Predictive Value of Inflammatory Cytokines as Potential Biomarkers for Takayasu Arteritis: A Systematic Review and Meta-Analysis

Abstract

Takayasu arteritis (TA) is a chronic autoimmune disease caused by non-specific inflammation, with complicated pathomechanisms involving a variety of cytokines and immunological pathways. The assessment of inflammatory cytokines associated with TA may help to better understand its pathophysiology, and the circulating levels of these cytokines may act as potential biomarkers reflecting disease activity. Therefore, the aim of this study was to conduct a meta-analysis based on studies detailing differential inflammatory cytokines related to TA and to evaluate the predictive value of these inflammatory cytokines for TA. To achieve this goal, a comprehensive literature search was performed using PubMed, EMBASE, Cochrane Library, and Web of Science, and a total of 18 studies reporting the predictive value of these inflammatory cytokines as biomarkers of TA were included. The results of the meta-analysis showed that 20 biomarker candidates were reported, and the serum levels of TNF-α, IFN-γ, IL-6, IL-8, IL-12 and IL-17A in TA patients were significantly increased, which may be helpful for the auxiliary diagnosis of TA. Regarding the identification of the phase of disease activity, TNF-α, IL-6, IL-12, and IL-17A were significant, while serum IL-10 was a biomarker for the inactive stage of TA. In conclusion, this meta-analysis suggests that 7 inflammatory cytokines could serve as potential circulating biomarkers with predictive value for TA, and our conclusion further verifies that the over-activation of Th1 and Th17 pathways and the imbalance between Treg and Th17 are the immunopathological characteristics of TA.

Graphical abstract

Keywords

Takayasu Arteritis / Inflammatory cytokines / Biomarkers / IL-6 / IL-10

Introduction

Takayasu arteritis (TA) is a large vasculitis of unknown etiology[1], mainly involving the elastic arteries[2], causing arterial segmental stenosis, occlusion, dilation and/or aneurysm formation[3]. It can eventually lead to transient ischemic attack, stroke, coronary artery and other related diseases, which greatly affect the quality of life of patients and even endanger their lives[4,5]. Current established management for TA includes medicine treatment (glucocorticoids, immunosuppressants and biological agents) and surgical interventions like open surgeries and endovascular repair. A ten-year follow-up showed that although the survival rate after surgical intervention is as high as 80%–90% in patients with TA. However, the ten-year primary patency in both open group and endovascular group are only 48.8% and 31.8% respectively[6]. This suggests that long-term monitoring and evaluation of disease status and recurrence in TA patients is particularly important. What happed inside the culprit vessels attracts researchers during the past decades. Abundant studies were conducted to explore the pathophysiological mechanisms of TA from various aspects such as genomic variants identified by genome-wide association studies (GWAS)[7], chemokine profiling[8]. Many state-of-art techniques have also been applied in this field like single cell RNA-sequencing[9]. Among these studies, the determination of soluble cytokines and chemokines has been widely studied because of its advantages such as non-invasive, easy operation, low monitoring cost and convenient follow-up.

The pathophysiological mechanisms of TA remains unclear, but its prominent pathological features are heterogeneous inflammatory infiltration of the arterial wall by immune cells such as CD4⁺ T cells, CD8⁺ T cells, γδ T cells, natural killer cells, macrophages, multinucleated giant cells, and granulophils, as well as vascular remodeling and fibrosis caused by early vascular inflammatory response[10–12]. Cytokines and chemokines as inflammatory factors are mainly produced by a variety of immune cells such as macrophages in the state of acute inflammation to up-regulate the inflammatory response and play an important role in driving and controlling inflammatory processes[13–15]. In recent years, many studies have found that cytokines such as interleukin-6 (IL-6), interleukin-12 (IL-12) and tumor necrosis factor-α (TNF-α) play an important role in the disease progression of TA[16–18]. This suggests that the fluctuation of cytokine levels may reflect the dynamic process of arterial wall inflammation in TA patients to a certain extent, which provides a theoretical basis for assessing disease activity and predicting disease deterioration through biomarker level detection.

