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Home › Dataset Library › Analyses of heterogeneous renal allograft biopsies reveal conserved rejection signatures and molecular pathways I, partB

Dataset: Analyses of heterogeneous renal allograft biopsies reveal conserved rejection signatures and molecular pathways I, partB

Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize...

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Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining “molecular Banff” signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set comprises all renal allograft biopsies for clinical indications from patients at Hôpital Tenon, Paris (February 2003 until September 2004) and few respective patients from Hôpital Bicêtre, Paris, Hôpital Pellegrin, Bordeaux, and Hôpital Dupuytren, Limoges, plus control normal kidney samples from Hôpital Tenon, Paris, France (first batch). We used microarrays to identify different gene expression signatures of renal allograft biopsies that can classify them according to different types of allograft rejection or CAN. Keywords: disease state analysis Keywords: Expression profiling by array 16 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to BANFF'97 criteria (additional samples associated with GSE9489)

Species:
human

Samples:
16

Source:
E-GEOD-17861

PubMed:
19017305

Updated:
Dec.12, 2014

Registered:
Sep.15, 2014


Factors: (via ArrayExpress)
Sample AGE OF PATIENT PATIENT IDENTIFIER SERUM CREATININE RENAL GRAFT BX SEX 97
GSM442670 53 4285557 107 microMol/L Z01 female non-rejecting
GSM44267 52 7409460 n.d. Renal graft bx: Z02 not specified female non-rejecting
GSM442672 47 652033 94 microMol/L Z05 male borderline changes
GSM442673 53 525928 167 microMol/L Z06 male non-rejecting
GSM442674 53 525928 163 microMol/L Z07 male AR IB, IIA
GSM442675 45 718181 95 microMol/L Z10 male non-rejecting
GSM442676 45 718181 106 microMol/L Z11 male non-rejecting
GSM442677 30 7358285 159 microMol/L Z13 male non-rejecting
GSM442678 64 7974116 115 microMol/L Z14 female non-rejecting
GSM442679 64 7974116 114 microMol/L Z15 female non-rejecting
GSM442680 53 2727137 117 microMol/L Z16 male non-rejecting
GSM44268 29 4260341 152 microMol/L Z17 male non-rejecting
GSM442682 29 4260341 108 microMol/L Z18 male non-rejecting
GSM442683 59 4138406 144 microMol/L Z19 male AR IIA
GSM442684 52 7409460 n.d. microMol/L Z20 female non-rejecting
GSM442685 30 6836879 94 microMol/L Z21 female non-rejecting

Tags

  • disease
  • kidney

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