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Lopez LN, Durbin-Johnson B, Vargas CR, Ruzinski J, Goodling A, Mehrotra R, Vaisar T, Rocke DM, Afkarian M. Comparative Analysis of Protein Quantification by the SomaScan Assay versus Orthogonal Methods in Urine from People with Diabetic Kidney Disease. J Proteome Res 2024; 23:2598-2607. [PMID: 38965919 DOI: 10.1021/acs.jproteome.4c00322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/06/2024]
Abstract
To our knowledge, calibration curves or other validations for thousands of SomaScan aptamers are not publicly available. Moreover, the abundance of urine proteins obtained from these assays is not routinely validated with orthogonal methods (OMs). We report an in-depth comparison of SomaScan readout for 23 proteins in urine samples from patients with diabetic kidney disease (n = 118) vs OMs, including liquid chromatography-targeted mass spectrometry (LC-MS), ELISA, and nephelometry. Pearson correlation between urine abundance of the 23 proteins from SomaScan 3.2 vs OMs ranged from -0.58 to 0.86, with a median (interquartile ratio, [IQR]) of 0.49 (0.18, 0.53). In multivariable linear regression, the SomaScan readout for 6 of the 23 examined proteins (26%) was most strongly associated with the OM-derived abundance of the same (target) protein. For 3 of 23 (13%), the SomaScan and OM-derived abundance of each protein were significantly associated, but the SomaScan readout was more strongly associated with OM-derived abundance of one or more "off-target" proteins. For the remaining 14 proteins (61%), the SomaScan readouts were not significantly associated with the OM-derived abundance of the targeted proteins. In 6 of the latest group, the SomaScan readout was not associated with urine abundance of any of the 23 quantified proteins. To sum, over half of the SomaScan results could not be confirmed by independent orthogonal methods.
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Affiliation(s)
- Lauren N Lopez
- Division of Nephrology, Department of Medicine, University of California, Davis, California 95616, United States
| | - Blythe Durbin-Johnson
- Division of Biostatistics, Department of Public Health Sciences, School of Medicine, University of California, Davis, California 95616, United States
| | - Chenoa R Vargas
- Division of Nephrology, Department of Medicine, University of California, Davis, California 95616, United States
| | - John Ruzinski
- Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington 98195, United States
| | - Anne Goodling
- Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington 98195, United States
| | - Rajnish Mehrotra
- Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington 98195, United States
| | - Tomas Vaisar
- Diabetes Institute, Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, University of Washington, Seattle,Washington98195,United States
| | - David M Rocke
- Division of Biostatistics, Department of Public Health Sciences, School of Medicine, University of California, Davis, California 95616, United States
| | - Maryam Afkarian
- Division of Nephrology, Department of Medicine, University of California, Davis, California 95616, United States
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Avello A, Guerrero-Mauvecin J, Sanz AB. Urine MMP7 as a kidney injury biomarker. Clin Kidney J 2024; 17:sfad233. [PMID: 38186894 PMCID: PMC10768779 DOI: 10.1093/ckj/sfad233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Indexed: 01/09/2024] Open
Abstract
Matrix metalloproteinase 7 (MMP-7) is a secreted endopeptidase involved in the degradation of extracellular matrix components and the activation of cytokines and growth factors. The regulation of MMP-7 can be transcriptionally regulated by AP-1 or Wnt/β-catenin or post-translationally by proteolytic activation. MMP-7 expression is low or absent in the healthy kidney, but is significantly upregulated in kidney injury, including AKI and CKD. The function of MMP-7 in kidney disease may differ for CKD and AKI; it may have a profibrotic role in CKD and an anti-apoptotic and regenerative function in AKI. Additionally, the potential of MMP-7 as a biomarker has been studied in different kidney diseases, and the results are promising. Recently, combined unbiased kidney proteomics and transcriptomics approaches identified kidney MMP-7 as the protein having the strongest association with both fibrosis and eGFR and confirmed the predictive role of plasma MMP-7 levels for kidney function decline in over 11 000 individuals. Additionally, urinary MMP-7, combined with urinary cystatin C (CysC) and retinol binding protein (RBP) was reported to provide information on tubular injury in focal segmental glomerulosclerosis and minimal change disease. We now present an overview of research on MMP-7 expression and function in kidney diseases and discuss its potential as a biomarker of kidney diseases.
