The value of serial serum cell adhesion molecules in predicting acute kidney injury after severe sepsis in adults

Clinical significance of miR-625-5p in patients with sepsis-induced acute kidney injury based on bioinformatics analysis

PURPOSE

Sepsis often leads to a cluster of life-threatening symptoms affecting multiple organ systems. Among the organs most vulnerable to damage in this state is the kidney; those afflicted with severe sepsis frequently encounter acute kidney injury (AKI). The study was to investigate the diagnostic role of miR-625-5p in sepsis and sepsis-induced acute kidney injury (SI-AKI) and predict the possible pathways of miR-625-5p involved in SI-AKI by bioinformatics method.

METHODS

RT-qPCR was used to detect the level of miR-625-5p, and the diagnostic value of miR-625-5p was analyzed using ROC curve. The proliferation and the concentration of inflammatory factors of HK-2 cells induced by LPS were detected by CCK-8 and ELISA. The pathway of miR-625-5p involved in SI-AKI was analyzed by bioinformatics method.

RESULTS

The miR-625-5p expression was downregulated in sepsis as well as SI-AKI and has predictive value for sepsis as well as SI-AKI. In addition, miR-625-5p promoted LPS-induced cell proliferation and inhibited the levels of inflammatory cytokines.

CONCLUSION

miR-625-5p may be a diagnostic biomarker for SI-AKI.

Urinary proteome analysis of acute kidney injury in post-cardiac surgery patients using enrichment materials with high-resolution mass spectrometry

Background: Cardiac surgery-associated acute kidney injury (CSA-AKI) may increase the mortality and incidence rates of chronic kidney disease in critically ill patients. This study aimed to investigate the underlying correlations between urinary proteomic changes and CSA-AKI.

Methods: Nontargeted proteomics was performed using nano liquid chromatography coupled with Orbitrap Exploris mass spectrometry (MS) on urinary samples preoperatively and postoperatively collected from patients with CSA-AKI. Gemini C18 silica microspheres were used to separate and enrich trypsin-hydrolysed peptides under basic mobile phase conditions. Differential analysis was conducted to screen out urinary differential expressed proteins (DEPs) among patients with CSA-AKI for bioinformatics. Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis was adopted to identify the altered signal pathways associated with CSA-AKI.

Results: Approximately 2000 urinary proteins were identified and quantified through data-independent acquisition MS, and 324 DEPs associated with AKI were screened by univariate statistics. According to KEGG enrichment analysis, the signal pathway of protein processing in the endoplasmic reticulum was enriched as the most up-regulated DEPs, and cell adhesion molecules were enriched as the most down-regulated DEPs. In protein–protein interaction analysis, the three hub targets in the up-regulated DEPs were α-1-antitrypsin, β-2-microglobulin and angiotensinogen, and the three key down-regulated DEPs were growth arrest-specific protein 6, matrix metalloproteinase-9 and urokinase-type plasminogen activator.

Conclusion: Urinary protein disorder was observed in CSA-AKI due to ischaemia and reperfusion. The application of Gemini C18 silica microspheres can improve the protein identification rate to obtain highly valuable resources for the urinary DEPs of AKI. This work provides valuable knowledge about urinary proteome biomarkers and essential resources for further research on AKI.

Rates, predictors, and mortality of sepsis-associated acute kidney injury: a systematic review and meta-analysis

BACKGROUND

Due to the high incidence and mortality of sepsis-associated acute kidney injury, a significant number of studies have explored the causes of sepsis-associated acute kidney injury (AKI). However, the opinions on relevant predictive risk factors remain inconclusive. This study aimed to provide a systematic review and meta-analysis to determine the predisposing factors for sepsis-associated AKI.

METHOD

A systematic literature search was performed in the Medline, Embase, Cochrane Library, PubMed, and Web of Science, databases, with an end-date of 25th May 2019. Valid data were retrieved in compliance with specific inclusion and exclusion criteria.

