A genome-wide association study identifies novel loci of vertigo in an Asian population-based cohort
Bibliographic record
Abstract
The contributing genetic factors of vertigo remain poorly characterized, particularly in individuals of non-European ancestries. Here we show the genetic landscape of vertigo in an Asian population-based cohort. In a two-stage genome-wide association study (Ncase = 6199; Ncontrol = 54,587), we identify vertigo-associated genomic loci in DROSHA and ZNF91/LINC01224, with the latter replicating the findings in European ancestries. Gene-based association testing corroborates these findings. Interestingly, both genes are enriched in cerebellum, a key structure receiving sensory input from the vestibular system. Subjects carrying risk alleles from lead SNPs of DROSHA and ZNF91 incur a 1.74-fold risk of vertigo than those without. Moreover, composite clinical-polygenic risk scores allow differentiation between patients and controls, yielding an area under receiver operating characteristic curve of 0.69. This study identified novel genomic loci for vertigo in an Asian population-based cohort, which may help identifying high risk subjects and provide mechanistic insight in understanding the pathogenesis of vertigo. A genome-wide study in a Taiwanese population identifies the genomic landscape of vertigo, which demonstrates the inter-ethnic commonalities and diversities of genetic susceptibility to vertigo and provides novel mechanistic insights.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".