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Affiliation(s)
- Alejandro Avello
- Laboratory of Experimental Nephrology, IIS-Fundacion Jimenez Diaz UAM, Madrid, Spain
| | | | - Ana Belen Sanz
- Laboratory of Experimental Nephrology, IIS-Fundacion Jimenez Diaz UAM, Madrid, Spain
- RICORS2040, Madrid, Spain
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Navarro J, Sanchez A, Ba Aqeel SH, Ye M, Rehman MZ, Wysocki J, Rademaker A, Molitch ME, Batlle D. Urinary Angiotensinogen in Patients With Type 1 Diabetes With Microalbuminuria: Gender Differences and Effect of Intensive Insulin Therapy. Kidney Int Rep 2022; 7:2657-2667. [PMID: 36506234 PMCID: PMC9727532 DOI: 10.1016/j.ekir.2022.09.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 08/25/2022] [Accepted: 09/12/2022] [Indexed: 12/15/2022] Open
Abstract
Introduction Angiotensinogen (AOG) is the precursor of peptides of the renin angiotensin system (RAS). Because insulin up-regulates transcriptional factors that normally repress kidney AOG synthesis, we evaluated urinary AOG (uAOG) in patients with type 1 diabetes (T1D) and microalbuminuria who are receiving either intensive or conventional insulin therapy. Methods Urine samples from participants of the Diabetes Control and Complications Trial (DCCT) were used for the following: (i) uAOG/creatinine measurements in 103 patients with microalbuminuria and 103 patients with normoalbuminuria, matched for age, gender, disease duration, and allocation to insulin therapy; and (ii) uAOG/creatinine measurements from patients with microalbuminuria allocated to intensive insulin therapy (n = 58) or conventional insulin therapy (n = 41) after 3 years on each modality. Results uAOG was higher in patients who started with microalbuminuria than in those with normoalbuminuria (6.65 vs. 4.0 ng/mg creatinine, P < 0.01). uAOG was higher in females than in males with microalbuminuria (11.7 vs. 5.4 ng/mg creatinine, P = 0.015). uAOG was lower in patients with microalbuminuria allocated to intensive insulin therapy than in conventional insulin therapy (3.98 vs. 7.42 ng/mg creatinine, P < 0.01). These differences in uAOG were observed though albumin excretion rate (AER) was not significantly different. Conclusion In patients with T1D and microalbuminuria, uAOG is increased and varies with gender and the type of insulin therapy independently of AER. This suggests that AOG production is increased in females and it is decreased by intensive insulin therapy. The reduction in uAOG with intensive insulin therapy, by kidney RAS downregulation, may contribute to the known renoprotective action associated with intensive insulin and improved glycemic control.
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Affiliation(s)
- Jessica Navarro
- Division of Nephrology and Hypertension, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Alejandro Sanchez
- Division of Nephrology and Hypertension, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Sheeba H. Ba Aqeel
- Division of Nephrology and Hypertension, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Minghao Ye
- Division of Nephrology and Hypertension, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Mohammed Z. Rehman
- Division of Nephrology and Hypertension, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Jan Wysocki
- Division of Nephrology and Hypertension, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Alfred Rademaker
- Division of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Mark E. Molitch
- Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Daniel Batlle
- Division of Nephrology and Hypertension, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA,Correspondence: Daniel Batlle, Division of Nephrology and Hypertension, Department of Medicine, The Feinberg School of Medicine, Northwestern University, 320 E Superior, Chicago, Illinois 60611, USA.
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Al-Regaiey KA, Habib SS, Alshamasi AR, Alnuwaybit AF, Alwhaibi BA, Alsulais NM, Alothman AI, Alomar FM, Iqbal M. Relationship of Plasma Gremlin 1 Levels with Body Adiposity and Glycemic Control in Saudi Female Type 2 Diabetes Patients. Diabetes Metab Syndr Obes 2022; 15:3429-3436. [PMID: 36353668 PMCID: PMC9639591 DOI: 10.2147/dmso.s372146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 10/11/2022] [Indexed: 11/21/2022] Open
Abstract
OBJECTIVE Gremlin 1 is a novel adipokine that plays an important role in obesity and type 2 diabetes mellitus (T2DM). In the current study, we aimed to evaluate plasma levels of Gremlin 1 in diabetic and non-diabetic Saudi adult females and its correlation with body composition, glycemic control and lipid profile. METHODS A case-control study was conducted among 41 T2DM and 31 non-diabetic adult age matched females (controls). All patients underwent body composition by bioelectrical impedance analysis, with a commercially available body analyzer. Fasting venous samples were analyzed for glycemic markers and lipids, while plasma Gremlin 1 was measured by ELISA. The results were compared between the two groups and correlated with other anthropometric and adiposity parameters. RESULTS Gremlin 1 levels were elevated in T2DM patients (345 ± 26 ng/mL) when compared to control subjects (272 ± 16 ng/mL, p < 0.05). Diabetic patients having poor glycemic control had significantly higher Gremlin 1 levels (382 ± 34 ng/mL) compared to patients with good glycemic control (291 ± 37 ng/mL, p < 0.05). Pearson correlation analysis revealed a positive correlation of Gremlin 1 with fat mass (r = 0.246, p = 0.012), HbA1C (r = 0.262, p = 0.008) and HOMA-IR index (r = 0.321, p = 0.001). CONCLUSION Our study demonstrates an important role of Gremlin 1 in glycemic control and body adiposity in the pathophysiology of obesity and T2DM. Gremlin 1 may emerge as a promising biomarker and therapeutic target in obesity and T2DM.
