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      Variants in Exon 11 of MEF2A Gene and Coronary Artery Disease: Evidence from a Case-Control Study, Systematic Review, and Meta-Analysis

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          Abstract

          Background

          Coronary artery disease (CAD) is the most common heart disease worldwide. Association of CAD with variants in the myocyte enhancer factor 2A ( MEF2A) gene, the first identified CAD-causing gene, has attracted special attention but the results are controversial. We aimed to evaluate this genetic association via a case-control study and meta-analysis.

          Methodology/Principal Findings

          We performed a case-control association study to investigate the relationship between variations in exon 11 of MEF2A gene and CAD in 1045 sporadic patients and 1008 controls enrolled angiographically among southern Chinese population, and then the data from this study were compared and discussed in a systematic review and meta-analysis with all available published studies on MEF2A gene and CAD. In total, eight variants were identified (21-bp deletion, CAG repeats, CCG repeats, a CCA deletion and four SNPs). No significant link was observed between the common (CAG) n polymorphism and CAD, whereas the rare 21-bp deletion was detected only in five affected individuals. The meta-analysis of (CAG) n polymorphism and CAD risk, including nine studies with 3801 CAD patients and 4020 controls, also provided no convincing evidence for the genetic association, even upon stratification by race (mainly Whites and Chinese). However, the 21-bp deletion was regarded as a potentially logical, albeit undetermined, candidate for CAD in the following systematic review.

          Conclusions/Significance

          Our findings failed to demonstrate a correlation between (CAG) n polymorphism with CAD, however, we concluded that the rare 21-bp deletion might have a more compelling effect on CAD than the common (CAG) n polymorphism, and MEF2A genetic variant might be a rare but specific cause of CAD/MI.

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          Most cited references45

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          Association study designs for complex diseases.

          Assessing the association between DNA variants and disease has been used widely to identify regions of the genome and candidate genes that contribute to disease. However, there are numerous examples of associations that cannot be replicated, which has led to skepticism about the utility of the approach for common conditions. With the discovery of massive numbers of genetic markers and the development of better tools for genotyping, association studies will inevitably proliferate. Now is the time to consider critically the design of such studies, to avoid the mistakes of the past and to maximize their potential to identify new components of disease.
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            How meta-analysis increases statistical power.

            One of the most frequently cited reasons for conducting a meta-analysis is the increase in statistical power that it affords a reviewer. This article demonstrates that fixed-effects meta-analysis increases statistical power by reducing the standard error of the weighted average effect size (T.) and, in so doing, shrinks the confidence interval around T.. Small confidence intervals make it more likely for reviewers to detect nonzero population effects, thereby increasing statistical power. Smaller confidence intervals also represent increased precision of the estimated population effect size. Computational examples are provided for 3 effect-size indices: d (standardized mean difference), Pearson's r, and odds ratios. Random-effects meta-analyses also may show increased statistical power and a smaller standard error of the weighted average effect size. However, the authors demonstrate that increasing the number of studies in a random-effects meta-analysis does not always increase statistical power.
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              Mutation of MEF2A in an inherited disorder with features of coronary artery disease.

              The early genetic pathway(s) triggering the pathogenesis of coronary artery disease (CAD) and myocardial infarction (MI) remain largely unknown. Here, we describe an autosomal dominant form of CAD/MI (adCAD1) that is caused by the deletion of seven amino acids in transcription factor MEF2A. The deletion disrupts nuclear localization of MEF2A, reduces MEF2A-mediated transcription activation, and abolishes synergistic activation by MEF2A and by the transcription factor GATA-1 through a dominant-negative mechanism. The MEF2A protein demonstrates strong expression in the endothelium of coronary arteries. These results identify a pathogenic gene for a familial vascular disease with features of CAD and implicate the MEF2A signaling pathway in the pathogenesis of CAD/MI.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                21 February 2012
                : 7
                : 2
                : e31406
                Affiliations
                [1 ]Department of Cardiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
                [2 ]State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
                College of Pharmacy, University of Florida, United States of America
                Author notes

                Conceived and designed the experiments: YL WJ. Performed the experiments: ZW XS QC. Analyzed the data: YL WN WJ. Contributed reagents/materials/analysis tools: WN ZW LL. Wrote the paper: YL WN WJ. Reference collection and data management: YL WN WJ.

                Article
                PONE-D-11-23284
                10.1371/journal.pone.0031406
                3283621
                22363637
                5cb9059f-73f5-479a-a51c-7450f8199a1d
                Liu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 8 November 2011
                : 10 January 2012
                Page count
                Pages: 10
                Categories
                Research Article
                Biology
                Computational Biology
                Population Genetics
                Medicine
                Cardiovascular
                Clinical Genetics
                Clinical Research Design
                Epidemiology

                Uncategorized
                Uncategorized

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