Investigating the relationship between melatonin levels, melatonin system, microbiota composition and bipolar disorder psychopathology across the different phases of the disease
Bibliographic record
Abstract
BACKGROUND: Bipolar disorder (BD) is characterized by recurrent episodes of depression and mania/hypomania alternating with intervals of well-being. The neurobiological underpinnings of BD are still veiled although there is evidence pointing to a malfunction of the circadian clock system that is regulated by the neuromodulator melatonin (MLT). Small sample size studies in BD patients have shown that changes in the levels of MLT are associated with shifts in illness status. Moreover, mood stabilizers (including lithium and valproic acid) influence the MLT system. Of interest, MLT also modulates intestinal microbiota, and recent work suggests an important role of microbiota alterations in neuropsychiatric disorders, including BD. This study is designed to explore whether the possible patterns of associations between changes in the levels of MLT and its precursors and BD mood phases are modulated by variants within the genes encoding for the elements of the MLT system and/or by the microbiota composition. METHODS: We will conduct a 2-year follow-up study in 50 BD patients during the three different mood phases of the disease. For each phase, we will perform a blood withdrawal for the analysis of MLT levels and of variants of the genes related to the MLT pathway between 8 and 10 a.m. after an overnight fasting, a stool specimen collection for the analysis of microbiota composition, and a detailed psychometric assessment for depression, mania, impulsivity and cognitive abilities. We will also recruit 50 healthy age-matched controls in whom we will perform a blood withdrawal between 8 and 10 a.m. after an overnight fasting, a stool specimen collection, and a psychometric assessment to exclude the presence of psychiatric disorders. DISCUSSION: In this cross sectional (case-control vs. BD comparisons) and longitudinal (24 months) study, we expect to clarify the link between the MLT system, microbiota and BD psychopathology. We expect to identify some typical BD symptomatic clusters that will be more strictly associated with variations in the MLT system. In a personalized medicine perspective, this subgroup of BD patients may benefit from a pharmacological therapy targeting the MLT system. Trial registration This study protocol was approved by the Ethics Committee of the University Hospital Agency of Cagliari (PG/2019/6277).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".