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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.

Anemia is a common complication of chronic kidney disease (CKD). The prevalence of anemia in CKD strongly increases as the estimated Glomerular Filtration Rate (eGFR) decreases. The pathophysiology of anemia in CKD is complex. The main causes are erythropoietin (EPO) deficiency and functional iron deficiency (FID). The administration of injectable preparations of recombinant erythropoiesis-stimulating agents (ESAs), especially epoetin and darbepoetin, coupled with oral or intravenous(iv) iron supplementation, is the current treatment for anemia in CKD for both dialysis and non-dialysis patients. This approach reduces patients’ dependence on transfusion, ensuring the achievement of optimal hemoglobin target levels. However, there is still no evidence that treating anemia with ESAs can significantly reduce the risk of cardiovascular events. Meanwhile, iv iron supplementation causes an increased risk of allergic reactions, gastrointestinal side effects, infection, and cardiovascular events. Currently, there are no studies defining the best strategy for using ESAs to minimize possible risks. One class of agents under evaluation, known as prolyl hydroxylase inhibitors (PHIs), acts to stabilize hypoxia-inducible factor (HIF) by inhibiting prolyl hydroxylase (PH) enzymes. Several randomized controlled trials showed that HIF-PHIs are almost comparable to ESAs. In the era of personalized medicine, it is possible to envisage and investigate specific contexts of the application of HIF stabilizers based on the individual risk profile and mechanism of action.