S.; data curation, M.S.; writing—original draft preparation, N.S.; writing—review and editing, M.R. and M.S.; visualization, R.H.M.; supervision, N.S.; project administration, R.H.M.; funding acquisition, N.S. All authors have read and agreed to the published version of the manuscript.

Funding

None.

Availability of data and materials

Data and materials used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.