Metabolic and Molecular Changes in Visceral Obesity
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Date
2025
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Saudi Digital Library
Abstract
Rodent models have played a crucial role in obesity research, particularly for understanding polygenic
obesity, which mirrors human obesity more closely than monogenic forms. The genetically diverse outbred
Crl:CD SD rats provide a relevant system for studying obesity-related metabolic changes. This study
categorized male Crl:CD SD rats into overweight, average-weight, and underweight groups based on body
weight percentiles. Without intervention, the overweight rats exhibited increased food intake, adiposity,
hyperinsulinemia, hyperglycemia, and hyperleptinemia, reinforcing their suitability for studying polygenic
obesity.
Expanding on these findings, a multi-omics approach was employed to investigate molecular differences
in epididymal white adipose tissue (EWAT). Proteomics, phospho-proteomics, and kinase activity assays
revealed significant alterations in adipogenesis pathways, cell cycle regulation, inflammatory markers, and
insulin signaling. Notably, overweight rats demonstrated increased activity of the dual specificity mitogen
activated protein kinase 7 (MKK7) and the never in mitosis gene A (NEK2), alongside
hyperphosphorylation of O-GlcNAcase (OGA) at serine 364.
To further assess the functional roles of these proteins, gene knockdown experiments were conducted in
3T3-L1 adipocytes. While Mkk7 knockdown did not impair adipogenesis, it influenced cytokine production,
suggesting a role in adipose tissue inflammation. Conversely, Oga knockdown resulted in reduced cell
viability and impaired adipogenesis, highlighting its importance in adipocyte differentiation.
Taken together, these findings establish Crl:CD SD rats as a valuable model for studying polygenic visceral
obesity and its molecular underpinnings. Additionally, MKK7 and OGA emerge as potential therapeutic
targets for mitigating adipose tissue inflammation and visceral adiposity, though further in vivo studies are
required to elucidate their specific mechanisms.
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Keywords
Obesity, Type 2 diabete, Multiomics
