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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00064165%3A_____%2F22%3A10437870" target="_blank" >RIV/00064165:_____/22:10437870 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216208:11110/22:10437870

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Kxub3peREn" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Kxub3peREn</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1093/ndt/gfaa307" target="_blank" >10.1093/ndt/gfaa307</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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 m(2) 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/potassiumtransporting 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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30217 - Urology and nephrology

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Nephrology, Dialysis, Transplantation

  • ISSN

    0931-0509

  • e-ISSN

    1460-2385

  • Volume of the periodical

    37

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    11

  • Pages from-to

    42-52

  • UT code for WoS article

    000743609700009

  • EID of the result in the Scopus database

    2-s2.0-85125130465