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Gene Expression as a Guide to the Development of Novel Therapies in Primary Glomerular Diseases. J Clin Med 2021; 10:jcm10112262. [PMID: 34073694 PMCID: PMC8197155 DOI: 10.3390/jcm10112262] [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: 04/07/2021] [Revised: 05/10/2021] [Accepted: 05/19/2021] [Indexed: 11/17/2022] Open
Abstract
Despite improvements in understanding the pathogenic mechanisms of primary glomerular diseases, therapy still remains nonspecific. We sought to identify novel therapies targeting kidney-intrinsic injury of distinct primary glomerulonephritides through computational systems biology approaches. We defined the unique transcriptional landscape within kidneys from patients with focal segmental glomerulosclerosis (FSGS), minimal change disease (MCD), immunoglobulin A nephropathy (IgAN), membranous nephropathy (MN) and thin basement membrane nephropathy (TBMN). Differentially expressed genes were functionally annotated with enrichment analysis, and distinct biological processes and pathways implicated in each primary glomerular disease were uncovered. Finally, we identified novel drugs and small-molecule compounds that may reverse each glomerulonephritis phenotype, suggesting they should be further tested as precise therapy in primary glomerular diseases.
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Ahn HS, Kim JH, Jeong H, Yu J, Yeom J, Song SH, Kim SS, Kim IJ, Kim K. Differential Urinary Proteome Analysis for Predicting Prognosis in Type 2 Diabetes Patients with and without Renal Dysfunction. Int J Mol Sci 2020; 21:ijms21124236. [PMID: 32545899 PMCID: PMC7352871 DOI: 10.3390/ijms21124236] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/05/2020] [Accepted: 06/12/2020] [Indexed: 12/28/2022] Open
Abstract
Renal dysfunction, a major complication of type 2 diabetes, can be predicted from estimated glomerular filtration rate (eGFR) and protein markers such as albumin concentration. Urinary protein biomarkers may be used to monitor or predict patient status. Urine samples were selected from patients enrolled in the retrospective diabetic kidney disease (DKD) study, including 35 with good and 19 with poor prognosis. After removal of albumin and immunoglobulin, the remaining proteins were reduced, alkylated, digested, and analyzed qualitatively and quantitatively with a nano LC-MS platform. Each protein was identified, and its concentration normalized to that of creatinine. A prognostic model of DKD was formulated based on the adjusted quantities of each protein in the two groups. Of 1296 proteins identified in the 54 urine samples, 66 were differentially abundant in the two groups (area under the curve (AUC): p-value < 0.05), but none showed significantly better performance than albumin. To improve the predictive power by multivariate analysis, five proteins (ACP2, CTSA, GM2A, MUC1, and SPARCL1) were selected as significant by an AUC-based random forest method. The application of two classifiers—support vector machine and random forest—showed that the multivariate model performed better than univariate analysis of mucin-1 (AUC: 0.935 vs. 0.791) and albumin (AUC: 1.0 vs. 0.722). The urinary proteome can reflect kidney function directly and can predict the prognosis of patients with chronic kidney dysfunction. Classification based on five urinary proteins may better predict the prognosis of DKD patients than urinary albumin concentration or eGFR.
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Affiliation(s)
- Hee-Sung Ahn
- Asan Institute for Life Sciences, Asan Medical Center, Seoul 05505, Korea; (H.-S.A.); (J.Y.)
| | - Jong Ho Kim
- Department of Internal Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Korea; (J.H.K.); (S.H.S.); (S.S.K.)
| | - Hwangkyo Jeong
- Department of Biomedical Sciences, University of Ulsan College of Medicine, Seoul 05505, Korea;
| | - Jiyoung Yu
- Asan Institute for Life Sciences, Asan Medical Center, Seoul 05505, Korea; (H.-S.A.); (J.Y.)
| | - Jeonghun Yeom
- Convergence Medicine Research Center, Asan Institute for Life Sciences, Seoul 05505, Korea;
| | - Sang Heon Song
- Department of Internal Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Korea; (J.H.K.); (S.H.S.); (S.S.K.)
| | - Sang Soo Kim
- Department of Internal Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Korea; (J.H.K.); (S.H.S.); (S.S.K.)
| | - In Joo Kim
- Department of Internal Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Korea; (J.H.K.); (S.H.S.); (S.S.K.)
