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Peters B, Beige J, Siwy J, Rudnicki M, Wendt R, Ortiz A, Sanz AB, Mischak H, Reich HN, Nasic S, Mahmood D, Persson A, Fernström A, Weiner M, Stegmayr B. Dynamics of urine proteomics biomarker and disease progression in patients with IgA nephropathy. Nephrol Dial Transplant 2023; 38:2826-2834. [PMID: 37349951 PMCID: PMC10689155 DOI: 10.1093/ndt/gfad125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND Immunoglobulin A nephropathy (IgAN) frequently leads to kidney failure. The urinary proteomics-based classifier IgAN237 may predict disease progression at the time of kidney biopsy. We studied whether IgAN237 also predicts progression later in the course of IgAN. METHODS Urine from patients with biopsy-proven IgAN was analyzed using capillary electrophoresis-mass spectrometry at baseline (IgAN237-1, n = 103) and at follow-up (IgAN237-2, n = 89). Patients were categorized as "non-progressors" (IgAN237 ≤0.38) and "progressors" (IgAN237 >0.38). Estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine ratio slopes were calculated. RESULTS Median age at biopsy was 44 years, interval between biopsy and IgAN237-1 was 65 months and interval between IgAN237-1 and IgAN237-2 was 258 days (interquartile range 71-531). IgAN237-1 and IgAN237-2 values did not differ significantly and were correlated (rho = 0.44, P < .001). Twenty-eight percent and 26% of patients were progressors based on IgAN237-1 and IgAN237-2, respectively. IgAN237 inversely correlated with chronic eGFR slopes (rho = -0.278, P = .02 for score-1; rho = -0.409, P = .002 for score-2) and with ±180 days eGFR slopes (rho = -0.31, P = .009 and rho = -0.439, P = .001, respectively). The ±180 days eGFR slopes were worse for progressors than for non-progressors (median -5.98 versus -1.22 mL/min/1.73 m2 per year for IgAN237-1, P < .001; -3.02 vs 1.08 mL/min/1.73 m2 per year for IgAN237-2, P = .0047). In multiple regression analysis baseline progressor/non-progressor according to IgAN237 was an independent predictor of eGFR180days-slope (P = .001). CONCLUSION The urinary IgAN237 classifier represents a risk stratification tool in IgAN also later in the course of the dynamic disease. It may guide patient management in an individualized manner.
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Affiliation(s)
- Björn Peters
- Department of Molecular and Clinical Medicine, Institute of Medicine, the Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
- Department of Nephrology, Skaraborg Hospital, Skövde, Sweden
| | - Joachim Beige
- Kuratorium for Dialysis and Transplantation, Neu Isenburg/Leipzig, Germany
- Division of Nephrology, Rheumatology and Endocrinology, Martin-Luther University Halle-Wittenberg, Halle/Saale., Germany
| | | | - Michael Rudnicki
- Department of Internal Medicine IV – Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria
| | - Ralph Wendt
- Division of Nephrology and KfH Renal Unit, Hospital St Georg, Leipzig, Germany
| | - Alberto Ortiz
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD UAM), Madrid, Spain
| | - Ana Belen Sanz
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD UAM), Madrid, Spain
| | | | - Heather N Reich
- Department of Medicine, University of Toronto and Division of Nephrology, University Health Network, Toronto, Ontario, Canada
- Gabor Zellerman Chair in Nephrology Research, University of Toronto, Toronto, Ontario, Canada
| | - Salmir Nasic
- Department of Molecular and Clinical Medicine, Institute of Medicine, the Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
- Research and Development Centre at Skaraborg Hospital, Skövde, Sweden
| | - Dana Mahmood
- Department of Public Health and Clinical Medicine, Unit Östersund, Umeå University, Umea, Sweden
| | - Anders Persson
- Department of Public Health and Clinical Medicine, Unit Sundsvall, Umeå University, Umea, Sweden
| | - Anders Fernström
- Department of Nephrology and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Maria Weiner
- Department of Nephrology and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Bernd Stegmayr
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