Many studies have also focused on potential biomarker using in the auxiliary diagnosis and assessing activity[19–21]. Acute phase response (APR) is frequently advocated for disease assessment, but it was shown to be neither sensitive nor specific enough to monitor the disease activity[22–24]. IL-6 is more widely studied in TA[25]. As early as 1999, Marina Noris proposed a strong correlation between serum IL-6 and RANTES levels and the disease activity, and raised the possibility that monitoring them in sera could help clinicians find appropriate therapeutic adjustments in individual patients[16]. However, the elevation of IL-6 was not statistically significant in some studies, and its use value in diagnosis and active phase assessment is still controversial[26]. What’s more, TNF-α, INF-γ, IL-6, IL-12 and IL-18 are involved in the pathogenesis of several inflammatory diseases that feature granuloma information[27–29], and these factors have been reported to be correlated with the active stage of aortitis. However, due to the limited sample size in each single center, limitations in the cross-sectional design, and the lack of a gold standard to evaluate the activity of aortitis, the results of relevant studies are heterogeneous. To provide a higher level of evidence we performed a meta-analysis of the available studies.

This study aimed to evaluate some cytokines as potential biomarkers in patients with TA especially those related to imflammatory damage by systematically review and meta-analysis and discussing the predictive value of these inflammatory cytokines as potential biomarkers for TA.

Materials and methods

Systematic review and search strategy

To characterize difference of the inflammatory cytokines, we conduct the systermatic review. The protocol for this meta-analysis has been published previously, which registered on the International Prospective Register of Systematic Reviews (CRD42023442946). This study was performed in accordance with the recommendations in the Preferred Reporting of Systematic Reviews and Meta-Analysis (PRISMA) statement[30]. A search of PubMed, EMBASE, Web of Science and Cochrane Library was interrogated to identify Electronic bibliographic studies updated to May 2023. The search string was: (cytokine) OR (cytokines) OR (inflammatory) OR (chemokines) OR (chemokine) OR (interleukin) OR (interleukin)) AND (Takayasu OR Takayasu Arteritis). Potentially eligible studies were screened for title and abstract and assessed for full text. Only English language articles were considered due to limited funding for translation and we also searched the reference lists of included studies and reviews for relevant reports.

The inclusion and exclusion criteria

According to the PRISMA report published in 2009, the inclusion and exclusion criteria were listed as followed[31]. The inclusion criteria includes: (1) The eligible studies were clinical case-control studies or cohort studies using inflammatory cytokines as biomarkers to monitor the clinical course of TA and/or predict the degree of disease activity; (2) Studies provide data for serum/plasma inflammatory cytokines levels in TA patients and controls and data between serum/plasma cytokines and chemokines factors levels and/or disease activity are also provided; (3) Studies clarified the diagnostic criteria and evaluation criteria of TA and its disease activity.

The exclusion criteria includes: (1) Literature based on study type, namely case reports, case series, one-arm studies, and literature reviews, conference abstract were excluded; (2) Articles containing insufficient data < 25% of predefined variables extractable were excluded; (3) In the cases of the same population of patients were identified or if study populations overlapped, only the most detailed or the latest reports were included to avoid duplication of data, unless the outcomes were mutually exclusive.

Data extraction

Titles and abstracts were reviewed independently for suitability based on the inclusion criteria by two authors (LYF and ZQ). The full texts of suitable studies were independently and related data extraction was performed independently by the same reviewers. When disagreement occurred, a third author (CWK) was resorted to resolve the controversy. Information extracted from each study included the following: basic information about the included studies, such as first author, publication year, number of patients, group, inflammatory cytokines studied and diagnostic criteria of TA and evaluation criteria of activity period.

