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Lookup NU author(s): David Langton, Rohan Bhalekar, Professor Tom Joyce, Professor Stephen Rushton, Dr Rebecca Darlay
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2022, The Author(s). Background: Over five million joint replacements are performed across the world each year. Cobalt chrome (CoCr) components are used in most of these procedures. Some patients develop delayed-type hypersensitivity (DTH) responses to CoCr implants, resulting in tissue damage and revision surgery. DTH is unpredictable and genetic links have yet to be definitively established. Methods: At a single site, we carried out an initial investigation to identify HLA alleles associated with development of DTH following metal-on-metal hip arthroplasty. We then recruited patients from other centres to train and validate an algorithm incorporating patient age, gender, HLA genotype, and blood metal concentrations to predict the development of DTH. Accuracy of the modelling was assessed using performance metrics including time-dependent receiver operator curves. Results: Using next-generation sequencing, here we determine the HLA genotypes of 606 patients. 176 of these patients had experienced failure of their prostheses; the remaining 430 remain asymptomatic at a mean follow up of twelve years. We demonstrate that the development of DTH is associated with patient age, gender, the magnitude of metal exposure, and the presence of certain HLA class II alleles. We show that the predictive algorithm developed from this investigation performs to an accuracy suitable for clinical use, with weighted mean survival probability errors of 1.8% and 3.1% for pre-operative and post-operative models respectively. Conclusions: The development of DTH following joint replacement appears to be determined by the interaction between implant wear and a patient’s genotype. The algorithm described in this paper may improve implant selection and help direct patient surveillance following surgery. Further consideration should be given towards understanding patient-specific responses to different biomaterials.
Author(s): Langton DJ, Bhalekar RM, Joyce TJ, Rushton SP, Wainwright BJ, Nargol ME, Shyam N, Lie BA, Pabbruwe MB, Stewart AJ, Waller S, Natu S, Ren R, Hornick R, Darlay R, Su EP, Nargol AVF
Publication type: Article
Publication status: Published
Journal: Communications Medicine
Year: 2022
Volume: 2
Online publication date: 24/06/2022
Acceptance date: 07/06/2022
Date deposited: 30/04/2024
ISSN (electronic): 2730-664X
Publisher: Springer Nature
URL: https://doi.org/10.1038/s43856-022-00137-0
DOI: 10.1038/s43856-022-00137-0
Data Access Statement: Raw genetic data of the extreme phenotype groups are included in Supplementary Data 1 and Supplementary Table 1. Supplementary Data 2 provides the source data for Figs. 4, 5, and 6. Further demographic and clinical details of study patients are included in Supplementary Tables 3 and 4. Patient consent was not obtained to share the individual genetic results on a public repository. However, further data that support the findings of this study are available from the corresponding author upon reasonable request following ethical approval. The computer code software algorithm is proprietary and therefore not available to the general reader. The code can be supplied from the corresponding author upon reasonable request for use in non commercial, ethically approved research.
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