Linking 24-h urines to clinical phenotypes: what alternatives does the future bring?. Issue 2 (March 2020)

• Record Type: Journal Article
• Authors: Sui, Wilson; Hsi, Ryan S.
• Is Part Of: Current opinion in urology. Volume 30:Issue 2(2020:Mar.)
• Publication Date: 2020-03
• Subjects: biomarker -- metabolomics -- proteomics -- stone -- urine; Urology -- Periodicals; Review Literature -- Bibliography; Review Literature -- Periodicals; Male Urogenital Diseases -- Bibliography; Male Urogenital Diseases -- Periodicals; Female Urogenital Diseases -- Bibliography; Female Urogenital Diseases -- Periodicals; Urologic Diseases -- Bibliography; Urologic Diseases -- Periodicals; Periodicals; 616.6005
• DOI: 10.1097/MOU.0000000000000702
• Languages: English
• ISSNs: 1473-6586

Abstract

Abstract : Purpose of review: The 24-h urine test is recommended as part of the metabolic evaluation for patients with nephrolithiasis to guide preventive interventions. However, this test may be challenging to interpret and has limits in its predictive ability. In this review, we summarize and discuss the most recent research on the opportunities and challenges for utilizing urinary biomarkers for kidney stone prevention. Recent findings: Contemporary studies utilizing the 24-h urine test have improved our understanding of how to better administer testing and interpret test results. Beyond the standard panel of 24-h urine parameters, recent applications of proteomics and metabolomics have identified protein and metabolic profiles of stone formers. These profiles can be assayed in future studies as potential biomarkers for risk stratification and prediction. Broad collaborative efforts to create large datasets and biobanks from kidney stone formers will be invaluable for kidney stone research. Summary: Recent advances in our understanding of kidney stone risk have opened opportunities to improve metabolic testing for kidney stone formers. These strategies do not appear to be mutually exclusive of 24-h urine testing but instead complementary in their approach. Finally, large clinical datasets hold promise to be leveraged to identify new avenues for stone prevention.