Risk of bias

Quality assessment was conducted by the latest version of the non-randomized study Newcastle-OttaAwa Scale (NOS)[32]. These scales assess selection, comparability, and outcome. We judge this non-randomized study from three aspects of study subject selection, comparability, outcome and exposure to evaluate the methodological quality level. The studies were then assigned as “low risk,” “high risk,” or “unclear” based on the risk of bias.

Statistical analysis

Meta-analysis was used to evaluate the difference in mean levels of serum inflammatory cytokines between patients and control subjects, between inactive group and active group. For the analysis of circulating inflammatory cytokines levels in TA patients and controls, appling Mantel-Haenszel method with random-effect models[33], standardized mean differences (SMDs) estimating with corresponding 95% CIs were calculated by RevMan 5.3 as the outcome effect index and the forest plot was used to describe the effect size of each study and the combined outcome effect index. Funnel plot, Begg’s test were used to assess publication bias by Stata version 12.0 when there were ≥ 2 studies. When there was significant publication bias, the Duval and Tweedie’s trim-and-fill method was used to further explore the robustness of the results. As described by Higgins[34], heterogeneity among studies was assessed by using the χ² and I² tests and graded as high (I² > 75%), medium (25 < I² < 75%), or low (I² < 25%). Due to the limited number of eligible studies, subgroup analyses and meta-regression were not performed for biomarkers other than IL-6. For studies about IL-6, we performed random-effects meta-regression analyses according to country of enrollment, method of serum interleukin-6 testing, and number of cases. All tests were 2-tailed, with P < 0.05 considered statistically significant.

Results

Study selection

A total of 1403 studies discussing TA and either inflammatory cytokines were initially identified. After screening the titles and abstracts, 60 full-text articles were assessed for eligibility. When carefully review of the full text, we excluded an additional 42 articles based on the reasons listed in the Figure 1. Only 18 studies ultimately met all the eligibility criteria were retained and were included in the meta-analysis (The specific procedure of literature screening and exclusion is shown in Figure 1).

Study characteristics

Eighteen studies published between 1999 and May 2022 were initially included in this study, as shown in Table 1. Fifteen of them tested the levels of inflammatory cytokines as potential biomarkers in TA patients (n = 719) and controls (n = 561). And Fifteen studies compared the concentrations of protential inflammatory biomarkers between the active (n = 546) and inactive (n = 605) TA patients.

Risk of bias of included studies

Most studies reported age, sex, and country of patients, as well as sample size and data precision measures. Two authors (LYF, ZQ) independently assessed the methodological quality of the selected studies using the New castle-Ottawa Scale for retrospective studies showing in Figure 2. The thorough Newcastle-Ottawa Scale core > 6 (18 of 18 studies), all indicate high quality of including studies (Table S1).

Effect of potential biomarkers

A total of 20 potential inflammatory biomarkers of TA were proposed in the 18 included papers (Table S2). The biomarkers were included for downstream analysis if they are tested in at least two studies. The meta-analysis showed IFN-γ, TNF-α, IL-6, IL-8, IL-12, IL-17A were significantly highly expressed in TA group and six significantly expressed inflammatory biomarkers in active group of TA patients including TNF-α, IL-6, IL-10, IL-12, IL-17A as shown in Table 2.

Effect of potential biomarker both on the auxiliary diagnosis and activity assessment of TA

Several inflammatory cytokines were elevated have significant statistical significance both in the auxiliary diagnosis and activity assessment of TA. The potential biomarkers that were significantly increased in patients with TA compared with control participants including TNF-α [SMD = 1.35, 95% CI (0.68–2.01), P < 0.0001], IL-12 [SMD = 0.42, 95% CI (0.10–0.74), P = 0.009] and IL-17A [SMD = 0.64, 95% CI (0.24–1.04), P = 0.002] (Figure 3a-c). Compared to active patients group, TNF-α [SMD = 0.40, 95% CI (0.17–0.64), P = 0.0007], IL-12 [SMD = 0.82, 95% CI (0.16–1.47), P = 0.01), IL-17a [SMD = 0.66, 95% CI (0.20–1.12), P = 0.005] (Figure 3d-f) were significantly higher than inactive patients. The between-study heterogeneity all range from not important to moderate.

