title: The 82-plex plasma protein signature that predicts increasing inflammation.
abstract: The objective of the study was to define the specific plasma protein signature that predicts the increase of the inflammation marker C-reactive protein from index day to next-day using proteome analysis and novel bioinformatics tools. We performed a prospective study of 91 incident kidney transplant recipients and quantified 359 plasma proteins simultaneously using nano-Liquid-Chromatography-Tandem Mass-Spectrometry in individual samples and plasma C-reactive protein on the index day and the next day. Next-day C-reactive protein increased in 59 patients whereas it decreased in 32 patients. The prediction model selected and validated 82 plasma proteins which determined increased next-day C-reactive protein (area under receiver-operator-characteristics curve, 0.772; 95% confidence interval, 0.669 to 0.876; P < 0.0001). Multivariable logistic regression showed that 82-plex protein signature (P < 0.001) was associated with observed increased next-day C-reactive protein. The 82-plex protein signature outperformed routine clinical procedures. The category-free net reclassification index improved with 82-plex plasma protein signature (total net reclassification index, 88.3%). Using the 82-plex plasma protein signature increased net reclassification index with a clinical meaningful 10% increase of risk mainly by the improvement of reclassification of subjects in the event group. An 82-plex plasma protein signature predicts an increase of the inflammatory marker C-reactive protein.
authors.affiliation: Department of Nephrology, Odense University Hospital, and University of Southern Denmark, Institute of Molecular Medicine, Cardiovascular and Renal Research, Institute of Clinical Research.
authors.forename: Martin
authors.initials: M
authors.lastname: Tepel
authors.affiliation: Department of Clinical Biochemistry and Pharmacology, Centre for Individualized Medicine in Arterial Diseases (Odense University Hospital), and Centre for Clinical Proteomics (Odense University Hospital/University of Southern Denmark).
authors.forename: Hans C
authors.initials: HC
authors.lastname: Beck
authors.affiliation: Department of Epidemiology, Biostatistics and Biodemography, Institute of Public Health; Unit of Human Genetics, Institute of Clinical Research, University of Southern Denmark.
authors.forename: Qihua
authors.initials: Q
authors.lastname: Tan
authors.affiliation: Department of Nephrology, Odense University Hospital, and University of Southern Denmark, Institute of Molecular Medicine, Cardiovascular and Renal Research, Institute of Clinical Research.
authors.forename: Christoffer
authors.initials: C
authors.lastname: Borst
authors.affiliation: Department of Clinical Biochemistry and Pharmacology, Centre for Individualized Medicine in Arterial Diseases (Odense University Hospital), and Centre for Clinical Proteomics (Odense University Hospital/University of Southern Denmark).
authors.forename: Lars M
authors.initials: LM
authors.lastname: Rasmussen
mesh_terms: D000328:Adult; D000368:Aged; D002097:C-Reactive Protein / Q000378:metabolism*; D002853:Chromatography, Liquid; D005260:Female; D006801:Humans; D007249:Inflammation / Q000097:blood / Q000175:diagnosis; D016030:Kidney Transplantation; D016015:Logistic Models; D008297:Male; D055442:Metabolome; D008875:Middle Aged; D011379:Prognosis; D011446:Prospective Studies; D012372:ROC Curve; D051436:Renal Insufficiency, Chronic / Q000097:blood* / Q000473:pathology / Q000601:surgery; D053719:Tandem Mass Spectrometry
chemical_list: D002097:C-Reactive Protein