Empirically determined baseline masking strategies and other considerations for gene-level burden tests

Rare-variant association studies typically perform gene-level tests in which coding variants are filtered (or 'masked') and aggregated based on functional annotation and allele frequency. Through a systematic literature review, we cataloged 664 masks used across 234 studies and found that masking strategies (that is, sets of masks) rarely repeat across studies and are rarely justified. To quantify their impact on association results, we applied all previously employed strategies to 54 traits within 189,947 UK Biobank exomes. Here we find that the number of significant associations greatly depends on the masking strategy (ranging from 58 to 2,523 associations), which is a key reason for the modest overlap (<30%) of associations between separate published analyses of this dataset. We empirically determine masking strategies with high discovery power for low-frequency and rare variant gene-level associations across numerous datasets and traits, and we use these to explore the impact of other factors on burden test results. These findings offer a baseline strategy in burden tests to increase study power and replicability, addressing one source of inconsistency in previous studies.

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Publication Details

Journal
Nature Genetics
Published
2026-05-08
DOI
https://doi.org/10.1038/s41588-026-02597-9
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

Empirically determined baseline masking strategies and other considerations for gene-level burden tests

Ryan Koesterer, Annie Moriondo, T M Nguyen, Patrick Smadbeck et al.
Nature Genetics
Genetic Associations and Epidemiology
article

Empirically determined baseline masking strategies and other considerations for gene-level burden tests

Ryan Koesterer, Annie Moriondo, T M Nguyen, Patrick Smadbeck, Peter Dornbos, Dongkeun Jang, Sean J. Jurgens, Poeya Haydarlou, Connie R. Bezzina, Oliver Ruebenacker, Quy Hoang, Jason Flannick, Satoshi Yoshiji, Alex Llamas, Noël P. Burtt, Patrick Ellinor
article en

Abstract

Rare-variant association studies typically perform gene-level tests in which coding variants are filtered (or 'masked') and aggregated based on functional annotation and allele frequency. Through a systematic literature review, we cataloged 664 masks used across 234 studies and found that masking strategies (that is, sets of masks) rarely repeat across studies and are rarely justified. To quantify their impact on association results, we applied all previously employed strategies to 54 traits within 189,947 UK Biobank exomes. Here we find that the number of significant associations greatly depends on the masking strategy (ranging from 58 to 2,523 associations), which is a key reason for the modest overlap (<30%) of associations between separate published analyses of this dataset. We empirically determine masking strategies with high discovery power for low-frequency and rare variant gene-level associations across numerous datasets and traits, and we use these to explore the impact of other factors on burden test results. These findings offer a baseline strategy in burden tests to increase study power and replicability, addressing one source of inconsistency in previous studies.

Nature Genetics
Broad Institute (US), Boston Children's Hospital (US), Harvard University (US), Regeneron (United States) (US), Kyoto University (JP), Jewish General Hospital (CA), Genome Canada (CA), Massachusetts General Hospital (US), McGill Genome Centre (CA), Amsterdam University Medical Centers (NL), McGill University (CA), University of Amsterdam (NL)
European Commission, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, National Institutes of Health, National Human Genome Research Institute, National Institute of Diabetes and Digestive and Kidney Diseases, HORIZON EUROPE European Innovation Council
Openalex Percentile: Top 6%
Genetic Associations and Epidemiology
DOIOpen Access PDFOpenAlex
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