Leptin Signaling: Decoding of Genetic Pathways using Bioinformatics; Shaping Bariatric Surgery Outcomes

Background: Leptin, a hormone central to energy homeostasis and appetite regulation, plays a pivotal role in obesity and metabolic health. Single nucleotide polymorphisms (SNPs) in the leptin (LEP) and leptin receptor (LEPR) genes influence leptin signaling and may explain variability in outcomes following bariatric surgery. This bioinformatics-driven study examines the role of LEP and LEPR SNPs in modulating weight loss, metabolic changes, and hormonal responses post-surgery. Methods: A total of 55 leptin SNPs and 216 leptin receptor SNPs were assessed for functional impact using SIFT, PolyPhen-2, and Mutation Assessor. Pathway enrichment analyses using DAVID and g:Profiler identified biological processes and signaling pathways linked to leptin function. Protein-protein interaction (PPI) networks were constructed via STRING and visualized in Cytoscape to explore molecular interactions. Statistical models evaluated associations between SNPs and surgical outcomes, including weight loss and metabolic improvements. Key pathways with false discovery rates (FDR) < 0.01 were highlighted to emphasize significance. Results: Bioinformatics analyses revealed LEP and LEPR as critical variants associated with bariatric surgery outcomes. Specifically, LEP rs7799039 G allele carriers exhibited diminished weight loss (p < 0.05) and metabolic improvements. Functional prediction tools consistently indicated deleterious effects on leptin signaling. Pathway enrichment analyses identified leptin's involvement in critical pathways, including the adipocytokine signaling pathway (hsa04920, 2 of 68 genes, strength = 2.46, FDR = 0.0042)," "AMPK signaling pathway (hsa04152, 2 of 120 genes, strength = 2.22, FDR = 0.0064)," and "non-alcoholic fatty liver disease (NAFLD) pathway (hsa04932, 2 of 146 genes, strength = 2.13, FDR = 0.0064). PPI networks underscored leptin’s interactions with key metabolic and inflammatory regulators, such as TNF-α and IL-6, suggesting a broader impact on energy metabolism and inflammation. Conclusion: This study demonstrates the utility of bioinformatics in elucidating the genetic basis of variable bariatric surgery outcomes. LEP and LEPR SNPs modulate critical pathways influencing weight loss and metabolic responses. Integrating genetic insights with bariatric care could advance precision medicine approaches for obesity management. Future studies with larger cohorts are warranted to confirm these findings and strengthen predictive models.

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Journal
International Journal of Statistics in Medical Research
Published
2024-12-27
DOI
https://doi.org/10.6000/1929-6029.2024.13.35
Primary Topic
Diet and metabolism studies
Type
article
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article

Leptin Signaling: Decoding of Genetic Pathways using Bioinformatics; Shaping Bariatric Surgery Outcomes

Usha Adiga, Adam A. Augustine, Sampara Vasishta
International Journal of Statistics in Medical Research
Diet and metabolism studies
article

Leptin Signaling: Decoding of Genetic Pathways using Bioinformatics; Shaping Bariatric Surgery Outcomes

Usha Adiga, Adam A. Augustine, Sampara Vasishta
article en

Abstract

Background: Leptin, a hormone central to energy homeostasis and appetite regulation, plays a pivotal role in obesity and metabolic health. Single nucleotide polymorphisms (SNPs) in the leptin (LEP) and leptin receptor (LEPR) genes influence leptin signaling and may explain variability in outcomes following bariatric surgery. This bioinformatics-driven study examines the role of LEP and LEPR SNPs in modulating weight loss, metabolic changes, and hormonal responses post-surgery. Methods: A total of 55 leptin SNPs and 216 leptin receptor SNPs were assessed for functional impact using SIFT, PolyPhen-2, and Mutation Assessor. Pathway enrichment analyses using DAVID and g:Profiler identified biological processes and signaling pathways linked to leptin function. Protein-protein interaction (PPI) networks were constructed via STRING and visualized in Cytoscape to explore molecular interactions. Statistical models evaluated associations between SNPs and surgical outcomes, including weight loss and metabolic improvements. Key pathways with false discovery rates (FDR) < 0.01 were highlighted to emphasize significance. Results: Bioinformatics analyses revealed LEP and LEPR as critical variants associated with bariatric surgery outcomes. Specifically, LEP rs7799039 G allele carriers exhibited diminished weight loss (p < 0.05) and metabolic improvements. Functional prediction tools consistently indicated deleterious effects on leptin signaling. Pathway enrichment analyses identified leptin's involvement in critical pathways, including the adipocytokine signaling pathway (hsa04920, 2 of 68 genes, strength = 2.46, FDR = 0.0042)," "AMPK signaling pathway (hsa04152, 2 of 120 genes, strength = 2.22, FDR = 0.0064)," and "non-alcoholic fatty liver disease (NAFLD) pathway (hsa04932, 2 of 146 genes, strength = 2.13, FDR = 0.0064). PPI networks underscored leptin’s interactions with key metabolic and inflammatory regulators, such as TNF-α and IL-6, suggesting a broader impact on energy metabolism and inflammation. Conclusion: This study demonstrates the utility of bioinformatics in elucidating the genetic basis of variable bariatric surgery outcomes. LEP and LEPR SNPs modulate critical pathways influencing weight loss and metabolic responses. Integrating genetic insights with bariatric care could advance precision medicine approaches for obesity management. Future studies with larger cohorts are warranted to confirm these findings and strengthen predictive models.

International Journal of Statistics in Medical ResearchVol. 13
Apollo Institute of Medical Sciences & Research (IN)
Affordable and clean energy
Openalex Percentile: Top 66%
Diet and metabolism studies
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