No significant association between SNPs in the <i>CLOCK</i> and <i>ADH4</i> genes and susceptibility to cluster headaches: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: The circadian locomotor output cycles kaput (CLOCK) gene and the alcohol dehydrogenase 4 (ADH4) gene are promising candidates for susceptibility to cluster headaches (CH). Associations of the three single nucleotide polymorphisms (SNPs)-CLOCK SNP rs1801260 and ADH4 SNPs rs1800759, and rs1126671-with CH were studied previously, but the results were inconsistent. METHODS: Associations between the three SNPs (rs1801260, rs1126671, and rs1800759) and CH risk were separately assessed by pooled odds ratios (ORs) along with 95% confidence intervals (95% CIs) based on five different genetic models. Methodological quality was assessed using the Newcastle-Ottawa Quality Assessment Scale (NOS). All statistical analyses were carried out with RevMan 5.3 software. RESULTS: Eight studies involving 1437 CH patients and 2541 healthy controls were selected for quantitative synthesis, from five studies on CLOCK rs1801260, five on ADH4 rs1800759, and three on ADH4 rs1126671. Our pooled data did not support associations between the three SNPs (rs1801260 in the CLOCK gene, rs1800759 and rs1126671 in the ADH4 gene) and susceptibility to CH (rs1801260: OR 1.10, 95% CI: 0.95-1.28; p = 0.19; rs1800759: OR 1.06, 95% CI: 0.93-1.22; p = 0.37; and rs1126671: OR 1.09, 95% CI: 0.92-1.28; p = 0.32). CONCLUSION: We found no significant associations between the three SNPs (rs1801260 in the CLOCK gene and rs1800759 and rs1126671 in the ADH4 gene) and the susceptibility to CH across both Caucasian and Asian ethnicities in our meta-analysis.
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.029 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".