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. 2015 Aug 15;8(8):11958-84.
eCollection 2015.

The role of gene variants of the inflammatory markers CRP and TNF-α in cardiovascular heart disease: systematic review and meta-analysis

Yazmín Hernández-Díaz  1 , Carlos Alfonso Tovilla-Zárate  2 , Isela Juárez-Rojop  3 , Manuel Alfonso Baños-González  4 , Manuel Eduardo Torres-Hernández  4 , María Lilia López-Narváez  5 , Teresa Guadalupe Yañez-Rivera  6 , Thelma Beatriz González-Castro  1
Affiliations

The role of gene variants of the inflammatory markers CRP and TNF-α in cardiovascular heart disease: systematic review and meta-analysis

Yazmín Hernández-Díaz et al. Int J Clin Exp Med. .

Abstract

It is widely acknowledged that cardiovascular heart disease (CHD) has a genetic influence. Several studies have investigated the role of inflammatory markers like C-reactive protein (CRP) and tumor necrosis factor α (TNF-α) in the causation of cardiovascular diseases. Although there have been several positive studies associating CRP and TNF-α genes with CHD, the evidence is not entirely consistent. Therefore, we performed a meta-analysis to gain a better understanding into this issue. The meta-analysis was conducted with 22 articles of genetic association studies of CRP (G1059C rs1800947, C1444T rs1130864, C717T rs2794521 and G3872A rs1205) and TNF-α (C857T rs1799724, C863A rs1800630 and T1031C rs1799964) genes. To analyze the association of these variants with CHD we used the following models: allelic, additive, dominant and recessive. In addition, we performed a sub-group analysis by Caucasian population using the same four models. CRP and TNF-α gene polymorphisms showed a positive significant association with CHD. This study provides evidence that rs2794521 of the CRP gene and rs1799724, rs1800630 and rs1799964 of the TNF-α gene polymorphisms may be risk factors to manifest CHD. The analysis of rs1800947 and rs1205 of the CRP gene yielded a protective effect in the pathogenesis of this disease. Only the analysis of the rs1130864 polymorphism showed a lack of association with CHD. To have conclusive outcomes it is necessary to integrate more studies to confirm our findings.

Keywords: C-reactive protein; Cardiovascular disease; TNF-α; meta-analysis and systematic review; polymorphisms.

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Figures

Figure 1
Figure 1
Flow-chart showing the search strategy and inclusion/exclusion criteria used in the meta-analysis and systematic review.
Figure 2
Figure 2
Odds ratios and forest plots of the PCR rs1800947 variant in overall studies, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 3
Figure 3
Egger’s funnel plots in overall studies indicating publication bias in studies on CHD and PCR rs1800947 variant, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 4
Figure 4
Odds ratios and forest plots of PCR rs1130864 variant in overall studies, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 5
Figure 5
Egger’s funnel plots in overall studies indicating publication bias in studies on CHD and PCR rs1130864 variant, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 6
Figure 6
Odds ratios and forest plots of the PCR rs2794521 variant in overall studies, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 7
Figure 7
Egger’s funnel plots in overall studies indicating publication bias in studies on CHD and PCR rs2794521 variant, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 8
Figure 8
Odds ratios and forest plots of the PCR rs1205 variant in overall studies, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 9
Figure 9
Egger’s funnel plots in overall studies indicating publication bias in studies on CHD and PCR rs1205 variant, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 10
Figure 10
Odds ratios and forest plots of the TNF-α rs1799724 variant in overall studies, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 11
Figure 11
Egger’s funnel plots in overall studies indicating publication bias in studies on CHD and TNF-α rs1799724 variant, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 12
Figure 12
Odds ratios and forest plots of the TNF-α rs1800630 variant in overall studies, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 13
Figure 13
Egger’s funnel plots in overall studies indicating publication bias in studies on CHD and TNF-α rs1800630 variant, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 14
Figure 14
Odds ratios and forest plots of the TNF-α rs1799964 variant in overall studies, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
Figure 15
Figure 15
Egger’s funnel plots in overall studies indicating publication bias in studies on CHD and TNF-α rs1799964 variant, without heterogeneity, using the following models: A. Allelic; B. Additive; C. Dominant, and D. Recessive.
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