Genome-wide association analyses identify new Brugada syndrome risk loci and highlight a new mechanism of sodium channel regulation in disease susceptibility.
Journal
Nature genetics
ISSN: 1546-1718
Titre abrégé: Nat Genet
Pays: United States
ID NLM: 9216904
Informations de publication
Date de publication:
03 2022
03 2022
Historique:
received:
25
09
2020
accepted:
13
12
2021
pubmed:
26
2
2022
medline:
28
4
2022
entrez:
25
2
2022
Statut:
ppublish
Résumé
Brugada syndrome (BrS) is a cardiac arrhythmia disorder associated with sudden death in young adults. With the exception of SCN5A, encoding the cardiac sodium channel Na
Identifiants
pubmed: 35210625
doi: 10.1038/s41588-021-01007-6
pii: 10.1038/s41588-021-01007-6
pmc: PMC9376964
mid: NIHMS1817393
doi:
Substances chimiques
MAPRE2 protein, human
0
Microtubule-Associated Proteins
0
NAV1.5 Voltage-Gated Sodium Channel
0
Types de publication
Journal Article
Meta-Analysis
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
232-239Subventions
Organisme : NHLBI NIH HHS
ID : R01 HL047678
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL139731
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL092577
Pays : United States
Organisme : NHGRI NIH HHS
ID : T32 HG010464
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL134328
Pays : United States
Organisme : NIGMS NIH HHS
ID : P50 GM115305
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL152201
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL149826
Pays : United States
Organisme : NHLBI NIH HHS
ID : K24 HL105780
Pays : United States
Organisme : NHLBI NIH HHS
ID : K23 HL127704
Pays : United States
Organisme : Wellcome Trust
ID : 076113
Pays : United Kingdom
Organisme : NHLBI NIH HHS
ID : R56 HL138103
Pays : United States
Organisme : British Heart Foundation
ID : FS/11/71/28918
Pays : United Kingdom
Organisme : NHLBI NIH HHS
ID : R01 HL128914
Pays : United States
Organisme : Wellcome Trust
ID : 085475
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 090355
Pays : United Kingdom
Investigateurs
Konstantin Strauch
(K)
Annette Peters
(A)
Holger Schulz
(H)
Lars Schwettmann
(L)
Reiner Leidl
(R)
Margit Heier
(M)
Pascal Defaye
(P)
Frédéric Anselme
(F)
Jean Philippe Darmon
(JP)
François Wiart
(F)
Commentaires et corrections
Type : ErratumIn
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.
Références
Brugada, P. & Brugada, J. Right bundle branch block, persistent ST segment elevation and sudden cardiac death: a distinct clinical and electrocardiographic syndrome. A multicenter report. J. Am. Coll. Cardiol. 20, 1391–1396 (1992).
pubmed: 1309182
doi: 10.1016/0735-1097(92)90253-J
Priori, S. G. et al. 2015 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: The Task Force for the Management of Patients with Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death of the European Society of Cardiology (ESC). Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC). Eur. Heart J. 36, 2793–2867 (2015).
pubmed: 26320108
doi: 10.1093/eurheartj/ehv316
Chen, Q. et al. Genetic basis and molecular mechanism for idiopathic ventricular fibrillation. Nature 392, 293–296 (1998).
pubmed: 9521325
doi: 10.1038/32675
Le Scouarnec, S. et al. Testing the burden of rare variation in arrhythmia-susceptibility genes provides new insights into molecular diagnosis for Brugada syndrome. Hum. Mol. Genet. 24, 2757–2763 (2015).
pubmed: 25650408
doi: 10.1093/hmg/ddv036
Bezzina, C. R. et al. Common variants at SCN5A-SCN10A and HEY2 are associated with Brugada syndrome, a rare disease with high risk of sudden cardiac death. Nat. Genet. 45, 1044–1049 (2013).
pubmed: 23872634
pmcid: 3869788
doi: 10.1038/ng.2712
Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
pubmed: 25642630
pmcid: 4495769
doi: 10.1038/ng.3211
Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565–569 (2010).
pubmed: 20562875
pmcid: 3232052
doi: 10.1038/ng.608
Mizusawa, Y. & Wilde, A. A. M. Brugada syndrome. Circ. Arrhythm. Electrophysiol. 5, 606–616 (2012).
pubmed: 22715240
doi: 10.1161/CIRCEP.111.964577
van den Boogaard, M. et al. A common genetic variant within SCN10A modulates cardiac SCN5A expression. J. Clin. Invest. 124, 1844–1852 (2014).
pubmed: 24642470
pmcid: 3973109
doi: 10.1172/JCI73140
van Eif, V. W. W., Devalla, H. D., Boink, G. J. J. & Christoffels, V. M. Transcriptional regulation of the cardiac conduction system. Nat. Rev. Cardiol. 15, 617–630 (2018).
pubmed: 29875439
doi: 10.1038/s41569-018-0031-y
Gaborit, N. et al. Cooperative and antagonistic roles for Irx3 and Irx5 in cardiac morphogenesis and postnatal physiology. Development 139, 4007–4019 (2012).
pubmed: 22992950
pmcid: 3472592
doi: 10.1242/dev.081703
Shen, T. et al. Tbx20 regulates a genetic program essential to adult mouse cardiomyocyte function. J. Clin. Invest. 121, 4640–4654 (2011).
pubmed: 22080862
pmcid: 3223071
doi: 10.1172/JCI59472
Veerman, C. C. et al. The Brugada syndrome susceptibility gene HEY2 modulates cardiac transmural ion channel patterning and electrical heterogeneity. Circ. Res. 121, 537–548 (2017).
pubmed: 28637782
doi: 10.1161/CIRCRESAHA.117.310959
Tarradas, A. et al. Transcriptional regulation of the sodium channel gene (SCN5A) by GATA4 in human heart. J. Mol. Cell. Cardiol. 102, 74–82 (2017).
pubmed: 27894866
doi: 10.1016/j.yjmcc.2016.10.013
Arnolds, D. E. et al. TBX5 drives Scn5a expression to regulate cardiac conduction system function. J. Clin. Invest. 122, 2509–2518 (2012).
pubmed: 22728936
pmcid: 3386825
doi: 10.1172/JCI62617
Braz, J. C. et al. PKC-alpha regulates cardiac contractility and propensity toward heart failure. Nat. Med. 10, 248–254 (2004).
pubmed: 14966518
doi: 10.1038/nm1000
Goldspink, D. A. et al. The microtubule end-binding protein EB2 is a central regulator of microtubule reorganisation in apico-basal epithelial differentiation. J. Cell. Sci. 126, 4000–4014 (2013).
pubmed: 23813963
Ajima, R. et al. Deficiency of Myo18B in mice results in embryonic lethality with cardiac myofibrillar aberrations. Genes Cells 13, 987–999 (2008).
pubmed: 18761673
doi: 10.1111/j.1365-2443.2008.01226.x
Gusev, A. et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat. Genet. 48, 245–252 (2016).
pubmed: 26854917
pmcid: 4767558
doi: 10.1038/ng.3506
GTEx Consortium et al.Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).
pmcid: 5776756
doi: 10.1038/nature24277
de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015).
pubmed: 25885710
pmcid: 4401657
doi: 10.1371/journal.pcbi.1004219
Finucane, H. K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat. Genet. 50, 621–629 (2018).
pubmed: 29632380
pmcid: 5896795
doi: 10.1038/s41588-018-0081-4
Iotchkova, V. et al. GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals. Nat. Genet. 51, 343–353 (2019).
pubmed: 30692680
pmcid: 6908448
doi: 10.1038/s41588-018-0322-6
Gu, C. et al. The microtubule plus-end tracking protein EB1 is required for Kv1 voltage-gated K
pubmed: 17145502
doi: 10.1016/j.neuron.2006.10.022
Wilde, A. A. M. et al. The pathophysiological mechanism underlying Brugada syndrome: depolarization versus repolarization. J. Mol. Cell. Cardiol. 49, 543–553 (2010).
pubmed: 20659475
pmcid: 2932806
doi: 10.1016/j.yjmcc.2010.07.012
Talmud, P. J. et al. Use of low-density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case-control study. Lancet 381, 1293–1301 (2013).
pubmed: 23433573
doi: 10.1016/S0140-6736(12)62127-8
Lahrouchi, N. et al. Transethnic genome-wide association study provides insights in the genetic architecture and heritability of long QT syndrome. Circulation 142, 324–338 (2020).
pubmed: 32429735
pmcid: 7382531
doi: 10.1161/CIRCULATIONAHA.120.045956
Sotoodehnia, N. et al. Common variants in 22 loci are associated with QRS duration and cardiac ventricular conduction. Nat. Genet. 42, 1068–1076 (2010).
