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

Shona M. Kerr; Lucija Klaric; Mihail Halachev; Caroline Hayward; Thibaud S. Boutin; Alison M. Meynert; Colin A. Semple; Annukka M. Tuiskula; Heikki Swan; Javier Santoyo-Lopez; Veronique Vitart; Chris Haley; John Dean; Zosia Miedzybrodzka; Timothy J. Aitman; James F. Wilson

doi:10.1038/s41598-019-47436-6

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

Shona M. Kerr, Lucija Klaric, Mihail Halachev, Caroline Hayward, Thibaud S. Boutin, Alison M. Meynert, Colin A. Semple, Annukka M. Tuiskula, Heikki Swan, Javier Santoyo-Lopez, Veronique Vitart, Chris Haley, John Dean, Zosia Miedzybrodzka, Timothy J. Aitman, James F. Wilson^* (Corresponding Author)

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

5 Downloads (Pure)

Abstract

The Viking Health Study Shetland is a population-based research cohort of 2,122 volunteer participants with ancestry from the Shetland Isles in northern Scotland. The high kinship and detailed phenotype data support a range of approaches for associating rare genetic variants, enriched in this isolate population, with quantitative traits and diseases. As an exemplar, the c.1750G > A; p.Gly584Ser variant within the coding sequence of the KCNH2 gene implicated in Long QT Syndrome (LQTS), which occurred once in 500 whole genome sequences from this population, was investigated. Targeted sequencing of the KCNH2 gene in family members of the initial participant confirmed the presence of the sequence variant and identified two further members of the same family pedigree who shared the variant. Investigation of these three related participants for whom single nucleotide polymorphism (SNP) array genotypes were available allowed a unique shared haplotype of 1.22 Mb to be defined around this locus. Searching across the full cohort for this haplotype uncovered two additional apparently unrelated individuals with no known genealogical connection to the original kindred. All five participants with the defined haplotype were shown to share the rare variant by targeted Sanger sequencing. If this result were verified in a healthcare setting, it would be considered clinically actionable, and has been actioned in relatives ascertained independently through clinical presentation. The General Practitioners of four study participants with the rare variant were alerted to the research findings by letters outlining the phenotype (prolonged electrocardiographic QTc interval). A lack of detectable haplotype sharing between c.1750G > A; p.Gly584Ser chromosomes from previously reported individuals from Finland and those in this study from Shetland suggests that this mutation has arisen more than once in human history. This study showcases the potential value of isolate population-based research resources for genomic medicine. It also illustrates some challenges around communication of actionable findings in research participants in this context.

Original language	English
Article number	10964
Number of pages	11
Journal	Scientific Reports
Volume	9
DOIs	https://doi.org/10.1038/s41598-019-47436-6
Publication status	Published - 29 Jul 2019

Bibliographical note

Acknowledgements
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.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1038/s41598-019-47436-6Licence: CC BY

Kerr-et-al-sr-an-actionable
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Final published version, 1.43 MBLicence: CC BY

Cite this

Kerr, 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, 9, Article 10964. https://doi.org/10.1038/s41598-019-47436-6

Kerr, SM, Klaric, L, Halachev, M, Hayward, C, Boutin, TS, Meynert, AM, Semple, CA, Tuiskula, AM, Swan, H, Santoyo-Lopez, J, Vitart, V, Haley, C, Dean, J , Miedzybrodzka, Z, Aitman, TJ & Wilson, JF 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/s41598-019-47436-6

@article{c16dbb6f0e5e45f38347d7637994c956,

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

abstract = "The Viking Health Study Shetland is a population-based research cohort of 2,122 volunteer participants with ancestry from the Shetland Isles in northern Scotland. The high kinship and detailed phenotype data support a range of approaches for associating rare genetic variants, enriched in this isolate population, with quantitative traits and diseases. As an exemplar, the c.1750G > A; p.Gly584Ser variant within the coding sequence of the KCNH2 gene implicated in Long QT Syndrome (LQTS), which occurred once in 500 whole genome sequences from this population, was investigated. Targeted sequencing of the KCNH2 gene in family members of the initial participant confirmed the presence of the sequence variant and identified two further members of the same family pedigree who shared the variant. Investigation of these three related participants for whom single nucleotide polymorphism (SNP) array genotypes were available allowed a unique shared haplotype of 1.22 Mb to be defined around this locus. Searching across the full cohort for this haplotype uncovered two additional apparently unrelated individuals with no known genealogical connection to the original kindred. All five participants with the defined haplotype were shown to share the rare variant by targeted Sanger sequencing. If this result were verified in a healthcare setting, it would be considered clinically actionable, and has been actioned in relatives ascertained independently through clinical presentation. The General Practitioners of four study participants with the rare variant were alerted to the research findings by letters outlining the phenotype (prolonged electrocardiographic QTc interval). A lack of detectable haplotype sharing between c.1750G > A; p.Gly584Ser chromosomes from previously reported individuals from Finland and those in this study from Shetland suggests that this mutation has arisen more than once in human history. This study showcases the potential value of isolate population-based research resources for genomic medicine. It also illustrates some challenges around communication of actionable findings in research participants in this context.",

author = "Kerr, {Shona M.} and Lucija Klaric and Mihail Halachev and Caroline Hayward and Boutin, {Thibaud S.} and Meynert, {Alison M.} and Semple, {Colin A.} and Tuiskula, {Annukka M.} and Heikki Swan and Javier Santoyo-Lopez and Veronique Vitart and Chris Haley and John Dean and Zosia Miedzybrodzka and Aitman, {Timothy J.} and Wilson, {James F.}",

note = "Acknowledgements 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. ",

year = "2019",

month = jul,

day = "29",

doi = "10.1038/s41598-019-47436-6",

language = "English",

volume = "9",

journal = "Scientific Reports",

issn = "2045-2322",

publisher = "Nature Publishing Group",

}

TY - JOUR

T1 - An actionable KCNH2 Long QT Syndrome variant detected by sequence and haplotype analysis in a population research cohort

AU - Kerr, Shona M.

