Association Study between Norepinephrine Transporter Gene Polymorphism and Schizophrenia in a Korean Population
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Bibliographic record
Abstract
OBJECTIVE: We aimed to investigate possible associations between three norepinephrine transporter gene (SLC6A2) single nucleotide polymorphisms (T182C, A3081T, and G1287A) and schizophrenia. Also, we investigated the relationships of those polymorphisms with clinical severity and characteristics of schizophrenia. METHODS: Participants were 220 schizophrenia patients in the acute phase and 167 healthy controls. The genotype, allele frequency, and haplotype of each group were analyzed for T182C, A3081T, and G1287A polymorphisms. Of the 220 schizophrenia patients, 163 patients were evaluated with the Positive and Negative Syndrome Scale (PANSS) and the Korean version of the Calgary depression scale for schizophrenia (K-CDSS) at baseline. RESULTS: We found no significant differences between the schizophrenia patient group and the control group in genotype distribution or allele frequency of the three tested polymorphisms. Likewise, we could not find any significant differences in genotype or allele frequency by analyzing according to gender. In the haplotype study, no significant association emerged between specific haplotype combinations and schizophrenia. We also found no association between clinical scales (PANSS and K-CDSS) and the studied polymorphisms. CONCLUSION: Our results suggest that the investigated polymorphisms of the NET gene are not associated with susceptibility to schizophrenia or its clinical features in a Korean population. However, this study remains significant because it is the first haplotype study to investigate associations between NET gene (SLC6A2) single nucleotide polymorphisms and schizophrenia in a Korean population. Future research with a larger sample size and more genetic markers is needed to replicate our results.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it