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Updated: Oct 21, 2026

Multidisciplinary Approach to Obesity Management: A Case Report
Published on: May 30, 2025
Determinants of variable response to GLP-1 receptor agonists: A mechanism-informed framework for precision treatment
1Nightingale Hospital, Kolkata, India.
Introduction:
The management of obesity changed significantly with the introduction of glucagon-like peptide-1 receptor agonists (GLP-1RAs). However, considerable interindividual variability in weight-loss response remains, and its determinants are incompletely understood.This review proposes an integrated mechanistic and clinical framework for understanding interindividual variability in GLP-1RA response and explores whether biologically defined obesity phenotypes could ultimately inform precision treatment.
Methods:
This was a structured literature review and framework synthesis that drew from PubMed/MEDLINE and CENTRAL to integrate clinical, mechanistic, and translational evidence into a multi-level, hypothesis-generating model of GLP-1RA response.
Results:
Pharmacokinetic exposure, receptor-level signalling, and central nervous system involvement were integrated into a three-level framework. This framework was overlaid onto a spectrum of candidate biological domains spanning appetite/satiety, reward/hedonic processes, metabolic dysfunction, and energy conservation. Complementary pharmacological pathways involving GIP, amylin, and glucagon were subsequently mapped onto these domains as mechanistically plausible treatment hypotheses. However, evidence that these phenotypes predict differential treatment effects is currently insufficient to define therapeutic endotypes.
Conclusion:
Interindividual variability in GLP-1RA response may partly reflect underlying biological heterogeneity. Mechanism-informed phenotyping offers a testable framework for investigating this variability, but prospective demonstration of phenotype-by-treatment interactions will be required before such phenotypes can be considered therapeutic endotypes or used to guide treatment selection.
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