Genome-wide association meta-analysis of human olfactory identification discovers sex-specific and sex-differential genetic variants
Bibliographic record
Abstract
Abstract Smelling is a human sense, expressing strong sexual dimorphisms. We aim to improve the knowledge of the genetics of human olfactory perception by performing an exploratory genome-wide association meta-analysis of up to 21,495 individuals of European ancestry. By sex-stratified and overall analysis of the identification of twelve odours and an identification score, we discovered ten independent loci, seven of them novel, with trait-wise genome-wide significance (p < 5 × 10−8) involving five odours. Seven of these loci, including four novel ones, are also significant using a stricter study-wide significance threshold (p < 3.85 × 10− 9). Loci were predominantly located within clusters of olfactory receptors. Two loci were female-specific while one was sex-differential with respective candidate genes containing androgen response elements. Two-sample Mendelian randomization was applied to search for causal relationships between sex hormones, odour identification and neurodegenerative diseases. A causal negative effect was detected for Alzheimer’s disease on the identification score. These findings deepen our understanding of the genetic basis of olfactory perception and its interaction with sex, prioritizing mechanisms for further molecular research.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".