Review: Analysis of Smoking and Obesity Therapy Pathway Mapping Using DEG (Differentially Expressed Genes) Data
DOI:
10.29303/jppipa.v12i5.10906Published:
2026-05-31Downloads
Abstract
Therapeutic pathway impacts of smoking and obesity can be mapped through analysis of Differentially Expressed Gene (DEG) datasets. Data used in this study were obtained from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), a reputable biomedical data repository. This study identified a total of 17 eligible GEO datasets for analysis to detect genes with differential expression (DEGs) in response to smoking and obesity exposure. Identified DEGs were further categorized according to their functional profiles. Our findings provide deeper insights into the molecular impacts of smoking and obesity and hold potential for therapeutic strategy development and biomarker discovery related to tobacco exposure and adiposity. Retrieved datasets were synthesized into eight distinct functional gene categories covering metabolism, immunity, cell cycle, and cardiovascular pathways.
Keywords:
Smoking Obesity DEG GEO TranscriptomicsReferences
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