Loong, L, Huntley, C, McRonald, F et al. (48 more authors) (2022) Germline mismatch repair (MMR) gene analyses from English NHS regional molecular genomics laboratories 1996–2020: development of a national resource of patient-level genomics laboratory records. Journal of Medical Genetics (JMG). ISSN 0022-2593
Abstract
Objective To describe national patterns of National Health Service (NHS) analysis of mismatch repair (MMR) genes in England using individual-level data submitted to the National Disease Registration Service (NDRS) by the NHS regional molecular genetics laboratories.
Design Laboratories submitted individual-level patient data to NDRS against a prescribed data model, including (1) patient identifiers, (2) test episode data, (3) per-gene results and (4) detected sequence variants. Individualised per-laboratory algorithms were designed and applied in NDRS to extract and map the data to the common data model. Laboratory-level MMR activity audit data from the Clinical Molecular Genetics Society/Association of Clinical Genomic Science were used to assess early years’ missing data.
Results Individual-level data from patients undergoing NHS MMR germline genetic testing were submitted from all 13 English laboratories performing MMR analyses, comprising in total 16 722 patients (9649 full-gene, 7073 targeted), with the earliest submission from 2000. The NDRS dataset is estimated to comprise >60% of NHS MMR analyses performed since inception of NHS MMR analysis, with complete national data for full-gene analyses for 2016 onwards. Out of 9649 full-gene tests, 2724 had an abnormal result, approximately 70% of which were (likely) pathogenic. Data linkage to the National Cancer Registry demonstrated colorectal cancer was the most frequent cancer type in which full-gene analysis was performed.
Conclusion The NDRS MMR dataset is a unique national pan-laboratory amalgamation of individual-level clinical and genomic patient data with pseudonymised identifiers enabling linkage to other national datasets. This growing resource will enable longitudinal research and can form the basis of a live national genomic disease registry.
Data availability statement
Data are available upon reasonable request. Data may be obtained from a third party and are not publicly available. All data relevant to the study are included in the article or uploaded as supplementary information. All summary data relevant to the study are included in the article or uploaded as online supplementary information. Individual level data detailed in this study are held within NHS Digital with access available on application.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Author(s) (or their employer(s)) 2022. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
Keywords: | Databases, Genetic; Genetic Testing; Genetics, Medical; Genetics, Population; Genomics |
Dates: |
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Institution: | The University of Leeds |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 Jan 2023 08:09 |
Last Modified: | 13 Jan 2023 15:27 |
Status: | Published online |
Publisher: | BMJ Publishing Group |
Identification Number: | 10.1136/jmg-2022-108800 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:194874 |