Dataset Information

Multi-omics and imaging mass cytometry characterization of human kidneys to identify pathways and phenotypes associated with kidney damage

ABSTRACT: Despite the recent advances in our understanding of the role of lipids, metabolites and related enzymes in mediating kidney injury, there is limited integrated multi-omics data identifying potential metabolic pathways driving human kidney damage (KD). The limited availability of kidney biopsies from living donors with kidney disease has remained a major constraint. Here, we validated the use of deceased transplant donor kidneys as a good model to study kidney disease in humans and characterized these kidneys using imaging and multi-omics approaches. We demonstrated that changes in kidney injury and inflammatory markers following KD were consistent with the changes in pre-donation renal function in donors. Neighborhood and correlation analyses of imaging mass cytometry data showed that a subset of renal cells (e.g., fibroblasts) are associated with the expression profile of renal immune cells, potentially linking these cells to kidney inflammation. Integrated transcriptomic and metabolomic analysis of human kidneys showed that renal arachidonic acid metabolism and seven other metabolic pathways were upregulated following KD. To validate the therapeutic potential of targeting the arachidonic acid pathway, we demonstrated increased levels of cytosolic phospholipase A2 (cPLA2) protein and related lipid mediators (e.g., prostaglandin E2) in the injured kidneys. The inhibition of cPLA2 reduced injury and inflammation in human renal proximal tubular epithelial cells (RPTEC) in vitro. This study identifies cell types and metabolic pathways that may be critical for controlling inflammation associated with KD in humans.

ORGANISM(S): Homo sapiens

PROVIDER: GSE217427 | GEO | 2022/11/10

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Metabolic syndrome is a growing global health problem and is strongly associated with the development of chronic kidney disease (CKD). Recently, the prevalence of CKD has been increasing worldwide, particularly among the older adults. We previously demonstrated that aged kidneys are prone to developing tertiary lymphoid tissues (TLTs) and sustain chronic inflammation after injury; however, the relationship between renal TLT formation and metabolic syndrome is unknown. In the present study, we demonstrated that high-fat diet (HFD) feeding partly promoted TLT formation and chronic inflammation in the kidneys via sterol-O acyltransferase (SOAT) 1-dependent lipid deposition. Wild-type mice fed a HFD prior to ischemic reperfusion injury (IRI) exhibited pronounced TLT formation with respect to size, number and maturity in the kidneys, and sustained chronic inflammation compared to the controls. Untargeted lipidomics revealed that the levels of a selective group of lipids, including cholesteryl esters (CEs), were significantly increased in aged kidneys associated with TLT formation after renal IRI. Consistently, the gene expression level of Soat1 was significantly increased in aged kidneys associated with TLT formation after renal IRI. Notably, treatment with avasimibe, a SOAT inhibitor, significantly attenuated TLT maturation and improved renal inflammation and fibrosis in HFD-fed mice subjected to IRI. Together, our findings suggest the importance of dysregulated lipid metabolism, particularly SOAT1-dependent CE accumulation, in the pathophysiology of CKDs associated with TLT formation. Mice+injury analysis (dataset 1) is reported in the current study <a href='https://www.ebi.ac.uk/metabolights/MTBLS4988' rel='noopener noreferrer' target='_blank'>MTBLS4988</a>.Mice+diet analysis (dataset 2) is reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS4994' rel='noopener noreferrer' target='_blank'>MTBLS4994</a>.

Project description:Metabolic syndrome is a growing global health problem and is strongly associated with the development of chronic kidney disease (CKD). Recently, the prevalence of CKD has been increasing worldwide, particularly among the older adults. We previously demonstrated that aged kidneys are prone to developing tertiary lymphoid tissues (TLTs) and sustain chronic inflammation after injury; however, the relationship between renal TLT formation and metabolic syndrome is unknown. In the present study, we demonstrated that high-fat diet (HFD) feeding partly promoted TLT formation and chronic inflammation in the kidneys via sterol-O acyltransferase (SOAT) 1-dependent lipid deposition. Wild-type mice fed a HFD prior to ischemic reperfusion injury (IRI) exhibited pronounced TLT formation with respect to size, number and maturity in the kidneys, and sustained chronic inflammation compared to the controls. Untargeted lipidomics revealed that the levels of a selective group of lipids, including cholesteryl esters (CEs), were significantly increased in aged kidneys associated with TLT formation after renal IRI. Consistently, the gene expression level of Soat1 was significantly increased in aged kidneys associated with TLT formation after renal IRI. Notably, treatment with avasimibe, a SOAT inhibitor, significantly attenuated TLT maturation and improved renal inflammation and fibrosis in HFD-fed mice subjected to IRI. Together, our findings suggest the importance of dysregulated lipid metabolism, particularly SOAT1-dependent CE accumulation, in the pathophysiology of CKDs associated with TLT formation. Mice+diet analysis (dataset 2) is reported in the current study <a href='https://www.ebi.ac.uk/metabolights/MTBLS4994' rel='noopener noreferrer' target='_blank'>MTBLS4994</a>.Mice+injury analysis (dataset 1) is reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS4988' rel='noopener noreferrer' target='_blank'>MTBLS4988</a>.

Project description:Microarray analysis of human kidneys with acute kidney injury (AKI) has been limited because such kidneys are seldom biopsied. However, all kidney transplants experience AKI, and early kidney transplants without rejection are an excellent model for human AKI: they are screened to exclude chronic kidney disease, frequently biopsied, and have extensive follow-up. We used histopathology and microarrays to compare indication biopsies from 28 transplants with AKI to 11 pristine protocol biopsies of stable transplants. Kidneys with AKI showed increased expression of 394 injury-repair response associated transcripts, including many known epithelial injury molecules (e.g. ITGB6, LCN2), tissue remodeling molecules (e.g. VCAN), and inflammation molecules (S100A8, ITGB3). Many other genes also predict the phenotype, depending on statistical filtering rules, including AKI biomarkers as HAVCR1 and IL18. Most mouse orthologs of the top injury-repair transcripts were increased in published mouse AKI models. Pathway analysis of the injury-repair transcripts revealed similarities to cancer, development, and cell movement. The injury-repair transcript score AKI kidneys correlated with reduced function, future recovery, brain death, and need for dialysis, but not future graft loss. In contrast, histologic features of "acute tubular injury" did not correlate with function or with the molecular changes. Thus the injury-repair associated transcripts represent a massive coordinate injury-repair response of kidney parenchyma to AKI, similar to mouse AKI models, and provide an objective measure for assessing the severity of AKI in kidney biopsies and validation for the use of many AKI biomarkers. AKI biopsies sample names and CEL files are from GSE21374. All consenting renal transplant patients undergoing biopsies for cause as standard of care between 09/2004 and 10/2007 at the university of Alberta or between 11/2006 and 02/2007 at the University of Illinois were included in the analysis. In addition to the cores required for standard histopathology, we collected one core for gene expression studies. the relationship between gene expression in the biopsy and subsequent graft loss was analyzed. This dataset is part of the TransQST collection.

Dataset Information

Multi-omics and imaging mass cytometry characterization of human kidneys to identify pathways and phenotypes associated with kidney damage

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets