Assessment of ‘molecular organ age’ in pre-transplant kidney biopsies
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE222868 | GEO | 2024/08/16
REPOSITORIES: GEO
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Project description:Histologic assessment of kidney transplant biopsies relies on cortex rather than medulla, but for microarray studies, the proportion cortex in a biopsy is typically unknown and could affect the molecular readings. The present study aimed to develop a molecular estimate of proportion cortex in biopsies and examine its effect on molecular diagnoses. Microarrays from 26 kidney transplant biopsies divided into cortex and medulla components and processed separately showed that many of the most significant differences were in glomerular genes e.g. NPHS2, NPHS1, CLIC5, PTPRO, PLA2R1, PLCE1, PODXL and REN. Using NPHS2 (podocin) to estimate proportion cortex, we examined whether proportion cortex influenced molecular assessment in the Molecular Microscope Diagnostic System. In 1190 unselected kidney transplant indication biopsies (Clinicaltrials.govNCT01299168), only 11% had <50% cortex. Molecular scores for ABMR, TCMR, and injury were independent of proportion cortex. Rejection was diagnosed in many biopsies that were mostly or all medulla. Agreement in molecular diagnoses in paired cortex/medulla samples (23/26) was similar to biological replicates (32/37). We conclude that NPHS2 expression can estimate proportion cortex; that proportion cortex has little influence on molecular diagnosis of rejection, and that, although histology cannot assess medulla, rejection does occur in medulla as well as cortex.
2017-04-27 | GSE95611 | GEO
Project description:Histologic assessment of kidney transplant biopsies relies on cortex rather than medulla, but for microarray studies, the proportion cortex in a biopsy is typically unknown and could affect the molecular readings. The present study aimed to develop a molecular estimate of proportion cortex in biopsies and examine its effect on molecular diagnoses. Microarrays from 26 kidney transplant biopsies divided into cortex and medulla components and processed separately showed that many of the most significant differences were in glomerular genes e.g. NPHS2, NPHS1, CLIC5, PTPRO, PLA2R1, PLCE1, PODXL and REN. Using NPHS2 (podocin) to estimate proportion cortex, we examined whether proportion cortex influenced molecular assessment in the Molecular Microscope Diagnostic System. In 1190 unselected kidney transplant indication biopsies (Clinicaltrials.govNCT01299168), only 11% had <50% cortex. Molecular scores for ABMR, TCMR, and injury were independent of proportion cortex. Rejection was diagnosed in many biopsies that were mostly or all medulla. Agreement in molecular diagnoses in paired cortex/medulla samples (23/26) was similar to biological replicates (32/37). We conclude that NPHS2 expression can estimate proportion cortex; that proportion cortex has little influence on molecular diagnosis of rejection, and that, although histology cannot assess medulla, rejection does occur in medulla as well as cortex. We studied 26 pairs of cortex/medulla biopsies from 26 patients (4 unpaired), characterizing the clinical and histological features, and defined the mRNA phenotype with Affymetrix expression microarrays. We also studied 37 pairs of biopsies from biological replicates and 12 pairs from technical replicates. This dataset is part of the TransQST collection.
2017-04-27 | E-GEOD-95611 | biostudies-arrayexpress
Project description:We microdissected kidneys into inner medulla, outer medulla inner stripe, outer medulla outer stripe and cortex.
2022-06-02 | PXD007749 | Pride
Project description:We analyzed the transcriptomes from 81139 cells from 5 kidney transplant biopsies. We sequenced the germline coding sequence from donor and recipient pairs corresponding to each biopsy as a reference to determine donor host chimerism in each kidney.
2020-07-22 | GSE145927 | GEO
Project description:Molecular phenotyping of biopsies affords opportunities for increased precision and improved disease classification to address the limitations of conventional histologic diagnostic systems. We applied archetypal analysis, an unsupervised method similar to cluster analysis, to microarray data from 1208 prospectively collected kidney transplant biopsies from 13 centers. Seven machine learning-generated cross-validated classifier scores per biopsy were used as input for the archetypal analysis. Six archetypes representing extreme phenotypes were generated: no rejection; T cell-mediated rejection (TCMR); three phenotypes associated with antibody-mediated rejection (ABMR) - early-stage, fully-developed, and late-stage; and mixed rejection (TCMR plus early-stage ABMR). Each biopsy was assigned six scores, one for each archetype, that together represent a probabilistic assessment of that biopsy based on its rejection-related molecular properties. Viewed as clusters, the archetypes were similar to existing histologic Banff categories, but there was 32% disagreement, much of it probably reflecting the “noise” in the current histologic assessment system. Graft survival was worst for fully-developed and late-stage ABMR and was better predicted by molecular archetype scores than histologic diagnoses. The results provide a system for precision molecular assessment of biopsies and a new standard for recalibrating conventional diagnostic systems. (ClinicalTrials.gov NTC1299168)
2017-07-10 | GSE98320 | GEO
Project description:Molecular phenotyping of biopsies affords opportunities for increased precision and improved disease classification to address the limitations of conventional histologic diagnostic systems. We applied archetypal analysis, an unsupervised method similar to cluster analysis, to microarray data from 1208 prospectively collected kidney transplant biopsies from 13 centers. Seven machine learning-generated cross-validated classifier scores per biopsy were used as input for the archetypal analysis. Six archetypes representing extreme phenotypes were generated: no rejection; T cell-mediated rejection (TCMR); three phenotypes associated with antibody-mediated rejection (ABMR) - early-stage, fully-developed, and late-stage; and mixed rejection (TCMR plus early-stage ABMR). Each biopsy was assigned six scores, one for each archetype, that together represent a probabilistic assessment of that biopsy based on its rejection-related molecular properties. Viewed as clusters, the archetypes were similar to existing histologic Banff categories, but there was 32% disagreement, much of it probably reflecting the “noise” in the current histologic assessment system. Graft survival was worst for fully-developed and late-stage ABMR and was better predicted by molecular archetype scores than histologic diagnoses. The results provide a system for precision molecular assessment of biopsies and a new standard for recalibrating conventional diagnostic systems. (ClinicalTrials.gov NTC1299168) We applied archetypal analysis, an unsupervised method similar to cluster analysis, to microarray data from 1208 prospectively collected kidney transplant biopsies from 13 centers. This dataset is part of the TransQST collection.
2017-07-10 | E-GEOD-98320 | biostudies-arrayexpress
Project description:The effect of cortex/medulla proportions on molecular diagnoses in kidney transplant biopsies: rejection and injury can be assessed in medulla
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Project description:This SuperSeries is composed of the following subset Series: GSE28283: Renal cortex microRNA expression differences between hypertensive and normotensive patients GSE28344: Renal medulla microRNA expression differences between hypertensive and normotensive patients GSE28345: Renal cortex expression differences between hypertensive and normotensive patients GSE28360: Renal medulla expression differences between hypertensive and normotensive patients Refer to individual Series
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