Affiliation:
1. Department of Internal Medicine, Evangelismos General Hospital, 45-47 Ipsilantou Str., 10676 Athens, Greece
2. Department of Microbiology, “KAT” General Hospital of Attica, 14561 Athens, Greece
3. Department of Internal Medicine, Democritus University of Thrace, Dragana, 68100 Alexandroupoli, Greece
4. Second Department of Critical Care, Attikon University Hospital, 1 Rimini Str., 12462 Athens, Greece
5. Department of Biological Chemistry, National and Kapodistrian University of Athens, 75 Mikras Asias Str., 11527 Athens, Greece
Abstract
Worldwide, sepsis is a well-recognized cause of death. Acute kidney injury (AKI) may be related to sepsis in up to 70% of AKI cases. Sepsis-associated AKI (SA-AKI) is defined as the presence of AKI according to the Kidney Disease: Improving Global Outcomes criteria in the context of sepsis. SA-AKI is categorized into early, which presents during the first 48 h of sepsis, and late, presenting between 48 h and 7 days of sepsis. SA-AKI is associated with a worse prognosis among patients with sepsis. However, there are different SA-AKI phenotypes as well as different pathophysiological pathways of SA-AKI. The aim of this review is to provide an updated synopsis of the pathogenetic mechanisms underlying the development of SA-AKI as well as to analyze its different phenotypes and prognosis. In addition, potential novel diagnostic and prognostic biomarkers as well as therapeutic approaches are discussed. A plethora of mechanisms are implicated in the pathogenesis of SA-AKI, including inflammation and metabolic reprogramming during sepsis; various types of cell death such as apoptosis, necroptosis, pyroptosis and ferroptosis; autophagy and efferocytosis; and hemodynamic changes (macrovascular and microvascular dysfunction). Apart from urine output and serum creatinine levels, which have been incorporated in the definition of AKI, several serum and urinary diagnostic and prognostic biomarkers have also been developed, comprising, among others, interleukins 6, 8 and 18, osteoprotegerin, galectin-3, presepsin, cystatin C, NGAL, proenkephalin A, CCL-14, TIMP-2 and L-FABP as well as biomarkers stemming from multi-omics technologies and machine learning algorithms. Interestingly, the presence of long non-coding RNAs (lncRNAs) as well as microRNAs (miRNAs), such as PlncRNA-1, miR-22-3p, miR-526b, LncRNA NKILA, miR-140-5p and miR-214, which are implicated in the pathogenesis of SA-AKI, may also serve as potential therapeutic targets. The combination of omics technologies represents an innovative holistic approach toward providing a more integrated view of the molecular and physiological events underlying SA-AKI as well as for deciphering unique and specific phenotypes. Although more evidence is still necessary, it is expected that the incorporation of integrative omics may be useful not only for the early diagnosis and risk prognosis of SA-AKI, but also for the development of potential therapeutic targets that could revolutionize the management of SA-AKI in a personalized manner.