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Meta-Analysis
. 2019 Jun;98(26):e15963.
doi: 10.1097/MD.0000000000015963.

Tumor necrosis factor-α-308 polymorphism is not associated with Kawasaki disease: A meta-analysis of case-control studies

Affiliations
Meta-Analysis

Tumor necrosis factor-α-308 polymorphism is not associated with Kawasaki disease: A meta-analysis of case-control studies

Ye Yuan et al. Medicine (Baltimore). 2019 Jun.

Abstract

Background: Genetic factors in the pathogenesis of Kawasaki disease (KD) have received a lot of attention during the past decade. Some studies have reported that tumor necrosis factor (TNF)-α-308 polymorphism has been associated with KD. However, there have been inconsonant results among different studies. To increase the power for clarifying the influence of TNF on KD, a meta-analysis of case-control studies were performed.

Methods: The following databases were searched to identify related studies: PubMed, Embase, Cochrane Library, CNKI, Wanfang, and VIP databases according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Search terms included "Kawasaki disease" or "KD," "tumor necrosis factor-alpha" or "TNF-α," and "polymorphism" or "mutation." Two reviewers independently extracted data and assessed study quality using Newcastle-Ottawa Scale. Odds ratios (ORs) with corresponding 95% confidence intervals (CI) were used to assess the strength of the association. Accounting for heterogeneity, a fixed or random effects model was respectively adopted. Heterogeneity was checked using the Q test and the I statistic. A cumulative meta-analysis was conducted to estimate the tendency of pooled OR. Funnel plots and Egger tests were performed to test for possible publication bias and sensitivity analyses were done to ensure authenticity of the outcome.

Results: Eleven separate studies were suitable for the inclusion criterion. The selected studies contained 2582 participants, including 841 in KD group and 1741controls. The pooled odds ratio of G versus A with the random effect model was 1.09 (95% CI = 0.69-1.70, P = .72) and the genotype effects for GG versus GA+AA was 1.14 (95% CI = 0.68-1.90, P = .62) in the whole population separately. Unfortunately, no significant association was detected between the TNF-α-308 polymorphism and KD risk under allele and genotype model.

Conclusion: No association between the TNF-α-308 polymorphism and KD was found in our meta-analysis and further studies with larger sample size and more ethnicities are expected to be conducted in the future to validate the results.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Flowchart of study selection.
Figure 2
Figure 2
Forest plot of KD and TNF-α-308 in a G versus A model, the horizontal lines correspond to the study-specific OR and 95% CI, respectively. The area of the squares reflects the study-specific weight. The diamond represents the pooled results of OR and 95% CI. CI = confidence intervals, KD = Kawasaki disease, OR = odds ratios, TNF = tumor necrosis factor.
Figure 3
Figure 3
Forest plot of KD and TNF-α-308 in a GG versus GA+AA model, the horizontal lines correspond to the study-specific OR and 95% CI, respectively. The area of the squares reflects the study-specific weight. The diamond represents the pooled results of OR and 95% CI. CI = confidence intervals, KD = Kawasaki disease, OR = odds ratios, TNF = tumor necrosis factor.
Figure 4
Figure 4
Forest plot of KD and TNF-α-308 in Caucasian and Asian subgroup, the horizontal lines correspond to the study-specific OR and 95% CI, respectively. The area of the squares reflects the study-specific weight. The diamond represents the pooled results of OR and 95% CI. CI = confidence intervals, KD = Kawasaki disease, OR = odds ratios, TNF = tumor necrosis factor.
Figure 5
Figure 5
Begg funnel plot for publication bias tests. Each point represents a separate study for the indicated association. Log or represents natural logarithm of OR. Vertical line represents the mean effects size. OR = odds ratios.
Figure 6
Figure 6
Potential outliers (i.e., data points that are far outside the norm) were identified by a sensitivity analysis.

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