Question · asked by 1 review
rs10974056 effect allele A (intron variant in GLIS3, chr9:3,889,264) vs Non-effect allele C: Dental caries
- Population
- Adults from Japanese and European cohorts (present-study Japanese direct-to-consumer cohort + GLIDE consortium and UK Biobank European cohorts); self-reported dental caries cases vs controls
- Intervention
- rs10974056 effect allele A (intron variant in GLIS3, chr9:3,889,264)
- Comparison
- Non-effect allele C
- Outcome
- Dental caries
Meta-analysis identified a novel genome-wide-significant locus for dental caries at rs10974056 in GLIS3 (P=3.93E-08); ungraded.
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
rs10974056 effect allele A (intron variant in GLIS3, chr9:3,889,264) vs Non-effect allele C Dental caries (meta of mixed phenotypes: present-study self-report + GLIDE clinical DMFS + UKB self-report/dentures) · Adults from Japanese and European cohorts (present-study Japanese direct-to-consumer cohort + GLIDE consortium and UK… · Lifelong (germline genotype), Population-based genetic association study (Japanese direct-to-consumer cohort + European GLIDE/UKB cohorts), Meta-analysis: present study + GLIDE + UKB Meta-analysis identified a novel genome-wide-significant locus for dental caries at rs10974056 in GLIS3 (P=3.93E-08); ungraded. Genome-wide association meta-analysis identifies two novel loci associated with dental caries. (2024) All outcomes | Z-score (meta) -5.494 | 3 studies · 533348 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Genome-wide association meta-analysis identifies two novel loci associated with dental caries. 2024 All outcomes | Not applicable (primary GWAS with meta-analysis of one previously published GWAS; no systematic literature search) | 1 | Not applicable |
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.