Abstract：
OBJECTIVE: This study identified metabolite modules associated with adiposity and body fat distribution in childhood using gold-standard measurements.
METHODS: We used cross-sectional data from 329 children at mid-childhood (age 5.3 ± 0.3 years; BMI 15.7 ± 1.5 kg/m2) from the Genetics of Glucose regulation in Gestation and Growth (Gen3G), a prospective pre-birth cohort. We quantified 1038 plasma metabolites and measured body composition using the gold-standard dual-energy x-ray absorptiometry (DXA), in addition to skinfold, waist circumference, and BMI. We applied weighted-correlation network analysis to identify a network of highly correlated metabolite modules. Spearman\'s partial correlations were applied to determine the associations of adiposity with metabolite modules and individual metabolites with false discovery rate (FDR) correction.
RESULTS: We identified a \'green\' module of 120 metabolites, primarily comprised of lipids (mostly sphingomyelins and phosphatidylcholine), that showed positive correlations (all FDR p < 0.05) with DXA estimates of total and truncal fat (ρadjusted = 0.11-0.19), skinfold measures (ρadjusted = 0.09-0.26), and BMI and waist circumference (ρadjusted = 0.15 and 0.18, respectively). These correlations were similar when stratified by sex. Within this module, sphingomyelin (d18:2/14:0, d18:1/14:1)*, a sphingomyelin sub-specie that is an important component of cell membranes, showed the strongest associations.
CONCLUSIONS: A module of metabolites was associated with adiposity measures in childhood.
METHODS: We used cross-sectional data from 329 children at mid-childhood (age 5.3 ± 0.3 years; BMI 15.7 ± 1.5 kg/m2) from the Genetics of Glucose regulation in Gestation and Growth (Gen3G), a prospective pre-birth cohort. We quantified 1038 plasma metabolites and measured body composition using the gold-standard dual-energy x-ray absorptiometry (DXA), in addition to skinfold, waist circumference, and BMI. We applied weighted-correlation network analysis to identify a network of highly correlated metabolite modules. Spearman\'s partial correlations were applied to determine the associations of adiposity with metabolite modules and individual metabolites with false discovery rate (FDR) correction.
RESULTS: We identified a \'green\' module of 120 metabolites, primarily comprised of lipids (mostly sphingomyelins and phosphatidylcholine), that showed positive correlations (all FDR p < 0.05) with DXA estimates of total and truncal fat (ρadjusted = 0.11-0.19), skinfold measures (ρadjusted = 0.09-0.26), and BMI and waist circumference (ρadjusted = 0.15 and 0.18, respectively). These correlations were similar when stratified by sex. Within this module, sphingomyelin (d18:2/14:0, d18:1/14:1)*, a sphingomyelin sub-specie that is an important component of cell membranes, showed the strongest associations.
CONCLUSIONS: A module of metabolites was associated with adiposity measures in childhood.
摘要：
目的：本研究使用金标准测量方法确定了与儿童肥胖和体脂分布相关的代谢模块。
方法：我们使用了329名儿童（年龄5.3±0.3岁；BMI15.7±1.5kg/m2）的横断面数据，这些数据来自妊娠和生长中葡萄糖调节的遗传学（Gen3G），前瞻性出生前队列。我们使用金标准双能X射线吸收法（DXA）定量了1038种血浆代谢物并测量了身体成分，除了皮肤褶皱,腰围,BMI。我们应用加权相关网络分析来识别高度相关的代谢物模块网络。Spearman的部分相关性用于确定肥胖与代谢物模块和具有错误发现率（FDR）校正的个体代谢物的关联。
结果：我们确定了一个由120种代谢物组成的“绿色”模块，主要由脂质（主要是鞘磷脂和磷脂酰胆碱）组成，显示与总脂肪和躯干脂肪的DXA估计呈正相关(所有FDRp<0.05)(ρ调整=0.11-0.19)，皮褶测量(ρ调整=0.09-0.26)，和BMI和腰围（ρ调整=0.15和0.18，分别）。按性别分层时，这些相关性相似。在这个模块中，鞘磷脂(d18:2/14:0,d18:1/14:1)*,鞘磷脂亚种是细胞膜的重要组成部分，表现出最强的联想。
结论：一个代谢模块与儿童肥胖指标相关。
方法：我们使用了329名儿童（年龄5.3±0.3岁；BMI15.7±1.5kg/m2）的横断面数据，这些数据来自妊娠和生长中葡萄糖调节的遗传学（Gen3G），前瞻性出生前队列。我们使用金标准双能X射线吸收法（DXA）定量了1038种血浆代谢物并测量了身体成分，除了皮肤褶皱,腰围,BMI。我们应用加权相关网络分析来识别高度相关的代谢物模块网络。Spearman的部分相关性用于确定肥胖与代谢物模块和具有错误发现率（FDR）校正的个体代谢物的关联。
结果：我们确定了一个由120种代谢物组成的“绿色”模块，主要由脂质（主要是鞘磷脂和磷脂酰胆碱）组成，显示与总脂肪和躯干脂肪的DXA估计呈正相关(所有FDRp<0.05)(ρ调整=0.11-0.19)，皮褶测量(ρ调整=0.09-0.26)，和BMI和腰围（ρ调整=0.15和0.18，分别）。按性别分层时，这些相关性相似。在这个模块中，鞘磷脂(d18:2/14:0,d18:1/14:1)*,鞘磷脂亚种是细胞膜的重要组成部分，表现出最强的联想。
结论：一个代谢模块与儿童肥胖指标相关。
