Decreasing severity of obesity from early to late adolescence and young adulthood associates with longitudinal metabolomic changes implicated in lower cardiometabolic disease risk

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.

Increased innate immune responses in adolescents with obesity and its relation to subclinical cardiovascular measures: An exploratory study

Cardiometabolic risk accrues across the life course and childhood and adolescence are key periods for effective prevention. Obesity is associated with inflammation in adults, but pediatric data are scarce. In a cross-sectional and longitudinal study, we investigated immune cell composition and activation in 31 adolescents with obesity (41.9% male, BMIz>2.5, 14.4 years) and 22 controls with healthy weight (45.1% male, -1.5 Collapse

Key Words

• Disease
• Health sciences
• Immunology
• Pathophysiology
• Risk factor

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Affiliation(s)

Siroon Bekkering Department of Internal Medicine, Radboud University Medical Centre, Nijmegen 6525 GA, the Netherlands Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia
Christoph Saner Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Division of Pediatric Endocrinology, Diabetology and Metabolism, Department of Pediatrics, University Children`s Hospital Bern, Inselspital, Bern 3010, Switzerland Department of Biomedical Research, University of Bern, 3010 Bern, Switzerland
Boris Novakovic Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
Toby Mansell Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
Danielle K. Longmore Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Endocrinology, The Royal Children`s Hospital, Parkville, VIC 3052, Australia
Zoe McCallum Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia Department of Neurodevelopment and Disability, Royal Children’s Hospital, Parkville, VIC 3052, Australia
Anne-Louise Ponsonby Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC 3052, Australia
Markus Juonala Department of Medicine, University of Turku, 20500 Turku, Finland Division of Medicine, Turku University Hospital, 20500 Turku, Finland
Mihai G. Netea Department of Internal Medicine, Radboud University Medical Centre, Nijmegen 6525 GA, the Netherlands Department of Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
Matthew A. Sabin Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Endocrinology, The Royal Children`s Hospital, Parkville, VIC 3052, Australia Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
Richard Saffery Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
Niels P. Riksen Department of Internal Medicine, Radboud University Medical Centre, Nijmegen 6525 GA, the Netherlands
David P. Burgner Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia Department of Pediatrics, Monash University, Clayton, VIC 3168, Australia

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Exploring the complex dynamics of BMI, age, and physiological indicators in early adolescents

BACKGROUND AND OBJECTIVES

To investigate the relationship between body mass index (BMI) and blood biochemical indicators in early adolescence, and to provide ideas for early prevention of diseases and explore possible disease-related predictors.

METHODS

3125 participants aged 10 ∼ 14 years were selected from China from the survey of "China Nutrition and Health Surveillance ( 2016 ∼ 2017 ) ". Employing advanced statistical methods, including generalized linear models, heatmaps, hierarchical clustering, and generalized additive models, the study delved into the associations between BMI and various biochemical indicators.

RESULTS

In early adolescence, indicators including systolic pressure, diastolic pressure, weight, height, BMI, hemoglobin, blood uric acid, serum creatinine, albumin, vitamin A presented increasing trends with the increase of age ( P < 0.05 ), whereas LDL-C, vitamin D, and ferritin showed decreasing trends with the increase of age ( P < 0.05 ). The increase in hemoglobin and blood uric acid levels with age was more pronounced in males compared to females ( P < 0.05 ). BMI was positively correlated with blood glucose, hemoglobin, triglyceride, LDL-C, blood uric acid, serum creatinine, ferritin, transferrin receptor, hs-CRP, total protein, vitamin A ( P < 0.05 ). There was a significant BMI × age interaction in the correlation analysis with LDL-C, transferrin receptor, serum creatinine, and hs-CRP ( P < 0.05 ). BMI was a risk factor for hypertension, hypertriglyceridemia, low high density lipoprotein cholesterolemia, and metabolic syndrome in all age groups ( OR > 1, P < 0.05 ).

CONCLUSIONS

High BMI was a risk factor for hypertension, hypertriglyceridemia, low high density lipoprotein cholesterolemia, and MetS in early adolescents. With the focus on energy intake beginning in early adolescence, the maintenance of a healthy weight warrants greater attention.

Altered adolescents obesity metabolism is associated with hypertension: a UPLC-MS-based untargeted metabolomics study

Objective

This study aimed to explore the relationship between the plasma metabolites of adolescent obesity and hypertension and whether metabolite alterations had a mediating effort between adolescent obesity and hypertension.

Methods

We applied untargeted ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to detect the plasma metabolomic profiles of 105 adolescents. All participants were selected randomly based on a previous cross-sectional study. An orthogonal partial least squares- discriminant analysis (OPLS-DA), followed by univariate statistics and enrichment analysis, was used to identify differential metabolites. Using logistic regression for variable selection, an obesity-related metabolite score (OMS, OMS=∑k=1nβnmetabolite n) was constructed from the metabolites identified, and hypertension risk was estimated.

Results

In our study, based on P< 0.05, variable importance in projection (VIP) > 1.0, and impact value > 0.1, we identified a total of 12 differential metabolites. Significantly altered metabolic pathways were the sphingolipid metabolism, purine metabolism, pyrimidine metabolism, phospholipid metabolism, steroid hormone biosynthesis, tryptophan, tyrosine, and phenylalanine biosynthesis. The logistic regression selection resulted in a four-metabolite score (thymidine, sphingomyelin (SM) d40:1, 4-hydroxyestradiol, and L-lysinamide), which was positively associated with hypertension risk (odds ratio: 7.79; 95% confidence interval: 2.13, 28.47; for the quintile 4 compared with quartile 1 of OMS) after multivariable adjustment.

Conclusions

The OMS constructed from four differential metabolites was used to predict the risk of hypertension in adolescents. These findings could provide sensitive biomarkers for the early recognition of hypertension in adolescents with obesity.

The alteration of left ventricular strain in later-onset spinal muscular atrophy children

Background

Patients with spinal muscular atrophy (SMA) may suffer from multisystem injury, including an impaired cardiovascular system. However, M-mode echocardiography, the current dominant echocardiographic modality, is limited in the detection of myocardial injury. We considered the use of left ventricular strain imaging in detecting myocardial injury and explored the serum lipid profile related to cardiovascular disease in later-onset SMA children.

Methods

A case-control study involving 80 patients with later-onset SMA and 80 age-, gender-, and body surface area-matched control children was conducted in a single tertiary pediatric hospital in China. Data on the left ventricular strain measured using two-dimensional speckle tracking echocardiography, left ventricular function parameters assessed by M-mode echocardiography, and serum lipid profile of these two groups were retrospectively collected for differential analysis.

Results

The mean age of the 80 SMA patients were (6.87 ± 2.87) years, of which 46 were type 2 and 34 were type 3 patients. The global longitudinal strain (GLS) of the SMA group (−18.7 ± 2.9%, p < 0.001) was lower than that of the control group; the time to peak longitudinal strain (TTPLS) of the SMA group (22.9 ± 13.6 ms, p < 0.001) was higher than that of the control group, while left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS), measured by the Teichholz method of M-mode echocardiography, showed no significant differences between the two groups. In addition, independent indicators for cardiovascular risk, including total cholesterol (TC)/HDL, low-density lipoprotein (LDL)/HDL, and Apo B/Apo A1 levels, were higher in SMA children than in the control group.

Conclusion

Compared with healthy controls, later-onset SMA children presented with reduced GLS and prolonged TTPLS while the LVEF and LVFS values were within normal range. In particular, whether a reduced GLS or prolonged TTPLS in later-onset SMA compared to the control group can predict the risk of future cardiomyopathy remains to be investigated.