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Rudnicki M, Siwy J, Wendt R, Lipphardt M, Koziolek MJ, Maixnerova D, Peters B, Kerschbaum J, Leierer J, Neprasova M, Banasik M, Sanz AB, Perez-Gomez MV, Ortiz A, Stegmayr B, Tesar V, Mischak H, Beige J, Reich HN. Urine proteomics for prediction of disease progression in patients with IgA nephropathy. Nephrol Dial Transplant 2021; 37:42-52. [PMID: 33313853 PMCID: PMC8719618 DOI: 10.1093/ndt/gfaa307] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Risk of kidney function decline in immunoglobulin A (IgA) nephropathy (IgAN) is significant and may not be predicted by available clinical and histological tools. To serve this unmet need, we aimed at developing a urinary biomarker-based algorithm that predicts rapid disease progression in IgAN, thus enabling a personalized risk stratification. METHODS In this multicentre study, urine samples were collected in 209 patients with biopsy-proven IgAN. Progression was defined by tertiles of the annual change of estimated glomerular filtration rate (eGFR) during follow-up. Urine samples were analysed using capillary electrophoresis coupled mass spectrometry. The area under the receiver operating characteristic curve (AUC) was used to evaluate the risk prediction models. RESULTS Of the 209 patients, 64% were male. Mean age was 42 years, mean eGFR was 63 mL/min/1.73 m2 and median proteinuria was 1.2 g/day. We identified 237 urine peptides showing significant difference in abundance according to the tertile of eGFR change. These included fragments of apolipoprotein C-III, alpha-1 antitrypsin, different collagens, fibrinogen alpha and beta, titin, haemoglobin subunits, sodium/potassium-transporting ATPase subunit gamma, uromodulin, mucin-2, fractalkine, polymeric Ig receptor and insulin. An algorithm based on these protein fragments (IgAN237) showed a significant added value for the prediction of IgAN progression [AUC 0.89; 95% confidence interval (CI) 0.83-0.95], as compared with the clinical parameters (age, gender, proteinuria, eGFR and mean arterial pressure) alone (0.72; 95% CI 0.64-0.81). CONCLUSIONS A urinary peptide classifier predicts progressive loss of kidney function in patients with IgAN significantly better than clinical parameters alone.
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Affiliation(s)
- Michael Rudnicki
- Department of Internal Medicine IV, Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria
| | | | - Ralph Wendt
- Division of Nephrology and KfH Renal Unit, Hospital St Georg, Leipzig, Germany
| | - Mark Lipphardt
- Department of Nephrology and Rheumatology, University Medical Centre Göttingen, Göttingen, Germany
| | - Michael J Koziolek
- Department of Nephrology and Rheumatology, University Medical Centre Göttingen, Göttingen, Germany
| | - Dita Maixnerova
- Department of Nephrology, 1st School of Medicine and General University Hospital, Charles University, Prague, Czech Republic
| | - Björn Peters
- Department of Nephrology, Skaraborg Hospital, Skövde, Sweden
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Julia Kerschbaum
- Department of Internal Medicine IV, Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria
| | - Johannes Leierer
- Department of Internal Medicine IV, Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria
| | - Michaela Neprasova
- Department of Nephrology, 1st School of Medicine and General University Hospital, Charles University, Prague, Czech Republic
| | - Miroslaw Banasik
- Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Ana Belen Sanz
- Research Health Institute, Fundación Jiménez Díaz University, Madrid, Spain
| | | | - Alberto Ortiz
- Research Health Institute, Fundación Jiménez Díaz University, Madrid, Spain
| | - Bernd Stegmayr
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Vladimir Tesar
- Department of Nephrology, 1st School of Medicine and General University Hospital, Charles University, Prague, Czech Republic
| | | | - Joachim Beige
- Division of Nephrology and KfH Renal Unit, Hospital St Georg, Leipzig, Germany
- Martin-Luther-University Halle/Wittenberg, Halle/Saale, Germany
| | - Heather N Reich
- Department of Medicine, Division of Nephrology, University Health Network, University of Toronto, Toronto, Canada
- Nephrology Research, University of Toronto, Toronto, Ontario, Canada
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