And IL-6, as the most widely used potential biomarker in clinical studies for auxiliary diagnosis and active stage assessment was higher in TA than control participants [SMD = 1.20, 95% CI (0.77–1.64), P < 0.00001] (Figure 4a) and active groups also higher than inactive groups [SMD = 1.14, 95% CI (0.67–1.61), P < 0.00001] (Figure 4b). However, Q test showed a high degree of heterogeneity among the studies for auxiliary diagnosis (P < 0.00001, I² = 82%) and disease activity (P ≤ 0.00001, I² = 88%).

Effect of potiential biomarker only on the auxiliary diagnosis or assessment active of TA

In addition, meta-analysis results suggested that serum concentrations of IFN-γ and IL-8 in TA patients were higher than those in healthy controls, which had a statistically significant, although they showed poor performance in the assessment of activity in TA patients. The combined effect sizes respectively were [SMD = 0.70, 95% CI (0.17–1.22), P = 0.009]; [SMD = 0.41, 95% CI (0.14–0.68), P = 0.003]. And the heterogeneity of the results in two cytokines was low: TNF-γ (P = 0.14, I² = 49%); IL-8 (P = 0.73, I² = 0) (Figure 5a-b). We also observed an interesting phenomenon through meta-analysis that IL-10 seemed to be a protective factor for TA patients. The results of meta-analysis showed that serum IL-10 concentration was negatively correlated with disease activity in TA patients, and IL-10 in inactive group was higher than that in active group, with statistically significant combined effect size of SMD = −0.47, 95% CI (−0.93, −0.00), P = 0.05 (Figure 5c). Although heterogeneity was high (P = 0.05, I² = 67%), the small number of included literatures could not further clarify the source of heterogeneity.

Meta-regression, subgroup analysis for high heterogeneity of IL-6

To explore the source of heterogeneity, we conduct meta-regression and subgroup analysis for IL-6. In terms of auxiliary diagnosis, we performed meta-regression according to the countries of the included studies, the methods of serum interleukin-6 detection, and the number of cases to find the sources of heterogeneity. The results suggested that the number of cases was a heterogeneous source (Table S3). Bubble plot showed that the heterogeneity gradually decreased with the increase of the number of cases (Figure 6a-c). Subgroup analysis was performed on the number of cases. When the number of cases was less than 50, the difference of IL-6 serum levels between the TA group and the control group was statistically significant [SMD = 2.48, 95% CI (1.55–3.42), P < 0.000], and the heterogeneity was moderate. Number of cases > 50. There was still a significant difference in the serum level of IL-6 between the TA group and the control group [SMD = 1.20, 95% CI (0.77–1.64), P < 0.000], and the heterogeneity was low (Figure 6d and Table 3). In terms of assessing activity, while meta regression analysis suggested that countries, serum IL-6 detection and case numbers were not heterogeneous sources (Figure S1a–b). We were not able to explain other sources of heterogeneity in cases where I² was higher than 75%. Further sensitivity analyses were performed to ensure robustness.

Funnel plots

Except for studies testing IL-6 of TA activity evaluation, funnel plots were all symmetrical and all Begg’s test found no significant publication bias (P > 0.05) (in the Data Supplement). In terms of assessing activity by IL-6, begg’s test suggested significant publication bias (P = 0.02) (Figure S1d). In order to further eliminate publication bias, to prove the robustness of test results, The combined total effect size was still statistically significant after the interpolation of four similar virtual literatures with the Duval and Tweedie’s trim-and-fill method [SMD = 1.723, 95% CI = (1.031, 2.879), P = 0.038], indicating that the results were robust (Figure S1e).