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Affiliation(s)
- Khalid A Al-Regaiey
- Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
- Correspondence: Khalid A Al-Regaiey; Muhammad Iqbal, Email ;
| | - Syed Shahid Habib
- Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Ahmed R Alshamasi
- Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Abdullah F Alnuwaybit
- Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Bader A Alwhaibi
- Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Naif M Alsulais
- Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Abdullah I Alothman
- Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Faisal M Alomar
- Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Muhammad Iqbal
- Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
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Matrix metalloproteinases and tissue inhibitors of matrix metalloproteinases in kidney disease. Adv Clin Chem 2021; 105:141-212. [PMID: 34809827 DOI: 10.1016/bs.acc.2021.02.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Matrix metalloproteinases (MMPs) are a group of zinc and calcium endopeptidases which cleave extracellular matrix (ECM) proteins. They are also involved in the degradation of cell surface components and regulate multiple cellular processes, cell to cell interactions, cell proliferation, and cell signaling pathways. MMPs function in close interaction with the endogenous tissue inhibitors of matrix metalloproteinases (TIMPs), both of which regulate cell turnover, modulate various growth factors, and participate in the progression of tissue fibrosis and apoptosis. The multiple roles of MMPs and TIMPs are continuously elucidated in kidney development and repair, as well as in a number of kidney diseases. This chapter focuses on the current findings of the significance of MMPs and TIMPs in a wide range of kidney diseases, whether they result from kidney tissue changes, hemodynamic alterations, tubular epithelial cell apoptosis, inflammation, or fibrosis. In addition, the potential use of these endopeptidases as biomarkers of renal dysfunction and as targets for therapeutic interventions to attenuate kidney disease are also explored in this review.
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Ba Aqeel S, Ye M, Wysocki J, Sanchez A, Khattab A, Lores E, Rademaker A, Gao X, Bebu I, Nelson RG, Molitch M, Batlle D. Urinary angiotensinogen antedates the development of stage 3 CKD in patients with type 1 diabetes mellitus. Physiol Rep 2020; 7:e14242. [PMID: 31605461 PMCID: PMC6788980 DOI: 10.14814/phy2.14242] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 08/28/2019] [Accepted: 08/29/2019] [Indexed: 12/12/2022] Open
Abstract
We examined if urinary angiotensinogen (uAOG), a marker of intrarenal renin‐angiotensin system activity, antedates stage 3 chronic kidney disease (CKD) using samples from participants in the Diabetes Control and Complications Trial (DCCT) and later in the Epidemiology of Diabetes Intervention and Complications (EDIC) trial. In a nested case–control design, cases were matched at the outcome visit (eGFR less than 60, 21‐59 mL/min per 1.73 m2) on age, gender, and diabetes duration, with controls: eGFR (95, 75‐119, mL/min per 1.73 m2.) Additionally, in an exploratory analysis progressive renal decline (PRD), defined as eGFR loss >3.5 mL/min per 1.73m2/year, was evaluated using only data from EDIC because no progressions were observed during DCCT. At the EDIC visit, which antedated the GFR outcome visit by 2 years (range 1–7years) the median uAOG/creatinine was markedly higher in cases than in controls (13.9 vs. 3.8 ng/mg P = 0.003) whereas at the DCCT visit, which antedated the GFR outcome by 17 to 20 years it was not (2.75 vs. 3.16 ng/mg, respectively). The Odds Ratio for uAOG and CKD stage 3 development was significant after adjusting for eGFR, HbA1c, and systolic blood pressure 1.82 (1.00–3.29) but no longer significant when Albumin Excretion Ratio (AER) was included 1.21 (0.65–2.24).In the PRD analysis, uAOG/creatinine was sixfold higher in participants who experienced PRD than in those who did not (26 vs. 4.0 ng/mg, P = 0.003). The Odds Ratio for uAOG and PRD was significant after adjusting for eGFR, HbA1c, and systolic blood pressure 2.48 (1.46–4.22) but no longer significant when AER was included 1.32 (0.76–2.30). In people with type1 diabetes, a robust increase in uAOG antedates the development of stage 3 CKD but is not superior to AER in predicting this renal outcome. Increased uAOG moreover is associated with PRD, an index of progression to End Stage Kidney Disease (ESKD).
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Affiliation(s)
- Sheeba Ba Aqeel
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Minghao Ye
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Jan Wysocki
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Alejandro Sanchez
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Ahmed Khattab
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Enrique Lores
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Alfred Rademaker
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Xiaoyu Gao
- George Washington University, Rockville, Maryland
| | - Ionut Bebu
- George Washington University, Rockville, Maryland
| | - Robert G Nelson
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | - Mark Molitch
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Daniel Batlle
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
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7
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VEGFR2 Blockade Improves Renal Damage in an Experimental Model of Type 2 Diabetic Nephropathy. J Clin Med 2020; 9:jcm9020302. [PMID: 31973092 PMCID: PMC7074274 DOI: 10.3390/jcm9020302] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2019] [Revised: 01/14/2020] [Accepted: 01/16/2020] [Indexed: 12/29/2022] Open
Abstract
The absence of optimal treatments for Diabetic Nephropathy (DN) highlights the importance of the search for novel therapeutic targets. The vascular endothelial growth factor receptor 2 (VEGFR2) pathway is activated in experimental and human DN, but the effects of its blockade in experimental models of DN is still controversial. Here, we test the effects of a therapeutic anti-VEGFR2 treatment, using a VEGFR2 kinase inhibitor, on the progression of renal damage in the BTBR ob/ob (leptin deficiency mutation) mice. This experimental diabetic model develops histological characteristics mimicking the key features of advanced human DN. A VEGFR2 pathway-activation blockade using the VEGFR2 kinase inhibitor SU5416, starting after kidney disease development, improves renal function, glomerular damage (mesangial matrix expansion and basement membrane thickening), tubulointerstitial inflammation and tubular atrophy, compared to untreated diabetic mice. The downstream mechanisms involved in these beneficial effects of VEGFR2 blockade include gene expression restoration of podocyte markers and downregulation of renal injury biomarkers and pro-inflammatory mediators. Several ligands can activate VEGFR2, including the canonical ligands VEGFs and GREMLIN. Activation of a GREMLIN/VEGFR2 pathway, but not other ligands, is correlated with renal damage progression in BTBR ob/ob diabetic mice. RNA sequencing analysis of GREMLIN-regulated genes confirm the modulation of proinflammatory genes and related-molecular pathways. Overall, these data show that a GREMLIN/VEGFR2 pathway activation is involved in diabetic kidney disease and could potentially be a novel therapeutic target in this clinical condition.
