Association of interleukin-6 and interleukin-10 expression, gene polymorphisms, and Takayasu arteritis in a Chinese Han population

Interleukin 6 Levels and Disease Activity in Takayasu Arteritis: A Systematic Review With Meta-analysis

BACKGROUND

Various studies have suggested interleukin 6 (IL-6) as a potential biomarker for detecting disease activity in Takayasu arteritis.

METHODS

A systematic review and meta-analysis was performed to assess differences in IL-6 levels in patients with active (aTA) and inactive Takayasu arteritis (iTA), as well as healthy controls (HCs), using validated activity scores. Study quality and the risk of bias were assessed using STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and the Newcastle-Ottawa and Joanna Briggs checklist, respectively. For the meta-analysis, we pooled the raw mean IL-6 levels in each group and then estimated and pooled the crude mean differences between the groups. We applied a random-effects model in all analyses.

RESULTS

Of the 93 eligible articles, 10 were included after removing duplicates and studies that met the exclusion criteria. Overall, 1825 patients with a mean age ranging from 24 to 40.6 years were included. The pooled levels of IL-6 increased depending on disease activity as follows: HCs: 3.08 (95% confidence interval [CI], 0.88-5.28), iTA: 7.21 (3.61-10.82), and aTA: 22.67 (12.44-32.91) pg/mL. Patients with aTA had higher IL-6 levels than HCs (21.52 [95% CI, -0.43 to 43.47]) and those with iTA (16.69 [95% CI, 5.32-28.06]), whereas IL-6 levels were not different between HCs and patients with iTA (3.62 [95% CI, -13.18 to 20.42]).

CONCLUSIONS

Interleukin 6 levels are significantly increased in patients with aTA compared with those with iTA and HCs but not in patients with iTA compared with HCs. More studies are needed to establish the IL-6 cutoff value for assessing disease activity.

Systemic review and meta-analysis of the association between interleukin-10 and Takayasu arteritis

OBJECTIVE

The aim of this meta-analysis is to investigate the relationship between interleukin (IL)-10 levels and its polymorphism and Takayasu arteritis (TAK).

METHODS

Five databases including PubMed, Web of Science, Ovid, Sinomed and China National Knowledge Infrastructure (CNKI) were gone through from inception to March 31, 2022. Studies were screened according to the inclusion and exclusion criteria. Newcastle-Ottawa Scale (NOS) was applied to assess study quality. Strengths of association were evaluated by odds ratio (OR) and 95% CI. The T v. t (allele contrast), TT v. tt (homozygous contrast), Tt vs tt (heterozygous contrast), TT + Tt vs tt (dominant contrast) and TT vs Tt + tt (recessive contrast) models were adopted.

RESULTS

Seven studies were included. No significant relationship between IL-10 and TAK was detected in the included patients (P > 0.05). The levels of IL-10 were lower in the active group than those in the stable group, which was -0.47 (95% CI: -0.93, 0.00) (P = 0.05). No significant relationships between IL-10 and TAK were found under all contrasts for polymorphisms rs1800871, rs1800872 and rs1800896 (P > 0.05).

CONCLUSIONS

There was no significant difference in IL-10 levels between TAK patients and control subjects. The levels of IL-10 were lower in TAK patients in the active stage. There was no significant association between IL-10 gene polymorphisms and TAK. Further well-designed studies with larger sample sizes in patients with different stages are needed.

Biomarker Changes and Molecular Signatures Associated with Takayasu Arteritis Following Treatment with Glucocorticoids and Tofacitinib

Objective

This study aimed to analyze biomarker changes in patients with TAK following treatment with glucocorticoids (GCs) and tofacitinib (TOF).

Methods

Seventeen patients from a prospective TAK cohort treated with GCs and TOF and 12 healthy individuals were recruited. TAK associated cytokines, chemokines, growth factors, and MMPs were analyzed in these patients before and after GCs and TOF treatment, and healthy controls. Molecular signatures associated with clinical features were evaluated.

Results

Patients’ cytokines (PTX3, IL-6, IFN-γ), chemokines (IL-16, CCL22, CCL2), growth factors (VEGF), and MMP9 levels were significantly higher at baseline (all p < 0.05), while patients’ FGF-2 levels were significantly lower (p = 0.02). After treatment, IL-10 was significantly increased at 6 months (p=0.007), and inflammatory cytokines such as PTX3, IL-6 demonstrated a downward trend. Patients without vascular occlusion had higher baseline CCL22 levels than patients with it (p = 0.05), which remained persistently higher after treatment. Radar plot analysis demonstrated that PTX3 was closely correlated with disease activity. In addition, patients without imaging improvement had relatively higher baseline levels of CCL22, FGF-2, and PDGF-AB (p = 0.056, p = 0.06 and p = 0.08 respectively) and lower baseline levels of TNFα, ESR, and CRP (p=0.04, p=0.056, p=0.07, respectively) compared with patients without it.

Conclusion

GCs and TOF are effective in decreasing inflammatory molecules but have limited efficacy in regulating multiple other markers involved in TAK. PTX3 is a prominent marker for disease activity, and CCL22 may have a predictive value for vascular progression.

Using the co-expression network of T cell-activation-related genes to assess the disease activity in Takayasu's arteritis patients

Background

There have been lacking reliable serum biomarkers in assessing the disease activity of Takayasu’s arteritis (TAK). This study aimed to assess the disease activity of TAK by assayed gene expression levels in peripheral mononuclear cells (PBMCs).

Methods

The expression level of genes that essential in T cell activation in PBMCs in active TAK patients, inactive TAK patients, and healthy controls were detected by real-time fluorescence quantitative polymerase chain reaction, including TCR, CD28, CD40, CD40L, PD-1, PD-L1, PD-L2, CTLA4, TIGIT, TIM3, LAG3, CCL5, T-bet, RORC, and FOXP3. Gene co-expression network was established, and the signature of the topology structure in active TAK patients compared to the inactive TAK patients were extracted and described by formulas. Respectively, the disease activity was assessed by the routine serum biomarkers, including ESR, CRP, IL-6, and TNF-α, the gene expression level of TCR, CD28, T-bet, and RORC, as well as the signature of the topology structure, and the diagnostic efficacies were compared.

Results

Compared with the inactive TAK patient group, the active TAK patient group had a greater clustering coefficient in the network consisting of genes that essential in T cell activation. When assessing the disease activity used this signature of topology structure, the sensitivity was 90.9%, the specificity was 100%, and the AUC was 0.98, which was greater than the AUCs of these biomarkers.

Conclusions

The signature of the topology structure could distinguish the active TAK patients from inactive TAK patients. This maybe is a novel evaluation algorithm of disease activity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02636-2.