Sepsis is the primary cause of acute kidney injury (AKI) and is associated with high mortality rates. Growing evidence suggests that noncoding RNAs are vitally involved in kidney illnesses, whereas the role of circular RNAs (circRNAs) in sepsis-induced AKI (SAKI) remains largely unknown. In this present study, caecal ligation and puncture (CLP) in mice was performed to establish an SAKI model. The expression of circRNAs and mRNAs was analysed using circRNA microarray or next-generation sequencing. The results revealed that the expressions of 197 circRNAs and 2509 mRNAs were dysregulated. Validation of the selected circRNAs was performed by qRT-PCR. Bioinformatics analyses and chromatin immunoprecipitation demonstrated that NF-κB/p65 signalling induced the upregulation of circC3, circZbtb16, and circFkbp5 and their linear counterparts by p65 transcription in mouse tubular epithelial cells (mTECs). Furthermore, competitive endogenous RNA (ceRNA) networks demonstrated that some components of NF-κB signalling were potential targets of these dysregulated circRNAs. Among them, Tnf-α was increased by circFkbp5 through the downregulation of miR-760-3p in lipopolysaccharide (LPS)-stimulated mTECs. Knocking down circFkbp5 inhibited the p65 phosphorylation and apoptosis in injured mTECs. These findings suggest that the selected circRNAs and the related ceRNA networks provide new knowledge into the fundamental mechanism of SAKI and circFkbp5/miR-760-3p/Tnf-α axis might be therapeutic targets.
Differentially methylated regions (DMRs) are genomic regions with methylation patterns across multiple CpG sites that are associated with a phenotype. In this study, we proposed a Principal Component (PC) based DMR analysis method for use with data generated using the Illumina Infinium MethylationEPIC BeadChip (EPIC) array. We obtained methylation residuals by regressing the M-values of CpGs within a region on covariates, extracted PCs of the residuals, and then combined association information across PCs to obtain regional significance. Simulation-based genome-wide false positive (GFP) rates and true positive rates were estimated under a variety of conditions before determining the final version of our method, which we have named DMRPC. Then, DMRPC and another DMR method, coMethDMR, were used to perform epigenome-wide analyses of several phenotypes known to have multiple associated methylation loci (age, sex, and smoking) in a discovery and a replication cohort. Among regions that were analysed by both methods, DMRPC identified 50% more genome-wide significant age-associated DMRs than coMethDMR. The replication rate for the loci that were identified by only DMRPC was higher than the rate for those that were identified by only coMethDMR (90% for DMRPC vs. 76% for coMethDMR). Furthermore, DMRPC identified replicable associations in regions of moderate between-CpG correlation which are typically not analysed by coMethDMR. For the analyses of sex and smoking, the advantage of DMRPC was less clear. In conclusion, DMRPC is a new powerful DMR discovery tool that retains power in genomic regions with moderate correlation across CpGs.
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