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Cardiometabolic Traits in Adult Twins: Heritability and BMI Impact with Age
Background: The prevalence of obesity and cardiometabolic diseases continues to rise globally and obesity is a significant risk factor for cardiometabolic diseases. However, to our knowledge, evidence of the relative roles of genes and the environment underlying obesity and cardiometabolic disease t...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824881/ https://www.ncbi.nlm.nih.gov/pubmed/36615821 http://dx.doi.org/10.3390/nu15010164 |
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author | Hong, Xuanming Wu, Zhiyu Cao, Weihua Lv, Jun Yu, Canqing Huang, Tao Sun, Dianjianyi Liao, Chunxiao Pang, Yuanjie Pang, Zengchang Cong, Liming Wang, Hua Wu, Xianping Liu, Yu Gao, Wenjing Li, Liming |
author_facet | Hong, Xuanming Wu, Zhiyu Cao, Weihua Lv, Jun Yu, Canqing Huang, Tao Sun, Dianjianyi Liao, Chunxiao Pang, Yuanjie Pang, Zengchang Cong, Liming Wang, Hua Wu, Xianping Liu, Yu Gao, Wenjing Li, Liming |
author_sort | Hong, Xuanming |
collection | PubMed |
description | Background: The prevalence of obesity and cardiometabolic diseases continues to rise globally and obesity is a significant risk factor for cardiometabolic diseases. However, to our knowledge, evidence of the relative roles of genes and the environment underlying obesity and cardiometabolic disease traits and the correlations between them are still lacking, as is how they change with age. Method: Data were obtained from the Chinese National Twin Registry (CNTR). A total of 1421 twin pairs were included. Univariate structural equation models (SEMs) were performed to evaluate the heritability of BMI and cardiometabolic traits, which included blood hemoglobin A1c (HbA1c), fasting blood glucose (FBG), systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), triglycerides (TGs), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C). Bivariate SEMs were used to assess the genetic/environmental correlations between them. The study population was divided into three groups for analysis: ≤50, 51–60, and >60 years old to assess the changes in heritability and genetic/environmental correlations with ageing. Results: Univariate SEMs showed a high heritability of BMI (72%) and cardiometabolic traits, which ranged from 30% (HbA1c) to 69% (HDL-C). With age increasing, the heritability of all phenotypes has different degrees of declining trends. Among these, BMI, SBP, and DBP presented significant monotonous declining trends. The bivariate SEMs indicated that BMI correlated with all cardiometabolic traits. The genetic correlations were estimated to range from 0.14 (BMI and LDL-C) to 0.39 (BMI and DBP), while the environmental correlations ranged from 0.13 (BMI and TC/LDL-C) to 0.31 (BMI and TG). The genetic contributions underlying the correlations between BMI and SBP and DBP, TC, TG, and HDL-C showed a progressive decrease as age groups increased. In contrast, environmental correlations displayed a significant increasing trend for HbA1c, SBP, and DBP. Conclusions: The findings suggest that genetic and environmental factors have essential effects on BMI and all cardiometabolic traits. However, as age groups increased, genetic influences presented varying degrees of decrement for BMI and most cardiometabolic traits, suggesting the increasing importance of environments. Genetic factors played a consistently larger role than environmental factors in the phenotypic correlations between BMI and cardiometabolic traits. Nevertheless, the relative magnitudes of genetic and environmental factors may change over time. |
format | Online Article Text |
id | pubmed-9824881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98248812023-01-08 Cardiometabolic Traits in Adult Twins: Heritability and BMI Impact with Age Hong, Xuanming Wu, Zhiyu Cao, Weihua Lv, Jun Yu, Canqing Huang, Tao Sun, Dianjianyi Liao, Chunxiao Pang, Yuanjie Pang, Zengchang Cong, Liming Wang, Hua Wu, Xianping Liu, Yu Gao, Wenjing Li, Liming Nutrients Article Background: The prevalence of obesity and cardiometabolic diseases continues to rise globally and obesity is a significant risk factor for cardiometabolic diseases. However, to our knowledge, evidence of the relative roles of genes and the environment underlying obesity and cardiometabolic disease traits and the correlations between them are still lacking, as is how they change with age. Method: Data were obtained from the Chinese National Twin Registry (CNTR). A total of 1421 twin pairs were included. Univariate structural equation models (SEMs) were performed to evaluate the heritability of BMI and cardiometabolic traits, which included blood hemoglobin A1c (HbA1c), fasting blood glucose (FBG), systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), triglycerides (TGs), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C). Bivariate SEMs were used to assess the genetic/environmental correlations between them. The study population was divided into three groups for analysis: ≤50, 51–60, and >60 years old to assess the changes in heritability and genetic/environmental correlations with ageing. Results: Univariate SEMs showed a high heritability of BMI (72%) and cardiometabolic traits, which ranged from 30% (HbA1c) to 69% (HDL-C). With age increasing, the heritability of all phenotypes has different degrees of declining trends. Among these, BMI, SBP, and DBP presented significant monotonous declining trends. The bivariate SEMs indicated that BMI correlated with all cardiometabolic traits. The genetic correlations were estimated to range from 0.14 (BMI and LDL-C) to 0.39 (BMI and DBP), while the environmental correlations ranged from 0.13 (BMI and TC/LDL-C) to 0.31 (BMI and TG). The genetic contributions underlying the correlations between BMI and SBP and DBP, TC, TG, and HDL-C showed a progressive decrease as age groups increased. In contrast, environmental correlations displayed a significant increasing trend for HbA1c, SBP, and DBP. Conclusions: The findings suggest that genetic and environmental factors have essential effects on BMI and all cardiometabolic traits. However, as age groups increased, genetic influences presented varying degrees of decrement for BMI and most cardiometabolic traits, suggesting the increasing importance of environments. Genetic factors played a consistently larger role than environmental factors in the phenotypic correlations between BMI and cardiometabolic traits. Nevertheless, the relative magnitudes of genetic and environmental factors may change over time. MDPI 2022-12-29 /pmc/articles/PMC9824881/ /pubmed/36615821 http://dx.doi.org/10.3390/nu15010164 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hong, Xuanming Wu, Zhiyu Cao, Weihua Lv, Jun Yu, Canqing Huang, Tao Sun, Dianjianyi Liao, Chunxiao Pang, Yuanjie Pang, Zengchang Cong, Liming Wang, Hua Wu, Xianping Liu, Yu Gao, Wenjing Li, Liming Cardiometabolic Traits in Adult Twins: Heritability and BMI Impact with Age |
title | Cardiometabolic Traits in Adult Twins: Heritability and BMI Impact with Age |
title_full | Cardiometabolic Traits in Adult Twins: Heritability and BMI Impact with Age |
title_fullStr | Cardiometabolic Traits in Adult Twins: Heritability and BMI Impact with Age |
title_full_unstemmed | Cardiometabolic Traits in Adult Twins: Heritability and BMI Impact with Age |
title_short | Cardiometabolic Traits in Adult Twins: Heritability and BMI Impact with Age |
title_sort | cardiometabolic traits in adult twins: heritability and bmi impact with age |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824881/ https://www.ncbi.nlm.nih.gov/pubmed/36615821 http://dx.doi.org/10.3390/nu15010164 |
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