Metabolic factors modulate effort-based decision-making in major depressive disorder
Bibliographic record
Abstract
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. 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. 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. Post-hoc analysis using a relatively small sample of convenience. 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. • Abnormalities in effort-based decision-making have been repeatedly reported in MDD. • Metabolic factors are independently associated with reward disturbances. • We assessed the moderating effect of metabolic factors on effort behavior in MDD. • Metabolic factors independently and distinctively correlated with effort behavior. • Insulin resistance and cholesterol were associated with elevated effort discounting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".