Abstract

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 22patients 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 aninitial 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 (allpatients 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, usinghigh-throughput technology, our study identified a candidate MSK biomarker possibly employable in future forthe early diagnosis of this disease.

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