<i>Mycobacterium abscessus</i> Genomic Clusters Span Geography and Patient Groups

Abstract

Background: Mycobacterium abscessus has emerged as a significant clinical concern following reports that it is readily transmissible in healthcare settings between patients with Cystic Fibrosis (CF). Methods: We analysed consecutive M. abscessus whole-genome sequencing data from England (February-2015 to November-2019) to identify genomically similar isolates. Linkage to a national healthcare usage database was used to investigate possible contacts between patients. Multivariable regression analysis was performed to investigate factors associated with acquisition of a genomically clustered strain (within ≤25 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 ≥10 patients, all but one contained patients with CF and patients without CF. Patients with CF were equally likely to have clustered isolates as those without CF. High-density phylogenetic clusters were randomly distributed over a wide geographical area. The majority of 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 but not time spent as an hospital inpatient/outpatient. We identified two CF sibling pairs with genetically highly divergent isolates and 1 pair with closely related isolates, as well as 25 uninfected presumed household contacts with CF. Interpretation: Previously identified widely disseminated dominant clones of M. abscessus are not restricted to CF patients and occur in other chronic respiratory diseases. Our analysis does not support person-to-person transmission as an important mechanism in M. abscessus dissemination at a national level in England. Funding Statement: 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. T Peto, AS Walker and DW Crook 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. Declaration of Interests: SL is supported by a Medical Research Council Clinical Research Training Fellowship. DWE declares lecture fees from Gilead, outside the submitted work. TMW is a Wellcome Trust Clinical Career Development Fellow (214560/Z/18/Z). The remaining authors declare no conflicts of interest. Ethics Approval Statement: This work was carried out as a public health investigation with internal approval from Public Health England and therefore ethics committee approval was not required.