Association of MAOA gene functional promoter polymorphism with CSF dopamine turnover and atypical depression
Bibliographic record
Abstract
OBJECTIVE: Monoamine oxidase-A (MAO-A) is a key mitochondrial enzyme that metabolizes biogenic amine neurotransmitters such as dopamine and serotonin. Individuals with atypical depression (AD) are particularly responsive to treatment with MAO inhibitors (MAOIs). Biomarker tests are essential for prompt diagnosis of AD, and to identify those with an altered brain neurotransmitter metabolism who may selectively respond to MAOI therapy. METHODS: In a sample of 118 Scandinavian patients with treatment-resistant depression who are naive to MAOI therapy, we investigated the associations between a common MAOA functional promoter polymorphism (MAOA-uVNTR), cerebrospinal fluid (CSF) neurotransmitter metabolites, and AD susceptibility. The metabolites for dopamine (homovanillic acid, HVA), serotonin (5-hydroxyindoleacetic acid) and noradrenaline (3-methoxy-4-hydroxyphenylglycol) were measured in the CSF. RESULTS: AD was associated with the female sex and a higher HVA in CSF (P=0.008). The carriers of the MAOA-uVNTR short allele were significantly overrepresented among women with AD (P=0.005; odds ratio=4.76; 95% confidence interval=1.5-13.1; statistical power=80.0%). Moreover, the MAOA-uVNTR genotype significantly influenced the HVA concentration (P=0.01) and showed a strong trend in relation to 5-hydroxyindoleacetic acid concentration (P=0.057) in women. The mediational statistical analyses showed the CSF-HVA concentration as a key driver of the relationship between MAOA-uVNTR genotype and AD. CONCLUSION: The association of the MAOA-uVNTR with both susceptibility to AD and dopamine metabolite (HVA) concentration lends further biological plausibility for high MAO-A enzyme activity as a mechanistic factor for genetic predisposition to AD through altered dopamine turnover. Our observations provide new evidence on the in-vivo functional significance of the MAOA-uVNTR short allele as a high activity variant.
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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) | 0.002 | 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".