Episode 89

July 28, 2025

00:20:28

️ 89: Decoding the Genetics of Smell: Sex-Specific Variants in Olfactory Identification

Hosted by

Gustavo B Barra
️ 89: Decoding the Genetics of Smell: Sex-Specific Variants in Olfactory Identification
Base by Base
️ 89: Decoding the Genetics of Smell: Sex-Specific Variants in Olfactory Identification

Jul 28 2025 | 00:20:28

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Show Notes

️ Episode 89: Decoding the Genetics of Smell: Sex-Specific Variants in Olfactory Identification

In this episode of PaperCast Base by Base, we explore how a genome-wide association meta-analysis of olfactory identification across 21,495 individuals reveals novel genetic loci underlying human smell perception.

Study Highlights:

Using the Sniffin’ Sticks screening test across four European cohorts totaling 21,495 individuals, the authors conducted a genome-wide association meta-analysis of twelve common odorant identifications and an overall identification score. The study discovered ten independent loci reaching genome-wide significance, seven of which were novel and included candidate genes within olfactory receptor clusters as well as GPCR signalling genes such as ADCY2. Sex-stratified analyses identified two female-specific loci and one locus with sex-differential effects implicating androgen response elements in candidate genes. Mendelian randomization analyses revealed a negative causal effect of Alzheimer’s disease risk on overall odor identification while finding no significant causal roles for sex hormones or olfactory performance on neurodegenerative outcomes.

Conclusion:

These discoveries refine our understanding of the genetic architecture of human olfaction and pave the way for targeted molecular investigations into sex-specific sensory mechanisms.

Reference:

Förster F, Emmert D, Horn K, Pott J, Frasnelli J, Imtiaz MA et al. Genome-wide association meta-analysis of human olfactory identification discovers sex-specific and sex-differential genetic variants. Nat Commun. 2025;16:5434. https://doi.org/10.1038/s41467-025-61330-y

License:

This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

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