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Get Free AccessThe detection of founder pathogenic variants, those observed in high frequency only in a group of individuals with increased inter-relatedness, can help improve delivery of health care for that community. We identified 16 groups with shared ancestry, based on genomic segments that are shared through identity by descent (IBD), in New York City using the genomic data of 25,366 residents from the All Of Us Research Program and the Mount Sinai Bio Me biobank. From these groups we defined 7 as founder populations, mostly communities currently under-represented in medical genomics research, such as Puerto Rican and Garifuna. The enrichment analysis of ClinVar pathogenic or likely pathogenic (P/LP) variants in each group identified 201 of these damaging variants across the seven founder populations. We confirmed disease-causing variants previously reported to occur at increased frequencies in Ashkenazi Jewish and Puerto Rican genetic ancestry groups, but most of the damaging variants identified have not been previously associated with any such founder populations, and most of these founder populations have not been described to have increased prevalence of the associated rare disease. Twenty-two of 47 variants meeting Tier 2 prenatal screening criteria (1/100 carrier frequency within these founder groups) have never previously been reported. We show how population structure studies can provide insights into rare diseases disproportionately affecting under-represented founder populations, delivering a health care benefit but also a potential source of stigmatization of these communities, who should be part of the decision-making about implementation into health care delivery.
Mariko Isshiki, Anthony Griffen, Paul Meissner, Paulette Spencer, Michael D. Cabana, Susan Klugman, M. Nocito Colón, Zoya Maksumova, Shakira Suglia, Carmen R. Isasi, John M. Greally, Srilakshmi M. Raj (2025). Genetic disease risks of under-represented founder populations in New York City. , 21(6), DOI: https://doi.org/10.1371/journal.pgen.1011755.
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Type
Article
Year
2025
Authors
12
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1371/journal.pgen.1011755
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