Abstract
Peritoneal dialysis (PD) is one therapeutic option for patients with end-stage kidney disease (ESKD). Molecular profiling of samples from PD patients using different Omics technologies has led to the discovery of dysregulated molecular processes due to PD treatment in recent years. In particular, a number of transcriptomics (TX) datasets are currently available in the public domain in the context of PD. We set out to perform a meta-analysis of TX datasets to identify dysregulated receptor-ligand interactions in the context of PD-associated complications. We consolidated transcriptomics profiles from twelve untargeted genome-wide gene expression studies focusing on human cell cultures or samples from human PD patients. Gene set enrichment analysis was used to identify enriched biological processes. Receptor-ligand interactions were identified using data from CellPhoneDB. We identified 2591 unique differentially expressed genes in the twelve PD studies. Key enriched biological processes included angiogenesis, cell adhesion, extracellular matrix organization, and inflammatory response. We identified 70 receptor-ligand interaction pairs, with both interaction partners being dysregulated on the transcriptional level in one of the investigated tissues in the context of PD. Novel receptor-ligand interactions without prior annotation in the context of PD included BMPR2-GDF6, FZD4-WNT7B, ACKR2-CCL2, or the binding of EPGN and EREG to the EGFR, as well as the binding of SEMA6D to the receptors KDR and TYROBP. In summary, we have consolidated human transcriptomics datasets from twelve studies in the context of PD and identified sets of novel receptor-ligand pairs being dysregulated in the context of PD that warrant investigation in future functional studies.
Highlights
Other studies have investigated the impact of optimized Peritoneal dialysis (PD) fluids on gene expression as compared with control medium, with one study investigating the differences in gene expression patterns when comparing peritoneal cells from long-term PD patients versus short-term PD patients
We identified 3179 differentially expressed transcripts in total that were mapped to 2591 unique differentially expressed genes (DEGs), and 1360 genes were reported to be upregulated in the diseased/damaged state as compared with the control group, with 1346 genes showing downregulation in the diseased/damaged state
Among the receptor-ligand pairs, we found a few well-studied interactions such as the links between TGFB2 and its two receptors TGFBR2 and TGFBR3, and the binding of certain isoforms of the vascular endothelial growth factor (VEGFA and VEGFD) to the kinase insert domain receptor (KDR), fms-related receptor tyrosine kinase 1 (FLT1), and neuropilin 1 (NRP1) in the context of angiogenesis
Summary
Peritoneal dialysis is one therapeutic option next to hemodialysis and renal transplantation for patients with end-stage kidney disease. High-throughput omics technologies such as microarrays, RNA-sequencing, or proteomics methods allow for simultaneous measurements of thousands of molecular features and support elucidation of dysregulated processes in diseases along with the identification of molecular biomarkers and novel drug targets. A combined analysis of transcriptomics and proteomics data in the context of PD recently led to the identification of the beneficial impact of lithium on peritoneal membrane integrity, demonstrating that an integrated analysis of Omics data can lead to novel therapeutic strategies [3]. A number of individual Omics studies in the context of PD have been published in the past couple of years investigating the impact of different dialysis fluids or different additives on patient outcome and the discovery of associated molecular pathways [4,5]. Gene expression profiling has been used to characterize changes on the transcriptional level in different cell types such as mesothelial cells, peritoneal cells, and endothelial cells, as well as in peripheral blood mononuclear cells (PBMCs) playing a major role in inflammatory responses linked to PD-associated complications
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