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An actionable KCNH2 Long QT Syndrome variant detected by sequence and haplotype analysis in a population research cohort

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dc.contributor.authorKerr, Shona M.
dc.contributor.authorKlaric, Lucija
dc.contributor.authorHalachev, Mihail
dc.contributor.authorHayward, Caroline
dc.contributor.authorBoutin, Thibaud S.
dc.contributor.authorMeynert, Alison M.
dc.contributor.authorSemple, Colin A.
dc.contributor.authorTuiskula, Annukka M.
dc.contributor.authorSwan, Heikki
dc.contributor.authorSantoyo-Lopez, Javier
dc.contributor.authorVitart, Veronique
dc.contributor.authorHaley, Chris
dc.contributor.authorDean, John
dc.contributor.authorMiedzybrodzka, Zosia
dc.contributor.authorAitman, Timothy J.
dc.contributor.authorWilson, James F.
dc.contributor.institutionUniversity of Aberdeen.Applied Medicineen
dc.contributor.institutionUniversity of Aberdeen.Grampian Data Safe Haven (DaSH)en
dc.date.accessioned2019-08-23T11:50:17Z
dc.date.available2019-08-23T11:50:17Z
dc.date.issued2019-07-29
dc.descriptionAcknowledgements This research was made possible due to the infrastructure and funding provided by the Scottish Genomes Partnership, for which we are grateful. We thank the members of the Scottish Genomes Partnership Ethics Advisory Group (in particular the Chair Dr Anne Lampe) for their suggestions for improvement and constructive criticisms of the project. The University of Edinburgh Academic and Clinical Central Office for Research and Development (ACCORD) also provided helpful advice. VIKING DNA extractions and array genotyping were performed at the Edinburgh Clinical Research Facility, University of Edinburgh and were funded by the Medical Research Council UK quinquennial programme grant to the MRC Human Genetics Unit. Emily Weiss and Reka Nagy assembled the Shetland pedigree using records kept at the General Register Ofce and study information, building on earlier pedigree work in the Northern Isles. Nicola Pirastu selected the most appropriate participants for WGS using the ANCHAP software. Whole Genome Sequencing was carried out at Edinburgh Genomics, The University of Edinburgh. We thank Susan Campbell and technical services at MRC HGU for the Sanger sequencing. We thank Archie Campbell and Rachel Edwards for transfer of ECG data into an SQL database and for expert support with extraction of EHR data. Te linkage to data in the EHR provided by patients and collected by the NHS as part of their care and support was facilitated by Dionysis Vragkos, eData Research and Innovation Service (eDRIS). We would like to acknowledge the invaluable contributions of the research nurses in Shetland and the administrative team in Edinburgh. Finally and most importantly, we thank the people of Shetland for their involvement in and ongoing support for our research. This work was funded by the MRC University Unit award to the MRC Human Genetics Unit, University of Edinburgh, MC_UU_00007/10. Whole genome sequencing was funded by the Chief Scientist Office of the Scottish Government Health Directorates (grant reference SGP/1) and the Medical Research Council Whole Genome Sequencing for Health and Wealth Initiative (MC/PC/15080). LK is supported by a UKRI innovation fellowship in data science. The funders had no kerole in designing or performing the study, or in preparation for publication. There is neither research ethics committee approval, nor consent from individual participants, to permit open release of the individual level research data underlying this study. The datasets generated and analysed during the current study are therefore not publicly available. Instead, the haplotype data and/or DNA samples are available from the corresponding author Professor Jim Wilson (accessQTL@ed.ac.uk) on reasonable request, following approval by the VIKING Data Access Committee and in line with the consent given by participants.en
dc.description.statusPeer revieweden
dc.format.extent11
dc.format.extent1500600
dc.identifier146956890
dc.identifierc16dbb6f-0e5e-45f3-8347-d7637994c956
dc.identifier85069904367
dc.identifier31358886
dc.identifier.citationKerr, S M, Klaric, L, Halachev, M, Hayward, C, Boutin, T S, Meynert, A M, Semple, C A, Tuiskula, A M, Swan, H, Santoyo-Lopez, J, Vitart, V, Haley, C, Dean, J, Miedzybrodzka, Z, Aitman, T J & Wilson, J F 2019, 'An actionable KCNH2 Long QT Syndrome variant detected by sequence and haplotype analysis in a population research cohort', Scientific Reports, vol. 9, 10964. https://doi.org/10.1038/s41598-019-47436-6en
dc.identifier.doi10.1038/s41598-019-47436-6
dc.identifier.issn2045-2322
dc.identifier.otherMendeley: 4ad5f5c5-6cbe-3360-95ce-d083417cec28
dc.identifier.otherPubMedCentral: PMC6662790
dc.identifier.otherORCID: /0000-0003-2890-8136/work/175113425
dc.identifier.urihttp://hdl.handle.net/2164/12770
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85069904367&partnerID=8YFLogxKen
dc.identifier.urlhttp://www.mendeley.com/research/actionable-kcnh2-long-qt-syndrome-variant-detected-sequence-haplotype-analysis-population-research-cen
dc.identifier.vol9en
dc.language.isoeng
dc.relation.ispartofScientific Reportsen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subjectR Medicineen
dc.subjectGeneralen
dc.subject.lccRen
dc.titleAn actionable KCNH2 Long QT Syndrome variant detected by sequence and haplotype analysis in a population research cohorten
dc.typeJournal articleen

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