z-logo
open-access-imgOpen Access
Proteomic-based research strategy identified laminin subunit alpha 2 as a potential urinary-specific biomarker for the medullary sponge kidney disease
Author(s) -
Antonia Fabris,
Maurizio Bruschi,
Laura Santucci,
Giovanni Candiano,
Simona Granata,
Alessandra Dalla Gassa,
Nadia Antonucci,
Andrea Petretto,
Gian Marco Ghiggeri,
Giovanni Gambaro,
Antonio Lupo,
Gianluigi Zaza
Publication year - 2016
Publication title -
kidney international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.499
H-Index - 276
eISSN - 1523-1755
pISSN - 0085-2538
DOI - 10.1016/j.kint.2016.09.035
Subject(s) - medicine , biomarker , urinary system , kidney , proteomics , kidney stones , urine , cohort , kidney disease , pathology , urology , bioinformatics , biology , biochemistry , gene
Medullary sponge kidney (MSK) disease, a rare kidney malformation featuring recurrent renal stones and nephrocalcinosis, continues to be diagnosed using expensive and time-consuming clinical/instrumental tests (mainly urography). Currently, no molecular diagnostic biomarkers are available. To identify such we employed a proteomic-based research strategy utilizing urine from 22 patients with MSK and 22 patients affected by idiopathic calcium nephrolithiasis (ICN) as controls. Notably, two patients with ICN presented cysts. In the discovery phase, the urine of 11 MSK and 10 controls, were randomly selected, processed, and analyzed by mass spectrometry. Subsequently, several statistical algorithms were undertaken to select the most discriminative proteins between the two study groups. ELISA, performed on the entire patients' cohort, was used to validate the proteomic results. After an initial statistical analysis, 249 and 396 proteins were identified exclusive for ICN and MSK, respectively. A Volcano plot and ROC analysis, performed to restrict the number of MSK-associated proteins, indicated that 328 and 44 proteins, respectively, were specific for MSK. Interestingly, 119 proteins were found to differentiate patients with cysts (all patients with MSK and the two ICN with renal cysts) from ICN without cysts. Eventually, 16 proteins were found to be common to three statistical methods with laminin subunit alpha 2 (LAMA-2) reaching the higher rank by a Support Vector Machine, a binary classification/prediction scheme. ELISA for LAMA-2 validated proteomic results. Thus, using high-throughput technology, our study identified a candidate MSK biomarker possibly employable in future for the early diagnosis of this disease.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom