Metabolite Profiles of the Relationship between Body Mass Index (BMI) Milestones and Metabolic Risk during Early Adolescence

Metabolomic signatures for blood pressure from early to late adolescence: findings from a U.S. cohort

INTRODUCTION

Metabolite signatures for blood pressure (BP) may reveal biomarkers, elucidate pathogenesis, and provide prevention targets for high BP. Knowledge regarding metabolites associated with BP in adolescence remains limited.

OBJECTIVES

Investigate the associations between metabolites and adolescent BP, both cross-sectionally (in early and late adolescence) and prospectively (from early to late adolescence).

METHODS

Participants are from the Project Viva prospective cohort. During the early (median: 12.8 years; N = 556) and late (median: 17.4 years; N = 501) adolescence visits, we conducted untargeted plasma metabolomic profiling and measured systolic (SBP) and diastolic BP (DBP). We used linear regression to identify metabolites cross-sectionally associated with BP at each time point, and to assess prospective associations of changes in metabolite levels from early to late adolescence with late adolescence BP. We used Weighted Gene Correlation Network Analysis and Spearman's partial correlation to identify metabolite clusters associated with BP at each time point.

RESULTS

In the linear models, higher androgenic steroid levels were consistently associated with higher SBP and DBP in early and late adolescence. A cluster of 59 metabolites, mainly composed of androgenic steroids, correlated with higher SBP and DBP in early adolescence. A cluster primarily composed of fatty acid lipids was marginally associated with higher SBP in females in late adolescence. Multiple metabolites, including those in the creatine and purine metabolism sub-pathways, were associated with higher SBP and DBP both cross-sectionally and prospectively.

CONCLUSION

Our results shed light on the potential metabolic processes and pathophysiology underlying high BP in adolescents.

Faecal Microbiota transplantation affects liver DNA methylation in Non-alcoholic fatty liver disease: a multi-omics approach

Individuals with nonalcoholic fatty liver disease (NAFLD) have an altered gut microbiota composition. Moreover, hepatic DNA methylation may be altered in the state of NAFLD. Using a fecal microbiota transplantation (FMT) intervention, we aimed to investigate whether a change in gut microbiota composition relates to altered liver DNA methylation in NAFLD. Moreover, we assessed whether plasma metabolite profiles altered by FMT relate to changes in liver DNA methylation. Twenty-one individuals with NAFLD underwent three 8-weekly vegan allogenic donor (n = 10) or autologous (n = 11) FMTs. We obtained hepatic DNA methylation profiles from paired liver biopsies of study participants before and after FMTs. We applied a multi-omics machine learning approach to identify changes in the gut microbiome, peripheral blood metabolome and liver DNA methylome, and analyzed cross-omics correlations. Vegan allogenic donor FMT compared to autologous FMT induced distinct differential changes in I) gut microbiota profiles, including increased abundance of Eubacterium siraeum and potential probiotic Blautia wexlerae; II) plasma metabolites, including altered levels of phenylacetylcarnitine (PAC) and phenylacetylglutamine (PAG) both from gut-derived phenylacetic acid, and of several choline-derived long-chain acylcholines; and III) hepatic DNA methylation profiles, most importantly in Threonyl-TRNA Synthetase 1 (TARS) and Zinc finger protein 57 (ZFP57). Multi-omics analysis showed that Gemmiger formicillis and Firmicutes bacterium_CAG_170 positively correlated with both PAC and PAG. E siraeum negatively correlated with DNA methylation of cg16885113 in ZFP57. Alterations in gut microbiota composition by FMT caused widespread changes in plasma metabolites (e.g. PAC, PAG, and choline-derived metabolites) and liver DNA methylation profiles in individuals with NAFLD. These results indicate that FMTs might induce metaorganismal pathway changes, from the gut bacteria to the liver.

Age, Sex, Body Mass Index, Diet and Menopause Related Metabolites in a Large Homogeneous Alpine Cohort

Metabolomics in human serum samples provide a snapshot of the current metabolic state of an individuum. Metabolite concentrations are influenced by both genetic and environmental factors. Concentrations of certain metabolites can further depend on age, sex, menopause, and diet of study participants. A better understanding of these relationships is pivotal for the planning of metabolomics studies involving human subjects and interpretation of their results. We generated one of the largest single-site targeted metabolomics data sets consisting of 175 quantified metabolites in 6872 study participants. We identified metabolites significantly associated with age, sex, body mass index, diet, and menopausal status. While most of our results agree with previous large-scale studies, we also found novel associations including serotonin as a sex and BMI-related metabolite and sarcosine and C2 carnitine showing significantly higher concentrations in post-menopausal women. Finally, we observed strong associations between higher consumption of food items and certain metabolites, mostly phosphatidylcholines and lysophosphatidylcholines. Most, and the strongest, relationships were found for habitual meat intake while no significant relationships were found for most fruits, vegetables, and grain products. Summarizing, our results reconfirm findings from previous population-based studies on an independent cohort. Together, these findings will ultimately enable the consolidation of sets of metabolites which are related to age, sex, BMI, and menopause as well as to participants’ diet.

Pre-Birth and Early-Life Factors Associated With the Timing of Adiposity Peak and Rebound: A Large Population-Based Longitudinal Study

Background: The late occurrence of adiposity peak (AP) and the early occurrence of adiposity rebound (AR) are considered the earliest indicators for obesity and its related health conditions later in life. However, there is still limited information for their upstream factors. Therefore, in this study, we aimed to identify the parental and child factors associated with the timing of AP and AR in the early stage of life. Methods: This is a population-based longitudinal study conducted in Shanghai, China. The BMI data of children born between September 2010 and October 2013 were followed from birth to 80 months. Subject-specific body mass index trajectories were fitted by non-linear mixed-effect models with natural cubic spline functions, and the individual's age at AP and AR was estimated. The generalized linear regression models were applied to identify the upstream factors of late occurrence of AP and early occurrence AR. Results: For 7,292 children with estimated AP, boys were less likely to have a late AP [adjusted risk ratio (RR) = 0.83, 95% confidence interval (CI): 0.77-0.90, p < 0.001], but preterm born children had a higher risk of a late AP (adjusted RR = 1.25, 95% CI: 1.07-1.47, p < 0.01). For 10,985 children with estimated AR, children with breastfeeding longer than 4 months were less likely to have an early AR (adjusted RR = 0.80, 95% CI: 0.73-0.87, p < 0.001), but children who were born to advanced-age mothers and who were born small for gestational age had a higher risk of having an early AR (adjusted RR = 1.21, 95% CI: 1.07-1.36, p < 0.01; adjusted RR = 1.20, 95% CI: 1.04-1.39, p = 0.01). Conclusions: Modifiable pre-birth or early-life factors associated with the timing of AP or AR were found. Our findings may help develop prevention and intervention strategies at the earliest stage of life to control later obesity and the health conditions and diseases linked to it.