Lack of association between the norepinephrine transporter gene and major depression in a Han Chinese population
Bibliographic record
Abstract
OBJECTIVE: Although the physiological mechanisms contributing to the development of major depression remain unclear, several lines of evidence suggest that the catecholaminergic system involving the norepinephrine transporter (NET) is implicated in the etiology of major depression. This study aims to determine whether major depression is associated with the NET gene in a Han Chinese population. METHODS: We analyzed the NET promoter T-182C polymorphism and another silent polymorphism G1287A in exon 9 of the NET gene with a polymerase chain reaction (PCR)-based method in 216 patients with major depression and 210 unrelated, age-and sex-matched healthy control subjects. We interviewed all subjects with the Chinese Version of the Modified Schedule of Affective Disorders and Schizophrenia-Lifetime; major depressive disorder was diagnosed according to DSM-IV criteria. In addition, to reduce the clinical heterogeneity, we performed a subtype analysis with clinically important variables, such as family history of major affective disorder and age at onset of major depression. RESULTS: No significant difference was observed between the patients and healthy control subjects in the genotype distributions and allele frequencies for the investigated NET polymorphisms. Similarly, no significant differences were found between more homogeneous subgroups of patients and normal control subjects. CONCLUSIONS: This study suggests that the investigated polymorphisms in the NET gene are not major risk factors in increasing susceptibility to either major depression or its clinical subtypes in a Han Chinese population. However, larger replication studies with different ethnic samples are needed.
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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 | 0.001 | 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 | 0.000 |
| 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".