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Associations of Body Composition Measurements with Serum Lipid, Glucose and Insulin Profile: A Chinese Twin Study

OBJECTIVES: To quantitate and compare the associations of various body composition measurements with serum metabolites and to what degree genetic or environmental factors affect obesity-metabolite relation. METHODS: Body mass index (BMI), waist circumference (WC), lean body mass (LBM), percent body...

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Autores principales: Liao, Chunxiao, Gao, Wenjing, Cao, Weihua, Lv, Jun, Yu, Canqing, Wang, Shengfeng, Zhou, Bin, Pang, Zengchang, Cong, Liming, Wang, Hua, Wu, Xianping, Li, Liming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640552/
https://www.ncbi.nlm.nih.gov/pubmed/26556598
http://dx.doi.org/10.1371/journal.pone.0140595
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author Liao, Chunxiao
Gao, Wenjing
Cao, Weihua
Lv, Jun
Yu, Canqing
Wang, Shengfeng
Zhou, Bin
Pang, Zengchang
Cong, Liming
Wang, Hua
Wu, Xianping
Li, Liming
author_facet Liao, Chunxiao
Gao, Wenjing
Cao, Weihua
Lv, Jun
Yu, Canqing
Wang, Shengfeng
Zhou, Bin
Pang, Zengchang
Cong, Liming
Wang, Hua
Wu, Xianping
Li, Liming
author_sort Liao, Chunxiao
collection PubMed
description OBJECTIVES: To quantitate and compare the associations of various body composition measurements with serum metabolites and to what degree genetic or environmental factors affect obesity-metabolite relation. METHODS: Body mass index (BMI), waist circumference (WC), lean body mass (LBM), percent body fat (PBF), fasting serum high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglycerides (TG), total cholesterol (TC), glucose, insulin and lifestyle factors were assessed in 903 twins from Chinese National Twin Registry (CNTR). Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated from fasting serum glucose and insulin. Linear regression models and bivariate structural equation models were used to examine the relation of various body composition measurements with serum metabolite levels and genetic/environmental influences on these associations, respectively. RESULTS: At individual level, adiposity measurements (BMI, WC and PBF) showed significant associations with serum metabolite concentrations in both sexes and the associations still existed in male twins when using within-MZ twin pair comparison analyses. Associations of BMI with TG, insulin and HOMA-IR were significantly stronger in male twins compared to female twins (BMI-by-sex interaction p = 0.043, 0.020 and 0.019, respectively). Comparison of various adiposity measurements with levels of serum metabolites revealed that WC explained the largest fraction of variance in serum LDL-C, TG, TC and glucose concentrations while BMI performed best in explaining variance in serum HDL-C, insulin and HOMA-IR levels. Of these phenotypic correlations, 64–81% were attributed to genetic factors, whereas 19–36% were attributed to unique environmental factors. CONCLUSIONS: We observed different associations between adiposity and serum metabolite profile and demonstrated that WC and BMI explained the largest fraction of variance in serum lipid profile and insulin resistance, respectively. To a large degree, shared genetic factors contributed to these associations with the remaining explained by twin-specific environmental factors.
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spelling pubmed-46405522015-11-13 Associations of Body Composition Measurements with Serum Lipid, Glucose and Insulin Profile: A Chinese Twin Study Liao, Chunxiao Gao, Wenjing Cao, Weihua Lv, Jun Yu, Canqing Wang, Shengfeng Zhou, Bin Pang, Zengchang Cong, Liming Wang, Hua Wu, Xianping Li, Liming PLoS One Research Article OBJECTIVES: To quantitate and compare the associations of various body composition measurements with serum metabolites and to what degree genetic or environmental factors affect obesity-metabolite relation. METHODS: Body mass index (BMI), waist circumference (WC), lean body mass (LBM), percent body fat (PBF), fasting serum high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglycerides (TG), total cholesterol (TC), glucose, insulin and lifestyle factors were assessed in 903 twins from Chinese National Twin Registry (CNTR). Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated from fasting serum glucose and insulin. Linear regression models and bivariate structural equation models were used to examine the relation of various body composition measurements with serum metabolite levels and genetic/environmental influences on these associations, respectively. RESULTS: At individual level, adiposity measurements (BMI, WC and PBF) showed significant associations with serum metabolite concentrations in both sexes and the associations still existed in male twins when using within-MZ twin pair comparison analyses. Associations of BMI with TG, insulin and HOMA-IR were significantly stronger in male twins compared to female twins (BMI-by-sex interaction p = 0.043, 0.020 and 0.019, respectively). Comparison of various adiposity measurements with levels of serum metabolites revealed that WC explained the largest fraction of variance in serum LDL-C, TG, TC and glucose concentrations while BMI performed best in explaining variance in serum HDL-C, insulin and HOMA-IR levels. Of these phenotypic correlations, 64–81% were attributed to genetic factors, whereas 19–36% were attributed to unique environmental factors. CONCLUSIONS: We observed different associations between adiposity and serum metabolite profile and demonstrated that WC and BMI explained the largest fraction of variance in serum lipid profile and insulin resistance, respectively. To a large degree, shared genetic factors contributed to these associations with the remaining explained by twin-specific environmental factors. Public Library of Science 2015-11-10 /pmc/articles/PMC4640552/ /pubmed/26556598 http://dx.doi.org/10.1371/journal.pone.0140595 Text en © 2015 Liao et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Liao, Chunxiao
Gao, Wenjing
Cao, Weihua
Lv, Jun
Yu, Canqing
Wang, Shengfeng
Zhou, Bin
Pang, Zengchang
Cong, Liming
Wang, Hua
Wu, Xianping
Li, Liming
Associations of Body Composition Measurements with Serum Lipid, Glucose and Insulin Profile: A Chinese Twin Study
title Associations of Body Composition Measurements with Serum Lipid, Glucose and Insulin Profile: A Chinese Twin Study
title_full Associations of Body Composition Measurements with Serum Lipid, Glucose and Insulin Profile: A Chinese Twin Study
title_fullStr Associations of Body Composition Measurements with Serum Lipid, Glucose and Insulin Profile: A Chinese Twin Study
title_full_unstemmed Associations of Body Composition Measurements with Serum Lipid, Glucose and Insulin Profile: A Chinese Twin Study
title_short Associations of Body Composition Measurements with Serum Lipid, Glucose and Insulin Profile: A Chinese Twin Study
title_sort associations of body composition measurements with serum lipid, glucose and insulin profile: a chinese twin study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640552/
https://www.ncbi.nlm.nih.gov/pubmed/26556598
http://dx.doi.org/10.1371/journal.pone.0140595
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