| 1. |
- Heinzel, Andreas, et al.
(författare)
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Validation of Plasma Biomarker Candidates for the Prediction of eGFR Decline in Patients With Type 2 Diabetes
- 2018
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Ingår i: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 41:9, s. 1947-1954
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Tidskriftsartikel (refereegranskat)abstract
- RESEARCH DESIGN AND METHODS: We studied participants in PROVALID (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers), a prospective multinational cohort study of patients with type 2 diabetes and a follow-up of more than 24 months (n = 2,560; baseline median eGFR, 84 mL/min/1.73 m2; urine albumin-to-creatinine ratio, 8.1 mg/g). The 17 biomarkers were measured at baseline in 481 samples using Luminex and ELISA. The prediction of eGFR decline was evaluated by linear mixed modeling.RESULTS: In univariable analyses, 9 of the 17 markers showed significant differences in median concentration between stable and fast-progressing patients. A linear mixed model for eGFR obtained by variable selection exhibited an adjusted R2 of 62%. A panel of 12 biomarkers was selected by the procedure and accounted for 34% of the total explained variability, of which 32% was due to 5 markers. The individual contribution of each biomarker to the prediction of eGFR decline on top of clinical predictors was generally low. When included into the model, baseline eGFR exhibited the largest explained variability of eGFR decline (R2 of 79%), and the contribution of each biomarker dropped below 1%.CONCLUSIONS: In this longitudinal study of patients with type 2 diabetes and maintained eGFR at baseline, 12 of the 17 candidate biomarkers were associated with eGFR decline, but their predictive power was low.OBJECTIVE: The decline of estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes is variable, and early interventions would likely be cost-effective. We elucidated the contribution of 17 plasma biomarkers to the prediction of eGFR loss on top of clinical risk factors.
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| 2. |
- Kammer, Michael, et al.
(författare)
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Integrative analysis of prognostic biomarkers derived from multiomics panels helps discrimination of chronic kidney disease trajectories in people with type 2 diabetes
- 2019
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Ingår i: Kidney International. - : Elsevier BV. - 0085-2538. ; 96:6, s. 1381-1388
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Tidskriftsartikel (refereegranskat)abstract
- Clinical risk factors explain only a fraction of the variability of estimated glomerular filtration rate (eGFR) decline in people with type 2 diabetes. Cross-omics technologies by virtue of a wide spectrum screening of plasma samples have the potential to identify biomarkers for the refinement of prognosis in addition to clinical variables. Here we utilized proteomics, metabolomics and lipidomics panel assay measurements in baseline plasma samples from the multinational PROVALID study (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers) of patients with incident or early chronic kidney disease (median follow-up 35 months, median baseline eGFR 84 mL/min/1.73 m2, urine albumin-to-creatinine ratio 8.1 mg/g). In an accelerated case-control study, 258 individuals with a stable eGFR course (median eGFR change 0.1 mL/min/year) were compared to 223 individuals with a rapid eGFR decline (median eGFR decline -6.75 mL/min/year) using Bayesian multivariable logistic regression models to assess the discrimination of eGFR trajectories. The analysis included 402 candidate predictors and showed two protein markers (KIM-1, NTproBNP) to be relevant predictors of the eGFR trajectory with baseline eGFR being an important clinical covariate. The inclusion of metabolomic and lipidomic platforms did not improve discrimination substantially. Predictions using all available variables were statistically indistinguishable from predictions using only KIM-1 and baseline eGFR (area under the receiver operating characteristic curve 0.63). Thus, the discrimination of eGFR trajectories in patients with incident or early diabetic kidney disease and maintained baseline eGFR was modest and the protein marker KIM-1 was the most important predictor.
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| 3. |
- Liu, Peidi, et al.
