Epistatic and Functional Interactions of Catechol-O-Methyltransferase (COMT) and AKT1 on Neuregulin1-ErbB Signaling in Cell Models
Bibliographic record
Abstract
BACKGROUND: Neuregulin1 (NRG1)-ErbB signaling has been implicated in the pathogenesis of cancer and schizophrenia. We have previously reported that NRG1-stimulated migration of B lymphoblasts is PI3K-AKT1dependent and impaired in patients with schizophrenia and significantly linked to the catechol-o-methyltransferase (COMT) Val108/158Met functional polymorphism. METHODOLOGY/PRINCIPAL FINDINGS: We have now examined AKT1 activation in NRG1-stimulated B lymphoblasts and other cell models and explored a functional relationship between COMT and AKT1. NRG1-induced AKT1 phosphorylation was significantly diminished in Val carriers compared to Met carriers in both normal subjects and in patients. Further, there was a significant epistatic interaction between a putatively functional coding SNP in AKT1 (rs1130233) and COMT Val108/158Met genotype on AKT1 phosphorylation. NRG1 induced translocation of AKT1 to the plasma membrane also was impaired in Val carriers, while PIP(3) levels were not decreased. Interestingly, the level of COMT enzyme activity was inversely correlated with the cells' ability to synthesize phosphatidylserine (PS), a factor that attracts the pleckstrin homology domain (PHD) of AKT1 to the cell membrane. Transfection of SH-SY5Y cells with a COMT Val construct increased COMT activity and significantly decreased PS levels as well as NRG1-induced AKT1 phosphorylation and migration. Administration of S-adenosylmethionine (SAM) rescued all of these deficits. These data suggest that AKT1 function is influenced by COMT enzyme activity through competition with PS synthesis for SAM, which in turn dictates AKT1-dependent cellular responses to NRG1-mediated signaling. CONCLUSION/SIGNIFICANCE: Our findings implicate genetic and functional interactions between COMT and AKT1 and may provide novel insights into pathogenesis of schizophrenia and other ErbB-associated human diseases such as cancer.
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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 | 0.001 |
| 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".