AU - Klaric, Lucija

AU - Halachev, Mihail

AU - Hayward, Caroline

AU - Boutin, Thibaud S.

AU - Meynert, Alison M.

AU - Semple, Colin A.

AU - Tuiskula, Annukka M.

AU - Swan, Heikki

AU - Santoyo-Lopez, Javier

AU - Vitart, Veronique

AU - Haley, Chris

AU - Dean, John

AU - Miedzybrodzka, Zosia

AU - Aitman, Timothy J.

AU - Wilson, James F.

N1 - Acknowledgements 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.

PY - 2019/7/29

Y1 - 2019/7/29

N2 - The Viking Health Study Shetland is a population-based research cohort of 2,122 volunteer participants with ancestry from the Shetland Isles in northern Scotland. The high kinship and detailed phenotype data support a range of approaches for associating rare genetic variants, enriched in this isolate population, with quantitative traits and diseases. As an exemplar, the c.1750G > A; p.Gly584Ser variant within the coding sequence of the KCNH2 gene implicated in Long QT Syndrome (LQTS), which occurred once in 500 whole genome sequences from this population, was investigated. Targeted sequencing of the KCNH2 gene in family members of the initial participant confirmed the presence of the sequence variant and identified two further members of the same family pedigree who shared the variant. Investigation of these three related participants for whom single nucleotide polymorphism (SNP) array genotypes were available allowed a unique shared haplotype of 1.22 Mb to be defined around this locus. Searching across the full cohort for this haplotype uncovered two additional apparently unrelated individuals with no known genealogical connection to the original kindred. All five participants with the defined haplotype were shown to share the rare variant by targeted Sanger sequencing. If this result were verified in a healthcare setting, it would be considered clinically actionable, and has been actioned in relatives ascertained independently through clinical presentation. The General Practitioners of four study participants with the rare variant were alerted to the research findings by letters outlining the phenotype (prolonged electrocardiographic QTc interval). A lack of detectable haplotype sharing between c.1750G > A; p.Gly584Ser chromosomes from previously reported individuals from Finland and those in this study from Shetland suggests that this mutation has arisen more than once in human history. This study showcases the potential value of isolate population-based research resources for genomic medicine. It also illustrates some challenges around communication of actionable findings in research participants in this context.

AB - The Viking Health Study Shetland is a population-based research cohort of 2,122 volunteer participants with ancestry from the Shetland Isles in northern Scotland. The high kinship and detailed phenotype data support a range of approaches for associating rare genetic variants, enriched in this isolate population, with quantitative traits and diseases. As an exemplar, the c.1750G > A; p.Gly584Ser variant within the coding sequence of the KCNH2 gene implicated in Long QT Syndrome (LQTS), which occurred once in 500 whole genome sequences from this population, was investigated. Targeted sequencing of the KCNH2 gene in family members of the initial participant confirmed the presence of the sequence variant and identified two further members of the same family pedigree who shared the variant. Investigation of these three related participants for whom single nucleotide polymorphism (SNP) array genotypes were available allowed a unique shared haplotype of 1.22 Mb to be defined around this locus. Searching across the full cohort for this haplotype uncovered two additional apparently unrelated individuals with no known genealogical connection to the original kindred. All five participants with the defined haplotype were shown to share the rare variant by targeted Sanger sequencing. If this result were verified in a healthcare setting, it would be considered clinically actionable, and has been actioned in relatives ascertained independently through clinical presentation. The General Practitioners of four study participants with the rare variant were alerted to the research findings by letters outlining the phenotype (prolonged electrocardiographic QTc interval). A lack of detectable haplotype sharing between c.1750G > A; p.Gly584Ser chromosomes from previously reported individuals from Finland and those in this study from Shetland suggests that this mutation has arisen more than once in human history. This study showcases the potential value of isolate population-based research resources for genomic medicine. It also illustrates some challenges around communication of actionable findings in research participants in this context.

UR - http://www.scopus.com/inward/record.url?scp=85069904367&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/actionable-kcnh2-long-qt-syndrome-variant-detected-sequence-haplotype-analysis-population-research-c

U2 - 10.1038/s41598-019-47436-6

DO - 10.1038/s41598-019-47436-6

M3 - Article

C2 - 31358886

AN - SCOPUS:85069904367

SN - 2045-2322

VL - 9

JO - Scientific Reports

JF - Scientific Reports

M1 - 10964

ER -

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

Abstract

Bibliographical note

UN SDGs

Access to Document

Other files and links

Fingerprint

Zosia Miedzybrodzka

Cite this

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

Abstract

Bibliographical note

UN SDGs

Access to Document

Other files and links

Fingerprint

Profiles

Zosia Miedzybrodzka

Cite this