BACKGROUND: Carotid intima-media thickness (CIMT) is highly heritable and associated with stroke and myocardial infarction, making it a promising quantitative intermediate phenotype for genetic studies of vascular disease. There have been many CIMT candidate gene association studies, but no systematic review to identify consistent, reliable findings. METHODS AND RESULTS: We comprehensively sought all published studies of association between CIMT and any genetic polymorphism. We obtained additional unpublished data and performed meta-analyses for the 5 most commonly studied genes (studied in at least 2 studies in a total of >5000 subjects). We used a 3-step meta-analysis method: meta-analysis of variance; genetic model selection; and random effects meta-analysis of the mean CIMT difference between genotypes. We performed subgroup analyses to investigate effects of ethnicity, vascular risk status, and study size. We accounted for potential reporting bias by assessing qualitatively the possible effects of including unavailable data. Polymorphisms in 3 of the 5 genes (apolipoprotein E, angiotensin I converting enzyme, and 5,10-methylenetetrahydrofolate reductase) had an apparent association with CIMT, but for all these, we found evidence of small study bias. Apolipoprotein E epsilon2/epsilon3/epsilon4 was the only polymorphism with a persistent, statistically significant but modest association when we restricted analysis to larger studies (>1000 subjects). CONCLUSIONS: Of the most extensively studied polymorphisms, apolipoprotein E epsilon2/epsilon3/epsilon4 is the only one so far with a convincing association with CIMT. Larger studies than have generally been performed so far may be needed to confirm the associations identified in future genome-wide association studies, and to investigate modification of effect according to characteristics such as ethnicity and vascular risk status.
BACKGROUND: Carotid intima-media thickness (CIMT) is highly heritable and associated with stroke and myocardial infarction, making it a promising quantitative intermediate phenotype for genetic studies of vascular disease. There have been many CIMT candidate gene association studies, but no systematic review to identify consistent, reliable findings. METHODS AND RESULTS: We comprehensively sought all published studies of association between CIMT and any genetic polymorphism. We obtained additional unpublished data and performed meta-analyses for the 5 most commonly studied genes (studied in at least 2 studies in a total of >5000 subjects). We used a 3-step meta-analysis method: meta-analysis of variance; genetic model selection; and random effects meta-analysis of the mean CIMT difference between genotypes. We performed subgroup analyses to investigate effects of ethnicity, vascular risk status, and study size. We accounted for potential reporting bias by assessing qualitatively the possible effects of including unavailable data. Polymorphisms in 3 of the 5 genes (apolipoprotein E, angiotensin I converting enzyme, and 5,10-methylenetetrahydrofolate reductase) had an apparent association with CIMT, but for all these, we found evidence of small study bias. Apolipoprotein E epsilon2/epsilon3/epsilon4 was the only polymorphism with a persistent, statistically significant but modest association when we restricted analysis to larger studies (>1000 subjects). CONCLUSIONS: Of the most extensively studied polymorphisms, apolipoprotein E epsilon2/epsilon3/epsilon4 is the only one so far with a convincing association with CIMT. Larger studies than have generally been performed so far may be needed to confirm the associations identified in future genome-wide association studies, and to investigate modification of effect according to characteristics such as ethnicity and vascular risk status.
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Authors: P Coletta; G Barbarossa; D Pergolini; L D'Erasmo; A Renzi; L Mercuri; M G Anatra; E Ciociola; A Verrienti; M Maranghi Journal: Endocrine Date: 2012-08-17 Impact factor: 3.633
Authors: Phillip E Melton; Melanie A Carless; Joanne E Curran; Thomas D Dyer; Harald H H Göring; Jack W Kent; Eugene Drigalenko; Matthew P Johnson; Jean W Maccluer; Eric K Moses; Anthony G Comuzzie; Michael C Mahaney; Daniel H O'Leary; John Blangero; Laura Almasy Journal: Circ Cardiovasc Genet Date: 2013-03-13
Authors: Brett Doliner; Chuanhui Dong; Susan H Blanton; Hannah Gardener; Mitchell S V Elkind; Ralph L Sacco; Ryan T Demmer; Moise Desvarieux; Tatjana Rundek Journal: J Stroke Cerebrovasc Dis Date: 2017-11-02 Impact factor: 2.136
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Authors: Tauseef A Khan; Tina Shah; David Prieto; Weili Zhang; Jackie Price; Gerald R Fowkes; Jackie Cooper; Philippa J Talmud; Steve E Humphries; Johan Sundstrom; Jaroslav A Hubacek; Shah Ebrahim; Debbie A Lawlor; Yoav Ben-Shlomo; Mohammad R Abdollahi; Arjen J C Slooter; Zoltan Szolnoki; Manjinder Sandhu; Nicholas Wareham; Ruth Frikke-Schmidt; Anne Tybjærg-Hansen; Gerda Fillenbaum; Bastiaan T Heijmans; Tomohiro Katsuya; Grazyna Gromadzka; Andrew Singleton; Luigi Ferrucci; John Hardy; Bradford Worrall; Stephen S Rich; Mar Matarin; John Whittaker; Tom R Gaunt; Peter Whincup; Richard Morris; John Deanfield; Ann Donald; George Davey Smith; Mika Kivimaki; Meena Kumari; Liam Smeeth; Kay-Tee Khaw; Michael Nalls; James Meschia; Kai Sun; Rutai Hui; Ian Day; Aroon D Hingorani; Juan P Casas Journal: Int J Epidemiol Date: 2013-04 Impact factor: 7.196