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Cardiorespiratory Fitness in Children with Overweight-Obesity: Insights into the Molecular Mechanisms

ABSTRACT: This study aimed to analyze the whole-blood transcriptome profile of fit children with overweight/obesity (OW/OB) compared to unfit children with OW/OB. Methods: 27 children with OW/OB (10.14 ± 1.3 years, 59% boys) from the ActiveBrains project were evaluated. VO2peak was assessed using a gas analyzer, and participants were categorized into fit or unfit according to the CVD risk-related cut-points. Whole-blood transcriptome profile (RNA sequencing) was analyzed. Differential gene expression analysis was performed using Limma R/Bioconductor software package (analyses adjusted by sex and maturational status). Results: 256 genes were differentially expressed in fit children with OW/OB compared to unfit children with OW/OB after adjusting by sex and maturational status (FDR < 0.05). Enriched pathways analysis identified gene pathways related to inflammation (e.g., dopaminergic and GABAergic synapse pathways). Conclusion: The distinct pattern of whole-blood gene expression in fit children with OW/OB reveals genes and gene pathways that might play a role in reducing CVD risk factors later in life.

ORGANISM(S): Homo sapiens

PROVIDER: GSE164873 | GEO | 2021/08/05

REPOSITORIES: GEO

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Project description:Background and aims: Youth populations with overweight/obesity (OW/OB) exhibit heterogeneity in cardiometabolic health phenotypes (e.g. fasting glucose, serum triglycerides, etc.). The underling mechanisms for those differences are still unclear. This study aimed to analyze the whole blood transcriptome profile (RNA-seq) of children with metabolic healthy overweight/obesity (MHO) and metabolic unhealthy overweight/obesity (MUO) phenotypes. Methods: 27 children with OW/OB (10.14 ± 1.3 years, 59% boys) from the ActiveBrains project were included. MHO was defined as having none of the following criteria for metabolic syndrome: elevated fasting glucose, high serum triglycerides, low high-density lipoprotein cholesterol, and high systolic or diastolic blood pressure, while MUO was defined as presenting one or more of these criteria. Inflammatory markers interleukin-1β (IL-1β), IL-6, tumor necrosis factor-α (TNF-α), epidermal growth factor (EGF) and, vascular endothelial growth factor A (VEGF) were additionally determined. Total-blood RNA was analyzed by 5’-end RNA sequencing. Two different bioinformatics approaches were performed: 1) Differential gene expression analyses using Limma R/Bioconductor software package (analyses adjusted by sex and maturational status) and 2) weighted gene coexpression network analyses (WGCNA). Results: Children with MHO had lower values of pro-inflammatory cytokines TNF-α and IL-6 compared to MUO (p < 0.05). 40 genes were differentially expressed (FDR < 0.05) in children with MHO compared to MUO. WGCNA analysis identified 23 gene coexpression modules (i.e. clusters of genes) with low preservation (Zsummary < 2) in children with MHO compared to MUO. Differential and WGCNA gene expression patterns identified 32 genes linked to metabolism, mitochondrial and immune functions. Conclusions: Whole blood transcriptome analysis revealed a distinct pattern of gene expression in children with MHO compared to MUO children. The identified gene expression patterns related to metabolism, mitochondrial and immune functions can promote a better understanding of cardiovascular disease prognosis in individuals with MHO.

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Cardiorespiratory Fitness in Children with Overweight-Obesity: Insights into the Molecular Mechanisms

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