Dataset Information

A Functional Landscape of CKD Entities From Public Transcriptomic Data.

ABSTRACT: Introduction:To develop effective therapies and identify novel early biomarkers for chronic kidney disease, an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in chronic kidney disease (CKD) origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for 9 kidney disease entities that account for most of CKD worldwide. Our primary goal was to demonstrate the possibilities and potential on data analysis and integration to the nephrology community. Methods:We integrated data from 5 publicly available studies and compared glomerular gene expression profiles of disease with that of controls from nontumor parts of kidney cancer nephrectomy tissues. A major challenge was the integration of the data from different sources, platforms, and conditions that we mitigated with a bespoke stringent procedure. Results:We performed a global transcriptome-based delineation of different kidney disease entities, obtaining a transcriptomic diffusion map of their similarities and differences based on the genes that acquire a consistent differential expression between each kidney disease entity and nephrectomy tissue. We derived functional insights by inferring the activity of signaling pathways and transcription factors from the collected gene expression data and identified potential drug candidates based on expression signature matching. We validated representative findings by immunostaining in human kidney biopsies indicating, for example, that the transcription factor FOXM1 is significantly and specifically expressed in parietal epithelial cells in rapidly progressive glomerulonephritis (RPGN) whereas not expressed in control kidney tissue. Furthermore, we found drug candidates by matching the signature on expression of drugs to that of the CKD entities, in particular, the Food and Drug Administration-approved drug nilotinib. Conclusion:These results provide a foundation to comprehend the specific molecular mechanisms underlying different kidney disease entities that can pave the way to identify biomarkers and potential therapeutic targets. To facilitate further use, we provide our results as a free interactive Web application: https://saezlab.shinyapps.io/ckd_landscape/. However, because of the limitations of the data and the difficulties in its integration, any specific result should be considered with caution. Indeed, we consider this study rather an illustration of the value of functional genomics and integration of existing data.

SUBMITTER: Tajti F

PROVIDER: S-EPMC7000845 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Functional Landscape of CKD Entities From Public Transcriptomic Data.

Tajti Ferenc F Kuppe Christoph C Antoranz Asier A Ibrahim Mahmoud M MM Kim Hyojin H Ceccarelli Francesco F Holland Christian H CH Olauson Hannes H Floege Jürgen J Alexopoulos Leonidas G LG Kramann Rafael R Saez-Rodriguez Julio J

Kidney international reports 20191113 2

<h4>Introduction</h4>To develop effective therapies and identify novel early biomarkers for chronic kidney disease, an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in chronic kidney disease (CKD) origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for 9 kidney disease entities that account for most of CKD worldwide. Our primary goal was to ...[more]

PMID: 32043035

Similar Datasets

Project description:While recent integrative analyses of copy number and gene expression data in breast cancer have revealed a complex molecular landscape with multiple subtypes and many oncogenic/tumour suppressor driver events, much less is known about the role of DNA methylation in shaping breast cancer taxonomy and defining driver events.Here, we applied a powerful integrative network algorithm to matched DNA methylation and RNA-Seq data for 724 estrogen receptor (ER)-positive (ER+) breast cancers and 111 normal adjacent tissue specimens from The Cancer Genome Atlas (TCGA) project, in order to identify putative epigenetic driver events and to explore the resulting molecular taxonomy. This revealed the existence of nine functionally deregulated epigenetic hotspots encompassing a total of 146 genes, which we were able to validate in independent data sets encompassing over 1000 ER+ breast cancers. Integrative clustering of the matched messenger RNA (mRNA) and DNA methylation data over these genes resulted in only two clusters, which correlated very strongly with the luminal-A and luminal B subtypes. Overall, luminal-A and luminal-B breast cancers shared the same epigenetically deregulated hotspots but with luminal-B cancers exhibiting increased aberrant DNA methylation patterns relative to normal tissue. We show that increased levels of DNA methylation and mRNA expression deviation from the normal state define a marker of poor prognosis. Our data further implicates epigenetic silencing of WNT signalling antagonists and bone morphogenetic proteins (BMP) as key events underlying both luminal subtypes but specially of luminal-B breast cancer. Finally, we show that DNA methylation changes within the identified epigenetic interactome hotspots do not exhibit mutually exclusive patterns within the same cancer sample, instead exhibiting coordinated changes within the sample.Our results indicate that the integrative DNA methylation and transcriptomic landscape of ER+ breast cancer is surprisingly homogeneous, defining two main subtypes which strongly correlate with luminal-A/B subtype status. In particular, we identify WNT and BMP signalling as key epigenetically deregulated tumour suppressor pathways in luminal ER+ breast cancer, with increased deregulation seen in luminal-B breast cancer.

Project description:ImportanceThree-dimensional cerebral organoids generated from patient-derived induced pluripotent stem cells (iPSCs) may be used to interrogate cellular-molecular underpinnings of schizophrenia.ObjectiveTo determine transcriptomic profiles and functional characteristics of cerebral organoids from patients with schizophrenia using gene expression studies, complemented with investigations of mitochondrial function through measurement of real-time oxygen consumption rate, and functional studies of neuronal firing with microelectrode arrays.Design, setting, and participantsThis case-control study was conducted at Massachusetts General Hospital between 2017 and 2019. Transcriptomic profiling of iPSC-derived cerebral organoids from 8 patients with schizophrenia and 8 healthy control individuals was undertaken to identify cellular pathways that are aberrant in schizophrenia. Induced pluripotent stem cells and cerebral organoids were generated from patients who had been diagnosed as having schizophrenia and from heathy control individuals.Main outcomes and measuresTranscriptomic analysis of iPSC-derived cerebral organoids from patients with schizophrenia show differences in expression of genes involved in synaptic biology and neurodevelopment and are enriched for genes implicated in schizophrenia genome-wide association studies (GWAS).ResultsThe study included iPSC lines generated from 11 male and 5 female white participants, with a mean age of 38.8 years. RNA sequencing data from iPSC-derived cerebral organoids in schizophrenia showed differential expression of genes involved in synapses, in nervous system development, and in antigen processing. The differentially expressed genes were enriched for genes implicated in schizophrenia, with 23% of GWAS genes showing differential expression in schizophrenia and control organoids: 10 GWAS genes were upregulated in schizophrenia organoids while 15 GWAS genes were downregulated. Analysis of the gene expression profiles suggested dysregulation of genes involved in mitochondrial function and those involved in modulation of excitatory and inhibitory pathways. Studies of mitochondrial respiration showed lower basal consumption rate, adenosine triphosphate production, proton leak, and nonmitochondrial oxygen consumption in schizophrenia cerebral organoids, without any differences in the extracellular acidification rate. Microelectrode array studies of cerebral organoids showed no differences in baseline electrical activity in schizophrenia but revealed a diminished response to stimulation and depolarization.Conclusions and relevanceInvestigations of patient-derived cerebral organoids in schizophrenia revealed gene expression patterns suggesting dysregulation of a number of pathways in schizophrenia, delineated differences in mitochondrial function, and showed deficits in response to stimulation and depolarization in schizophrenia.

Dataset Information

A Functional Landscape of CKD Entities From Public Transcriptomic Data.

Publications

A Functional Landscape of CKD Entities From Public Transcriptomic Data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets