Association between inflammatory-response gene polymorphisms and risk of acute kidney injury in children

Molecular mechanisms and potential targets of lycopene for alleviating renal ischemia-reperfusion injury revealed by network pharmacology and animal experiments

OBJECTIVE

Renal IRI is one of the leading causes of AKI. How to effectively mitigate renal IRI is important for the recovery of renal function. The regulatory mechanism of lycopene, a natural antioxidant, in renal IRI is currently unknown. Therefore, we utilized network pharmacology and animal experiments to explore the possible mechanisms and potential targets of lycopene for alleviating renal IRI.

METHODS

We obtained lycopene-regulated genes and renal IRI-related genes from the CTD database and GeneCards database, respectively. Subsequently, the two were intersected and the intersecting genes we defined as lycopene-regulated genes in renal IRI. Next, we explored their potential biological functions and mechanisms through enrichment analysis. Meanwhile, we constructed a rat renal IRI model and validated the protective effects of lycopene and related mechanisms. To further explore the Hub genes regulated by lycopene, we constructed a PPI protein interactions network and characterized the Hub genes using Cytoscape software. We also verified the expression of Hub genes using animal experiments and molecular docking techniques. Finally, we constructed TF-Hub gene and miRNA-Hub gene regulatory networks.

RESULTS

We obtained a total of 255 lycopene-regulated genes and 327 renal IRI-related genes. The enrichment analysis revealed that they were closely related to the regulation of oxidative stress as well as the regulation of inflammatory factors. At the same time, the MAPK signaling pathway was significantly enriched. Next, we found in animal experiments that lycopene significantly alleviated the level of oxidative stress and inflammation during renal IRI, and had a protective effect on kidney damage. Also, we found that this protective effect may be achieved by inhibiting the MAPK signaling pathway. Next, we identified a total of five Hub genes using Cytoscape software: TNF, AKT1, MAPK3, IL6 and CASP3. Both animal experiments and molecular docking techniques demonstrated that lycopene can effectively regulate the expression of Hub genes. Finally, our constructed TF-Hub gene and miRNA-Hub gene regulatory network provide a theoretical basis for further regulation of Hub genes in follow-up.

CONCLUSIONS

This study suggests that lycopene is a promising option in mitigating renal IRI. Lycopene may exert protective effects by inhibiting the MAPK signaling pathway.

Transcriptomics reveals key regulatory pathways and genes associated with skin diseases induced by face paint usage

The use of face paint cosmetics can cause skin diseases in opera performers due to the presence of heavy metals and other toxic ingredients in the cosmetics. However, the underlying molecular mechanism for these diseases remains unknown. Here we examined the transcriptome gene profile of human skin keratinocytes exposed to artificial sweat extracts of face paints, and identified the key regulatory pathways and genes, using RNA sequencing technique. Bioinformatics analyses suggested that the face paint exposure induced the differentially expression of 1531 genes and enriched inflammation-relevant TNF and IL-17 signaling pathways after just 4 h of exposure. Inflammation-relevant genes CREB3L3, FOS, FOSB, JUN, TNF, and NFKBIA were identified as the potential regulatory genes, and SOCS3 capable to prevent inflammation-induced carcinogenesis as the hub-bottleneck gene. Long-term exposure (24 h) could exacerbate inflammation, accompanied by interference in cellular metabolism pathways, and the potential regulatory genes (ATP1A1, ATP1B1, ATP1B2, FXYD2, IL6, and TNF) and hub-bottleneck genes (JUNB and TNFAIP3) were all related to inflammation induction and other adverse responses. We proposed that the exposure to face paint might cause the inflammatory factors TNF and IL-17, which are encoded by the genes TNF and IL17, to bind to receptors and activate TNF and IL-17 signaling pathways, leading to the expression of cell proliferation factors (CREB and AP-1) and proinflammatory mediators including transcription factors (FOS, JUN, and JUNB), inflammatory factors (TNF-α and IL6), and intracellular signaling factors (TNFAIP3). This finally resulted in cell inflammation, apoptosis, and other skin diseases. TNF was identified as the key regulator and connector in all the enriched signaling pathways. Our study provides the first insights into the cytotoxicity mechanism of face paints to skin cells and highlights the need for stricter regulations in face paint safety.

Investigation of the Relationship Between IL-18 (- 607 C/A), IL-18 (- 137 G/C), and MMP-2 (- 1306 C/T) Gene Variations and Serum Copper and Zinc Levels in Patients Diagnosed with Chronic Renal Failure

The aim of this study is to investigate the relationship between IL-18 (- 607 C/A), IL-18 (- 137 G/C), and MMP-2 (- 1306 C/T) gene variations and serum trace element levels in patients diagnosed with CRF. Genotype distributions of IL-18 (- 607 C/A, - 137 G/C) gene variations were determined by polymerase chain reaction (PCR) method. PCR-restriction fragment length polymorphism (RFLP) methods were used to determine the MMP-2 (- 1306 C/T) gene variation genotype distributions. Serum trace element levels were determined by atomic absorption spectrophotometer method. A significant difference was found between the CRF patient and healthy control groups in terms of genotype distributions of IL-18 (- 607 C/A) and MMP-2 (- 1306 C/T) gene variations (p < 0.05). The significant difference was found between the patient and control groups in terms of serum copper and zinc levels and copper/zinc ratio (p < 0.05). The significant difference was detected between patient and control groups in terms of copper and zinc levels and copper/zinc ratio according to IL-18 (- 607 C/A), IL-18 (- 137 G/C), and MMP-2 (- 1306 C/T) gene variations and genotype distributions (p < 0.05). In addition, significant difference was determined in terms of serum copper and zinc levels and copper/zinc ratio according to haplotypes of IL-18 (- 607 C/A), IL-18 (- 137 G/C), and MMP-2 (- 1306 C/T) gene variations between patient and control groups (p < 0.05). In conclusion, evaluation of IL-18 (- 607 C/A, - 137 G/C) and MMP-2 (- 1306 C/T) gene variations and serum trace element levels together is extremely important in terms of obtaining important biomarkers in CRF early diagnosis and progression.

Identification of key biomarkers and signaling pathways and analysis of their association with immune cells in immunoglobulin A nephropathy

Introduction

Immunoglobulin A nephropathy (IgAN) is the most common glomerular disease worldwide, with a poor prognosis. The aim of our study was to identify key biomarkers and their associations with immune cells to aid in the study of IgAN pathology and immunotherapy.

Material and methods

The data of IgAN were downloaded from a public database. The metaMA package and limma package were used to identify differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs), respectively. Biological functions of the DEmRNAs were analyzed. Machine learning was used to screen the mRNA biomarkers of IgAN. Pearson's correlation coefficient was used to analyze the correlation between mRNA biomarkers, immune cells and signaling pathways. Moreover, we constructed a miRNAs-mRNAs targeted regulatory network. Finally, we performed in vitro validation of the identified miRNAs and mRNAs.

Results

1205 DEmRNAs and 125 DEmiRNAs were identified. In gene set enrichment analysis (GSEA), tumor necrosis factor α (TNF-α) signaling via nuclear factor κB (NF-κB), apoptosis and MTORC-1 signaling were inhibited in IgAN. 8 mRNA biomarkers were screened by machine learning. In addition, the distribution of 8 immune cell types was found to be significantly different between normal controls and IgAN by difference analysis. Pearson correlation coefficient analysis demonstrated that AKAP8L was significantly negatively correlated with CD4⁺ memory T-cells. AKAP8L was also significantly negatively correlated with TNF-α signaling via NF-κB, apoptosis, and MTORC-1 signaling. Subsequently, 5 mRNA biomarkers predicted corresponding negative regulatory miRNAs.

Conclusions

The identification of 8 important biomarkers and their correlation with immune cells and biological signaling pathways provides new ideas for further study of IgAN.

Potential Value of TNF-α (-376 G/A) Polymorphism and Cystatin C (CysC) in the Diagnosis of Sepsis Associated Acute Kidney Injury (S-AK I) and Prediction of Mortality in Critically Ill patients