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Salem RM, Todd JN, Sandholm N, Cole JB, Chen WM, Andrews D, Pezzolesi MG, McKeigue PM, Hiraki LT, Qiu C, Nair V, Di Liao C, Cao JJ, Valo E, Onengut-Gumuscu S, Smiles AM, McGurnaghan SJ, Haukka JK, Harjutsalo V, Brennan EP, van Zuydam N, Ahlqvist E, Doyle R, Ahluwalia TS, Lajer M, Hughes MF, Park J, Skupien J, Spiliopoulou A, Liu A, Menon R, Boustany-Kari CM, Kang HM, Nelson RG, Klein R, Klein BE, Lee KE, Gao X, Mauer M, Maestroni S, Caramori ML, de Boer IH, Miller RG, Guo J, Boright AP, Tregouet D, Gyorgy B, Snell-Bergeon JK, Maahs DM, Bull SB, Canty AJ, Palmer CNA, Stechemesser L, Paulweber B, Weitgasser R, Sokolovska J, Rovīte V, Pīrāgs V, Prakapiene E, Radzeviciene L, Verkauskiene R, Panduru NM, Groop LC, McCarthy MI, Gu HF, Möllsten A, Falhammar H, Brismar K, Martin F, Rossing P, Costacou T, Zerbini G, Marre M, Hadjadj S, McKnight AJ, Forsblom C, McKay G, Godson C, Maxwell AP, Kretzler M, Susztak K, Colhoun HM, Krolewski A, Paterson AD, Groop PH, Rich SS, Hirschhorn JN, Florez JC. Genome-Wide Association Study of Diabetic Kidney Disease Highlights Biology Involved in Glomerular Basement Membrane Collagen. J Am Soc Nephrol 2019; 30:2000-2016. [PMID: 31537649 PMCID: PMC6779358 DOI: 10.1681/asn.2019030218] [Citation(s) in RCA: 111] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 07/08/2019] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Although diabetic kidney disease demonstrates both familial clustering and single nucleotide polymorphism heritability, the specific genetic factors influencing risk remain largely unknown. METHODS To identify genetic variants predisposing to diabetic kidney disease, we performed genome-wide association study (GWAS) analyses. Through collaboration with the Diabetes Nephropathy Collaborative Research Initiative, we assembled a large collection of type 1 diabetes cohorts with harmonized diabetic kidney disease phenotypes. We used a spectrum of ten diabetic kidney disease definitions based on albuminuria and renal function. RESULTS Our GWAS meta-analysis included association results for up to 19,406 individuals of European descent with type 1 diabetes. We identified 16 genome-wide significant risk loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain (COL4A3) gene, which encodes a major structural component of the glomerular basement membrane (GBM). Mutations in COL4A3 are implicated in heritable nephropathies, including the progressive inherited nephropathy Alport syndrome. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of diabetic kidney disease, including albuminuria and ESKD, and demonstrated a significant association with GBM width; protective allele carriers had thinner GBM before any signs of kidney disease, and its effect was dependent on glycemia. Three other loci are in or near genes with known or suggestive involvement in this condition (BMP7) or renal biology (COLEC11 and DDR1). CONCLUSIONS The 16 diabetic kidney disease-associated loci may provide novel insights into the pathogenesis of this condition and help identify potential biologic targets for prevention and treatment.
