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Phenotypic and genomic frameworks for precision pharmacotherapy in obesity: a narrative review
Dario S Lopez Delgado1, Miriam Gabriela Reyes-Zermeño2, Elian David Sanjuanelo Lemus3
1Fundación Hospital San Pedro, Pasto, Colombia.
Background:
Obesity is a chronic, heterogeneous disease with marked interindividual variability in response to anti-obesity medications. Although GLP-1 receptor agonists (GLP-1RAs) and dual incretin agonists produce substantial average weight loss in clinical trials, real-world effectiveness is limited by interindividual variability, gastrointestinal intolerance, incomplete dose escalation, cost and access barriers, poor long-term persistence, and weight plateau or regain in a subset of treated patients. Weight regain is particularly consistent after treatment discontinuation, reinforcing the chronic-care nature of obesity pharmacotherapy.
Objective:
To synthesize evidence on phenotypic and genomic determinants of variability in pharmacotherapy response and propose a pragmatic framework for precision pharmacotherapy in obesity.
Methods:
Narrative review integrating data from randomized trials, post-hoc subgroup analyses, observational cohorts, neurobehavioral studies, pharmacogenomic investigations, and polygenic risk score research addressing predictors of efficacy and tolerability.
Results:
Response heterogeneity reflects interactions among central satiety and reward circuitry, baseline metabolic and glycemic status, sex, baseline adiposity, treatment indication, previous GLP-1RA exposure, adherence, and tolerability. Early on-treatment weight change, usually assessed within 12-16 weeks and in some liraglutide studies as early as 1 month, is the most clinically actionable predictor of longer-term outcomes. Phenotype-guided approaches that classify dominant mechanisms such as impaired satiation, postprandial hunger, emotional or hedonic eating, and low energy expenditure offer a feasible bridge between pathophysiology and medication selection. Emerging genomic signals are promising but remain insufficiently replicated for routine clinical use.
Conclusion:
Precision pharmacotherapy in obesity is most viable today through phenotype-guided treatment, structured early-response monitoring, and proactive management of adherence and tolerability. Genomic tools may eventually refine treatment selection, but they remain investigational and require prospective, multi-ancestry validation.
Insights
Individual response to obesity medications varies greatly. Phenotype-guided treatment and early monitoring are key for precision pharmacotherapy, while genomics require further validation.
Area of Science:
- Endocrinology
- Pharmacology
- Genetics
Background:
- Obesity is a complex disease with significant variability in patient response to anti-obesity medications.
- While GLP-1 receptor agonists (GLP-1RAs) show average weight loss, real-world effectiveness is hindered by factors like side effects, cost, and weight regain.
- Weight regain after treatment cessation highlights the chronic nature of obesity management.
Purpose of the Study:
- To review evidence on phenotypic and genomic factors influencing pharmacotherapy response in obesity.
- To propose a framework for precision pharmacotherapy tailored to individual patient needs.
Main Methods:
- A narrative review of randomized trials, subgroup analyses, and observational studies.
- Integration of data from neurobehavioral, pharmacogenomic, and polygenic risk score research.
- Focus on predictors of medication efficacy and tolerability.
Main Results:
- Response variability is linked to central satiety/reward pathways, metabolic status, sex, adiposity, and treatment history.
- Early weight change (within 12-16 weeks) is a strong predictor of long-term outcomes.
- Phenotype-guided approaches (e.g., identifying eating patterns) can inform medication selection; genomics are promising but not yet clinically routine.
Conclusions:
- Precision pharmacotherapy for obesity currently relies on phenotype-guided strategies, early response assessment, and managing adherence/tolerability.
- Genomic tools show future potential for refining treatment but need further validation in diverse populations.
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