Nested case-control study reveals distinct sputum microbiome profiles predict Pseudomonas aeruginosa infection in cystic fibrosis, suggesting early microbial markers can guide risk stratification.
Rationale Pseudomonas aeruginosa (PA) is the archetypal cystic fibrosis (CF) pathogen, and a major contributor to morbidity and mortality. However, predictors of infection risk and persistence remain unclear. This study investigated whether baseline CF sputum microbiome associates with risk of incident PA (iPA) infection and persistence. Methods We conducted a retrospective nested case–control study using a longitudinal sputum biobank. Adults with CF who developed iPA infection (cases) were matched 1:2 to PA-negative controls by sex, age (±2 years), and birth cohort. Microbial community composition was profiled using 16S-rRNA gene sequencing, and PA abundance quantified by qPCR. Longitudinal analyses assessed microbiome changes across pre-infection, at-infection, and post-infection. Key Results In total, 368 sputum samples from 54 cases (85 episodes) and 96 controls (1998–2022) were analysed. Pre-infection community composition differed between cases and controls (PERMAVOVA, R 2 =0.75%, p=0.014). Burkholderia (LFC=1.18, p adj =1.41×10 −5 ) , and Achromobacter (LFC=3.17, p adj =1.51×10 −13 ) were enriched in controls, while Stenotrophomonas (LFC=1.03, p adj =9.16×10 −6 ) was enriched in pre-iPA cases. PA was detected by sequencing (p=0.027) and qPCR (p=0.007) a median of 5.2 months (IQR 3.5–8.7) before culture. At-infection, individuals progressing to chronic infection (n=16) had higher relative (p=0.010) and absolute (p=0.001) PA abundance than transient cases (n=38), with no difference in total bacterial load (p=0.169). Those developing chronic infection exhibited higher Escherichia/Shigella (LFC=4.68, p adj =2.58×10 −4 ) and Stenotrophomonas (LFC=2.78, p adj =0.001). Conclusions CF sputum microbiome composition associates with both risk of acquiring PA and its persistence. These findings suggest microbiome profiling may identify microbial candidates for PA infection risk and may inform future risk stratification.
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