Discussion

Current guidelines and consensuses mainly adopted ESR and CRP as circulating biomarkers for condiseration of diagnosis of TA or determination of active phase. However, limiations of these two serum biomarkers have trigerred researchers to search for more powerful biomarkers[19–21]. Therefore, we conducted a meta-analysis on related studies of different single centers, which expanded the sample size on the one hand and improved the level of evidence on the other hand, making the research results more reliable. The results suggested that seven cytokines and chemokines could serve as potential circulating biomarkers for patients with TA in diagnosis (TNF-α, IFN-γ, IL-6, IL-8, IL-12, IL-17A), at active stage (TNF-α, IL-6, IL-12, IL-17A) or inactive phase (IL-10). Insufficient stuidies of other biomarkers like MMP-3 and MMP-9, were not identified or included for this meta-analysis. Through a systematic meta-analysis of the included literature, we found that TNF-α, IL-6, IL-12, and IL-17A were increased in both TA patients and active patients, with statistical significance. Among them, the most significant statistical difference was interleukin-6, up to < 0.00001, which further provided a theoretical basis for a higher level of evidence for interleukin-6 as a biomarker of aortitis and demonstrates that the IL-6 so far by the cytokine that best reflects diseases status and diseases activity in TA. However, it is important to note that while IL-6 showed strong discriminatory power, our analysis could not provide pooled estimates of its sensitivity and specificity due to the nature of the included studies (mostly case-control comparisons of mean levels). Future diagnostic test accuracy studies are needed to establish these clinically crucial parameters. The high heterogeneity observed in IL-6 analyses, particularly for activity assessment (I² = 88%), underscores the complexity of translating this biomarker into clinical practice. Although our meta-regression explored factors like sample size, country, and detection method for diagnostic comparisons, other unmeasured variables likely contribute to the heterogeneity. These include differences in the criteria used to define disease activity across studies (e.g. NIH criteria, Kerr’s criteria, physician’s global assessment), variations in assay methods and manufacturers (e.g. different ELISA kits), and demographic diversity in patient populations (e.g. age, sex, ethnicity, treatment history). The Begg’s test indicated potential publication bias for IL-6 in activity assessment, suggesting that smaller studies with null results might be underrepresented. While the trim-and-fill adjustment confirmed the robustness of the significant finding, this bias cautions against overinterpreting the effect size and highlights the need for more prospective, well-designed studies with pre-specified endpoints.

Relevant studies have shown that IL-6 has good performance in the auxiliary diagnosis of TA, with a sensitivity of 78.3%–89.1% and a specificity of 72.5%–85.7%. These data further support the potential clinical application value of IL-6 as a core biomarker for TA.

Regarding clinical applicability, the integration of these inflammatory cytokines, particularly IL-6, into current diagnostic or monitoring protocols holds promise but faces several barriers. In diagnosis, they could serve as adjunctive tools to support clinical suspicion, especially in atypical cases where traditional markers like ESR and CRP are equivocal. For monitoring, serial measurement of a panel of cytokines (e.g. IL-6, TNF-α, IL-17A) might provide a more granular view of disease activity than acute-phase reactants alone, potentially guiding treatment adjustments earlier. However, key barriers to implementation exist. Assay standardization is a major hurdle; different commercial kits and platforms (e.g. ELISA, luminex) yield varying absolute values, complicating the establishment of universal cut-off points. Cost-effectiveness is another concern, as multiplex cytokine profiling is more expensive than routine ESR/CRP measurement. Furthermore, the incremental benefit of these biomarkers over careful clinical assessment and imaging needs to be demonstrated in prospective management trials before widespread adoption can be recommended.

