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Published on: August 2, 2018
Metabolic factors modulate effort-based decision-making in major depressive disorder
Hartej Gill1, Sebastian Badulescu1, Joshua D Di Vincenzo2
1Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
Background:
Abnormalities in effort-based decision-making have been consistently reported in major depressive disorder (MDD). Evidence indicates that metabolic factors, such as insulin resistance and dyslipidemia, which are highly prevalent in MDD, are independently associated with reward disturbances. Herein, we investigate the moderating effect of metabolic factors on effort-based decision-making in individuals with MDD.
Methods:
Forty-nine adults with MDD completed the Effort Expenditure for Rewards Task (EEfRT). Anthropometric and laboratorial parameters were assessed in all participants. We conducted a factor analysis to identify combinations of correlated metabolic variables, and reduce the number of comparisons.
Results:
Proxy markers of elevated insulin resistance (OR: 0.816, p < 0.001) and hyperglycemia (OR: 0.898, p = 0.021) were associated with a lower willingness to exert physical effort for rewards in the EEfRT. In contrast, elevated HDL (OR: 1.165, p = 0.004), and elevated non-HDL cholesterol and triglycerides (OR: 1.184, p < 0.001) were associated with increased frequency of hard task choices. These associations were independent of age, sex, depressive symptoms severity and medication use. Computational modeling revealed that the insulin resistance (β = 0.275, p = 0.035) and cholesterol factors (β = 0.565, p < 0.001) were independently associated with increased effort discounting.
Limitations:
Post-hoc analysis using a relatively small sample of convenience.
Conclusions:
Metabolic factors significantly and independently modulated effort-based decision-making in patients with MDD. These results have implications for our understanding of reward disturbances in MDD, and offer insights for further mechanistic investigations.
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