Leptin’s Inverse Association With Brain Morphology and Depressive Symptoms: A Discovery and Confirmatory Study Across 2 Independent Samples
Bibliographic record
Abstract
Major Depressive Disorder (MDD) has a complex, bi-directional relationship with metabolic dysfunction, yet the neural correlates of this association are not well understood. In this cross-sectional investigation, we employed a two-step 'discovery and confirmatory' strategy, utilizing two independent samples (Sample 1: 288 participants, Sample 2: 196 participants) to examine the association between circulating indicators of metabolic health (leptin and adiponectin) and brain structures in individuals with MDD. We found a replicable inverse correlation between leptin levels and cortical surface area within essential brain areas responsible for emotion regulation, such as the left posterior cingulate cortex, right pars orbitalis, right superior temporal gyrus, and right insula (standardized beta coefficient (SBC) ranged: -0.27 to -0.49, puncorrected <0.05). Notably, this relationship was independent of C-Reactive Protein levels. We also identified a significant interaction effect of leptin levels and diagnosis on the cortical surface area of the right superior temporal gyrus (SBC = 0.26 in sample 1, SBC = 0.30 in sample 2, puncorrected < 0.05). We also observed a positive correlation between leptin levels and atypical depressive symptoms in both MDD groups (r = 0.14 in sample 1, r = 0.29 in sample 2, puncorrected < 0.05). The inverse association between leptin and cortical surface area in brain regions that are important for emotion processing and leptin’s association with sleep disturbances supports the hypothesis that metabolic processes may be related to emotion regulation. However, the molecular mechanisms through which leptin might exert these effects should be explored further.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".