- Correspondence: (I.J.K.); (K.K.); Tel.: +82-51-240-7224 (I.J.K.); +82-2-1688-7575 (K.K.)
| | - Kyunggon Kim
- Asan Institute for Life Sciences, Asan Medical Center, Seoul 05505, Korea; (H.-S.A.); (J.Y.)
- Department of Biomedical Sciences, University of Ulsan College of Medicine, Seoul 05505, Korea;
- Clinical Proteomics Core Laboratory, Convergence Medicine Research Center, Asan Medical Center, Seoul 05505, Korea
- Bio-Medical Institute of Technology, Asan Medical Center, Seoul 05505, Korea
- Correspondence: (I.J.K.); (K.K.); Tel.: +82-51-240-7224 (I.J.K.); +82-2-1688-7575 (K.K.)
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Gooding JR, Agrawal S, McRitchie S, Acuff Z, Merchant ML, Klein JB, Smoyer WE, Sumner SJ. Predicting and Defining Steroid Resistance in Pediatric Nephrotic Syndrome Using Plasma Metabolomics. Kidney Int Rep 2020; 5:81-93. [PMID: 31922063 PMCID: PMC6943762 DOI: 10.1016/j.ekir.2019.09.010] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 09/09/2019] [Indexed: 12/18/2022] Open
Abstract
INTRODUCTION Nephrotic syndrome (NS) is a kidney disease that affects both children and adults. Glucocorticoids have been the primary therapy for >60 years but are ineffective in approximately 20% of children and approximately 50% of adult patients. Unfortunately, patients with steroid-resistant NS (SRNS; vs. steroid-sensitive NS [SSNS]) are at high risk for both glucocorticoid-induced side effects and disease progression. METHODS We performed proton nuclear magnetic resonance (1H NMR) metabolomic analyses on plasma samples (n = 86) from 45 patients with NS (30 SSNS and 15 SRNS) obtained at initial disease presentation before glucocorticoid initiation and after approximately 7 weeks of glucocorticoid therapy to identify candidate biomarkers able to either predict SRNS before treatment or define critical molecular pathways/targets regulating steroid resistance. RESULTS Stepwise logistic regression models identified creatinine concentration and glutamine concentration (odds ratio [OR]: 1.01; 95% confidence interval [CI]: 0.99-1.02) as 2 candidate biomarkers predictive of SRNS, and malonate concentration (OR: 0.94; 95% CI: 0.89-1.00) as a third candidate predictive biomarker using a similar model (only in children >3 years). In addition, paired-sample analyses identified several candidate biomarkers with the potential to identify mechanistic molecular pathways/targets that regulate clinical steroid resistance, including lipoproteins, adipate, pyruvate, creatine, glucose, tyrosine, valine, glutamine, and sn-glycero-3-phosphcholine. CONCLUSION Metabolomic analyses of serial plasma samples from children with SSNS and SRNS identified elevated creatinine and glutamine concentrations, and reduced malonate concentrations, as auspicious candidate biomarkers to predict SRNS at disease onset in pediatric NS, as well as additional candidate biomarkers with the potential to identify mechanistic molecular pathways that may regulate clinical steroid resistance.
