Evidence that COMT genotype and proline interact on negative-symptom outcomes in schizophrenia and bipolar disorder
Bibliographic record
Abstract
Elevated peripheral proline is associated with psychiatric disorders, and there is evidence that proline is a neuromodulator. The proline dehydrogenase (PRODH) gene, which encodes the enzyme that catalyzes proline catabolism, maps to human chromosome 22q11.2, a region conferring risk of schizophrenia. In the Prodh-null mouse, an interaction between elevated peripheral proline and another 22q11.2 gene, catechol-O-methyltransferase (COMT), on neurotransmission and behavior has been reported. We explored the relationship between fasting plasma proline levels and COMT Val(158)Met genotype on symptoms (positive, negative and total) in schizophrenia patients. In an exploratory study we also examined symptom change in patients with bipolar disorder. There was a significant interaction between peripheral proline and COMT on negative symptoms in schizophrenia (P<0.0001, n=95). In COMT Val/Val patients, high proline was associated with low Scale for the Assessment of Negative Symptom (SANS) scores. In contrast, high proline was associated with high SANS scores in patients carrying a Met allele. The relationship between proline and COMT also appears to modify negative symptoms across psychiatric illness. In bipolar disorder, a significant interaction was also observed on negative-symptom change (P=0.007, n=43). Negative symptoms are intractable and largely unaddressed by current medications. These data indicate a significant interaction between peripheral proline and COMT genotype, influencing negative symptoms in schizophrenia and bipolar disorder. That high proline has converse effects on symptoms by COMT genotype, may have implications for therapeutic decisions.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".