Literature DB >> 26139629

A national population-based e-cohort of people with psychosis (PsyCymru) linking prospectively ascertained phenotypically rich and genetic data to routinely collected records: overview, recruitment and linkage.

Keith Lloyd1, Joanna McGregor2, Ann John2, Nick Craddock3, James T Walters3, David Linden3, Ian Jones3, Richard Bentall4, Ronan A Lyons2, David V Ford2, Michael J Owen3.   

Abstract

PsyCymru was initially established as a proof of concept 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. PsyCymru aims to create a research platform and infrastructure for psychosis research in Wales by the establishment of two cohorts. The first is a well characterised clinically-assessed cohort of 490 individuals aged 16 and over, including genetic data. Consented individuals underwent a structured interview using a series of well-validated questionnaires and gave blood for the purpose of DNA extraction for sequencing and candidate gene identification. This data was linked to routinely collected health and social datasets with identity encryption used to protect privacy. The second is a much larger (12,097 individuals) but less well characterised population-based e-cohort of prevalent psychosis cases created using a previously validated algorithm applied to anonymised routine data. Both cohorts can be tracked prospectively and retrospectively using anonymised routinely collected electronic health and administrative data in the Secure Anonymised Information Linkage (SAIL) databank. This unique platform pools data together from multiple sources; linking clinical, psychological, biological, genetic and health care factors to address a wide variety of 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.
Copyright © 2015. Published by Elsevier B.V.

Entities:  

Keywords:  Clinical questionnaires; E-cohort; Health informatics; Phenotype; Routine data

Mesh:

Year:  2015        PMID: 26139629     DOI: 10.1016/j.schres.2015.05.036

Source DB:  PubMed          Journal:  Schizophr Res        ISSN: 0920-9964            Impact factor:   4.939


  5 in total

1.  Impact of schizophrenia genetic liability on the association between schizophrenia and physical illness: data-linkage study.

Authors:  Kimberley M Kendall; Ann John; Sze Chim Lee; Elliott Rees; Antonio F Pardiñas; Marcos Del Pozo Banos; Michael J Owen; Michael C O'Donovan; George Kirov; Keith Lloyd; Ian Jones; Sophie E Legge; James T R Walters
Journal:  BJPsych Open       Date:  2020-11-10

2.  Web-Based Cognitive Testing in Psychiatric Research: Validation and Usability Study.

Authors:  Amy Joanne Lynham; Ian R Jones; James T R Walters
Journal:  J Med Internet Res       Date:  2022-02-10       Impact factor: 5.428

3.  Evidence of increasing recorded diagnosis of autism spectrum disorders in Wales, UK: An e-cohort study.

Authors:  Jack Fg Underwood; Marcos DelPozo-Banos; Aura Frizzati; Ann John; Jeremy Hall
Journal:  Autism       Date:  2021-11-29

Review 4.  'Big data' in mental health research: current status and emerging possibilities.

Authors:  Robert Stewart; Katrina Davis
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2016-07-27       Impact factor: 4.328

5.  Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries.

Authors:  Romana Haneef; Marie Delnord; Michel Vernay; Emmanuelle Bauchet; Rita Gaidelyte; Herman Van Oyen; Zeynep Or; Beatriz Pérez-Gómez; Luigi Palmieri; Peter Achterberg; Mariken Tijhuis; Metka Zaletel; Stefan Mathis-Edenhofer; Ondřej Májek; Håkon Haaheim; Hanna Tolonen; Anne Gallay
Journal:  Arch Public Health       Date:  2020-06-10
  5 in total

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