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Affiliation(s)
- Rany M Salem
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, California
| | - Jennifer N Todd
- Division of Endocrinology, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts
- Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Center for Genomic Medicine and
| | - Niina Sandholm
- Folkhälsan Research Center, Folkhälsan Institute of Genetics, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine and
| | - Joanne B Cole
- Division of Endocrinology, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts
- Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Center for Genomic Medicine and
| | - Wei-Min Chen
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, Virginia
| | - Darrell Andrews
- Diabetes Complications Research Centre, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland
| | - Marcus G Pezzolesi
- Division of Nephrology and Hypertension, Diabetes and Metabolism Center, University of Utah, Salt Lake City, Utah
| | - Paul M McKeigue
- Usher Institute of Population Health Sciences and Informatics and
| | - Linda T Hiraki
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Chengxiang Qiu
- Departments of Medicine and Genetics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Viji Nair
- Division of Nephrology, Department of Internal Medicine and
| | - Chen Di Liao
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jing Jing Cao
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Erkka Valo
- Folkhälsan Research Center, Folkhälsan Institute of Genetics, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine and
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, Virginia
| | | | - Stuart J McGurnaghan
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Jani K Haukka
- Folkhälsan Research Center, Folkhälsan Institute of Genetics, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine and
| | - Valma Harjutsalo
- Folkhälsan Research Center, Folkhälsan Institute of Genetics, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine and
- The Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Eoin P Brennan
- Diabetes Complications Research Centre, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland
| | - Natalie van Zuydam
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Emma Ahlqvist
- Department of Genomics, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
| | - Ross Doyle
- Diabetes Complications Research Centre, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland
| | | | - Maria Lajer
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Maria F Hughes
- Diabetes Complications Research Centre, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland
| | - Jihwan Park
- Departments of Medicine and Genetics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jan Skupien
- Joslin Diabetes Center, Boston, Massachusetts
| | | | | | - Rajasree Menon
- Division of Nephrology, Department of Internal Medicine and
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | | | - Hyun M Kang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan
| | - Robert G Nelson
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona
| | - Ronald Klein
- University of Wisconsin-Madison, Madison, Wisconsin
| | | | | | - Xiaoyu Gao
- The George Washington University, Washington, DC
| | | | - Silvia Maestroni
- Complications of Diabetes Unit, Division of Immunology, Transplantation and Infectious Diseases, Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | | | | | - Rachel G Miller
- University of Pittsburgh Public Health, Pittsburgh, Pennsylvania
| | - Jingchuan Guo
- University of Pittsburgh Public Health, Pittsburgh, Pennsylvania
| | | | - David Tregouet
- INSERM UMR_S 1166, Sorbonne Université, UPMC Univ Paris 06, Paris, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, France
| | - Beata Gyorgy
- INSERM UMR_S 1166, Sorbonne Université, UPMC Univ Paris 06, Paris, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, France
| | | | - David M Maahs
- Department of Pediatrics-Endocrinology, Stanford University, Stanford, California
| | - Shelley B Bull
- The Lunenfeld-Tanenbaum Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Angelo J Canty
- Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada
| | - Colin N A Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Lars Stechemesser
- First Department of Medicine, Paracelsus Medical University, Salzburg, Austria
| | - Bernhard Paulweber
- First Department of Medicine, Paracelsus Medical University, Salzburg, Austria
| | - Raimund Weitgasser
- First Department of Medicine, Paracelsus Medical University, Salzburg, Austria
- Department of Medicine, Diakonissen-Wehrle Hospital, Salzburg, Austria
| | | | - Vita Rovīte
- Latvian Biomedical Research and Study Centre, Riga, Latvia
| | - Valdis Pīrāgs
- University of Latvia, Riga, Latvia
- Pauls Stradins University Hospital, Riga, Latvia
| | | | - Lina Radzeviciene
- Institute of Endocrinology, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Rasa Verkauskiene
- Institute of Endocrinology, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Nicolae Mircea Panduru
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- 2nd Clinical Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Leif C Groop
- Department of Genomics, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
- Genentech, 1 DNA Way, South San Francisco, California
| | - Harvest F Gu
- Department of Clinical Science, Intervention and Technology and
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Anna Möllsten
- Division of Pediatrics, Department of Clinical Sciences, Umeå University, Umeå, Sweden
| | - Henrik Falhammar
- Department of Molecular Medicine and Surgery, Rolf Luft Center for Diabetes Research and Endocrinology, Karolinska Institutet, Stockholm, Sweden
- Department of Endocrinology, Diabetes and Metabolism, Karolinska University Hospital, Stockholm, Sweden
| | - Kerstin Brismar
- Department of Molecular Medicine and Surgery, Rolf Luft Center for Diabetes Research and Endocrinology, Karolinska Institutet, Stockholm, Sweden
- Department of Endocrinology, Diabetes and Metabolism, Karolinska University Hospital, Stockholm, Sweden
| | - Finian Martin
- Diabetes Complications Research Centre, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland
| | - Peter Rossing
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- University of Copenhagen, Copenhagen, Denmark
| | - Tina Costacou
- University of Pittsburgh Public Health, Pittsburgh, Pennsylvania
| | - Gianpaolo Zerbini
- Complications of Diabetes Unit, Division of Immunology, Transplantation and Infectious Diseases, Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Michel Marre
- Department of Diabetology, Endocrinology and Nutrition, Bichat Hospital, DHU FIRE, Assistance Publique-Hôpitaux de Paris, Paris, France
- UFR de Médecine, Paris Diderot University, Sorbonne Paris Cité, Paris, France
