1
|
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.
Collapse
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
| |
Collapse
|