Meta-analysis of genome-wide association studies for panic disorder in the Japanese population
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Panic disorder (PD) is a moderately heritable anxiety disorder whose pathogenesis is not well understood. Due to the lack of power in previous association studies, genes that are truly associated with PD might not be detected. In this study, we conducted a genome-wide association study (GWAS) in two independent data sets using the Affymetrix Mapping 500K Array or Genome-Wide Human SNP Array 6.0. We obtained imputed genotypes for each GWAS and performed a meta-analysis of two GWAS data sets (718 cases and 1717 controls). For follow-up, 12 single-nucleotide polymorphisms (SNPs) were tested in 329 cases and 861 controls. Gene ontology enrichment and candidate gene analyses were conducted using the GWAS or meta-analysis results. We also applied the polygenic score analysis to our two GWAS samples to test the hypothesis of polygenic components contributing to PD. Although genome-wide significant SNPs were not detected in either of the GWAS nor the meta-analysis, suggestive associations were observed in several loci such as BDKRB2 (P=1.3 × 10(-5), odds ratio=1.31). Among previous candidate genes, supportive evidence for association of NPY5R with PD was obtained (gene-wise corrected P=6.4 × 10(-4)). Polygenic scores calculated from weakly associated SNPs (P<0.3 and 0.4) in the discovery sample were significantly associated with PD status in the target sample in both directions (sample I to sample II and vice versa) (P<0.05). Our findings suggest that large sets of common variants of small effects collectively account for risk of PD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 it