THE INTERPLAY BETWEEN BRAIN NEUROTRANSMITTERS AND OPIOID SYSTEMS IN MAJOR DEPRESSION (MD) AND COMORBID MD AND GENERALIZED ANXIETY
Bibliographic record
Abstract
Abstract Background Mu-opioid receptors (MOR) are known to have entangled regulation with dopamine and serotonin. The roles of brain neurotransmitters (NT) and and opioid receptor (OR) systems in the regulation of specific dynamical properties of behaviour were earlier summarised within the 12 components of the neurochemical framework Functional Ensemble of Temperament (FET). The FET framework allows having a neurochemistry-based structure of a taxonomy that can classify both, healthy bio-psychological traits and symptoms of psychopathology, with depression taken as an example for this study. Aims and objectives of this study were to investigate the predictions of the FET framework regarding the correspondence between the FET components and the Major Depression (MD) symptoms and comorbid MD and Generalized Anxiety (GAD) symptoms. Method FET-structured temperament profiles of patients and clients of private practice were collected for four groups: MD, GAD, comorbid MD-GAD and control (no mental illness), matched by age and sex. Results The FET- structured profiles showed a good convergence with the classic criteria of MD and GAD and showed a good differentiating power for the comorbid MD-GAD. Each symptom was presented in the framework of the interaction between the NT and OR and analysed in terms of differentiation between the symptoms recorded in four studied groups. Discussion & Conclusion Multi-systems neurochemical interaction of studied disorders is presented in the FET in terms of differentiation between the universal aspects of behaviour, such as orientation, integration and energetic maintenance analysed separately for physical, social and mental aspects of activity, plus three emotionality-related aspects. Each of 12 FET aspects is linked to a specific NT-OR team. Our results confirmed the expectations of the FET that MD is a result of a compromised serotonin-MOR interaction with dopamine, not affecting orientational aspects of behaviour but having a negative impact on energetic maintenance and integration of actions, as well as influencing dispositional moods. In contrast to MD, GAD involves more kappa-opioid and noradrenalinergic systems, inducing loss of focus, agitation and chronic anxiety but not necessarily a low dispositional mood, fatigue or lack of interest, as in MD. Finally, comorbid MD-GAD is the most serious condition out of three studied diagnoses, negatively impacting the cortical functioning, including probabilistic processing of environmental information (that involves brain acetylcholine, kappa-opioid receptors and glutaminergic systems). Structuring the contributions of multiple neurochemical systems in major diagnoses in line with the functional constructivism approach employed in the FET is a step forward to a systematic linking of these neurochemical biomarkers to specific consistent behavioural patterns, including symptoms of psychopathology. References Trofimova, I. (2018). Functionality vs dimensionality in psychological taxonomies, and a puzzle of emotional valence. Philosophical Transactions of the Royal Society, Biology, 373 (1744), doi: 10.1098/rstb.2017.0167. Trofimova, I. &Gaykalova, A. (2021). Emotionality vs. other biobehavioural traits: a look at neurochemical biomarkers for their differentiation. Frontiers in Psychology, 12: 781631 doi: 10.3389/fpsyg.2021.781631. Rezaei, S., Bakhshani, N.M., Fanaei, H., &Trofimova, I. (2021). Opium effect in pregnancy on the dynamics of maternal behaviour: testing a neurochemical model. Neuropsychobiology. 80(2), 147-157. doi: 10.1159/000512698. Trofimova, I. &Sulis W. (2018). There is more to mental illness than just negative affect: comprehensive temperament profiles in depression and anxiety. BMC Psychiatry. 18: 125. doi: 10.1186/s12888-018- 1695-x
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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 | 0.001 |
| 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 | 0.000 |
| 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".