2010
DOI: 10.1203/00006450-201011001-00618
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618 Significance of Murmurs in Infancy

Abstract: Posters 316 stress (serious quarrel with classmates, physical activities) have been observed. The patients had no coronary risk factors. Their average blood pressure was 150/90 mmHg and heart rate was 120 beats/ min. ST-segment elevations and T-wave inversions were registered on electrocardiograms of teenagers. Dysfunction and dyskinesia of the left ventricle apex and interventricular septum was detected on echocardiography. The levels of creatine kinase-MB and troponin I did not increase. Occlusions and anoma… Show more

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Cited by 9 publications
(13 citation statements)
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“…The bivariate twin model was primarily used to assess genetic pleiotropy between two phenotypes [ 19 ]. The same idea has been subsequently applied to longitudinal twin data to estimate the genetic correlation on levels of one phenotype measured over time on same individuals [ 17 , 18 ]. Using the typical structural equation modeling (SEM) approach [ 20 ], the bivariate twin model decomposed the total phenotype variance and covariance at and between the two waves into additive genetic (A), common or shared environmental (C), and unique environmental (E) components in fitting univariate and bivariate twin models.…”
Section: Methodsmentioning
confidence: 99%
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“…The bivariate twin model was primarily used to assess genetic pleiotropy between two phenotypes [ 19 ]. The same idea has been subsequently applied to longitudinal twin data to estimate the genetic correlation on levels of one phenotype measured over time on same individuals [ 17 , 18 ]. Using the typical structural equation modeling (SEM) approach [ 20 ], the bivariate twin model decomposed the total phenotype variance and covariance at and between the two waves into additive genetic (A), common or shared environmental (C), and unique environmental (E) components in fitting univariate and bivariate twin models.…”
Section: Methodsmentioning
confidence: 99%
“…Among them, Franz et al [ 17 ] reported that genetic factors explain 76% of phenotype correlation (genetic correlation of 0.6) between body mass index (BMI) at age 20 and age 48 in a cohort of male twins. Moderate genetic correlation on lipids levels (total cholesterol: 0.65; triglyceride: 0.73; low density lipoprotein cholesterol: 0.72; high density lipoprotein cholesterol: 0.45) measured over time was also estimated in adolescent twins during a seven years follow up [ 18 ]. Although focused on different traits in samples of different age groups, results from the two studies suggested important genetic contribution in stabilizing individual metabolic patterns over time.…”
Section: Introductionmentioning
confidence: 99%
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“…In another longitudinal study conducted in adult Caucasian twins, Goode et al [ 40 ] reported no significant proportion of genetic contribution to the variation in age-related change of blood lipids. Different from the results in adult twins, Middelberg et al [ 41 ] and Zhang et al [ 25 ] estimated significant genetic component in age-related change on the level of blood lipids in adolescent Caucasian and Chinese twins respectively. Comparing the results for adolescent and adult twins, one could conclude that the genes are important in regulating the developmental changes of blood lipids in adolescent twins in both Eastern and Western populations while in adult twins, the genetic effects on long-term change for some lipids (here TG in Danish twins and HDL in Chinese twins) could have been weakened and perhaps with population-specific patterns.…”
Section: Discussionmentioning
confidence: 83%
“…Suboptimal lipid levels contribute to the atherosclerotic process, with clinical trials and observational studies demonstrating a strong relation between blood lipid concentrations and CVD (Hokanson and Austin, 1996; LaRosa et al, 1999; Di Angelantonio et al, 2009; Huxley et al, 2011). The heritabilities of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride concentrations have long been established (Friedlander et al, 1997; Malhotra and Wolford, 2005; Luo et al, 2010; Zhang et al, 2010). More recently, genome-wide association studies (GWASs) have made important strides in identifying single nucleotide polymorphisms (SNPs) that contribute to the inter-individual variability in these complex phenotypes (Saxena et al, 2007; Kathiresan et al, 2008; Kooner et al, 2008; Wallace et al, 2008; Willer et al, 2008; Aulchenko et al, 2009; Kathiresan et al, 2009; Teslovich et al, 2010; Waterworth et al, 2010; Kim et al, 2011; Tan et al, 2012).…”
Section: Introductionmentioning
confidence: 99%