- INSERM UMRS 1138, Cordeliers Research Center, Paris, France
- Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - Samy Hadjadj
- Department of Endocrinology and Diabetology, Centre Hospitalier Universitaire de Poitiers, Poitiers, France
- INSERM CIC 1402, Poitiers, France
- L'institut du thorax, INSERM, CNRS, CHU Nantes, Nantes, France
| | - Amy J McKnight
- Centre for Public Health, Queens University of Belfast, Northern Ireland, UK
| | - Carol Forsblom
- Folkhälsan Research Center, Folkhälsan Institute of Genetics, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine and
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine and
| | - Gareth McKay
- Centre for Public Health, Queens University of Belfast, Northern Ireland, UK
| | - Catherine Godson
- Diabetes Complications Research Centre, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland
| | - A Peter Maxwell
- Centre for Public Health, Queens University of Belfast, Northern Ireland, UK
| | - Matthias Kretzler
- Division of Nephrology, Department of Internal Medicine and
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | - Katalin Susztak
- Departments of Medicine and Genetics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Helen M Colhoun
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | | | | | - Per-Henrik Groop
- Folkhälsan Research Center, Folkhälsan Institute of Genetics, Helsinki, Finland
- Abdominal Center Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine and
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, Victoria, Australia; and
| | - Stephen S Rich
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, Virginia
| | - Joel N Hirschhorn
- Division of Endocrinology, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts
- Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Jose C Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts;
- Center for Genomic Medicine and
- Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
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9
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Mezzano S, Droguett A, Lavoz C, Krall P, Egido J, Ruiz-Ortega M. Gremlin and renal diseases: ready to jump the fence to clinical utility? Nephrol Dial Transplant 2019; 33:735-741. [PMID: 28992340 DOI: 10.1093/ndt/gfx194] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Accepted: 04/18/2017] [Indexed: 12/31/2022] Open
Abstract
The current therapeutic strategy for the treatment of chronic kidney diseases only ameliorates disease progression. During renal injury, developmental genes are re-expressed and could be potential therapeutic targets. Among those genes reactivated in the adult damaged kidney, Gremlin is of particular relevance since recent data suggest that it could be a mediator of diabetic nephropathy and other progressive renal diseases. Earlier studies have shown that Gremlin is upregulated in trans-differentiated renal proximal tubular cells and in several chronic kidney diseases associated with fibrosis. However, not much was known about the mechanisms by which Gremlin acts in renal pathophysiology. The role of Gremlin as a bone morphogenetic protein antagonist has clearly been demonstrated in organogenesis and in fibrotic-related disorders. Gremlin binds to vascular endothelial growth factor receptor 2 (VEGFR2) in endothelial and tubular epithelial cells. Activation of the Gremlin-VEGFR2 axis was found in several human nephropathies. We have recently described that Gremlin activates the VEGFR2 signaling pathway in the kidney, eliciting a downstream mechanism linked to renal inflammatory response. Gremlin deletion improves experimental renal damage, diminishing fibrosis. Overall, the available data identify the Gremlin-VEGFR2 axis as a novel therapeutic target for kidney inflammation and fibrosis and provide a rationale for unveiling new concepts to investigate in several clinical conditions.
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Affiliation(s)
- Sergio Mezzano
- Division of Nephrology, School of Medicine, Universidad Austral de Chile, Valdivia, Chile
| | - Alejandra Droguett
- Division of Nephrology, School of Medicine, Universidad Austral de Chile, Valdivia, Chile
| | - Carolina Lavoz
- Division of Nephrology, School of Medicine, Universidad Austral de Chile, Valdivia, Chile
| | - Paola Krall
- Division of Nephrology, School of Medicine, Universidad Austral de Chile, Valdivia, Chile
| | - Jesús Egido
- Division of Nephrology and Hypertension, University Hospital, Fundación Jiménez Díaz-Universidad Autónoma, CIBERDEM, Instituto Renal Reina Sofía, Madrid, Spain
| | - Marta Ruiz-Ortega
- Cellular Biology in Renal Diseases Laboratory, Universidad Autónoma Madrid, IIS-Fundación Jiménez Díaz, RedinRen, Madrid, Spain
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10
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Droguett A, Valderrama G, Burgos ME, Carpio D, Saka C, Egido J, Ruiz-Ortega M, Mezzano S. Gremlin, A Potential Urinary Biomarker of Anca-Associated Crescentic Glomerulonephritis. Sci Rep 2019; 9:6867. [PMID: 31053735 PMCID: PMC6499786 DOI: 10.1038/s41598-019-43358-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 04/23/2019] [Indexed: 01/08/2023] Open
Abstract
Gremlin renal overexpression has been reported in diabetic nephropathy, pauci-immune crescentic glomerulonephritis and chronic allograft nephropathy and has been implicated in the pathophysiology of the progression of renal damage. However, it is unknown whether urinary Gremlin can be associated with renal functional status, renal biopsy findings and outcome. To examine these associations we studied 20 patients with ANCA+ renal vasculitis and very high urinary Gremlin (354 ± 76 ug/gCr), 86 patients with other glomerular diseases and moderately elevated urinary Gremlin (83 ± 14 ug/gCr) and 11 healthy controls (urinary Gremlin 11.3 ± 2.4 ug/gCr). Urinary Gremlin was significantly correlated with renal expression of Gremlin (r = 0.64, p = 0.013) observed in cellular glomerular crescents, tubular epithelial cells and interstitial inflammatory cells. Moreover, urinary Gremlin levels were correlated with the number of glomerular crescents (r = 0.53; p < 0.001), renal CD68 positive cells (r = 0.71; p < 0.005), tubulointerstitial fibrosis (r = 0.50; p < 0.05), and serum creatinine levels (r = 0.60; p < 0.001). Interestingly, Gremlin expression was colocalized with CD68, CD163 (monocyte/macrophage markers) and CCL18 positive cells. ROC curve analysis showed that the cutoff value of urinary Gremlin in glomerular diseases as 43 ug/gCr with 72% of sensitivity and 100% of specificity [AUC: 0.96 (CI 95% 0.92–0.99] (p < 0.001). For ANCA+ renal vasculitis the value of urinary Gremlin of 241 ug/gCr had 55% of sensitivity and 100% of specificity [AUC: 0.81 (CI 95% 0.68–0.94) (p < 0.001]. Based on these results we propose that urinary Gremlin represents a non-invasive biomarker in ANCA+ renal vasculitis, and suggest a role of Gremlin in the formation of crescents.
