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Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
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Exploring genetic susceptibility to obesity through genome functional pathway analysis
Alexander P Gabrielli1, Ann M Manzardo1, Merlin G Butler1
1Departments of Psychiatry and Behavioral Sciences and Pediatrics, University of Kansas Medical Center, Kansas City, Kansas, USA.
Obesity (Silver Spring, Md.)
|May 6, 2017
Summary
Genetic profiling reveals key biological pathways and compounds linked to obesity. This study highlights how disruptions in glucose and lipid metabolism signaling contribute to the disease.
Area of Science:
- Genetics
- Genomics
- Molecular Biology
Background:
- Obesity is a growing epidemic with significant genetic underpinnings.
- Understanding genetic factors is crucial for addressing obesity.
Purpose of the Study:
- To investigate the relationship between genetic factors and obesity using a gene-profiling approach.
- To identify specific genes, pathways, and biological processes associated with obesity.
Main Methods:
- Compiled an updated list of 494 obesity-related genes.
- Utilized GeneAnalytics software to analyze genomic databases (GeneCards®).
- Cross-referenced gene sets with diseases, pathways, gene ontology (GO) terms, phenotypes, and compounds.
Main Results:
- Identified 8 diseases, 46 pathways, 62 biological processes, 22 molecular functions, 148 phenotypes, and 286 compounds linked to obesity.
- Highlighted impacts on adipogenesis, G-protein coupled receptor signaling, and lipid metabolism involving insulin-related genes (IGF1, INS, IRS1).
- Found significant GO-biological processes including feeding behavior, cholesterol metabolism, and glucose homeostasis, and GO-molecular functions related to receptor binding.
Conclusions:
- Obesity pathogenesis may involve disrupted coordination of biological responses to glucose and lipids.
- Cellular signaling and biochemical cascades affected by receptor interactions are implicated.
- Genetic profiling offers insights into the complex molecular mechanisms of obesity.
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