To a certain extent, the study of inflammatory factors can indicate the pathophysiological process of diseases. Our results further verified that the over-activation of Th1and Th17 pathways and imbalance between Treg and Th17 are the immunopathological characteristics of TA disease (Figure 7). Through further analysis and study of the meta-analysis results, we found this interesting phenomenon: the proliferation of inflammatory factors coincided with the activation of Th1 and Th17 pathways. For IL-6, which showed high heterogeneity (I² > 80%) in both diagnostic and activity assessments, several potential reasons should be emphasized. Firstly, the detection methods of IL-6 varied across studies, including ELISA, luminescence immunology and other techniques, and the differences in kit sources and detection principles may lead to deviations in the test results. Secondly, the study populations had obvious differences in terms of age, gender composition and regional distribution, and the genetic background and living environment of patients in different regions may affect the expression level of IL-6. Thirdly, the definition of disease activity was inconsistent among studies, with some using NIH criteria and others using Kerr score and ITKAS, which may lead to different judgments on the correlation between IL-6 and disease activity.

T cells play a key role in the maintenance of vasculitis, a type of arterial granulomatous inflammation[35]. Verma et al. found the proportion of CD4⁺ T cells (Th1 cells) and CD4⁺ T cells (Th17 cells) producing IFN-γ in peripheral blood of aTA patients was significantly higher than that of rTA and HD patients[17]. This suggests that the Th17 and Th1 pathways are involved in the systemic and vascular manifestations of TA. Inflammatory cytokines as effector mediators of T cell responses play a role in adaptive immune responses[36]. The IL-6/IL-17 and IL-12/IFN-γ axes are two immune pathways that closely coincide with the presence of two T cell lineages, Th1 and Th17 cells[37,38]. IL-12 induces Th1 response in concert with IL-18 and IFN-γ[39], and IL-6 is a key cytokine in Th17 cell differentiation[40]. High levels of Th1 and Th17 cytokines are widely believed to be associated with the disease activity of vasculitis[41]. However, there are obvious differences in the cytokine profile between TA and other large-vessel vasculitides such as Giant Cell Arteritis (GCA). In GCA, IL-1β and IL-23 are considered to be core pathogenic cytokines, while in our study, IL-6, IL-17A and TNF-α showed more significant up-regulation in TA patients. In addition, the level of IL-10, a regulatory cytokine, is negatively correlated with the activity of TA, which has not been clearly confirmed in GCA research. These differences reflect the unique immunopathological mechanism of TA and provide a basis for distinguishing TA from other similar vasculitides. Through further analysis and study of the meta-analysis results, we found this interesting phenomenon: the proliferation of inflammatory factors coincided with the activation of Th1 and Th17 pathways[37,38]. Combined with the results of Meta-analysis, it was found that IL-6, one of the core factors in cytokine storm, is more extensively reported in TA studies[25]. Although different groups adopted different criteria for active phase of TA, the elevated circulating expression of IL-6 in active stage was consistent. What’s more, INF-γ, IL-12, IL-18 are higher in TA. Thus, elevated levels of IL-12, IL-18, and INF-γ may be responsible for the proliferation of Th1 cells, while elevated levels of IL-6 may lead to the enhancement of Th17 cells, which is consistent with increased disease activity and verified that the over-activation of Th1 and Th17 pathways is one of the immunopathological processes of TA disease (Figure 7).

