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Urine proteomics for prediction of disease progression in patients with IgA nephropathy

Rudnicki, Michael (författare)
Department of Internal Medicine IV, Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria
Siwy, Justyna (författare)
Mosaiques Diagnostics GmbH, Hannover, Germany
Wendt, Ralph (författare)
Division of Nephrology, KfH Renal Unit, Hospital St Georg, Leipzig, Germany
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Lipphardt, Mark (författare)
Department of Nephrology and Rheumatology, University Medical Centre Göttingen, Göttingen, Germany
Koziolek, Michael J (författare)
Department of Nephrology and Rheumatology, University Medical Centre Göttingen, Göttingen, Germany
Maixnerova, Dita (författare)
Department of Nephrology, 1st School of Medicine, General University Hospital, Charles University, Prague, Czech Republic
Peters, Björn, 1978- (författare)
Umeå universitet,Avdelningen för medicin,Department of Nephrology, Skaraborg Hospital, Skövde, Sweden
Kerschbaum, Julia (författare)
Department of Internal Medicine IV, Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria
Leierer, Johannes (författare)
Department of Internal Medicine IV, Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria
Neprasova, Michaela (författare)
Department of Nephrology, 1st School of Medicine, General University Hospital, Charles University, Prague, Czech Republic
Banasik, Miroslaw (författare)
Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland
Sanz, Ana Belen (författare)
Research Health Institute, Fundación Jiménez Diáz University, Madrid, Spain
Perez-Gomez, Maria Vanessa (författare)
Research Health Institute, Fundación Jiménez Diáz University, Madrid, Spain
Ortiz, Alberto (författare)
Research Health Institute, Fundación Jiménez Diáz University, Madrid, Spain
Stegmayr, Bernd, 1949- (författare)
Umeå universitet,Avdelningen för medicin
Tesar, Vladimir (författare)
Department of Nephrology, 1st School of Medicine, General University Hospital, Charles University, Prague, Czech Republic
Mischak, Harald (författare)
Mosaiques Diagnostics GmbH, Hannover, Germany
Beige, Joachim (författare)
Division of Nephrology, KfH Renal Unit, Hospital St Georg, Leipzig, Germany; Martin-Luther-University Halle/Wittenberg, Halle/Saale, Germany
Reich, Heather N. (författare)
Department of Medicine, Division of Nephrology, University Health Network, University of Toronto, Toronto, Canada; Nephrology Research, University of Toronto, ON, Toronto, Canada
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 (creator_code:org_t)
2020-12-14
2022
Engelska.
Ingår i: Nephrology, Dialysis and Transplantation. - : Oxford University Press. - 0931-0509 .- 1460-2385. ; 37:1, s. 42-52
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • 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.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Urologi och njurmedicin (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Urology and Nephrology (hsv//eng)

Nyckelord

biomarker
glomerulonephritis
IgAN
progression
urine proteomics

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