Metabolomics reveals sex-specific pathways associated with changes in adiposity and muscle mass in a cohort of Mexican adolescents

Associations of childhood BMI, general and visceral fat mass with metabolite profiles at school-age

BACKGROUND

Childhood obesity increases metabolic disease risk. Underlying mechanisms remain unknown. We examined associations of body mass index (BMI), total body fat mass, and visceral fat mass with serum metabolites at school-age, and explored whether identified metabolites improved the identification of children at risk of a metabolically unhealthy phenotype.

METHODS

We performed a cross-sectional analysis among 497 children with a mean age of 9.8 (95% range 9.1, 10.6) years, participating in a population-based cohort study. We measured BMI, total body fat mass using DXA, and visceral fat mass using MRI. Serum concentrations of amino-acids, non-esterified-fatty-acids, phospholipids, and carnitines were determined using LC-MS/MS. Children were categorized as metabolically healthy or metabolically unhealthy, according to BMI, blood pressure, lipids, glucose, and insulin levels.

RESULTS

Higher BMI and total body fat mass were associated with altered concentrations of branched-chain amino-acids, essential amino-acids, and free carnitines. Higher BMI was also associated with higher concentrations of aromatic amino-acids and alkyl-lysophosphatidylcholines (FDR-corrected p-values < 0.05). The strongest associations were present for Lyso.PC.a.C14.0 and SM.a.C32.2 (FDR-corrected p-values < 0.01). Higher visceral fat mass was only associated with higher concentrations of 6 individual metabolites, particularly Lyso.PC.a.C14.0, PC.aa.C32.1, and SM.a.C32.2. We selected 15 metabolites that improved the prediction of a metabolically unhealthy phenotype, compared to BMI only (AUC: BMI: 0.59 [95% CI 0.47,0.71], BMI + Metabolites: 0.91 [95% CI 0.85,0.97]).

CONCLUSIONS

An adverse childhood body fat profile, characterized by higher BMI and total body fat mass, is associated with metabolic alterations, particularly in amino acids, phospholipids, and carnitines. Fewer associations were present for visceral fat mass. We identified a metabolite profile that improved the identification of impaired cardiometabolic health in children, compared to BMI only.

metabCombiner 2.0: Disparate Multi-Dataset Feature Alignment for LC-MS Metabolomics

Liquid chromatography-high-resolution mass spectrometry (LC-HRMS), as applied to untargeted metabolomics, enables the simultaneous detection of thousands of small molecules, generating complex datasets. Alignment is a crucial step in data processing pipelines, whereby LC-MS features derived from common ions are assembled into a unified matrix amenable to further analysis. Variability in the analytical factors that influence liquid chromatography separations complicates data alignment. This is prominent when aligning data acquired in different laboratories, generated using non-identical instruments, or between batches from large-scale studies. Previously, we developed metabCombiner for aligning disparately acquired LC-MS metabolomics datasets. Here, we report significant upgrades to metabCombiner that enable the stepwise alignment of multiple untargeted LC-MS metabolomics datasets, facilitating inter-laboratory reproducibility studies. To accomplish this, a "primary" feature list is used as a template for matching compounds in "target" feature lists. We demonstrate this workflow by aligning four lipidomics datasets from core laboratories generated using each institution's in-house LC-MS instrumentation and methods. We also introduce batchCombine, an application of the metabCombiner framework for aligning experiments composed of multiple batches. metabCombiner is available as an R package on Github and Bioconductor, along with a new online version implemented as an R Shiny App.

High fat diet reveals sex-specific fecal and liver metabolic alterations in C57BL/6J obese mice

Obesity is a major health concern that poses significant risks for many other diseases, including diabetes, cardiovascular disease, and cancer. Prevalence of these diseases varies by biological sex. This study utilizes a mouse (C57BL/6J) model of obesity to analyze liver and fecal metabolic profiles at various time points of dietary exposure: 5, 9, and 12 months in control or high fat diet (HFD)-exposed mice. Our study discovered that the female HFD group has a more discernable perturbation and set of significant changes in metabolic profiles than the male HFD group. In the female mice, HFD fecal metabolites including pyruvate, aspartate, and glutamate were lower than control diet-exposed mice after both 9th and 12th month exposure time points, while lactate and alanine were significantly downregulated only at the 12th month. Perturbations of liver metabolic profiles were observed in both male and female HFD groups, compared to controls at the 12th month. Overall, the female HFD group showed higher lactate and glutathione levels compared to controls, while the male HFD group showed higher levels of glutamine and taurine compared to controls. These metabolite-based findings in both fecal and liver samples for a diet-induced effect of obesity may help guide future pioneering discoveries relating to the analysis and prevention of obesity in people, especially for females.

Sleep duration and timing are prospectively linked with insulin resistance during late adolescence

OBJECTIVE

The aim of this study was to evaluate whether short sleep duration or later sleep timing is a risk factor for insulin resistance (IR) in late adolescence.

METHODS

Mexico City adolescents enrolled in a longitudinal birth cohort (ELEMENT) took part in two study visits during peri-puberty that occurred approximately 2 years apart. IR was assessed with serum glucose and insulin. Four groups were defined using puberty-specific cut points: no IR over the follow-up period, transition from normal to IR, transition from IR to normal, and IR at both time points. Baseline sleep assessments were measured with 7-day wrist actigraphy. Multinomial logistic regression models were used to evaluate associations between sleep duration and timing with homeostatic model assessment of insulin resistance categories, adjusting for age, sex, and baseline pubertal status.

RESULTS

Adolescents who were ≥ 1 hour below the sleep duration recommendations-for-age were 2.74 times more likely to develop IR (95% CI: 1.0-7.4). Similarly, adolescents who were in the latest category of sleep midpoint (>4:33 a.m.) were more likely than those with earliest midpoints (1 a.m.-3 a.m.) to develop IR (odds ratio = 2.63, 95% CI: 1.0-6.7). Changes in adiposity over follow-up did not mediate sleep and IR.

CONCLUSIONS

Insufficient sleep duration and late sleep timing were associated with development of IR over a 2-year period in late adolescence.

Running in Natural Spaces: Gender Analysis of Its Relationship with Emotional Intelligence, Psychological Well-Being, and Physical Activity

Running is a complete and accessible physical exercise for the population, but little research has been done on the psychological and environmental variables related to its practice. The objective of this research was to determine how emotional intelligence, psychological well-being, and body dissatisfaction are related to running in natural spaces for men and women. A cross-sectional study was conducted on 331 runners from 20 states of the Mexican Republic (55.3% women), between 18 and 80 years old (m = 37.4; SD = 11.5), with an average of 7 years running experience (SD = 9.3). The Brief Emotional Intelligence Inventory, the Psychological Well-Being Scale, and the Body Shape Questionnaire were used. The results show that men who run in natural spaces have greater psychological well-being and emotional intelligence (stress management) and less body dissatisfaction, and they run more days per week than those who run in built spaces. Predictors of running in natural spaces were greater psychological well-being and emotional intelligence (stress management). On the other hand, women who run in natural spaces show lower emotional intelligence (stress management) and run for more minutes per day. The predictors for running in natural spaces were identified as lower emotional intelligence (stress management), running for more minutes per day, and practicing another physical exercise. In conclusion, in this heterogeneous sample, natural environments are likely to be related to better performance and certain psychological indicators for runners. However, these relationships differ between men and women, so further studies with larger sample sizes are needed to confirm our findings.