title: A 3-biomarker-panel predicts renal outcome in patients with proteinuric renal diseases.
abstract: BACKGROUND
  Clinical and histological parameters are valid prognostic markers in renal disease, although they may show considerable interindividual variability and sometimes limited prognostic value. Novel molecular markers and pathways have the potential to increase the predictive prognostic value of the so called "traditional markers".
  
  
  METHODS
  Transcriptomics profiles from laser-capture microdissected proximal tubular epithelial cells from routine kidney biopsies were correlated with a chronic renal damage index score (CREDI), an inflammation score (INSCO), and clinical parameters. We used data from 20 renal biopsies with various proteinuric renal diseases with a median follow-up of 49 months (discovery cohort). For validation we performed microarrays from whole kidney biopsies from a second cohort consisting of 16 patients with a median follow-up time of 28 months (validation cohort).
  
  
  RESULTS
  562 genes correlated with the CREDI score and 285 genes correlated with the INSCO panel, respectively. 39 CREDI and 90 INSCO genes also correlated with serum creatinine at follow-up. After hierarchical clustering we identified 5 genes from the CREDI panel, and 10 genes from the INSCO panel, respectively, which showed kidney specific gene expression. After exclusion of genes, which correlated to each other by > 50% we identified VEGF-C from the CREDI panel and BMP7, THBS1, and TRIB1 from the INSCO panel. Traditional markers for chronic kidney disease progression and inflammation score predicted 44% of the serum creatinine variation at follow-up. VEGF-C did not further enhance the predictive value, but BMP7, THBS1 and TRIB1 together predicted 94% of the serum creatinine at follow up (p < 0.0001). The model was validated in a second cohort of patients yielding also a significant prediction of follow up creatinine (48%, p = 0.0115).
  
  
  CONCLUSIONS
  We identified and validated a panel of three genes in kidney biopsies which predicted serum creatinine at follow-up and therefore might serve as biomarkers for kidney disease progression.
authors.forename: Hannes
authors.initials: H
authors.lastname: Neuwirt
authors.forename: Paul
authors.initials: P
authors.lastname: Perco
authors.forename: Alexander
authors.initials: A
authors.lastname: Kainz
authors.forename: Irmgard
authors.initials: I
authors.lastname: Mühlberger
authors.forename: Johannes
authors.initials: J
authors.lastname: Leierer
authors.forename: Suzie-Jane
authors.initials: SJ
authors.lastname: Braniff
authors.forename: Bernd
authors.initials: B
authors.lastname: Mayer
authors.forename: Gert
authors.initials: G
authors.lastname: Mayer
authors.forename: Michael
authors.initials: M
authors.lastname: Rudnicki
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000378:metabolism*; D055419:Bone Morphogenetic Protein 7 / Q000378:metabolism*; D016022:Case-Control Studies; D015331:Cohort Studies; D018450:Disease Progression; D005260:Female; D020869:Gene Expression Profiling; D015894:Genome, Human; D006801:Humans; D007249:Inflammation / Q000175:diagnosis* / Q000378:metabolism; D047908:Intracellular Signaling Peptides and Proteins / Q000378:metabolism*; D061346:Laser Capture Microdissection; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D017346:Protein Serine-Threonine Kinases / Q000037:antagonists & inhibitors* / Q000378:metabolism; D011507:Proteinuria / Q000175:diagnosis* / Q000378:metabolism; D051436:Renal Insufficiency, Chronic / Q000175:diagnosis* / Q000378:metabolism; D054928:Validation Studies as Topic; D042582:Vascular Endothelial Growth Factor C / Q000378:metabolism*
chemical_list: C525819:BMP7 protein, human; D015415:Biomarkers; D055419:Bone Morphogenetic Protein 7; D047908:Intracellular Signaling Peptides and Proteins; C493170:TRIB1 protein, human; D042582:Vascular Endothelial Growth Factor C; D017346:Protein Serine-Threonine Kinases