Association study of neurotrophic tyrosine kinase receptor type 2 (NTRK2) and childhood‐onset mood disorders
Bibliographic record
Abstract
Childhood-onset mood disorders (COMD) are often familial, and twin studies of COMD provide compelling evidence that genetic factors are involved. Deficits in neural plasticity have been suggested to underlie the development of depression. The receptor tropomyosin related kinase B (TrkB) and its ligand, brain derived neurotrophic factor (BDNF), play essential roles in neural plasticity, and mRNA expression of both of these genes has been shown to be influenced by stress and chronic antidepressant treatment. In addition, TrkB knock-out mice display inappropriate stress coping mechanisms. Having previously shown that BDNF is associated with COMD, in this study we investigated the gene encoding TrkB, neurotrophic tyrosine kinase, receptor, type 2 (NTRK2) as a susceptibility factor in COMD. We tested for association of NTRK2 with COMD in two independent samples: (a) a case-control sample matched on ethnicity and gender, consisting of 120 cases who met DSM III/IV criteria for major depressive or dysthymic disorder before age 14 or bipolar I/II before the age of 18, and controls, and (b) a family based control sample of 113 families collected in Hungary, identified by a proband between the age of 7 and 14 who met DSM IV criteria for major depressive disorder or bipolar I/II disorder. There was no evidence for an allelic or genotypic association of three polymorphisms of NTRK2 with COMD in the case-control sample. Also, in the family based sample, using the transmission disequilibrium test (TDT), we did not identify any evidence of allelic association for each marker individually or when haplotypes were analyzed. Based on these results, using these three polymorphisms, we do not find support for NTRK2 as a susceptibility gene for COMD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".