In addition to enhancement of Th1 and Th17, the roles of Th17 and regulatory T cells (Treg) cells also are found played important roles in the pathogenesis of autoimmune diseases[42]. Autoimmune diseases are characterized by impaired IL-2 production and dysregulated response of immune cells[43], resulting in functional deficits of Treg cell function and exaggerated effector cell expansion[44]. The differentiation of Treg and Th17 subsets is dichotomous cell fates of CD4⁺ T cells[45]. Different cytokines can have the potential to tip the subtle balance of between the Treg/Th17 lineages and alter by altering the fate of differentiating cells. This cell-fate decision is highly context-dependent, with transforming growth factor-β (TGF-β) acting as a common cytokine for both Th17 and Treg differentiation[46]. IL-2 has mainly an anti-inflammatory role by activating and inducing proliferation of Treg[47,48] and by inhibiting Th17 and follicular T cell differentiation[48]. However the balance between Th17 and Treg cells is in turn regulated by IL-6 as a driveing cytokine of Th17 cell differentiation[49]. Meanwhile, IL-10, mainly produced by Treg, regulates the immune response by suppressing the release and function of pro-inflammatory cytokines such as TNF-α, IL-1β and IL-6[50,51]. It has multiple effects on immunoregulation and inflammation, as it can inhibit the activation of macrophages and down-regulate the expression of Th1 cytokines[52] and limits immune responses during infectious states in order to prevent further damage to the host, that is essential for the maintenance of immune homeostasis and immune tolerance[53–55]. Through a review of the literature, We found that there are limited literature on interleukin 2, only Tripathy et al. was noted that IL-2 decreased during the active phase of aortitis[56]. As the same, some study have showed that the proportion of activated treg cells (the primary source of IL-10) in TA patients was lower than in healthy controls, regardless of disease activity[57]. Limited by the number of studies, a reduction in IL-2 cannot be directly demonstrated, but meta-analysis showed that active disease was associated with lower IL-10 levels compared with those in remission. The reduction of IL-10 further suggests that Treg is reduced in patients with TA. What’s more, Our meta analysis showed elevated IL-6 in TA and active patients, which may induce more treg conversion to Th17. Therefore, the decrease of IL-2 and the increase of IL-6 may be one of the mechanisms leading to the imbalance between Treg and Th17 which as one of the immunopathological processes of TA disease. A tendency showing elevated levels of IL-10 and low levels of IL-6 in stable patients shows that the balance of these critical cytokines may be a vital factor in controlling inflammation in TA patients on treatment[58] (Figure 7).

Considering several limitations of the included studies, the results of this meta-analysis should be discussed with cautions: (1) We must recognize that the immunopathological process of Takayasu’s arteritis is complex, and the assessment of disease status by cytokines as biomarkers is limited, but its clinical value and significance should not be completely denied. (2) The results of the study were affected by many factors, such as the year of publication, the number of samples included, gender, age, BMI, etc; Therefore, we have to acknowledge the existence of potential underexplored heterogeneity factors, which also makes the conclusions of the meta-analysis need to be treated with caution. (3) Among included studies, the inflammatory factors levels were detected by ELISA kits, luminescence immunology and so on. The sources and methods of inflammatory factors detection kits used were different, which may lead to the high heterogeneity among studies. Due to the small number of studies and insufficient information, no further regression analysis was conducted. In addition, for IL-6 with high heterogeneity in both diagnostic and activity assessments, there are other potential sources of heterogeneity that have not been fully explored. On the one hand, the criteria for evaluating disease activity in different studies are inconsistent, including NIH criteria, Kerr score, ITKAS and other standards, which leads to differences in the grouping of active and inactive patients. On the other hand, the demographic characteristics of patients such as age, gender and region also have certain impacts. The genetic background and living habits of patients in different regions may lead to differences in cytokine expression levels, which further increases the heterogeneity of the research results. (4) The asymmetrical funnel plots suggested the possibility of publication bias, implying a number of unpublished negative studies. Given the pressure for publications to focus on novel findings, it is not surprising that very few inflammatory biomarkers were tested in > 1 studies precluding meta-analysis of specific ones. However the Tweedie’s trim and fill method allows taking into account this bias and the risk estimates was comparable and still. In addition, due to the insufficient number of relevant studies, some cytokines such as IL-2 and IL-4 were not included in the meta-analysis. These cytokines are also involved in the regulation of the immune system and may play a role in the pathogenesis of TA. The lack of relevant analysis limits our comprehensive understanding of the immunopathological mechanism of TA. All in all, these limitations of past research may partly explain the lack of translation to clinical practice. It should be particularly emphasized that the Begg’s test for IL-6 activity assessment showed significant publication bias (P = 0.02). Although the Duval and Tweedie’s trim-and-fill method verified the robustness of the results, the potential existence of unpublished negative studies may still overestimate the correlation between IL-6 and TA activity. When interpreting this result, it is necessary to be cautious and not over-affirm the role of IL-6 in activity assessment.