pubmed: 21076409
pmcid: 3338195
doi: 10.1038/ng.716
van Setten, J. et al. PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity. Nat. Commun. 9, 2904 (2018).
pubmed: 30046033
pmcid: 6060178
doi: 10.1038/s41467-018-04766-9
Arking, D. E. et al. Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization. Nat. Genet. 46, 826–836 (2014).
pubmed: 24952745
pmcid: 4124521
doi: 10.1038/ng.3014
Roselli, C. et al. Multi-ethnic genome-wide association study for atrial fibrillation. Nat. Genet. 50, 1225–1233 (2018).
pubmed: 29892015
pmcid: 6136836
doi: 10.1038/s41588-018-0133-9
Nielsen, J. B. et al. Biobank-driven genomic discovery yields new insight into atrial fibrillation biology. Nat. Genet. 50, 1234–1239 (2018).
pubmed: 30061737
pmcid: 6530775
doi: 10.1038/s41588-018-0171-3
Rivaud, M. R. et al. A common co-morbidity modulates disease expression and treatment efficacy in inherited cardiac sodium channelopathy. Eur. Heart J. 39, 2898–2907 (2018).
pubmed: 29718149
doi: 10.1093/eurheartj/ehy247
Priori, S. G. et al. Executive summary: HRS/EHRA/APHRS expert consensus statement on the diagnosis and management of patients with inherited primary arrhythmia syndromes. Europace 15, 1389–1406 (2013).
pubmed: 23994779
doi: 10.1093/europace/eut272
Al-Khatib, S. M. et al. 2017 AHA/ACC/HRS guideline for management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. Circulation 138, e210–e271 (2018).
pubmed: 29084733
Richards, S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 17, 405–423 (2015).
pubmed: 25741868
pmcid: 4544753
doi: 10.1038/gim.2015.30
Whiffin, N. et al. CardioClassifier: disease- and gene-specific computational decision support for clinical genome interpretation. Genet. Med. 20, 1246–1254 (2018).
pubmed: 29369293
pmcid: 6558251
doi: 10.1038/gim.2017.258
Kapplinger, J. D. et al. An international compendium of mutations in the SCN5A-encoded cardiac sodium channel in patients referred for Brugada syndrome genetic testing. Heart Rhythm 7, 33–46 (2010).
pubmed: 20129283
doi: 10.1016/j.hrthm.2009.09.069
Walsh, R., Peters, N. S., Cook, S. A. & Ware, J. S. Paralogue annotation identifies novel pathogenic variants in patients with Brugada syndrome and catecholaminergic polymorphic ventricular tachycardia. J. Med. Genet. 51, 35–44 (2014).
pubmed: 24136861
doi: 10.1136/jmedgenet-2013-101917
Denham, N. C. et al. Systematic re-evaluation of SCN5A variants associated with Brugada syndrome. J. Cardiovasc. Electrophysiol. 30, 118–127 (2019).
pubmed: 30203441
doi: 10.1111/jce.13740
Walsh, R. et al. Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of HCM. Genome Med. 11, 5 (2019).
pubmed: 30696458
pmcid: 6350371
doi: 10.1186/s13073-019-0616-z
Das, S. et al. Next-generation genotype imputation service and methods. Nat. Genet. 48, 1284–1287 (2016).
pubmed: 27571263
pmcid: 5157836
doi: 10.1038/ng.3656
Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565–569 (2010).
pubmed: 20562875
pmcid: 3232052
doi: 10.1038/ng.608
Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).
pubmed: 21167468
pmcid: 3014363
doi: 10.1016/j.ajhg.2010.11.011
Lee, S. H., Wray, N. R., Goddard, M. E. & Visscher, P. M. Estimating missing heritability for disease from genome-wide association studies. Am. J. Hum. Genet. 88, 294–305 (2011).
pubmed: 21376301
pmcid: 3059431
doi: 10.1016/j.ajhg.2011.02.002
Vutthikraivit, W. et al. Worldwide prevalence of Brugada syndrome: a systematic review and meta-analysis. Acta Cardiol. Sin. 34, 267–277 (2018).
pubmed: 29844648
pmcid: 5968343
Machiela, M. J. & Chanock, S. J. LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinformatics 31, 3555–3557 (2015).
pubmed: 26139635
pmcid: 4626747
doi: 10.1093/bioinformatics/btv402
Hormozdiari, F. et al. Colocalization of GWAS and eQTL signals detects target genes. Am. J. Hum. Genet. 99, 1245–1260 (2016).
