Dataset Information

GNPS - Serum integrative omics reveals the landscape of human diabetic kidney disease

ABSTRACT: Diabetic kidney disease (DKD) is the most common microvascular complication of type 2 diabetes mellitus (2-DM). Currently, urine and kidney biopsy specimens are the major clinical resources for DKD diagnosis. The diagnostic values of blood in monitoring the onset and progression of DKD have not been well explored. To fully describe the biological changes in human blood after DKD, we recruited 1,513 participants including healthy adults and patients diagnosed with 2-DM, early stage of DKD (DKD-E), and advanced stage of DKD (DKD-A) from 4 independent medical centers. The collected serums were subjected to pilot proteomics and large-scale metabolomics, respectively. By performing deep profiling of serum proteomes and metabolomes, several insights were revealed. First, the pilot proteomics revealed that the combination of alpha 2-Macroglobulin, Cathepsin D, and CD324 served as a surrogate protein biomarker in monitoring DKD progression. Second, metabolomics demonstrated that galactose metabolism and glycerolipid metabolism are the major disturbed metabolic pathways in DKD. Serum metabolite, glycerol-3-galactoside, is an independent marker in predicting DKD. Third, integrating proteomics and metabolomics increased the diagnostic and predictive stability and accuracy in distinguishing DKD status. Our study provides a rich and open-access data resource to shed light on optimizing the management of diabetes.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Dong Zhou

PROVIDER: MSV000087487 | GNPS | Sat May 22 15:26:00 BST 2021

REPOSITORIES: GNPS

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Serum integrative omics reveals the landscape of human diabetic kidney disease.

Liu Shijia S Gui Yuan Y Wang Mark S MS Zhang Lu L Xu Tingting T Pan Yuchen Y Zhang Ke K Yu Ying Y Xiao Liangxiang L Qiao Yi Y Bonin Christopher C Hargis Geneva G Huan Tao T Yu Yanbao Y Tao Jianling J Zhang Rong R Kreutzer Donald L DL Zhou Yanjiao Y Tian Xiao-Jun XJ Wang Yanlin Y Fu Haiyan H An Xiaofei X Liu Silvia S Zhou Dong D

Molecular metabolism 20211101

<h4>Objective</h4>Diabetic kidney disease (DKD) is the most common microvascular complication of type 2 diabetes mellitus (2-DM). Currently, urine and kidney biopsy specimens are the major clinical resources for DKD diagnosis. Our study proposes to evaluate the diagnostic value of blood in monitoring the onset of DKD and distinguishing its status in the clinic.<h4>Methods</h4>This study recruited 1,513 participants including healthy adults and patients diagnosed with 2-DM, early-stage DKD (DKD-E ...[more]

PMID: 34737094

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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.