{"title":"Association of Four VEGFA Gene Variants with Rheumatoid Arthritis Risk: A Meta-analysis and Trial Sequential Analysis.","authors":"Ke Li, Yilu Wang, Peng Huang","doi":"10.1007/s10528-024-10834-1","DOIUrl":null,"url":null,"abstract":"<p><p>The association between rheumatoid arthritis (RA) risk and specific variants of the Vascular Endothelial Growth Factor A (VEGFA) gene remains contentious. This study sought to elucidate the correlations between RA risk and several VEGFA gene variants, including VEGFA-634 (rs2010963), VEGFA-C936 (rs3025039), VEGFA-2578 (rs699947), VEGFA-1154 (rs1570360), through a comprehensive meta-analysis. We systematically reviewed literature from the Cochrane Library database, Embase, PubMed, Web of Science, China National Knowledge Infrastructure, and the Wanfang Data Information Service platform to gather relevant case-control studies. Using odds ratio (OR) and 95% confidence interval (95% CI), we analyzed the data to assess potential correlations. Sensitivity analysis and the Egger's test were employed to ensure the results stability and to evaluate potential publication bias. Additionally, trial sequential analysis (TSA) was conducted to validate the findings. Our meta-analysis incorporated ten studies involving 2817 patients and 2855 controls. Results indicated that the AA genotype of VEGFA-1154 (rs1570360) is associated with a reduced risk of RA in the overall population (AG + GG vs AA: P = 0.032 OR = 1.932 95% CI 1.059-3.523). However, no significant association is found for VEGFA-634 (rs2010963), VEGFA-C936 (rs3025039), and VEGFA-2578 (rs699947) variants with RA risk. Subgroup analysis revealed a significant association between the VEGF rs3025039(C936) variant and RA risk in the PCR-RFLP group under the TC vs. CC model. TSA confirmed the sufficiency of the sample size for robust conclusions. These findings suggest that the G allele of VEGFA-1154 (rs1570360) may increase RA risk, whereas the A allele appears to confer a protective effect. This study enhances our understanding of the genetic predispositions to RA and underscores the potential role of VEGFA gene variants in its pathogenesis.</p>","PeriodicalId":482,"journal":{"name":"Biochemical Genetics","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochemical Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s10528-024-10834-1","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The association between rheumatoid arthritis (RA) risk and specific variants of the Vascular Endothelial Growth Factor A (VEGFA) gene remains contentious. This study sought to elucidate the correlations between RA risk and several VEGFA gene variants, including VEGFA-634 (rs2010963), VEGFA-C936 (rs3025039), VEGFA-2578 (rs699947), VEGFA-1154 (rs1570360), through a comprehensive meta-analysis. We systematically reviewed literature from the Cochrane Library database, Embase, PubMed, Web of Science, China National Knowledge Infrastructure, and the Wanfang Data Information Service platform to gather relevant case-control studies. Using odds ratio (OR) and 95% confidence interval (95% CI), we analyzed the data to assess potential correlations. Sensitivity analysis and the Egger's test were employed to ensure the results stability and to evaluate potential publication bias. Additionally, trial sequential analysis (TSA) was conducted to validate the findings. Our meta-analysis incorporated ten studies involving 2817 patients and 2855 controls. Results indicated that the AA genotype of VEGFA-1154 (rs1570360) is associated with a reduced risk of RA in the overall population (AG + GG vs AA: P = 0.032 OR = 1.932 95% CI 1.059-3.523). However, no significant association is found for VEGFA-634 (rs2010963), VEGFA-C936 (rs3025039), and VEGFA-2578 (rs699947) variants with RA risk. Subgroup analysis revealed a significant association between the VEGF rs3025039(C936) variant and RA risk in the PCR-RFLP group under the TC vs. CC model. TSA confirmed the sufficiency of the sample size for robust conclusions. These findings suggest that the G allele of VEGFA-1154 (rs1570360) may increase RA risk, whereas the A allele appears to confer a protective effect. This study enhances our understanding of the genetic predispositions to RA and underscores the potential role of VEGFA gene variants in its pathogenesis.
期刊介绍:
Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses.
Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication.
Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses.
Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods.
Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.