scholarly journals miRNA Polymorphisms and Risk of Cardio-Cerebrovascular Diseases: A Systematic Review and Meta-Analysis

2019 ◽  
Vol 20 (2) ◽  
pp. 293 ◽  
Author(s):  
Milad Bastami ◽  
Jalal Choupani ◽  
Zahra Saadatian ◽  
Sepideh Zununi Vahed ◽  
Yaser Mansoori ◽  
...  
Keyword(s):  
Systematic Review ◽  
Coronary Artery Disease ◽  
Congenital Heart Disease ◽  
Ischemic Stroke ◽  
Congenital Heart ◽  
Web Of Science ◽  
Meta Analysis ◽  
Cerebrovascular Diseases ◽  
Artery Disease

Recently extensive focus has been concentrated on the role of miRNAs in the initiation and progression of cardio-cerebrovascular diseases (CCDs) which constitute a range of conditions including cardiovascular diseases (CVDs, especially coronary artery disease (CAD)), congenital heart disease (CHD) and cerebrovascular diseases (CBVDs, especially the ischemic stroke (IS)). An increasing number of studies are evaluating the association between different miRNA polymorphisms and risk of CCDs, but results have been inconclusive. This study represents a comprehensive systematic review and meta-analysis of the association between miRNA polymorphisms and risk of CCDs. PubMed, Embase, Scopus, and Web of Science were queried to identify eligible articles. Odds ratios and 95% confidence intervals were used to assess the association of miRNA polymorphisms with CCD susceptibility. A total of 51 eligible articles evaluating the association of 31 miRNA polymorphisms were identified. Meta-analysis was performed for six miRNA polymorphisms. miR-146a rs2910164 (30 studies: 13,186 cases/14,497 controls), miR-149 rs2292832 (Nine studies: 4116 cases/3511 controls), miR-149 rs71428439 (Three studies: 1556 cases/1567 controls), miR-196a2 rs11614913 (20 studies: 10,144 cases/10,433 controls), miR-218 rs11134527 (Three studies: 2,322 cases/2,754 controls) were not associated with overall CCD. miR-499 rs3746444 was associated with CCD (20 studies: 9564 cases/8876 controls). In the subgroups, rs2910164 and rs3746444 were only associated with CVDs, especially CAD. In conclusion, the results support the existence of a role for miR-146a rs2910164 and miR-499 rs3746444 in determining susceptibility to CCDs, especially CAD.

scholarly journals Discrimination capability of pretest probability of stable coronary artery disease: a systematic review and meta-analysis suggesting how to improve validation procedures

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e047677
Author(s):  
Pierpaolo Mincarone ◽  
Antonella Bodini ◽  
Maria Rosaria Tumolo ◽  
Federico Vozzi ◽  
Silvia Rocchiccioli ◽  
...  
Keyword(s):  
Systematic Review ◽  
Coronary Artery Disease ◽  
Chest Pain ◽  
Coronary Artery ◽  
Quality Assessment ◽  
Meta Analysis ◽  
Stable Coronary Artery Disease ◽  
First Line ◽  
Discrimination Capability ◽  
Artery Disease

ObjectiveExternally validated pretest probability models for risk stratification of subjects with chest pain and suspected stable coronary artery disease (CAD), determined through invasive coronary angiography or coronary CT angiography, are analysed to characterise the best validation procedures in terms of discriminatory ability, predictive variables and method completeness.DesignSystematic review and meta-analysis.Data sourcesGlobal Health (Ovid), Healthstar (Ovid) and MEDLINE (Ovid) searched on 22 April 2020.Eligibility criteriaWe included studies validating pretest models for the first-line assessment of patients with chest pain and suspected stable CAD. Reasons for exclusion: acute coronary syndrome, unstable chest pain, a history of myocardial infarction or previous revascularisation; models referring to diagnostic procedures different from the usual practices of the first-line assessment; univariable models; lack of quantitative discrimination capability.MethodsEligibility screening and review were performed independently by all the authors. Disagreements were resolved by consensus among all the authors. The quality assessment of studies conforms to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A random effects meta-analysis of area under the receiver operating characteristic curve (AUC) values for each validated model was performed.Results27 studies were included for a total of 15 models. Besides age, sex and symptom typicality, other risk factors are smoking, hypertension, diabetes mellitus and dyslipidaemia. Only one model considers genetic profile. AUC values range from 0.51 to 0.81. Significant heterogeneity (p<0.003) was found in all but two cases (p>0.12). Values of I2 >90% for most analyses and not significant meta-regression results undermined relevant interpretations. A detailed discussion of individual results was then carried out.ConclusionsWe recommend a clearer statement of endpoints, their consistent measurement both in the derivation and validation phases, more comprehensive validation analyses and the enhancement of threshold validations to assess the effects of pretest models on clinical management.PROSPERO registration numberCRD42019139388.

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