title: Markers of cellular senescence in zero hour biopsies predict outcome in renal transplantation.
abstract: Although chronological donor age is the most potent predictor of long-term outcome after renal transplantation, it does not incorporate individual differences of the aging-process itself. We therefore hypothesized that an estimate of biological organ age as derived from markers of cellular senescence in zero hour biopsies would be of higher predictive value. Telomere length and mRNA expression levels of the cell cycle inhibitors CDKN2A (p16INK4a) and CDKN1A (p21WAF1) were assessed in pre-implantation biopsies of 54 patients and the association of these and various other clinical parameters with serum creatinine after 1 year was determined. In a linear regression analysis, CDKN2A turned out to be the best single predictor followed by donor age and telomere length. A multiple linear regression analysis revealed that the combination of CDKN2A values and donor age yielded even higher predictive values for serum creatinine 1 year after transplantation. We conclude that the molecular aging marker CDKN2A in combination with chronological donor age predict renal allograft function after 1 year significantly better than chronological donor age alone.
authors.affiliation: Division of Nephrology, Department of Internal Medicine, Medical University Innsbruck, Innsbruck, Austria.
authors.forename: Christian
authors.initials: C
authors.lastname: Koppelstaetter
authors.forename: Gabriele
authors.initials: G
authors.lastname: Schratzberger
authors.forename: Paul
authors.initials: P
authors.lastname: Perco
authors.forename: Johannes
authors.initials: J
authors.lastname: Hofer
authors.forename: Walter
authors.initials: W
authors.lastname: Mark
authors.forename: Robert
authors.initials: R
authors.lastname: Ollinger
authors.forename: Rainer
authors.initials: R
authors.lastname: Oberbauer
authors.forename: Christoph
authors.initials: C
authors.lastname: Schwarz
authors.forename: Christa
authors.initials: C
authors.lastname: Mitterbauer
authors.forename: Alexander
authors.initials: A
authors.lastname: Kainz
authors.forename: Henryk
authors.initials: H
authors.lastname: Karkoszka
authors.forename: Andrzej
authors.initials: A
authors.lastname: Wiecek
authors.forename: Bernd
authors.initials: B
authors.lastname: Mayer
authors.forename: Gert
authors.initials: G
authors.lastname: Mayer
mesh_terms: D000328:Adult; D000375:Aging / Q000378:metabolism; D015415:Biomarkers / Q000378:metabolism; D001706:Biopsy; D016922:Cellular Senescence; D003404:Creatinine / Q000097:blood; D019941:Cyclin-Dependent Kinase Inhibitor p16 / Q000235:genetics / Q000378:metabolism; D050759:Cyclin-Dependent Kinase Inhibitor p21 / Q000235:genetics / Q000378:metabolism; D003710:Demography; D005260:Female; D006801:Humans; D007668:Kidney / Q000473:pathology*; D016030:Kidney Transplantation; D008297:Male; D008875:Middle Aged; D011184:Postoperative Period; D012044:Regression Analysis; D016615:Telomere / Q000378:metabolism; D013997:Time Factors; D014019:Tissue Donors; D014184:Transplantation, Homologous; D016896:Treatment Outcome
chemical_list: D015415:Biomarkers; D019941:Cyclin-Dependent Kinase Inhibitor p16; D050759:Cyclin-Dependent Kinase Inhibitor p21; D003404:Creatinine