RESULT

Forty-seven observational studies were included for analysis, achieving a cumulative patient number of 55,911. The highest incidence of AKI was caused by septic shock. Thirty-one potential risk factors were included in the meta-analysis. Analysis showed that 20 factors were statistically significant. The odds ratio (OR) and 95% confidence interval (CI), as well as the prevalence of the most frequently-seen predisposing factors for sepsis-associated AKI, were as follows: septic shock [2.88 (2.36-3.52), 60.47%], hypertension [1.43 (1.20-1.70), 38.39%], diabetes mellitus [1.59 (1.47-1.71), 27.57%], abdominal infection [1.44 (1.32-1.58), 30.87%], the administration of vasopressors [2.95 (1.67-5.22), 64.61%], the administration of vasoactive drugs [3.85 (1.89-7.87), 63.22%], mechanical ventilation [1.64 (1.24-2.16), 68.00%], positive results from blood culture [1.60 (1.35-1.89), 41.19%], and a history of smoking [1.60 (1.09-2.36), 43.09%]. Other risk factors included cardiovascular diseases, coronary artery diseases, liver diseases, unknown infections, the administration of diuretics and ACEI/ARB, the infection caused by gram-negative bacteria, and organ transplantation.

CONCLUSION

Risk factors of S-AKI arise from a wide range of sources, making it difficult to predict and prevent this condition. Comorbidities, and certain drugs, are the main risk factors for S-AKI. Our review can provide guidance on the application of interventions to reduce the risks associated with sepsis-associated acute kidney injury and can also be used to tailor patient-specific treatment plans and management strategies in clinical practice.

Coagulative biomarkers on admission to the ICU predict acute kidney injury and mortality in patients with septic shock caused by intra-abdominal infection

Purpose

Sepsis-associated coagulopathy (SAC) contributes to the development of multiple organ failure (MOF) and increasing mortality. The present study was conducted to investigate whether coagulative biomarkers on admission to the intensive care unit (ICU) can predict acute kidney injury (AKI) and mortality in patients with septic shock caused by intra-abdominal infection (IAI).

Patients and methods

An observational retrospective study was conducted in the surgical ICU. We studied patients who met the criteria of septic shock (Sepsis-3) caused by IAI between January 1, 2013, and December 31, 2016. By adjusting for baseline characteristics, multivariate regression analyses were employed to identify independent risk factors for predicting AKI and mortality.

Results

Of the 138 enrolled patients, 65 patients developed AKI. The patients who developed AKI exhibited a dramatically higher Sequential Organ Failure Assessment (SOFA) score (median, 12), Acute Physiology and Chronic Health Evaluation (APACHE) II score (median, 27.5) and mortality rate. In both models, we found that activated partial thromboplastin time (APTT) (odds ratio (OR)=1.074, 95% confidence interval (CI) 1.030-1.120, p=0.001), prothrombin time (PT) (OR=1.162, 95% CI 1.037-1.302, p=0.010) and D-dimer level (OR=1.098, 95% CI 1.002-1.202, p=0.045) on admission to the ICU were significant risk factors for AKI. Moreover, Cox regression analysis showed that prolonged APTT (OR=1.065, 95% CI 1.025-1.107, p=0.001) was independently associated with high mortality.

Conclusion

In patients with septic shock caused by IAI, APTT, PT and D-dimer level on admission to the ICU were significantly associated with AKI. Furthermore, APTT was an independent predictor of 30-day mortality.

Proteomics and Metabolomics for AKI Diagnosis

Acute kidney injury (AKI) is a severe and frequent condition in hospitalized patients. Currently, no efficient therapy of AKI is available. Therefore, efforts focus on early prevention and potentially early initiation of renal replacement therapy to improve the outcome in AKI. The detection of AKI in hospitalized patients implies the need for early, accurate, robust, and easily accessible biomarkers of AKI evolution and outcome prediction because only a narrow window exists to implement the earlier-described measures. Even more challenging is the multifactorial origin of AKI and the fact that the changes of molecular expression induced by AKI are difficult to distinguish from those of the diseases associated or causing AKI as shock or sepsis. During the past decade, a considerable number of protein biomarkers for AKI have been described and we expect from recent advances in the field of omics technologies that this number will increase further in the future and be extended to other sorts of biomolecules, such as RNAs, lipids, and metabolites. However, most of these biomarkers are poorly defined by their AKI-associated molecular context. In this review, we describe the state-of-the-art tissue and biofluid proteomic and metabolomic technologies and new bioinformatics approaches for proteomic and metabolomic pathway and molecular interaction analysis. In the second part of the review, we focus on AKI-associated proteomic and metabolomic biomarkers and briefly outline their pathophysiological context in AKI.

