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Detection of distant relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT Syndrome

Rare genetic diseases are typically studied in referral populations, resulting in underdiagnosis and biased assessment of penetrance and phenotype. To address this, we developed a generalizable method of genotype inference based on distant relatedness and deployed this to identify undiagnosed Type 5...

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Autores principales: Lancaster, Megan C., Chen, Hung-Hsin, Shoemaker, M. Benjamin, Fleming, Matthew R., Baker, James T., Evans, Grahame, Polikowsky, Hannah G., Samuels, David C., Huff, Chad D., Roden, Dan M., Below, Jennifer E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543295/
https://www.ncbi.nlm.nih.gov/pubmed/37790303
http://dx.doi.org/10.21203/rs.3.rs-3314860/v1
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author Lancaster, Megan C.
Chen, Hung-Hsin
Shoemaker, M. Benjamin
Fleming, Matthew R.
Baker, James T.
Evans, Grahame
Polikowsky, Hannah G.
Samuels, David C.
Huff, Chad D.
Roden, Dan M.
Below, Jennifer E.
author_facet Lancaster, Megan C.
Chen, Hung-Hsin
Shoemaker, M. Benjamin
Fleming, Matthew R.
Baker, James T.
Evans, Grahame
Polikowsky, Hannah G.
Samuels, David C.
Huff, Chad D.
Roden, Dan M.
Below, Jennifer E.
author_sort Lancaster, Megan C.
collection PubMed
description Rare genetic diseases are typically studied in referral populations, resulting in underdiagnosis and biased assessment of penetrance and phenotype. To address this, we developed a generalizable method of genotype inference based on distant relatedness and deployed this to identify undiagnosed Type 5 Long QT Syndrome (LQT5) rare variant carriers in a non-referral population. We identified 9 LQT5 families referred to a single specialty clinic, each carrying p.Asp76Asn, the most common LQT5 variant. We uncovered recent common ancestry and a single shared haplotype among probands. Application to a non-referral population of 69,819 BioVU biobank subjects identified 22 additional subjects sharing this haplotype, subsequently confirmed to carry p.Asp76Asn. Referral and non-referral carriers had prolonged QTc compared to controls, and, among carriers, QTc polygenic score additively associated with QTc prolongation. Thus, our novel analysis of shared chromosomal segments identified undiagnosed cases of genetic disease and refined the understanding of LQT5 penetrance and phenotype.
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spelling pubmed-105432952023-10-03 Detection of distant relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT Syndrome Lancaster, Megan C. Chen, Hung-Hsin Shoemaker, M. Benjamin Fleming, Matthew R. Baker, James T. Evans, Grahame Polikowsky, Hannah G. Samuels, David C. Huff, Chad D. Roden, Dan M. Below, Jennifer E. Res Sq Article Rare genetic diseases are typically studied in referral populations, resulting in underdiagnosis and biased assessment of penetrance and phenotype. To address this, we developed a generalizable method of genotype inference based on distant relatedness and deployed this to identify undiagnosed Type 5 Long QT Syndrome (LQT5) rare variant carriers in a non-referral population. We identified 9 LQT5 families referred to a single specialty clinic, each carrying p.Asp76Asn, the most common LQT5 variant. We uncovered recent common ancestry and a single shared haplotype among probands. Application to a non-referral population of 69,819 BioVU biobank subjects identified 22 additional subjects sharing this haplotype, subsequently confirmed to carry p.Asp76Asn. Referral and non-referral carriers had prolonged QTc compared to controls, and, among carriers, QTc polygenic score additively associated with QTc prolongation. Thus, our novel analysis of shared chromosomal segments identified undiagnosed cases of genetic disease and refined the understanding of LQT5 penetrance and phenotype. American Journal Experts 2023-09-15 /pmc/articles/PMC10543295/ /pubmed/37790303 http://dx.doi.org/10.21203/rs.3.rs-3314860/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Lancaster, Megan C.
Chen, Hung-Hsin
Shoemaker, M. Benjamin
Fleming, Matthew R.
Baker, James T.
Evans, Grahame
Polikowsky, Hannah G.
Samuels, David C.
Huff, Chad D.
Roden, Dan M.
Below, Jennifer E.
Detection of distant relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT Syndrome
title Detection of distant relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT Syndrome
title_full Detection of distant relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT Syndrome
title_fullStr Detection of distant relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT Syndrome
title_full_unstemmed Detection of distant relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT Syndrome
title_short Detection of distant relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT Syndrome
title_sort detection of distant relatedness in biobanks for identification of undiagnosed carriers of a mendelian disease variant: application to long qt syndrome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543295/
https://www.ncbi.nlm.nih.gov/pubmed/37790303
http://dx.doi.org/10.21203/rs.3.rs-3314860/v1
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