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

Abstract

ObjectivesTo 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.MethodsBody 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.ResultsAt 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.ConclusionsWe 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.

Association of glutathione S-transferase GSTM1 and GSTT1 deletion polymorphisms with obesity and their relationship with body mass index, lipoprotein and hypertension among young age Saudis

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“…Previous research points to the fact that changes in weight and body composition cause a number of metabolic effects. The most important for health and body fitness are changes in the metabolism of carbohydrates and lipids related to the altered secretion of such hormones as TSH, leptin, cortisol, and insulin ( Bouchard, Tchernof, & Tremblay, 2014 ; Kitahara et al, 2012 ; Liao, et al, 2015 ).…”

The Chinese National Twin Registry: a ‘gold mine’ for scientific research

“…Researcher ApplicaƟon BMI-insulin 0.685 (95% CI 0.472, 0.999) [22] BMI-HOMA-IR 0.682 (95% CI 0.461, 0.999) [22] WC-TG 0.552 (95% CI 0.187, 0.999) [22] WC-GLU 0.530 (95% CI 0.163, 0.999) [22] WC-LDL-C 0.303 (95% CI 0.061, 0.600) [22] PBF-TG 0.795 (95% CI 0.427, 0.999) [22] PBF-TC 0.442 (95% CI 0.032, 0.801) [22] PBF-LDL-C 0.414 (95% CI 0.042, 0.725) [22] SBP-DBP 0.764 (95% CI 0.578, 0.827) [23] BMI-SBP 0.310 (95% CI 0.071, 0.640) [23] WC-SBP 0.309 (95% CI 0.046, 0.656) [23] BMI-DBP 0.369 (95% CI 0.145, 0.678) [23] WC-DBP 0.374 (95% CI 0.128, 0.722) [23] WHtR-DBP 0.392 (95% CI 0.079, 0.780) [23] WHtR-DBP 0.457 (95% CI 0.031, 1.000) [23] BMI-educational level (male) 0.015 (95% CI 0.006, 0.952) [24] BMI-educational level (female) À0.369 (95% CI À0.585, À0.148) [24] BMI, body mass index; CI, confidence interval; DBP, diastolic blood pressure; GLU, glucose; HOMA-IR, homoeostatic model assessment of insulin resistance; LDL-C, low-density lipoprotein cholesterol; PBF, percentage body fat; SBP, systolic blood pressure; TC, total cholesterol; TG, triglycerides; WC, waist circumference; WHtR, waist-height ratio.…”