Computational phenotyping of effort-based decision-making in type-2 diabetes on and off semaglutide

Abstract

Motivation plays a fundamental role in human behaviour. Dopaminergic pathways have long been implicated in individual differences in motivation. Emerging evidence suggests such neural mechanisms interact with metabolic processes to coordinate energy expenditure with energy resources, thereby linking motivation with metabolic health. We ask whether a cognitive-computational index of motivation—reliably linked to neuropsychiatric symptoms—is altered in the context of type-2 diabetes and treatment with a GLP-1 agonist (semaglutide). In a pre-registered experiment, we quantified computational effort-based decision-making parameters in participants with diabetes on (N = 58) or off (N = 54) semaglutide treatment, compared to two groups of matched controls without diabetes (N = 58 each). Subjects with type-2 diabetes showed a blunted acceptance bias, a computational parameter describing the bias to accept effort for reward. This effect was not driven by neuropsychiatric comorbidity or antidepressant use. Across all participants, we found that increasing diabetes risk linearly predicted reduced acceptance bias. Participants with diabetes treated with semaglutide did not show restored motivation. Metabolic ill-health is associated with reduced acceptance bias during motivational decision-making. This blunting mirrors—but is largely independent of—neuropsychiatric motivational deficits. This suggests metabolic ill-health is accompanied by a cognitive shift towards energy conservation, potentially contributing to comorbidity between metabolic ill-health and mental illness.