Dataset Information

Interferon-γ signaling in the progression from early to end stage kidney disease in type 2 diabetes

ABSTRACT: The effects of circulating pro-inflammatory factors on diabetic kidney disease (DKD) progression remain poorly defined. In this study, transcriptional and proteomic profiling of kidney tissue and blood samples from individuals with type 2 diabetes mellitus and early DKD was used to identify gene expression associated with kidney disease progression. Interferon gamma (IFNG) was both identified as an upstream regulator of gene expression and detected in the serum of individuals who progressed. Individual IFNG activation scores (representing summary expression of 72 downstream signaling mediators) early in disease correlated with DKD progression over an average of 9.7 years. IFNG pathway inhibition reduced gene activity associated with DKD progression in both kidney organoids generated from human pluripotent stem cells and mouse DKD models. Thus, expression of genes associated with IFNG activity early in DKD predicted disease progression; individuals demonstrating IFNG activity may benefit from targeted therapeutics early in the disease course.

ORGANISM(S): Homo sapiens

PROVIDER: GSE230848 | GEO | 2024/05/13

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Dyslipidemia is a significant risk factor for progression of diabetic kidney disease (DKD). To identify individual lipids and lipid networks that may be involved in DKD progression, we performed untargeted lipidomic analysis of kidney cortex tissue from diabetic db/db and db/db eNOS-/- mice along with nondiabetic littermate controls. A subset of mice were treated with the renin-angiotensin system (RAS) inhibitors, lisinopril and losartan, which improves the DKD phenotype in the db/db eNOS-/- mouse model. Of the three independent variables in this study, diabetes had the largest impact on overall lipid levels in the kidney cortex, while eNOS expression and RAS inhibition had smaller impacts on kidney lipid levels. Kidney lipid network architecture, particularly of networks involving glycerolipids such as triacylglycerols, was substantially disrupted by worsening kidney disease in the db/db eNOS-/- mice compared to the db/db mice, a feature that was reversed with RAS inhibition. This was associated with decreased expression of the stearoyl-CoA desaturases, Scd1 and Scd2, with RAS inhibition. In addition to the known salutary effect of RAS inhibition on DKD progression, our results suggest a previously unrecognized role for RAS inhibition on the kidney triacylglycerol lipid metabolic network. Keywords: Dyslipidemia is a significant risk factor for progression of diabetic kidney disease (DKD). To identify individual lipids and lipid networks that may be involved in DKD progression, we performed untargeted lipidomic analysis of kidney cortex tissue from diabetic db/db and db/db eNOS-/- mice along with non-diabetic littermate controls. A subset of mice were treated with the renin-angiotensin system (RAS) inhibitors, lisinopril and losartan, which improves the DKD phenotype in the db/db eNOS-/- mouse model. Of the three independent variables in this study, diabetes had the largest impact on overall lipid levels in the kidney cortex, while eNOS expression and RAS inhibition had smaller impacts on kidney lipid levels. Kidney lipid network architecture, particularly of networks involving glycerolipids such as triacylglycerols, was substantially disrupted by worsening kidney disease in the db/db eNOS-/- mice compared to the db/db mice, a feature that was reversed with RAS inhibition. This was associated with decreased expression of the stearoyl-CoA desaturases, Scd1 and Scd2, with RAS inhibition. In addition to the known salutary effect of RAS inhibition on DKD progression, our results suggest a previously unrecognized role for RAS inhibition on the kidney triacylglycerol lipid metabolic network.

Dataset Information

Interferon-γ signaling in the progression from early to end stage kidney disease in type 2 diabetes

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure