Key result
The AT1R+1166A/C polymorphism C allele was associated with increased MI risk (OR 1.13, p=0.005), but large between-study heterogeneity and bias suggest such genetic associations may be unreliable.
Why the study?
Are candidate genetic polymorphisms truly associated with an increased risk of myocardial infarction, or are the associations subject to bias?
Meta-Analysis (n=27,309)
Are candidate genetic polymorphisms truly associated with an increased risk of myocardial infarction, or are the associations subject to bias?
Many formally significant genetic associations for myocardial infarction in meta-analyses may be driven by bias rather than true genetic effects, emphasizing the need for large-scale, rigorous validation.
Genetic MI associations warrant caution due to bias risk; challenges many candidate-gene meta-analyses and leaves true effects open pending rigorous validation.
Several genetic polymorphisms have been proposed to be associated with myocardial infarction (MI). The authors examined the evidence and biases underlying such associations using a case-study meta-analysis and an overview of large-scale data. In a meta-analysis of 27 studies addressing the association of the angiotensin type 1 receptor (AT1R)+1166A/C polymorphism with MI (10,180 cases, 17,129 controls), the *C allele conferred an increase in MI risk (odds ratio = 1.13 per allele, p = 0.005). However, there was large between-study heterogeneity; the largest study showed no effect, contradicting smaller studies; and studies with blinded genotyping showed no effect. The authors conducted an overview of meta-analyses of genetic associations for MI or coronary artery disease, including at least three studies and 3,000 subjects. In their latest meta-analysis, another 14 polymorphisms were found to have formally significant associations. If true, these associations would already explain 42% of the MI risk for Caucasian populations. Significant between-study heterogeneity was common. Across the 32 largest studies, only two found formally significant results (nine would be expected if each meta-analysis showed a true association). Even with large-scale evidence from meta-analyses, significant associations for MI may be subject to bias. Large-scale single studies and prospective consortia should be used for detecting and validating the genetic determinants of MI.
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Ntzani et al. (2007) conducted a meta-analysis in Myocardial infarction (n=27,309). AT1R+1166A/C polymorphism (C allele) vs. Non-carriers / other alleles was evaluated on Myocardial infarction risk (OR 1.13, p=0.005). The AT1R+1166A/C polymorphism C allele was associated with increased MI risk (OR 1.13, p=0.005), but large between-study heterogeneity and bias suggest such genetic associations may be unreliable.
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