TY  - INPR
A1  - Willmann, Matthias
A1  - Götting, Stephan
A1  - Bezdan, Daniela
A1  - Maček, Boris
A1  - Velic, Ana
A1  - Marschal, Matthias
A1  - Vogel, Wichard
A1  - Flesch, Ingo
A1  - Markert, Uwe
A1  - Schmidt, Annika Mareike
A1  - Kübler, Pierre David Martin
A1  - Haug, Maria
A1  - Javed, Mumina
A1  - Jentzsch, Benedikt
A1  - Oberhettinger, Philipp
A1  - Schütz, Monika
A1  - Bohn, Erwin
A1  - Sonnabend, Michael
A1  - Klein, Kristina
A1  - Autenrieth, Ingo B.
A1  - Ossowski, Stephan
A1  - Schwarz, Sandra
A1  - Peter, Silke
T1  - Multi-omics approach identifies novel pathogen-derived prognostic biomarkers in patients with Pseudomonas aeruginosa bloodstream infection
T2  - bioRxiv
N2  - 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.
Y1  - 2018
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/72471
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-724713
UR  - https://www.biorxiv.org/content/10.1101/309898v1
IS  - 309898 Version 1
CY  - bioRxiv
ER  -