title: Transcriptional analysis of the molecular basis of human kidney aging using cDNA microarray profiling.
abstract: BACKGROUND
  The molecular basis of renal aging is not completely understood.
  
  
  METHODS
  We used global gene expression monitoring by cDNA microarrays to identify age associated genes in human kidney samples. Our samples included young (8 weeks-8 years, N= 4), adult (31-46 years, N= 7), and old kidneys (71-88 years, N= 9).
  
  
  RESULTS
  Old kidneys had more glomerulosclerosis, tubular atrophy, interstitial fibrosis, and fibrous intimal thickening in small arteries. We identified approximately 500 genes that were differentially expressed among the three age groups. Old kidneys appeared to have increased extracellular matrix turnover and a nonspecific inflammatory response, combined with a reduction in processes dependent on energy metabolism and mitochondrial function. Quantitative supervised bioinformatics analyses of adult and old kidney expression data correlated the expression of 255 gene profiles with renal pathology scores. Microarray class prediction analysis (PAM) identified 50 unique genes that segregated old kidneys into two distinct clusters: those more similar within age class (OO, N= 5) versus old kidneys more similar to adult kidneys (OA, N= 4). The expression of six functionally significant genes was further validated by quantitative reverse transcription-polymerase chain reaction (RT-PCR) (FN1, MMP7, TNC, SERPIN3A, BPHL, CSPG2) in the experiment group and, subsequently, confirmed independently in 17 additional old and adult age-stratified test kidney samples. The p53 inducible gene, CSPG2, performed best in separating OO kidneys from adults and OA samples in this analysis.
  
  
  CONCLUSIONS
  The method described in this study using independent validation samples can be envisioned to test utility of the identified genes in assessing age-related changes that contribute to decline in renal function.
authors.affiliation: Division of Nephrology and Transplantation Immunology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada. anette.melk@med.uni-heidelberg.de
authors.forename: Anette
authors.initials: A
authors.lastname: Melk
authors.forename: Elaine S
authors.initials: ES
authors.lastname: Mansfield
authors.forename: Szu-Chuan
authors.initials: SC
authors.lastname: Hsieh
authors.forename: Tina
authors.initials: T
authors.lastname: Hernandez-Boussard
authors.forename: Paul
authors.initials: P
authors.lastname: Grimm
authors.forename: David C
authors.initials: DC
authors.lastname: Rayner
authors.forename: Philip F
authors.initials: PF
authors.lastname: Halloran
authors.forename: Minnie M
authors.initials: MM
authors.lastname: Sarwal
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000235:genetics* / Q000473:pathology; D051925:CD79 Antigens / Q000378:metabolism; D002648:Child; D002675:Child, Preschool; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D007150:Immunohistochemistry; D007223:Infant; D007668:Kidney / Q000473:pathology / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D020133:Reverse Transcriptase Polymerase Chain Reaction; D014158:Transcription, Genetic
chemical_list: D051925:CD79 Antigens