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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

Lookup NU author(s): Dr David Bourn, Professor Sir John BurnORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ. 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.

Publication metadata

Author(s): Loong L, Huntley C, McRonald F, Santaniello F, Pethick J, Torr B, Allen S, Tulloch O, Goel S, Shand B, Rahman T, Luchtenborg M, Garrett A, Barber R, Bedenham T, Bourn D, Bradshaw K, Brooks C, Bruty J, Burghel GJ, Butler S, Buxton C, Callaway A, Callaway J, Drummond J, Durkie M, Field J, Jenkins L, McVeigh TP, Mountford R, Nyanhete R, Petrides E, Robinson R, Scott T, Stinton V, Tellez J, Wallace AJ, Yarram-Smith L, Sahan K, Hallowell N, Eccles DM, Pharoah P, Tischkowitz M, Antoniou AC, Evans DG, Lalloo F, Norbury G, Morris E, Burn J, Hardy S, Turnbull C

Publication type: Article

Publication status: Published

Journal: Journal of Medical Genetics

Year: 2023

Volume: 60

Issue: 7

Pages: 669-678

Print publication date: 01/07/2023

Online publication date: 26/12/2022

Acceptance date: 18/11/2022

Date deposited: 10/09/2026

ISSN (print): 0022-2593

ISSN (electronic): 1468-6244

Publisher: BMJ Publishing Group

URL: https://doi.org/10.1136/jmg-2022-108800

DOI: 10.1136/jmg-2022-108800

PubMed id: 36572524

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