PROTOCOL - Leptin Signaling and its Relationship with Obesity-Induced Insulin Resistance: A Bioinformatics-assisted Review [The Project ATA]

SIMPLE SUMMARY

Preliminary data shows that reduced sensitivity to leptin leads to diet-induced obesity. Hyperleptinemia serves as a marker of leptin resistance; thus, there is a correlation between genetics, dietary habits, and leptin deficiency in metabolic syndrome. This review aims to discuss the intricate molecular relationships between leptin, obesity, and insulin resistance.

METHODS

A bioinformatics-assisted review (BaR) will be performed following the procedure proposed by Bonilla et al. (2021, 2022). This review will be conducted as part of ‘The Project ATA’, a multicenter study proposed and currently led by the DBSS Research Division (ClinicalTrials.gov ID NCT05758311).

Search Strategy and Information Sources

The search process of the scientific literature was carried out using the free terms “leptin,” “insulin resistance,” and “obesity” through the databases PubMed/MEDLINE and Science Direct.

Manual Curation and Bioinformatics-assisted Review

The BaR addresses the lack of systematization in reviews that aim to update and/or analyze phenomena at the molecular level. To overcome subjective and manual time-consuming extraction of information, this approach utilizes experimentally validated, high-level manually curated, and reproducible data (open-source bioinformatics tools). Several public databases and repositories were accessed to retrieve manually curated biological information:

1. UniProtKB (https://www.uniprot.org/),
2. PDB (https://www.rcsb.org/),
3. Ensembl (https://www.ensembl.org/index.html),
4. The Gene Ontology Resource (http://geneontology.org/),
5. The human protein atlas (https://www.proteinatlas.org/),
6. BioGPS–Gene Portal System (http://biogps.org/).

Findings presentation

The functional annotations will be discussed within the literature review as well as the expert clinical interpretation as follows: i) Obesity, leptin resistance, and metabolic syndrome; ii) Relevant molecular mechanisms of leptin resistance; iii) Convergence of molecular pathways between leptin and insulin resistance; and iv) Conclusion.

REFERENCES

• Bonilla, D. A., Kreider, R. B., Stout, J. R., Forero, D. A., Kerksick, C. M., Roberts, M. D., & Rawson, E. S. (2021). Metabolic Basis of Creatine in Health and Disease: A Bioinformatics-Assisted Review. Nutrients, 13(4), 1238. https://doi.org/10.3390/nu13041238
• Bonilla, D. A., Moreno, Y., Petro, J. L., Forero, D. A., Vargas-Molina, S., Odriozola-Martínez, A., Orozco, C. A., Stout, J. R., Rawson, E. S., & Kreider, R. B. (2022). A Bioinformatics-Assisted Review on Iron Metabolism and Immune System to Identify Potential Biomarkers of Exercise Stress-Induced Immunosuppression. Biomedicines, 10(3), 724. https://doi.org/10.3390/biomedicines10030724

Uploaded by the Research Division, Dynamical Business & Science Society — DBSS International SAS, Bogotá 110311, Colombia. E-mail contact: dabonilla@dbss.pro