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Affiliation(s)
- Jessica R. Gooding
- National Institutes of Health Eastern Regional Comprehensive Metabolomics Resource Core (ERCMRC) at University of North Carolina, Chapel Hill, North Carolina, USA
- Discovery, Science and Technology, RTI International, Research Triangle Park, North Carolina, USA
| | - Shipra Agrawal
- Department of Pediatrics, The Ohio State University, Columbus, Ohio, USA
- Center for Clinical and Translational Research, Nationwide Children’s Hospital, Columbus, Ohio, USA
| | - Susan McRitchie
- National Institutes of Health Eastern Regional Comprehensive Metabolomics Resource Core (ERCMRC) at University of North Carolina, Chapel Hill, North Carolina, USA
- Nutrition Research Institute, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Zach Acuff
- National Institutes of Health Eastern Regional Comprehensive Metabolomics Resource Core (ERCMRC) at University of North Carolina, Chapel Hill, North Carolina, USA
- Discovery, Science and Technology, RTI International, Research Triangle Park, North Carolina, USA
| | | | - Jon B. Klein
- Kidney Disease Program, University of Louisville, Louisville, Kentucky, USA
- Robley Rex VA Medical Center, Louisville, Kentucky, USA
| | - William E. Smoyer
- Department of Pediatrics, The Ohio State University, Columbus, Ohio, USA
- Center for Clinical and Translational Research, Nationwide Children’s Hospital, Columbus, Ohio, USA
| | - Susan J. Sumner
- National Institutes of Health Eastern Regional Comprehensive Metabolomics Resource Core (ERCMRC) at University of North Carolina, Chapel Hill, North Carolina, USA
- Nutrition Research Institute, University of North Carolina, Chapel Hill, North Carolina, USA
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Finne K, Vethe H, Skogstrand T, Leh S, Dahl TD, Tenstad O, Berven FS, Reed RK, Vikse BE. Proteomic analysis of formalin-fixed paraffin-embedded glomeruli suggests depletion of glomerular filtration barrier proteins in two-kidney, one-clip hypertensive rats. Nephrol Dial Transplant 2014; 29:2217-27. [PMID: 25129444 PMCID: PMC4240179 DOI: 10.1093/ndt/gfu268] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Background It is well known that hypertension may cause glomerular damage, but the molecular mechanisms involved are still incompletely understood. Methods In the present study, we used formalin-fixed paraffin-embedded (FFPE) tissue to investigate changes in the glomerular proteome in the non-clipped kidney of two-kidney one-clip (2K1C) hypertensive rats, with special emphasis on the glomerular filtration barrier. 2K1C hypertension was induced in 6-week-old Wistar Hannover rats (n = 6) that were sacrificed 23 weeks later and compared with age-matched sham-operated controls (n = 6). Tissue was stored in FFPE tissue blocks and later prepared on tissue slides for laser microdissection. Glomeruli without severe morphological damage were isolated, and the proteomes were analysed using liquid chromatography–tandem mass spectrometry. Results 2K1C glomeruli showed reduced abundance of proteins important for slit diaphragm complex, such as nephrin, podocin and neph1. The podocyte foot process had a pattern of reduced abundance of transmembrane proteins but unchanged abundances of the podocyte cytoskeletal proteins synaptopodin and α-actinin-4. Lower abundance of important glomerular basement membrane proteins was seen. Possible glomerular markers of damage with increased abundance in 2K1C were transgelin, desmin and acyl-coenzyme A thioesterase 1. Conclusions Microdissection and tandem mass spectrometry could be used to investigate the proteome of isolated glomeruli from FFPE tissue. Glomerular filtration barrier proteins had reduced abundance in the non-clipped kidney of 2K1C hypertensive rats.
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Affiliation(s)
- Kenneth Finne
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Heidrun Vethe
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Trude Skogstrand
- Department of Clinical Medicine, University of Bergen, Bergen, Norway Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Sabine Leh
- Department of Clinical Medicine, University of Bergen, Bergen, Norway Department of Pathology, Haukeland University Hospital, Bergen, Norway
| | - Tone D Dahl
- Department of Clinical Medicine, University of Bergen, Bergen, Norway Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Olav Tenstad
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Frode S Berven
- Department of Biomedicine, University of Bergen, Bergen, Norway The Norwegian Multiple Sclerosis National Competence Centre, Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Rolf K Reed
- Department of Biomedicine, University of Bergen, Bergen, Norway Centre for Cancer Biomarkers (CCBIO), University of Bergen, Bergen, Norway
| | - Bjørn Egil Vikse
- Department of Clinical Medicine, University of Bergen, Bergen, Norway Department of Medicine, Haukeland University Hospital, Bergen, Norway Department of Medicine, Haugesund Hospital, Haugesund, Norway
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Affiliation(s)
- Börje Haraldsson
- From the Institute of Medicine, University of Gothenburg, Gothenburg, Sweden; and the Department of Medicine, Icahn School of Medicine at Mount Sinai, New York
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