Author

Audrey Virginia Grant

McGill UniversityORCID 0000-0002-4197-0818Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:GWAS summary statistics· 2 Approach:statistical model· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1

Frequent Co-Authors

Goodarz KolifarhoodiD· 2 shared Luda B. DiatchenkoiD· 2 shared Marc ParisieniD· 2 shared Amandeep Kaur· 1 shared Benjamin J. KaufmaniD· 1 shared C.X. CheniD· 1 shared Carolina B. MelotoiD· 1 shared Chen Yiran· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Goodarz KolifarhoodORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Causal evidence linking chronic pain genetics to late-onset asthma via the nervous system

Goodarz Kolifarhood, Marc Parisien, Matt Fillingim, C.X. Chen, Chen Yiran, Nikolay Dimitrov, Maha Zidan, Loveni Hanumunthadu, Peter Hyunwuk Her, Sahir Bhatnagar, Luda B. Diatchenko, Audrey Virginia Grant

The paper identifies a causal link between chronic pain genetics and late-onset asthma through the nervous system using genome-wide association and Mendelian randomization analyses.

British Journal of Anaesthesia · Jan 17, 2026Peer-reviewedGenetic & Genomic Medicine

A MULTI-TRAIT APPROACH IMPROVES POLYGENIC RISK SCORES FOR CHRONIC BACK PAIN ACROSS POPULATION-BASED AND CLINICALLY ASCERTAINED SAMPLES

Rachael O. Osagie, Goodarz Kolifarhood, Marc Parisien, Amandeep Kaur, Hsuan Megan Tsao, Benjamin J. Kaufman, Justin Pelletier, Claude Bhérer, Audrey Virginia Grant, Carolina B. Meloto

This paper improves polygenic risk scores for chronic back pain by combining multiple traits, showing better performance in clinical samples.

medRxiv · Aug 27, 2025 · PreprintGenetic & Genomic Medicine

A graph-embedded topic model enables characterization of diverse pain phenotypes among UK Biobank individuals

Yuening Wang, Rodrigo Benavides, Luda B. Diatchenko, Audrey Virginia Grant, Yue Li

The paper introduces a graph-embedded topic model to analyze UK Biobank data, identifying pain phenotypes and revealing cardiovascular-related medication and condition patterns.

iScience · May 11, 2022Peer-reviewedBioinformatics