Determinants of variable response to GLP-1 receptor agonists: A mechanism-informed framework for precision treatment of obesity.
- 1Nightingale Hospital, Kolkata, India.
Abstract
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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BibTeX
@article{ghosal2026determinants,
title = {{Determinants of variable response to GLP-1 receptor agonists: A mechanism-informed framework for precision treatment of obesity.}},
author = {Samit Ghosal},
journal = {Obesity pillars},
year = {2026},
month = oct,
doi = {10.1016/j.obpill.2026.100339},
url = {https://europepmc.org/article/MED/42898214},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Determinants of variable response to GLP-1 receptor agonists: A mechanism-informed framework for precision treatment of obesity.
AU - Samit Ghosal
PY - 2026
DA - 2026/10/07
JO - Obesity pillars
DO - 10.1016/j.obpill.2026.100339
UR - https://europepmc.org/article/MED/42898214
AB - 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.
SN - 2667-3681
ER -