OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction
Michele Provenzano, Raffaele Serra, Carlo Garofalo, Ashour Michael, Giuseppina Crugliano, Yuri Battaglia, Nicola Ielapi, Umberto Marcello Bracale, Teresa Faga, Giulia Capitoli, Stefania Galimberti, Michele Andreucci
Abstract
Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The 'omics' techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.