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Pseudomonas aeruginosa is a human pathogen that causes health-care associated blood stream infections (BSI). Although P. aeruginosa BSI are associated with high mortality rates, the clinical relevance of pathogen-derived prognostic biomarker to identify patients at risk for unfavorable outcome remains largely unexplored. We found novel pathogen-derived prognostic biomarker candidates by applying a multi-omics approach on a multicenter sepsis patient cohort. Multi-level Cox regression was used to investigate the relation between patient characteristics and pathogen features (2298 accessory genes, 1078 core protein levels, 107 parsimony-informative variations in reported virulence factors) with 30-day mortality. Our analysis revealed that presence of the helP gene encoding a putative DEAD-box helicase was independently associated with a fatal outcome (hazard ratio 2.01, p = 0.05). helP is located within a region related to the pathogenicity island PAPI-1 in close proximity to a pil gene cluster, which has been associated with horizontal gene transfer. Besides helP, elevated protein levels of the bacterial flagellum protein FliL (hazard ratio 3.44, p < 0.001) and of a bacterioferritin-like protein (hazard ratio 1.74, p = 0.003) increased the risk of death, while high protein levels of a putative aminotransferase were associated with an improved outcome (hazard ratio 0.12, p < 0.001). The prognostic potential of biomarker candidates and clinical factors was confirmed with different machine learning approaches using training and hold-out datasets. The helP genotype appeared the most attractive biomarker for clinical risk stratification due to its relevant predictive power and ease of detection.
Numerous studies have described a correlation between smoking and reduced bone mass. This not only increases fracture risk but also impedes reconstruction/fixation of bone. An increased frequency of complications following surgery is common. Here, we investigate the effect of smoking on the clinical outcome following total joint arthroplasty (TJA). 817 patients receiving primary or revision (including clinical transfers) TJA at our level-one trauma center have been randomly interviewed twice (pre- and six months post-surgery). We found that 159 patients developed complications (infections, disturbed healing, revisions, thrombosis, and/or death). Considering nutritional status, alcohol and cigarette consumption as possible risk factors, OR was highest for smoking. Notably, mean age was significantly lower in smokers (59.2 ± 1.0a) than non-smokers (64.6 ± 0.8; p < 0.001). However, the number of comorbidities was comparable between both groups. Compared to non-smokers (17.8 ± 1.9%), the complication rate increases with increasing cigarette consumption (1–20 pack-years (PY): 19.2 ± 2.4% and >20 PY: 30.4 ± 3.6%; p = 0.002). Consequently, mean hospital stay was longer in heavy smokers (18.4 ± 1.0 day) than non-smokers (15.3 ± 0.5 day; p = 0.009) or moderate smokers (15.9 ± 0.6 day). In line with delayed healing, bone formation markers (BAP and CICP) were significantly lower in smokers than non-smokers 2 days following TJA. Although, smoking increased serum levels of MCP-1, OPG, sRANKL, and Osteopontin as well as bone resorption markers (TRAP5b and CTX-I) were unaffected. In line with an increased infection rate, smoking reduced 25OH vitamin D3 (immune-modulatory), IL-1β, IL-6, TNF-α, and IFN-γ serum levels. Our data clearly show that smoking not only affects bone formation after TJA but also suppresses the inflammatory response in these patients. Thus, it is feasible that therapies favoring bone formation and immune responses help improve the clinical outcome in smokers following TJA.