Profiling of risk of subclinical atherosclerosis: possible interplay of genetic and environmental factors as the update of conventional approach

Sobenin, Igor A.; Myasoedova, Veronika A.; Kirichenko, Tatiana V.; Orekhova, Varvara A.; Khasanova, Zukhra B.; Sinyov, Vasily V.; Melnichenko, Alexandra А.; Grechko, Andrey V.; Orekhov, Alexander N.

doi:10.20517/2574-1209.2019.09

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“…It was shown that the same set of conventional cardiovascular risk factors explained 21% of the cIMT variability. The inclusion of the m.652delG, m.3256C>T, m.13513G>A, m.14459G>A, and m.15059G>A heteroplasmy levels in the linear regression model provided a significantly better explanatory level of 36% [17].…”

Section: Discussionmentioning

confidence: 99%

Impact of Mitochondrial DNA Mutations on Carotid Intima-Media Thickness in the Novosibirsk Region

Kirichenko

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Sinyov

et al. 2020

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The search for markers of predisposition to atherosclerosis development is very important for early identification of individuals with a high risk of cardiovascular disease. The aim of the present study was to investigate the association of mitochondrial DNA mutations with carotid intima-media thickness and to determine the impact of mitochondrial heteroplasmy measurements in the prognosis of atherosclerosis development. This cross-sectional, population-based study was conducted in 468 subjects from the Novosibirsk region. It was shown that the mean (carotid intima-media thickness) cIMT correlated with the following mtDNA mutations: m.15059G>A (r = 0.159, p = 0.001), m.12315G>A (r = 0.119; p = 0.011), m.5178C>A (r = 0.114, p = 0.014), and m.3256C>T (r = 0.130, p = 0.011); a negative correlation with mtDNA mutations m.14846G>A (r = −0.111, p = 0.042) and m.13513G>A (r = −0.133, p = 0.004) was observed. In the linear regression analysis, the addition of the set of mtDNA mutations to the conventional cardiovascular risk factors increased the ability to predict the cIMT variability from 17 to 27%. Multi-step linear regression analysis revealed the most important predictors of mean cIMT variability: age, systolic blood pressure, blood levels of total cholesterol, LDL and triglycerides, as well as the mtDNA mutations m.13513G>A, m.15059G>A, m.12315G>A, and m.3256C>T. Thus, a high predictive value of mtDNA mutations for cIMT variability was demonstrated. The association of mutation m.13513G>A and m.14846G>A with a low value of cIMT, demonstrated in several studies, represents a potential for the development of anti-atherosclerotic gene therapy.

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Section: Discussionmentioning

confidence: 99%