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Affiliation(s)
- Alejandra Droguett
- Nephrology Division, School of Medicine, Universidad Austral de Chile, Valdivia, Chile
| | - Graciela Valderrama
- Nephrology Division, School of Medicine, Universidad Austral de Chile, Valdivia, Chile
| | - María E Burgos
- Nephrology Division, School of Medicine, Universidad Austral de Chile, Valdivia, Chile
| | - Daniel Carpio
- Nephrology Division, School of Medicine, Universidad Austral de Chile, Valdivia, Chile
| | - Constanza Saka
- Nephrology Division, School of Medicine, Universidad Austral de Chile, Valdivia, Chile
| | - Jesús Egido
- Cellular Biology in Renal Disease Laboratory, Universidad Autónoma. IIS-Fundación Jiménez Díaz, Madrid, Spain
| | - Marta Ruiz-Ortega
- Cellular Biology in Renal Disease Laboratory, Universidad Autónoma. IIS-Fundación Jiménez Díaz, Madrid, Spain
| | - Sergio Mezzano
- Nephrology Division, School of Medicine, Universidad Austral de Chile, Valdivia, Chile.
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11
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Wysocki J, Goodling A, Burgaya M, Whitlock K, Ruzinski J, Batlle D, Afkarian M. Urine RAS components in mice and people with type 1 diabetes and chronic kidney disease. Am J Physiol Renal Physiol 2017; 313:F487-F494. [PMID: 28468961 DOI: 10.1152/ajprenal.00074.2017] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Revised: 04/14/2017] [Accepted: 04/24/2017] [Indexed: 02/07/2023] Open
Abstract
The pathways implicated in diabetic kidney disease (DKD) are largely derived from animal models. To examine if alterations in renin-angiotensin system (RAS) in humans are concordant with those in rodent models, we measured concentration of angiotensinogen (AOG), cathepsin D (CTSD), angiotensin-converting enzyme (ACE), and ACE2 and enzymatic activities of ACE, ACE2, and aminopeptidase-A in FVB mice 13-20 wk after treatment with streptozotocin (n = 9) or vehicle (n = 15) and people with long-standing type 1 diabetes, with (n = 37) or without (n = 81) DKD. In streptozotocin-treated mice, urine AOG and CTSD were 10.4- and 3.0-fold higher than in controls, respectively (P < 0.001). Enzymatic activities of ACE, ACE2, and APA were 6.2-, 3.2-, and 18.8-fold higher, respectively, in diabetic animals (P < 0.001). Angiotensin II was 2.4-fold higher in diabetic animals (P = 0.017). Compared with people without DKD, those with DKD had higher urine AOG (170 vs. 15 μg/g) and CTSD (147 vs. 31 μg/g). In people with DKD, urine ACE concentration was 1.8-fold higher (1.4 vs. 0.8 μg/g in those without DKD), while its enzymatic activity was 0.6-fold lower (1.0 vs. 1.6 × 109 RFU/g in those without DKD). Lower ACE activity, but not ACE protein concentration, was associated with ACE inhibitor (ACEI) treatment. After adjustment for clinical covariates, AOG, CTSD, ACE concentration, and ACE activity remained associated with DKD. In conclusion, in mice with streptozotocin-induced diabetes and in humans with DKD, urine concentrations and enzymatic activities of several RAS components are concordantly increased, consistent with enhanced RAS activity and greater angiotensin II formation. ACEI use was associated with a specific reduction in urine ACE activity, not ACE protein concentration, suggesting that it may be a marker of exposure to this widely-used therapy.