(författare)
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Transcriptomic and Proteomic Profiling Provides Insight into Mesangial Cell Function in IgA Nephropathy
- 2017
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Ingår i: Journal of the American Society of Nephrology. - : AMER SOC NEPHROLOGY. - 1046-6673 .- 1533-3450. ; 28:10, s. 2961-2972
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Tidskriftsartikel (refereegranskat)abstract
- IgA nephropathy (IgAN), the most common GN worldwide, is characterized by circulating galactose-deficient IgA (gd-IgA) that forms immune complexes. The immune complexes are deposited in the glomerular mesangium, leading to inflammation and loss of renal function, but the complete pathophysiology of the disease is not understood. Using an integrated global transcriptomic and proteomic profiling approach, we investigated the role of the mesangium in the onset and progression of IgAN. Global gene expression was investigated by microarray analysis of the glomerular compartment of renal biopsy specimens from patients with IgAN (n=19) and controls (n=22). Using curated glomerular cell type specific genes from the published literature, we found differential expression of a much higher percentage of mesangial cell positive standard genes than podocyte-positive standard genes in IgAN. Principal coordinate analysis of expression data revealed clear separation of patient and control samples on the basis of mesangial but not podocyte cell positive standard genes. Additionally, patient clinical parameters (serum creatinine values and eGFRs) significantly correlated with Z scores derived from the expression profile of mesangial cell positive standard genes. Among patients grouped according to Oxford MEST score, patients with segmental glomerulosclerosis had a significantly higher mesangial cell positive standard gene Z score than patients without segmental glomerulosclerosis. By investigating mesangial cell proteomics and glomerular transcriptomics, we identified 22 common pathways induced in mesangial cells by gd-IgA, most of which mediate inflammation. The genes, proteins, and corresponding pathways identified provide novel insights into the pathophysiologic mechanisms leading to IgAN.
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| 4. |
- Mulder, Skander, et al.
(författare)
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A metabolomics-based molecular pathway analysis of how the sodium-glucose co-transporter-2 inhibitor dapagliflozin may slow kidney function decline in patients with diabetes
- 2020
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Ingår i: Diabetes, obesity and metabolism. - : WILEY. - 1462-8902 .- 1463-1326. ; 22:7, s. 1157-1166
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Tidskriftsartikel (refereegranskat)abstract
- Aim To investigate which metabolic pathways are targeted by the sodium-glucose co-transporter-2 inhibitor dapagliflozin to explore the molecular processes involved in its renal protective effects. Methods An unbiased mass spectrometry plasma metabolomics assay was performed on baseline and follow-up (week 12) samples from the EFFECT II trial in patients with type 2 diabetes with non-alcoholic fatty liver disease receiving dapagliflozin 10 mg/day (n = 19) or placebo (n = 6). Transcriptomic signatures from tubular compartments were identified from kidney biopsies collected from patients with diabetic kidney disease (DKD) (n = 17) and healthy controls (n = 30) from the European Renal cDNA Biobank. Serum metabolites that significantly changed after 12 weeks of dapagliflozin were mapped to a metabolite-protein interaction network. These proteins were then linked with intra-renal transcripts that were associated with DKD or estimated glomerular filtration rate (eGFR). The impacted metabolites and their protein-coding transcripts were analysed for enriched pathways. Results Of all measured (n = 812) metabolites, 108 changed (P < 0.05) during dapagliflozin treatment and 74 could be linked to 367 unique proteins/genes. Intra-renal mRNA expression analysis of the genes encoding the metabolite-associated proteins using kidney biopsies resulted in 105 genes that were significantly associated with eGFR in patients with DKD, and 135 genes that were differentially expressed between patients with DKD and controls. The combination of metabolites and transcripts identified four enriched pathways that were affected by dapagliflozin and associated with eGFR: glycine degradation (mitochondrial function), TCA cycle II (energy metabolism), L-carnitine biosynthesis (energy metabolism) and superpathway of citrulline metabolism (nitric oxide synthase and endothelial function). Conclusion The observed molecular pathways targeted by dapagliflozin and associated with DKD suggest that modifying molecular processes related to energy metabolism, mitochondrial function and endothelial function may contribute to its renal protective effect.
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| 5. |
- Zeng, Bo, et al.
(författare)
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Orai channels are critical for receptor-mediated endocytosis of albumin
- 2017
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Impaired albumin reabsorption by proximal tubular epithelial cells (PTECs) has been highlighted in diabetic nephropathy (DN), but little is known about the underlying molecular mechanisms. Here we find that ORAI1-3, are preferentially expressed in PTECs and downregulated in patients with DN. Hyperglycemia or blockade of insulin signaling reduces the expression of ORAI1-3. Inhibition of ORAI channels by BTP2 and diethylstilbestrol or silencing of ORAI expression impairs albumin uptake. Transgenic mice expressing a dominant-negative Orai1 mutant (E108Q) increases albuminuria, and in vivo injection of BTP2 exacerbates albuminuria in streptozotocin-induced and Akita diabetic mice. The albumin endocytosis is Ca2+-dependent and accompanied by ORAI1 internalization. Amnionless (AMN) associates with ORAIs and forms STIM/ORAI/AMN complexes after Ca2+ store depletion. STIM1/ORAI1 colocalizes with clathrin, but not with caveolin, at the apical membrane of PTECs, which determines clathrin-mediated endocytosis. These findings provide insights into the mechanisms of protein reabsorption and potential targets for treating diabetic proteinuria.
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