pubmed: 27866706
pmcid: 5142122
doi: 10.1016/j.ajhg.2016.10.003
Watanabe, K., Taskesen, E., van Bochoven, A. & Posthuma, D. Functional mapping and annotation of genetic associations with FUMA. Nat. Commun. 8, 1826 (2017).
pubmed: 29184056
pmcid: 5705698
doi: 10.1038/s41467-017-01261-5
Schmitt, A. D. et al. A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell Rep. 17, 2042–2059 (2016).
pubmed: 27851967
pmcid: 5478386
doi: 10.1016/j.celrep.2016.10.061
Pers, T. H., Timshel, P. & Hirschhorn, J. N. SNPsnap: a Web-based tool for identification and annotation of matched SNPs. Bioinformatics 31, 418–420 (2015).
pubmed: 25316677
doi: 10.1093/bioinformatics/btu655
Leeuw, C. A., de, Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015).
pubmed: 25885710
pmcid: 4401657
doi: 10.1371/journal.pcbi.1004219
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
pubmed: 16199517
pmcid: 1239896
doi: 10.1073/pnas.0506580102
Finucane, H. K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).
pubmed: 26414678
pmcid: 4626285
doi: 10.1038/ng.3404
Backenroth, D. et al. FUN-LDA: a latent dirichlet allocation model for predicting tissue-specific functional effects of noncoding variation: methods and applications. Am. J. Hum. Genet. 102, 920–942 (2018).
pubmed: 29727691
pmcid: 5986983
doi: 10.1016/j.ajhg.2018.03.026
Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
pubmed: 20616382
pmcid: 2922887
doi: 10.1093/bioinformatics/btq340
Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
pubmed: 25826379
pmcid: 4380465
doi: 10.1371/journal.pmed.1001779
Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203–209 (2018).
pubmed: 30305743
pmcid: 6786975
doi: 10.1038/s41586-018-0579-z
Aragam, K. G. et al. Phenotypic refinement of heart failure in a national biobank facilitates genetic discovery. Circulation http://dx.doi.org/CIRCULATIONAHA.118.035774 (2018).
Choi, S. H. et al. Monogenic and polygenic contributions to atrial fibrillation risk: results from a national biobank. Circ. Res. 126, 200–209 (2020).
pubmed: 31691645
doi: 10.1161/CIRCRESAHA.119.315686
Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).
pubmed: 25722852
pmcid: 4342193
doi: 10.1186/s13742-015-0047-8
Panáková, D., Werdich, A. A. & Macrae, C. A. Wnt11 patterns a myocardial electrical gradient through regulation of the L-type Ca(2+) channel. Nature 466, 874–878 (2010).
pubmed: 20657579
pmcid: 2921013
doi: 10.1038/nature09249
Kuo, H.-H. et al. Negligible-cost and weekend-free chemically defined human iPSC culture. Stem Cell Rep. 14, 256–270 (2020).
doi: 10.1016/j.stemcr.2019.12.007
Burridge, P. W., Holmström, A. & Wu, J. C. Chemically defined culture and cardiomyocyte differentiation of human pluripotent stem cells. Curr. Protoc. Hum. Genet. 87, 21.3.1–21.3.15 (2015).
Burridge, P. W. et al. Chemically defined generation of human cardiomyocytes. Nat. Methods 11, 855–860 (2014).
pubmed: 24930130
pmcid: 4169698
doi: 10.1038/nmeth.2999
Veerman, C. C. et al. Immaturity of human stem-cell-derived cardiomyocytes in culture: fatal flaw or soluble problem? Stem Cells Dev. 24, 1035–1052 (2015).
pubmed: 25583389
doi: 10.1089/scd.2014.0533
Barry, P. H. & Lynch, J. W. Liquid junction potentials and small cell effects in patch-clamp analysis. J. Membr. Biol. 121, 101–117 (1991).
pubmed: 1715403
doi: 10.1007/BF01870526
Bravo, E. et al. Developing a guideline to standardize the citation of bioresources in journal articles (CoBRA). BMC Med. 13, 33 (2015).
pubmed: 25855867
pmcid: 4331335
doi: 10.1186/s12916-015-0266-y
Wang, Y. et al. The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions. Genome Biol. 19, 151 (2018).
pubmed: 30286773
pmcid: 6172833
doi: 10.1186/s13059-018-1519-9