Cardiometabolic Effects of Dual GLP-1 and Glucagon Receptor Agonists: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

Abstract

Selective glucagon-like protein 1 receptor (GLP-1R) agonists reduce body weight and improve cardiometabolic risk factors. However, whether dual GLP-1R and glucagon receptor (GCGR) agonism modifies these cardiometabolic effects remains unclear. Here, we assessed the effects of dual GLP-1R/GCGR agonists on cardiometabolic risk factors across randomized controlled trials. In this random-effects meta-analysis, Medical Literature Analysis and Retrieval System Online (MEDLINE), Embase, and Cochran Central Register of Controlled Trials (CENTRAL) were searched from database inception to 21 June 2026 for randomized controlled trials evaluating clinical efficacy of dual GLP-1R/GCGR agonists in adults with cardiometabolic disease with a treatment duration ≥12 weeks. The primary outcome was placebo-corrected change in body weight from baseline to end of treatment. Secondary outcomes were changes in waist circumference, atherogenic lipids (total cholesterol, LDL cholesterol, and triglycerides), glycated hemoglobin, and hemodynamic outcomes. Prespecified subgroup analyses evaluated effect modification by dose, treatment indication, and the use of an active comparator (selective GLP-1R agonists). A total of 6,593 records were identified, and 16 trials comprising 6,611 participants (47.3% male) were included. Dual GLP-1R/GCGR agonists significantly reduced body weight compared with placebo (-7.44% [95% CI -9.44, -5.43]; -7.27 kg [95% CI -9.28, -5.27]). Weight loss was accompanied by improvements across all cardiometabolic risk factors. Compared with selective GLP-1R agonists, dual GLP-1R/GCGR agonists were associated with a greater reduction in triglycerides (-0.28 mmol/L [95% CI -0.50, -0.06]). Dual GLP-1R/GCGR agonists consistently improved cardiometabolic risk factors across randomized clinical trials and may provide metabolic benefits beyond selective GLP-1R agonists. These findings support further evaluation in large-scale outcome studies.