Association between the DAOA/G72 gene and bipolar disorder and meta-analyses in bipolar disorder and schizophrenia
Bibliographic record
Abstract
OBJECTIVE: The D-amino acid oxidase activator (DAOA, or G72) is involved in the oxidation of D-serine, an endogenous modulator of N-methyl-D-aspartate receptors and thus represents an important candidate in psychotic disorders. Several studies reported the DAOA/G72 gene to be associated with schizophrenia (SZ) and bipolar disorder (BD); however, the associated polymorphisms varied between SZ and BD. This study attempts to replicate the DAOA/G72 findings in BD and to conduct subgroup analyses based on the presence or absence of psychotic symptoms. METHODS: Five polymorphisms of the DAOA/G72 gene (rs1341402, rs1935062, rs2391191, rs947267, and rs778294) were analysed for association with BD in a family-based study design (303 core families including 916 individuals). We also conducted a meta-analysis of DAOA/G72 polymorphisms in BD and SZ. RESULTS: Marker rs1935062 was significantly associated with BD diagnosis in our sample (Z-score for C-allele= -2.33, p=0.02, uncorrected for genome-wide multiple comparisons). When we examined the subset of BD patients with psychotic symptoms (157 families), no significant results were obtained. Our meta-analysis yielded negative findings for DAOA/G72 markers in BD and positive findings for marker rs2391191 in SZ in East Asians. However, significant heterogeneity across studies limits interpretation. CONCLUSIONS: Our results provide evidence that suggests a possible role of the DAOA/G72 gene in BD and SZ. Marker rs1935062 may be specifically associated with BD, while marker rs2391191 may be associated with SZ but not with BD. Together with previous studies, these findings suggest that the DAOA/G72 gene confers susceptibility to both BD and SZ, but that different polymorphisms may potentially differentiate between these two disorders.
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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) | 0.001 | 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".