A National Population-Based E-cohort of People with Psychosis (PsyCymru) Linkage of Phenotypical and Genetic Data to Routinely Collected Records

Introduction PsyCymru was established to investigate the feasibility of linking a prospectively ascertained, well characterised (linked clinical cohort) of people with psychosis in Wales, UK with large amounts of anonymised routinely collected health record data. We are now additionally linking gen...

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Main Authors: Keith Lloyd, Ann John, Nick Craddock, James Walters, David Linden, Ian Jones, Richard Bentall, Ronan Lyons, Sze Chim Lee, Michael Owen
Format: Article
Language:English
Published: Swansea University 2018-08-01
Series:International Journal of Population Data Science
Online Access:https://ijpds.org/article/view/706
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spelling doaj-e20a9f883c3748fd89703ee84c68c0fa2020-11-25T02:17:25ZengSwansea UniversityInternational Journal of Population Data Science2399-49082018-08-013410.23889/ijpds.v3i4.706A National Population-Based E-cohort of People with Psychosis (PsyCymru) Linkage of Phenotypical and Genetic Data to Routinely Collected RecordsKeith Lloyd0Ann John1Nick Craddock2James Walters3David Linden4Ian Jones5Richard Bentall6Ronan Lyons7Sze Chim Lee8Michael Owen9Swansea University Medical SchoolSwansea UniversityDepartment of Psychological Medicine and Neurology, Cardiff UniversityNational Centre for Mental Health, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff UniversityDivision of Psychological Medicine and Clinical Neurosciences, Cardiff UniversityNational Centre for Mental Health, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff UniversityDepartment of Psychology University of SheffieldFarr Institute, Swansea University Medical School David Ford, Swansea UniversitySwansea University Medical SchoolMRC Centre for Neuropsychiatric Genetics and Genomics; Division of Psychological Medicine and Clinical Neuroscience; Neuroscience and Mental Health Research Institute, Cardiff University Introduction PsyCymru was established to investigate the feasibility of linking a prospectively ascertained, well characterised (linked clinical cohort) of people with psychosis in Wales, UK with large amounts of anonymised routinely collected health record data. We are now additionally linking genetic data. Objectives and Approach PsyCymru aimed to create a research platform for psychosis research in Wales by establishing two cohorts. The first was a well-characterised clinically assessed cohort with genetic data. Consented individuals underwent structured interviews using well-validated questionnaires and gave blood sample for DNA extraction, sequencing, and candidate gene identification. This data was then linked to routinely collected health and social datasets with identity encryption. The second is a larger e-cohort of prevalent psychosis cases created using a validated algorithm applied to anonymised routine data. Both cohorts were tracked prospectively and retrospectively in the Secure Anonymised Information Linkage (SAIL) databank. Results In total, data from 958 individuals for the clinical cohort were imported to SAIL. Among these individuals, genetic data for 740 were analysed. The genetic data included robust loci for schizophrenia, pathogenic copy-number variations (CNVs) for various conditions (e.g., autism, intellectual disability, congenital malformations), polygenic risks scores for schizophrenia, as well as pathogenic/non-pathogenic duplications or deletions of chromosome spanning more than 500kb or 1Mb. For the e-cohort, 29,797 individuals were found having a psychosis diagnosis from primary and secondary care between 2004 to 2013. Social demographic data for both cohorts were also analysed based on sex, age, area deprivation, urbanicity, and employment status. Conclusion/Implications This unique platform pooled data together from multiple sources; linking clinical, psychological, biological, genetic, and health care factors to address assorted research questions. This resource will continue to expand over the coming years in size, breadth and depth of data, with continued recruitment and additional measures planned. https://ijpds.org/article/view/706
collection DOAJ
language English
format Article
sources DOAJ
author Keith Lloyd
Ann John
Nick Craddock
James Walters
David Linden
Ian Jones
Richard Bentall
Ronan Lyons
Sze Chim Lee
Michael Owen
spellingShingle Keith Lloyd
Ann John
Nick Craddock
James Walters
David Linden
Ian Jones
Richard Bentall
Ronan Lyons
Sze Chim Lee
Michael Owen
A National Population-Based E-cohort of People with Psychosis (PsyCymru) Linkage of Phenotypical and Genetic Data to Routinely Collected Records
International Journal of Population Data Science
author_facet Keith Lloyd
Ann John
Nick Craddock
James Walters
David Linden
Ian Jones
Richard Bentall
Ronan Lyons
Sze Chim Lee
Michael Owen
author_sort Keith Lloyd
title A National Population-Based E-cohort of People with Psychosis (PsyCymru) Linkage of Phenotypical and Genetic Data to Routinely Collected Records
title_short A National Population-Based E-cohort of People with Psychosis (PsyCymru) Linkage of Phenotypical and Genetic Data to Routinely Collected Records
title_full A National Population-Based E-cohort of People with Psychosis (PsyCymru) Linkage of Phenotypical and Genetic Data to Routinely Collected Records
title_fullStr A National Population-Based E-cohort of People with Psychosis (PsyCymru) Linkage of Phenotypical and Genetic Data to Routinely Collected Records
title_full_unstemmed A National Population-Based E-cohort of People with Psychosis (PsyCymru) Linkage of Phenotypical and Genetic Data to Routinely Collected Records
title_sort national population-based e-cohort of people with psychosis (psycymru) linkage of phenotypical and genetic data to routinely collected records
publisher Swansea University
series International Journal of Population Data Science
issn 2399-4908
publishDate 2018-08-01
description Introduction PsyCymru was established to investigate the feasibility of linking a prospectively ascertained, well characterised (linked clinical cohort) of people with psychosis in Wales, UK with large amounts of anonymised routinely collected health record data. We are now additionally linking genetic data. Objectives and Approach PsyCymru aimed to create a research platform for psychosis research in Wales by establishing two cohorts. The first was a well-characterised clinically assessed cohort with genetic data. Consented individuals underwent structured interviews using well-validated questionnaires and gave blood sample for DNA extraction, sequencing, and candidate gene identification. This data was then linked to routinely collected health and social datasets with identity encryption. The second is a larger e-cohort of prevalent psychosis cases created using a validated algorithm applied to anonymised routine data. Both cohorts were tracked prospectively and retrospectively in the Secure Anonymised Information Linkage (SAIL) databank. Results In total, data from 958 individuals for the clinical cohort were imported to SAIL. Among these individuals, genetic data for 740 were analysed. The genetic data included robust loci for schizophrenia, pathogenic copy-number variations (CNVs) for various conditions (e.g., autism, intellectual disability, congenital malformations), polygenic risks scores for schizophrenia, as well as pathogenic/non-pathogenic duplications or deletions of chromosome spanning more than 500kb or 1Mb. For the e-cohort, 29,797 individuals were found having a psychosis diagnosis from primary and secondary care between 2004 to 2013. Social demographic data for both cohorts were also analysed based on sex, age, area deprivation, urbanicity, and employment status. Conclusion/Implications This unique platform pooled data together from multiple sources; linking clinical, psychological, biological, genetic, and health care factors to address assorted research questions. This resource will continue to expand over the coming years in size, breadth and depth of data, with continued recruitment and additional measures planned.
url https://ijpds.org/article/view/706
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