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Responders Vs. Non-Responders or How to Predict the Response to GLP-1 or GLP-1/GIP Receptor Agonist Therapy
Alina Kuryłowicz1, Leszek Czupryniak2
1Department of Internal Medicine and Geriatric Cardiology, Center of Postgraduate Medical Education, Warsaw, Poland.
Background:
Glucagon-like peptide-1 receptor agonists (GLP-1RAs) and dual GLP-1/GIP receptor agonists have transformed the pharmacological management of type 2 diabetes (T2D) and obesity, yet substantial interindividual variability in treatment response remains a defining clinical challenge.
Methods:
Narrative review. PubMed was searched to 25 May 2026 (English language, human studies, 2005-2026) for biological, genetic, metabolic, hormonal, behavioural and psychosocial predictors of differential response. Evidence is organised across three clinically distinct contexts: glycaemic control in T2D; weight loss in people with overweight or obesity without T2D; and dual metabolic benefit in those with both conditions.
Results:
Response heterogeneity is most pronounced in obesity without diabetes, where non-response-commonly defined as less than 5% total body weight loss-affects approximately 10% of participants in controlled trials, with real-world cohorts suggesting a higher frequency in routine practice; glycaemic non-response in T2D is less common but clinically significant. Across all three contexts, early on-treatment response is the most readily actionable predictor currently available. A recent large genome-wide association study reported associations between variation in the GLP1R drug-target gene and both weight-loss efficacy and gastrointestinal tolerability, and between agent-specific GIPR variants and nausea and vomiting with tirzepatide; these self-reported, single-cohort and as-yet unreplicated findings remain hypothesis-generating rather than a basis for individual-level genotyping. Metabolic, microbiome and neuroendocrine predictors are at a comparably preliminary stage.
Conclusion:
No single baseline characteristic reliably predicts response. Structured assessment of early on-treatment response is currently the most defensible basis for individualising therapy; genetic, metabolic and microbiome markers require prospective replication before clinical application.
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