Facultad de Ciencias de la Salud

Chronic kidney disease (CKD) has been increasing over the last years, with a rate between 0.49% to 0.87% new cases per year. Currently, the number of affected people is around 850 million worldwide. CKD is a slowly progressive disease that leads to irreversible loss of kidney function, end-stage kidney disease, and premature death. Therefore, CKD is considered a global health problem, and this sets the alarm for necessary efficient prediction, management, and disease prevention. At present, modern computer analysis, such as in silico medicine (ISM), denotes an emergent data science that offers interesting promise in the nephrology field. ISM offers reliable computer predictions to suggest optimal treatments in a case-specific manner. In addition, ISM offers the potential to gain a better understanding of the kidney physiology and/or pathophysiology of many complex diseases, together with a multiscale disease modeling. Similarly, -omics platforms (including genomics, transcriptomics, metabolomics, and proteomics), can generate biological data to obtain information on gene expression and regulation, protein turnover, and biological pathway connections in renal diseases. In this sense, the novel patient-centered approach in CKD research is built upon the combination of ISM analysis of human data, the use of in vitro models, and in vivo validation. Thus, one of the main objectives of CKD research is to manage the disease by the identification of new disease drivers, which could be prevented and monitored. This review explores the wide-ranging application of computational medicine and the application of -omics strategies in evaluating and managing kidney diseases.

Nonalcoholic fatty liver disease or metabolic-associated fatty liver disease (MAFLD) is a common condicion with increasing prevalence and incidence, specially in patients with type 2 diabetes mellitus (T2DM). Both cardiovascular and renal disease are clearly increased in these patients, particularly in those with diabetic nephropathy. In the liver-heart-kidneymetabolic axis, the common pathophysiological basis of MAFLD, cardiovascular disease (CVD), chronic kidney disease (CKD), and T2DM is the same. The clinical relationship between all of them is clear and is multidirectional: MAFLD may precede the development of cardiovascular and renal disease, and may also worsen the prognosis of these complications once developed. In this review we emphasize the importance of targeting MAFLD in Diabetic kidney disease, with the goal of detecting high-risk patients in order to improve their prognosis.