Author

Matteo Di Scipio

Population Health Research InstituteORCID 0000-0001-6280-3739Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 2

Signature Assays, Organisms & Methods

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Assay:GWAS summary statistics· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:GWAS / association mapping· 1 Research Focus:polygenic risk· 1

Frequent Co-Authors

Guillaume ParéiD· 2 shared Alice ManiD· 1 shared Ann Le· 1 shared Conor S. JudgeiD· 1 shared Jeremy PetchiD· 1 shared Jianhan WuiD· 1 shared Michael ChongiD· 1 shared Mohammad Daud KhaniD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Guillaume ParéORCID

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2 papers

Recent·Most cited

Genetic & Genomic MedicinemedRxivPreprintApr 20, 2026

Biobank-scale survey of gene-diet interactions informs precision nutrition polygenic scores

Matteo Di Scipio, Alice Man, Ricky Lali…·G P Pare

The paper assesses gene-diet interactions in UK Biobank data to derive polygenic scores that associate with cardiometabolic outcomes and clinical conditions like gout.

DOI 10.64898/2026.04.13.26350340

humanGWAS summary statistics

𝕏 PostBluesky

Genetic & Genomic MedicinemedRxivPreprintApr 24, 2021

A versatile, fast and unbiased method for estimation of gene-by-environment interaction effects on biobank-scale datasets

Mohammad Daud Khan, Matteo Di Scipio, Conor S. Judge…·Guillaume Paré

This paper introduces MonsterLM, a method for estimating gene-by-environment interactions on large datasets, finding significant interaction variance and improved polygenic score prediction.

DOI 10.1101/2021.04.24.21255884

humanGWAS summary statistics

𝕏 PostBluesky