Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
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
_version_ 1783685388864323584
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
work_keys_str_mv AT pinsachabuinmellina analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT delolmobernat analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT perezagustinadrian analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT matesjesus analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT alleguecatarina analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT iglesiasanna analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT maqi analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT merkurjevdaria analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT konovalovsergiy analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT zhangjing analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT sheikhfarah analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT telentiamalio analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT brugadajosep analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT brugadaramon analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT gymrekmelissa analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT diiuliojulia analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT garciabassetsivan analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants
AT paganssara analysisofbrugadasyndromelocirevealsthatfinemappingclusteredgwashitsenhancestheannotationofdiseaserelevantvariants