The Genetic Background of Metabolic Trait Clusters in Children and Adolescents

Silventoinen, Karri; Jelenkovic, Aline; Maia, José; Antunes, António Manuel Marques; Carvalho, M. A. A. Pinheiro de; Brehm, António; Thomis, Martine; Lefevre, Johan; Kaprio, Jaakko; Freitas, Duarte L.

doi:10.1089/met.2017.0013

Cited by 4 publications

(4 citation statements)

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“…It is well known that metabolic CVD risk factors are correlated, and obesity is usually behind the clustering of metabolic factors in children and adolescents (Silventoinen, Gouveia et al, 2017). Our findings were not only consistent with the previous twin studies but also showed evidence for sex-specific phenotypic correlations, which was much larger in boys than in girls, such as BMI relating to WC with the range from .77 to .70 and SBP relating to DBP with the range from .69 to .62.…”

Section: Discussionmentioning

confidence: 99%

The Genetic Architecture of the Clustering of Cardiometabolic Risk Factors: A Study of 8- to 17-Year-Old Chinese Twins

Feng

Duan

et al. 2020

Twin Res Hum Genet

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We explored the genetic architecture of metabolic risk factors of cardiovascular diseases (CVDs) and their clustering in Chinese boys and girls. Seven metabolic traits (body mass index [BMI], waist circumference [WC], systolic blood pressure [SBP], diastolic blood pressure [DBP], total cholesterol [TC], triglyceride [TG], and uric acid [UA]) were measured in a sample of 1016 twins between 8 and 17 years of age, recruited from the Qingdao Twin Registry. Cholesky, independent pathway, and common pathway models were used to identify the latent genetic structure behind the clustering of these metabolic traits. Genetic architecture of these metabolic traits was largely similar in boys and girls. The highest heritability was found for BMI (a2 = 0.63) in boys and TC (a2 = .69) in girls. Three heritable factors, adiposity (BMI and WC), blood pressure (SBP and DBP), and metabolite factors (TC, TG, and UA), which formed one higher-order latent phenotype, were identified. Latent genetic, common environmental, and unique environmental factors indirectly impacted the three factors through one single latent factor. Our results suggest that there is one latent factor influencing several metabolic traits, which are known risk factors of CVDs in young Chinese twins. Latent genetic, common environmental, and unique environmental factors indirectly imposed on them. These results inform strategies for gene pleiotropic discovery and intervening of CVD risk factors during childhood and adolescence.

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Section: Discussionmentioning

confidence: 99%

The Genetic Architecture of the Clustering of Cardiometabolic Risk Factors: A Study of 8- to 17-Year-Old Chinese Twins

Feng

Duan

et al. 2020

Twin Res Hum Genet

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“…This suggests that the Pima Indians have a strong genetic predisposition to weight gain, but it is expressed only in the context of a Westernized diet and more generally the Westernized lifestyle. BMI also shares genetic variation with arterial stiffness (Tarnoki et al, 2013) and metabolic disorders (Silventoinen et al, 2017a), which can indicate pleiotropy but also causal associations between BMI and other metabolic traits. It is likely that environmental factors can modify this genetic covariance, as suggested by the current very high level of metabolic diseases in Pima Indians as compared to other ethnic groups in North America (Fagot-Campagna et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Obesity and eating behavior from the perspective of twin and genetic research

Silventoinen

Konttinen

2020

Neuroscience & Biobehavioral Reviews

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Obesity has dramatically increased during the last decades and is currently one of the most serious global health problems. We present a hypothesis that obesity is a neuro-behavioral disease having a strong genetic background mediated largely by eating behavior and is sensitive to the macro-environment; we study this hypothesis from the perspective of genetic research. Genetic family and genome-wide-association studies have shown well that body mass index (BMI, kg/m 2) is a highly heritable and polygenic trait. New genetic variation of BMI emerges after early childhood. Candidate genes of BMI notably express in brain tissue, supporting that this new variation is related to behavior. Obesogenic environments at both childhood family and societal levels reinforce the genetic susceptibility to obesity. Genetic factors have a clear influence on macro-nutrient intake and appetiterelated eating behavior traits. Results on the gene-by-diet interactions in obesity are mixed, but emerging evidence suggests that eating behavior traits partly mediate the effect of genes on BMI. However, more rigorous prospective study designs controlling for measurement bias are still needed.

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“…Sociodemographic characteristics have been identified as strong factors for identifying MR groups. Namely, differences between the sexes, skin color, residential’ and school’ areas, type of school, and other measures of socioeconomic status have been shown to be important predictors of MR [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Metabolic risk is associated with sociodemographic characteristics in adolescents from both rural and urban regions from southern Brazil

et al. 2022

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Background The prevalence of several cardiovascular metabolic disorders are increasingly cause for concern in adolescents worldwide. Given the complex interrelations between metabolic risk (MR) and sociodemographic variables, the present study aims to examine the association between the presence of MR with sociodemographic characteristics (sex, skin color, residential area, and parental socioeconomic status) in adolescents from Southern Brazil. Methods Cross-sectional study conducted with 1,152 adolescents (507 males) aged between 12 and 17 years. MR was assessed using a continuous score (cMetS; sum of Z-scores of the following variables: waist circumference, systolic blood pressure (SBP), glucose, high-density lipoprotein cholesterol [HDL-C, inverse], triglycerides [TG], and estimated cardiorespiratory fitness [CRF, inverse]). Poisson regression was used to examine associations between sociodemographic variables with the dichotomized cMetS and separate metabolic variables. The results were expressed with prevalence ratios (PR) and 95% confidence intervals (CI). Results The presence of MR (evaluated by the cMetS) was observed in 8.7% of adolescents. Higher MR was less prevalent among non-white adolescents (PR: 0.96; 95% CI: 0.93; 0.99). Adolescents living in rural areas had a lower prevalence of the following metabolic variables; low HDL-C (PR: 0.95; 95% CI: 0.94; 0.97), elevated TG (PR: 0.95; 95% CI: 0.92; 0.99), elevated glucose (PR: 0.96; 95% CI: 0.95; 0.98), and low CRF levels (PR: 0.88; 95% CI: 0.85; 0.92). Whereas, SBP was higher in those living in rural areas (PR: 1.11; 95% CI: 1.05; 1.17). In girls, there was a higher prevalence of raised TG (PR: 1.06; 95% CI: 1.02; 1.10) and lower levels of CRF (PR: 1.20; 95% CI: 1.16; 1.24), but a lower prevalence of elevated glucose (PR: 0.97; 95% CI: 0.97; 0.99). Conclusion Higher MR prevalence was lower in those self-reporting non-white skin color and selected MR factors were less prevalent in those living in rural areas. The identification of groups at higher MR is important for early prevention and monitoring strategies for both Type 2 diabetes and later cardiovascular disease. Future studies should be conducted to assess the socio-cultural aspects of the relationships between MR and socio-cultural and lifestyle variables.

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The Genetic Background of Metabolic Trait Clusters in Children and Adolescents

Cited by 4 publications

References 32 publications

The Genetic Architecture of the Clustering of Cardiometabolic Risk Factors: A Study of 8- to 17-Year-Old Chinese Twins

The Genetic Architecture of the Clustering of Cardiometabolic Risk Factors: A Study of 8- to 17-Year-Old Chinese Twins

Obesity and eating behavior from the perspective of twin and genetic research

Metabolic risk is associated with sociodemographic characteristics in adolescents from both rural and urban regions from southern Brazil

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