Our meta-analysis suggests that IL-6 may be the most useful biomarker for the assessment of disease activity in patients with TA. In addition, our findings suggest that IL-2, IL-6, IL-12, IL-17A, TNF-α may be involved in the pathogenesis of aortitis, especially in patients with active aortitis, and may benefit from biotherapy that blocks these inflammatory cytokines. Currently, There are some blockers that have been used clinically to treat TA. TNF-α antagonists, such as etanercept and infliximab, led to partial remission in 53.5%, complete remission in 37%, and 9.5% were non-responders[59,60]. Tocilizumab, a humanized IgG1 anti-IL-6R monoclonal antibody targeting the IL-6 signaling pathway, was widely used in clinical trials in the 1990s and has been used in a variety of diseases such as rheumatoid arthritis[61]. TOCITAKA trial showed that the disease activity was significantly reduced after 6 months of tocilizumab treatment in newly diagnosed TA patients. Thirty-six percent of patients are free of additional therapy for at least 18 months after treatment with tocilizumab[62]. All in all, biomarkers in blood can be used to closely track the extent of T-cell and monocyte abnormalities, and the multiple pathways driving this vasculitis can be inhibited and appropriately regulated by drugs. So future studies on the role of IL-12、IL-17A in vivo and the stimuli that induce its production in the disease would be of paramount importance and may provide a new basis for the development of immunotherapeutic Interventions for TA and other related vasculopathies. In terms of clinical applicability, these identified biomarkers can be integrated into the existing diagnostic and monitoring protocols of TA in multiple ways. In the diagnostic process, combining TNF-α, IL-6, IFN-γ and traditional indicators such as ESR and CRP can improve the diagnostic accuracy of TA, especially for early patients with atypical clinical symptoms. In the disease monitoring process, regular detection of IL-6, IL-12 and IL-17A can dynamically evaluate the disease activity, so as to timely adjust the treatment plan and avoid excessive treatment or insufficient treatment. In addition, these biomarkers can also be used to evaluate the therapeutic effect. For example, the decrease of IL-6 level after tocilizumab treatment can be used as an important indicator of treatment response. However, there are still some barriers to the clinical implementation of these biomarkers. Firstly, the lack of unified detection standards leads to inconsistent results between different laboratories, which affects the comparability of data. Secondly, the detection cost of some cytokines (such as detection by flow cytometry) is relatively high, which is not conducive to popularization in primary medical institutions. Thirdly, the current clinical guidelines have not included these cytokines as routine detection indicators, and there is a lack of relevant clinical consensus support.

Conclusion

This meta-analysis suggests 7 cytokines and chemokines could serve as potential circulating biomarkers on auxiliary diagnosis (TNF-α, IFN-γ, IL-6, IL-8, IL-12, IL-17A) and assessing activity (TNF-α, IL-6, IL-12, IL-17A, IL-10) in TA or inactive phase. But the sentitivity and specificity of these biomarkers require more validations. biomarkers are closely related to the pathophysiological process of the disease, and these biomarkers can be used to indicate the immune status in patients with TA. Our results further verified that the over-activation of Th1 and Th17 pathways and imbalance between Treg and Th17 are the immunopathological characteristics of TA disease Therapeutic goals can be achieved by inhibiting multiple inflammatory pathways that drive this vasculitis with the use of immunosuppressive agents. Further investigation of the role of relevant biomarkers in vivo as well as the associated inflammatory pathways is essential. It may provide a new direction for future research on TA disease progression and a new basis for the development of immunotherapy interventions against TA. However, due to the limited number of related studies, the number of included literatures and the sample size of patients are limited, and further relevant studies are needed to obtain more reliable conclusions.

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