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Affiliation(s)
- Jan Wysocki
- Division of Nephrology and Hypertension, Department of Medicine, The Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Anne Goodling
- Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
| | - Mar Burgaya
- Division of Nephrology and Hypertension, Department of Medicine, The Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Kathryn Whitlock
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, Washington; and
| | - John Ruzinski
- Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington
| | - Daniel Batlle
- Division of Nephrology and Hypertension, Department of Medicine, The Feinberg School of Medicine, Northwestern University, Chicago, Illinois;
| | - Maryam Afkarian
- Division of Nephrology, Department of Medicine, University of California, Davis, California
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12
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Heinzel A, Mühlberger I, Stelzer G, Lancet D, Oberbauer R, Martin M, Perco P. Molecular disease presentation in diabetic nephropathy. Nephrol Dial Transplant 2016. [PMID: 26209734 DOI: 10.1093/ndt/gfv267] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Diabetic nephropathy, as the most prevalent chronic disease of the kidney, has also become the primary cause of end-stage renal disease with the incidence of kidney disease in type 2 diabetics continuously rising. As with most chronic diseases, the pathophysiology is multifactorial with a number of deregulated molecular processes contributing to disease manifestation and progression. Current therapy mainly involves interfering in the renin-angiotensin-aldosterone system using angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers. Better understanding of molecular processes deregulated in the early stages and progression of disease hold the key for development of novel therapeutics addressing this complex disease. With the advent of high-throughput omics technologies, researchers set out to systematically study the disease on a molecular level. Results of the first omics studies were mainly focused on reporting the highest deregulated molecules between diseased and healthy subjects with recent attempts to integrate findings of multiple studies on the level of molecular pathways and processes. In this review, we will outline key omics studies on the genome, transcriptome, proteome and metabolome level in the context of DN. We will also provide concepts on how to integrate findings of these individual studies (i) on the level of functional processes using the gene-ontology vocabulary, (ii) on the level of molecular pathways and (iii) on the level of phenotype molecular models constructed based on protein-protein interaction data.
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Affiliation(s)
| | | | - Gil Stelzer
- Weizmann Institute of Science, Rehovot, Israel
| | | | | | - Maria Martin
- EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, UK
| | - Paul Perco
- emergentec biodevelopment GmbH, Vienna, Austria
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13
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Afkarian M, Zelnick LR, Ruzinski J, Kestenbaum B, Himmelfarb J, de Boer IH, Mehrotra R. Urine matrix metalloproteinase-7 and risk of kidney disease progression and mortality in type 2 diabetes. J Diabetes Complications 2015; 29:1024-31. [PMID: 26412030 PMCID: PMC5389898 DOI: 10.1016/j.jdiacomp.2015.08.024] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Revised: 08/25/2015] [Accepted: 08/30/2015] [Indexed: 02/06/2023]
Abstract
AIMS The renin-angiotensin-aldosterone system (RAAS), bone morphogenetic protein (BMP) and WNT pathways are dysregulated in diabetic kidney disease (DKD). Urine excretion of angiotensinogen, gremlin-1 and matrix metalloproteinase-7 (MMP-7), components of the RAAS, BMP and WNT pathways, respectively, is increased in DKD. We asked if this increase is associated with subsequent progression to end-stage renal disease (ESRD) or death. METHODS Using time-to-event analyses, we examined the association of baseline urine concentration of these proteins with progression to ESRD or death in a predominantly Mexican-American cohort with type 2 diabetes and proteinuric DKD (n=141). RESULTS Progression to ESRD occurred for 38 participants over a median follow-up of 3.0years; 39 participants died over a median follow-up of 3.6years. Urine MMP-7 and gremlin-1 were associated with increased risk of ESRD after adjustment for demographic and clinical covariates. Angiotensinogen showed a U-shaped relationship with ESRD, with the middle tertile associated with lowest risk of ESRD. After additional adjustment for glomerular filtration rate and albuminuria, all associations with ESRD lost significance. Only urine MMP-7 was associated with mortality, and this association remained robust in the fully adjusted model with a Hazard ratio of 3.59 (95% confidence interval 1.31 to 9.85) for highest vs. lowest tertile. Serum MMP-7 was not associated with mortality and did not attenuate the association of urine MMP-7 with mortality (HR 4.03 for highest vs. lowest urine MMP-7 tertile). CONCLUSIONS Among people with type 2 diabetes and proteinuric DKD, urine MMP-7 concentration was strongly associated with subsequent mortality.
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MESH Headings
- Aged
- Cohort Studies
- Diabetes Mellitus, Type 2/complications
- Diabetes Mellitus, Type 2/ethnology
- Diabetes Mellitus, Type 2/mortality
- Diabetes Mellitus, Type 2/urine
- Diabetic Nephropathies/complications
- Diabetic Nephropathies/epidemiology
- Diabetic Nephropathies/mortality
- Diabetic Nephropathies/physiopathology
- Disease Progression
- Female
- Follow-Up Studies
- Glomerular Filtration Rate
- Hospitals, Public
- Hospitals, Urban
- Humans
- Kidney/physiopathology
- Kidney Failure, Chronic/complications
- Kidney Failure, Chronic/epidemiology
- Kidney Failure, Chronic/mortality
- Kidney Failure, Chronic/physiopathology
- Los Angeles/epidemiology
- Male
- Matrix Metalloproteinase 7/urine
- Mexican Americans
- Middle Aged
- Prospective Studies
- Renal Insufficiency/complications
- Renal Insufficiency/epidemiology
- Renal Insufficiency/mortality
- Renal Insufficiency/physiopathology
- Risk
- Up-Regulation
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Affiliation(s)
- Maryam Afkarian
- Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA.
| | - Leila R Zelnick
- Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA; Department of Biostatistics, University of Washington
| | - John Ruzinski
- Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA
| | - Bryan Kestenbaum
- Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA
| | - Jonathan Himmelfarb
- Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA
| | - Ian H de Boer
- Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA
| | - Rajnish Mehrotra
- Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA
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