Epidemiology of Mycobacterium abscessus in England: an observational study

Samuel Lipworth*, Natasha Hough, Natasha Weston, Berit Muller-Pebody, Nicholas Phin, Richard Myers, Stephen Chapman, William Flight, Eliza Alexander, E. Grace Smith, Esther Robinson, Tim E.A. Peto, Derrick W. Crook, A. Sarah Walker, Susan Hopkins, David W. Eyre, Timothy M. Walker

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Background: Mycobacterium abscessus has emerged as a significant clinical concern following reports that it is readily transmissible in health-care settings between patients with cystic fibrosis. We linked routinely collected whole-genome sequencing and health-care usage data with the aim of investigating the extent to which such transmission explains acquisition in patients with and without cystic fibrosis in England. Methods: In this retrospective observational study, we analysed consecutive M abscessus whole-genome sequencing data from England (beginning of February, 2015, to Nov 14, 2019) to identify genomically similar isolates. Linkage to a national health-care usage database was used to investigate possible contacts between patients. Multivariable regression analysis was done to investigate factors associated with acquisition of a genomically clustered strain (genomic distance <25 single nucleotide polymorphisms [SNPs]). Findings: 2297 isolates from 906 patients underwent whole-genome sequencing as part of the routine Public Health England diagnostic service. Of 14 genomic clusters containing isolates from ten or more patients, all but one contained patients with cystic fibrosis and patients without cystic fibrosis. Patients with cystic fibrosis were equally likely to have clustered isolates (258 [60%] of 431 patients) as those without cystic fibrosis (322 [63%] of 513 patients; p=0·38). High-density phylogenetic clusters were randomly distributed over a wide geographical area. Most isolates with a closest genetic neighbour consistent with potential transmission had no identifiable relevant epidemiological contacts. Having a clustered isolate was independently associated with increasing age (adjusted odds ratio 1·14 per 10 years, 95% CI 1·04–1·26), but not time spent as an hospital inpatient or outpatient. We identified two sibling pairs with cystic fibrosis with genetically highly divergent isolates and one pair with closely related isolates, and 25 uninfected presumed household contacts with cystic fibrosis. Interpretation: Previously identified widely disseminated dominant clones of M abscessus are not restricted to patients with cystic fibrosis and occur in other chronic respiratory diseases. Although our analysis showed a small number of cases where person-to-person transmission could not be excluded, it did not support this being a major mechanism for M abscessus dissemination at a national level in England. Overall, these data should reassure patients and clinicians that the risk of acquisition from other patients in health-care settings is relatively low and motivate future research efforts to focus on identifying routes of acquisition outside of the cystic fibrosis health-care-associated niche. Funding: The National Institute for Health Research, Health Data Research UK, The Wellcome Trust, The Medical Research Council, and Public Health England.

Original languageEnglish
Pages (from-to)e498-e507
JournalThe Lancet Microbe
Volume2
Issue number10
DOIs
Publication statusPublished - Oct 2021

Bibliographical note

Funding Information:
The research was supported by the National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance (HPRU 2012–10041) at the University of Oxford in partnership with Public Health England (PHE) and by Oxford NIHR Biomedical Research Centre. TEAP, ASW, and DWC are NIHR senior investigators. Computation used the Oxford Biomedical Research Computing (BMRC) facility, a joint development between the Wellcome Centre for Human Genetics and the Big Data Institute supported by Health Data Research UK and the NIHR Oxford Biomedical Research Centre. The report presents independent research funded by NIHR. The views expressed in this publication are those of the authors and not necessarily those of the NHS, NIHR, the Department of Health or PHE . SL is supported by a Medical Research Council Clinical Research Training Fellowship.

Funding Information:
DWE declares grants from Robertson Foundation and lecture fees from Gilead, outside the submitted work. TMW is a Wellcome Trust Clinical Career Development Fellow (214560/Z/18/Z). All other authors declare no competing interests.

Funding Information:
DWE declares grants from Robertson Foundation and lecture fees from Gilead, outside the submitted work. TMW is a Wellcome Trust Clinical Career Development Fellow ( 214560/Z/18/Z ). All other authors declare no competing interests.

Publisher Copyright:
© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

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