Immunopathogenesis of Acute Kidney Injury

Pathophysiologically, the classification of acute kidney injury (AKI) can be divided into three categories: (1) prerenal, (2) intrinsic, and (3) postrenal. Emerging evidence supports the involvement of renal tubular epithelial cells and the innate and adaptive arms of the immune system in the pathogenesis of intrinsic AKI. Pro-inflammatory damage-associated molecular patterns, pathogen-associated molecular patterns, hypoxia inducible factors, toll-like receptors, complement system, oxidative stress, adhesion molecules, cell death, resident renal dendritic cells, neutrophils, T and B lymphocytes, macrophages, natural killer T cells, cytokines, and secreted chemokines contribute to the immunopathogenesis of AKI. However, other immune cells and pathways such as M2 macrophages, regulatory T cells, progranulin, and autophagy exhibit anti-inflammatory properties and facilitate kidney tissue repair after AKI. Thus, therapies for AKI include agents such as anti-inflammatory (e.g., recombinant alkaline phosphatase), antioxidants (iron chelators), and apoptosis inhibitors. In preclinical toxicity studies, drug-induced kidney injury can be seen after exposure to a nephrotoxicant test article due to immune mechanisms and dysregulation of innate, and/or adaptive cellular immunity. The focus of this review will be on intrinsic AKI, as it relates to the immune and renal systems cross talks focusing on the cellular and pathophysiologic mechanisms of AKI.

Markers of acute kidney injury in patients with sepsis: the role of soluble thrombomodulin

Background

Endothelial activation and damage occur early during sepsis, with activated coagulopathy and playing a major role in the pathophysiology of sepsis-induced acute kidney injury (AKI). The aim of this study was to compare the various biomarkers of endothelial injury with the biomarkers of coagulation and inflammation and to determine a significant predictor of AKI in patients with sepsis.

Methods

We conducted a single-center, retrospective, observational study on patients with sepsis fulfilling the Third International Consensus Definitions for Sepsis and Septic Shock criteria admitted to an adult intensive care unit (ICU) at a university hospital from June 2011 to December 2016. Levels of 13 biomarkers were measured on ICU admission, including markers of endothelial injury (soluble thrombomodulin [sTM], E-selectin, protein C, and plasminogen activator inhibitor-1 [PAI-1]) and markers of coagulation derangement (platelet count, fibrin degradation product [FDP], prothrombin time [PT], fibrinogen, α₂-plasminogen inhibitor [α₂-PI], antithrombin III [AT III], plasminogen, thrombin-antithrombin complex, and plasmin-α₂-plasmin inhibitor complex). All patients with sepsis were reviewed, and the development of AKI was evaluated. Multivariate logistic regression analysis was performed to identify significant independent predictive factors for AKI.

Results

Of the 514 patients admitted with sepsis, 351 (68.3%) developed AKI. Compared with the non-AKI group, all the endothelial biomarkers were significantly different in the AKI group (sTM [23.6 vs. 15.6 U/ml, P < 0.0001], E-selectin [65.5 vs. 46.2 ng/ml, P = 0.0497], PAI-1 [180.4 vs. 75.3 ng/ml, P = 0.018], and protein C [45.9 vs. 58.7 ng/ml, P < 0.0001]). Biomarkers of coagulopathy and inflammation, platelet counts, FDP, PT, α₂-PI, AT III, plasminogen, and C-reactive protein were significantly different between the two groups. Multivariable logistic regression analysis showed that sTM was an independent predictive factor of AKI, with an AUROC of 0.758 (P < 0.0001).

Conclusions

Endothelial biomarkers were significantly changed in the sepsis patients with AKI. Particularly, sTM was an independent predictive biomarker for the development of AKI that outperformed other coagulation and inflammation biomarkers as well as organ function in patients with sepsis.