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Analysis of Brugada syndrome loci reveals that fine-mapping clustered GWAS hits enhances the annotation of disease-relevant variants
Genome-wide association studies (GWASs) are instrumental in identifying loci harboring common single-nucleotide variants (SNVs) that affect human traits and diseases. GWAS hits emerge in clusters, but the focus is often on the most significant hit in each trait- or disease-associated locus. The rema...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080235/ https://www.ncbi.nlm.nih.gov/pubmed/33948580 http://dx.doi.org/10.1016/j.xcrm.2021.100250 |
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author | Pinsach-Abuin, Mel·lina del Olmo, Bernat Pérez-Agustin, Adrian Mates, Jesus Allegue, Catarina Iglesias, Anna Ma, Qi Merkurjev, Daria Konovalov, Sergiy Zhang, Jing Sheikh, Farah Telenti, Amalio Brugada, Josep Brugada, Ramon Gymrek, Melissa di Iulio, Julia Garcia-Bassets, Ivan Pagans, Sara |
author_facet | Pinsach-Abuin, Mel·lina del Olmo, Bernat Pérez-Agustin, Adrian Mates, Jesus Allegue, Catarina Iglesias, Anna Ma, Qi Merkurjev, Daria Konovalov, Sergiy Zhang, Jing Sheikh, Farah Telenti, Amalio Brugada, Josep Brugada, Ramon Gymrek, Melissa di Iulio, Julia Garcia-Bassets, Ivan Pagans, Sara |
author_sort | Pinsach-Abuin, Mel·lina |
collection | PubMed |
description | Genome-wide association studies (GWASs) are instrumental in identifying loci harboring common single-nucleotide variants (SNVs) that affect human traits and diseases. GWAS hits emerge in clusters, but the focus is often on the most significant hit in each trait- or disease-associated locus. The remaining hits represent SNVs in linkage disequilibrium (LD) and are considered redundant and thus frequently marginally reported or exploited. Here, we interrogate the value of integrating the full set of GWAS hits in a locus repeatedly associated with cardiac conduction traits and arrhythmia, SCN5A-SCN10A. Our analysis reveals 5 common 7-SNV haplotypes (Hap1–5) with 2 combinations associated with life-threatening arrhythmia—Brugada syndrome (the risk Hap(1/1) and protective Hap(2/3) genotypes). Hap1 and Hap2 share 3 SNVs; thus, this analysis suggests that assuming redundancy among clustered GWAS hits can lead to confounding disease-risk associations and supports the need to deconstruct GWAS data in the context of haplotype composition. |
format | Online Article Text |
id | pubmed-8080235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-80802352021-05-03 Analysis of Brugada syndrome loci reveals that fine-mapping clustered GWAS hits enhances the annotation of disease-relevant variants Pinsach-Abuin, Mel·lina del Olmo, Bernat Pérez-Agustin, Adrian Mates, Jesus Allegue, Catarina Iglesias, Anna Ma, Qi Merkurjev, Daria Konovalov, Sergiy Zhang, Jing Sheikh, Farah Telenti, Amalio Brugada, Josep Brugada, Ramon Gymrek, Melissa di Iulio, Julia Garcia-Bassets, Ivan Pagans, Sara Cell Rep Med Article Genome-wide association studies (GWASs) are instrumental in identifying loci harboring common single-nucleotide variants (SNVs) that affect human traits and diseases. GWAS hits emerge in clusters, but the focus is often on the most significant hit in each trait- or disease-associated locus. The remaining hits represent SNVs in linkage disequilibrium (LD) and are considered redundant and thus frequently marginally reported or exploited. Here, we interrogate the value of integrating the full set of GWAS hits in a locus repeatedly associated with cardiac conduction traits and arrhythmia, SCN5A-SCN10A. Our analysis reveals 5 common 7-SNV haplotypes (Hap1–5) with 2 combinations associated with life-threatening arrhythmia—Brugada syndrome (the risk Hap(1/1) and protective Hap(2/3) genotypes). Hap1 and Hap2 share 3 SNVs; thus, this analysis suggests that assuming redundancy among clustered GWAS hits can lead to confounding disease-risk associations and supports the need to deconstruct GWAS data in the context of haplotype composition. Elsevier 2021-04-20 /pmc/articles/PMC8080235/ /pubmed/33948580 http://dx.doi.org/10.1016/j.xcrm.2021.100250 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pinsach-Abuin, Mel·lina del Olmo, Bernat Pérez-Agustin, Adrian Mates, Jesus Allegue, Catarina Iglesias, Anna Ma, Qi Merkurjev, Daria Konovalov, Sergiy Zhang, Jing Sheikh, Farah Telenti, Amalio Brugada, Josep Brugada, Ramon Gymrek, Melissa di Iulio, Julia Garcia-Bassets, Ivan Pagans, Sara Analysis of Brugada syndrome loci reveals that fine-mapping clustered GWAS hits enhances the annotation of disease-relevant variants |
title | Analysis of Brugada syndrome loci reveals that fine-mapping clustered GWAS hits enhances the annotation of disease-relevant variants |
title_full | Analysis of Brugada syndrome loci reveals that fine-mapping clustered GWAS hits enhances the annotation of disease-relevant variants |
title_fullStr | Analysis of Brugada syndrome loci reveals that fine-mapping clustered GWAS hits enhances the annotation of disease-relevant variants |
title_full_unstemmed | Analysis of Brugada syndrome loci reveals that fine-mapping clustered GWAS hits enhances the annotation of disease-relevant variants |
title_short | Analysis of Brugada syndrome loci reveals that fine-mapping clustered GWAS hits enhances the annotation of disease-relevant variants |
title_sort | analysis of brugada syndrome loci reveals that fine-mapping clustered gwas hits enhances the annotation of disease-relevant variants |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080235/ https://www.ncbi.nlm.nih.gov/pubmed/33948580 http://dx.doi.org/10.1016/j.xcrm.2021.100250 |
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