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Transcriptomic landscape and metabolic phenotypization of Polydactylous rat with metabolic syndrome after high fat diet challenge

ABSTRACT: Metabolic syndrome, with its ever-rising incidence, is an important cause of worldwide morbidity and mortality. MetS is diagnosed if three or more of the following criteria are met: obesity, high serum triglycerides, low HDL-cholesterol, high blood pressure and high serum glucose. Metabolic syndrome has a complex pathogenesis which includes on one hand sedentary lifestyle and high caloric intake, on the other hand there is clear genetic predisposition with heritability in the range of 0.25-0.8. Polydactylous rat (PD hereafter) is a rodent model of metabolic syndrome manifesting dyslipidemia, insulin resistance and obesity without hypertension. To unravel the genetic and pathophysiologic background of this phenotype we compared liver transcriptomes as well as morphometric and metabolic parameters (lipidemic profiles and serum markers) among PD, Spontaneously hypertensive rat and Brown Norway rat lines after high fat diet challenge. We used microarray aproach to unravel gene expression differences between SHR, PD and BN responsible for the different phenotypes in our rat strains.

ORGANISM(S): Rattus norvegicus

PROVIDER: GSE164176 | GEO | 2021/06/03

REPOSITORIES: GEO

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Project description:Deficiency of fatty acid translocase Cd36 has been shown to play major role in pathogenesis of metabolic syndrome components in the spontaneously hypertensive rat (SHR). We have tested the hypothesis that effects of Cd36 mutation on features of metabolic syndrome are contextually-dependent on genomic background. We have derived two new congenic strains by introgression of limited chromosome 4 regions of SHR origin, both including defective Cd36 gene, into genetic background of highly inbred model of insulin resistance and dyslipidemia, polydactylous (PD) rat strain. We have subjected standard diet-fed adult males of PD and the 2 congenic PD.SHR4 strains to metabolic, morphometric and transcriptomic (Affymetrix Rat 1.0 ST Exon array) profiling. We observed significantly improved glucose tolerance and lower fasting insulin in PD.SHR4 congenics than in PD. One of the PD.SHR4 strains also showed lower triglyceride concentrations across major lipoprotein fractions combined with higher concentrations of LDL cholesterol compared to PD progenitor. The other PD.SHR4 strain had lower total and HDL cholesterol as well as lower LDL and HDL triacylglycerol content compared to PD. The hepatic transcriptome assessment revealed network of genes differentially expressed between PD and PD.SHR4 with significant enrichment by members of circadian rhythmicity pathway (Arntl (Bmal1), Clock, Nfil3, Per2 and Per3). In summary, the introduction of chromosome .4 region of SHR origin including defective Cd36 into PD genetic background resulted in disconnected shifts of metabolic profile along with distinct changes in hepatic transcriptome. The synthesis of the current results with those obtained in other Cd36-deficient strains indicate that the eventual metabolic effect of deleterious mutation such as that of SHR-derived Cd36 is not absolute, but rather a function of complex interactions between environment and genomic background, upon which it operates. Affymetrix GeneChip® Rat Exon 1.0 ST Array was used to determine the transcriptomic characteristics of the PD.SHR4a and the progenitor PD strain. We extracted total RNA from the liver of 4-month-old males of both strains (n=8/per strain) using phenol-chloroform and purified with the RNeasy Mini kit (Qiagen) in accordance with the manufacturer’s protocol. The quality of the total RNA was verified by the Agilent 2100 Bioanalyzer system. Double-stranded complementary DNA (cDNA) was synthesized from total RNA. The labeled and fragmented cDNA was pooled for each strain and hybridized to Affymetrix GeneChip® Rat Exon 1.0 ST Arrays (PD.SHR4a - 2 chips; PD - 3 chips). The whole hybridization procedure including DNA adjustment was performed according to the protocol recommended by Affymetrix.

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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Transcriptomic landscape and metabolic phenotypization of Polydactylous rat with metabolic syndrome after high fat diet challenge

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