Sepsis Associated Kidney Injury represents a major health concern as it is frequently associated with increased risk of mortality and morbidity. We aimed to evaluate the potential value of TNF-α (-376 G/A) and cystatin C in the diagnosis of S-AKI and prediction of mortality in critically ill patients. This study included 200 critically ill patients and 200 healthy controls. Patients were categorized into 116 with acute septic shock and 84 with sepsis, from which 142 (71%) developed S-AKI. Genotyping of TNF-α (-376 G/A) was performed by RT-PCR and serum CysC was assessed by Enzyme Linked Immunosorbent Assay. Our results showed a highly significant difference in the genotype frequencies of TNF-α (-376 G/A) SNP between S-AKI and non-AKI patients (p < 0.001). Additionally, sCysC levels were significantly higher in the S-AKI group (p = 0.011). The combination of both sCysC and TNF-α (-376 G/A) together had a better diagnostic ability for S-AKI than sCysC alone (AUC = 0.610, 0.838, respectively). Both GA and AA genotypes were independent predictors of S-AKI (p= < 0.001, p = 0.002 respectively). Additionally, sCysC was significantly associated with the risk of S-AKI development (Odds Ratio = 1.111). Both genotypes and sCysC were significant predictors of non-survival (p < 0.001), suggesting their potential role in the diagnosis of S-AKI and prediction of mortality.

Genetic Susceptibility to Acute Kidney Injury

Acute kidney injury (AKI) is a widely held concern related to a substantial burden of morbidity, mortality and expenditure in the healthcare system. AKI is not a simple illness but a complex conglomeration of syndromes that often occurs as part of other syndromes in its wide clinical spectrum of the disease. Genetic factors have been suggested as potentially responsible for its susceptibility and severity. As there is no current cure nor an effective treatment other than generally accepted supportive measures and renal replacement therapy, updated knowledge of the genetic implications may serve as a strategic tactic to counteract its dire consequences. Further understanding of the genetics that predispose AKI may shed light on novel approaches for the prevention and treatment of this condition. This review attempts to address the role of key genes in the appearance and development of AKI, providing not only a comprehensive update of the intertwined process involved but also identifying specific markers that could serve as precise targets for further AKI therapies.

Deciphering key genes in cardio-renal syndrome using network analysis

Cardio-renal syndrome (CRS) is a rapidly recognized clinical entity which refers to the inextricably connection between heart and renal impairment, whereby abnormality to one organ directly promotes deterioration of the other one. Biological markers help to gain insight into the pathological processes for early diagnosis with higher accuracy of CRS using known clinical findings. Therefore, it is of interest to identify target genes in associated pathways implicated linked to CRS. Hence, 119 CRS genes were extracted from the literature to construct the PPIN network. We used the MCODE tool to generate modules from network so as to select the top 10 modules from 23 available modules. The modules were further analyzed to identify 12 essential genes in the network. These biomarkers are potential emerging tools for understanding the pathophysiologic mechanisms for the early diagnosis of CRS. Ontological analysis shows that they are rich in MF protease binding and endo-peptidase inhibitor activity. Thus, this data help increase our knowledge on CRS to improve clinical management of the disease.

Ethnicity-Stratified Analysis of the Association between TNF-α Genetic Polymorphisms and Acute Kidney Injury: A Systematic Review and Meta-Analysis

Background

Several studies have reported conflicting findings regarding the association between tumor necrosis factor-alpha (TNF-α) genetic polymorphisms and acute kidney injury (AKI). Therefore, we performed this meta-analysis to further investigate whether TNF-α variants are related to AKI susceptibility.

Methods

A comprehensive search of observational studies on the association of TNF-α polymorphism with AKI susceptibility was conducted in the PubMed, Cochrane, and Embase databases through February 10, 2020. Pooled odds ratios (ORs) and 95% corresponding confidence intervals (95% CIs) were analyzed to evaluate the strength of the relationship.

Results

A total of 8 studies involving 6694 patients (2559 cases and 4135 controls) were included. Pooled analysis showed a trend of increased risk between the TNF-α rs1800629 variant and AKI (A vs. G: OR [95%CI] = 1.33 [0.98‐1.81]) among the overall population. Ethnicity-stratified analysis indicated that the TNF-α rs1800629 variant was a risk factor for Asians (OR [95%CI] = 1.93 [1.59‐2.35]) while it is not for Caucasians (OR [95%CI] = 1.04 [0.91‐1.20]). Additionally, we also found that TNF-α rs1799964 polymorphism was observed to have a significant relationship with AKI risk in Asian patients (C vs. T, OR [95%CI] = 1.26 [1.11‐1.43]).

Conclusions

The TNF rs1800629 polymorphism exhibited a trend toward AKI susceptibility with ethnic differences. The relationship was found to be significant among the Asian population, but not among those of Caucasian origin. Additionally, the TNF-α rs1799964 polymorphism was also related to a significantly increased risk of AKI in Asians.