Recent progress in bioinformatics has facilitated the clarification of biological processes associated with complex diseases. Numerous methods of co-expression analysis have been proposed for use in the study of pairwise relationships among genes. In the present study, a combined network based on gene pairs was constructed following the conversion and combination of gene pair score values using a novel algorithm across multiple approaches. Three hippocampal expression profiles of patients with Alzheimer's disease (AD) and normal controls were extracted from the ArrayExpress database, and a total of 144 differentially expressed (DE) genes across multiple studies were identified by a rank product (RP) method. Five groups of co-expression gene pairs and five networks were identified and constructed using four existing methods [weighted gene co-expression network analysis (WGCNA), empirical Bayesian (EB), differentially co-expressed genes and links (DCGL), search tool for the retrieval of interacting genes/proteins database (STRING)] and a novel rank-based algorithm with combined score, respectively. Topological analysis indicated that the co-expression network constructed by the WGCNA method had the tendency to exhibit small-world characteristics, and the combined co-expression network was confirmed to be a scale-free network. Functional analysis of the co-expression gene pairs was conducted by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The co-expression gene pairs were mostly enriched in five pathways, namely proteasome, oxidative phosphorylation, Parkinson's disease, Huntington's disease and AD. This study provides a new perspective to co-expression analysis. Since different methods of analysis often present varying abilities, the novel combination algorithm may provide a more credible and robust outcome, and could be used to complement to traditional co-expression analysis.

Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis.

Age-related cataract (ARC) is a common cause of blindness in elderly individuals. Long non-coding RNA (lncRNA) myocardial infarction associated transcript (MIAT) has been reported to participate in various biological processes in a number of diseases; however, the biological mechanism underlying MIAT during ARC is not completely understood. The expression levels of MIAT, microRNA (miR)-181a and connective tissue growth factor (CTGF) were measured by reverse transcription-quantitative PCR. The protein expression levels of CTGF, α-smooth muscle actin, fibronectin, collagen type I, ERK, phosphorylated (p)-ERK, mitogen-activated protein kinase (MEK), and p-MEK were detected by western blotting. Cell viability and migration were assessed using MTT and Transwell assays, respectively. Moreover, a dual-luciferase reporter assay was performed to investigate the interaction between miR-181a and MIAT or CTGF. MIAT and CTGF were upregulated, while miR-181a was significantly downregulated in ARC tissues compared with normal tissues. MIAT or CTGF knockdown decreased cell viability, migration, epithelial-mesenchymal transition and extracellular matrix production in TGF-β2-treated SRA01/04 cells. It was hypothesized that miR-181a may be sponged by MIAT and may target CTGF. Furthermore, the miR-181a inhibitor reversed the inhibitory effect of MIAT knockdown on the progression of TGF-β2-treated SRA01/04 cells. Moreover, CTGF knockdown also reversed MIAT overexpression-mediated progression of TGF-β2-treated SRA01/04 cells. In addition, MIAT and CTGF regulated the activity of the ERK signaling pathway. The results suggested that MIAT may regulate the progression of ARC via the miR-181a/CTGF/ERK signaling pathway, which may serve as a novel therapeutic target for ARC.

Silicosis is caused by exposure to crystalline silica and the molecular mechanism of silicotic fibrosis remains unclear. Therefore, the present study investigated the mRNA profiles of rats exposed to crystalline silica. RNA-sequencing techniques were used to observe differential expression of mRNAs in silicotic rats induced by chronic inhalation of crystalline silica particulates. Prediction of mRNA functions and signaling pathways was conducted using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Certain differentially expressed mRNAs were verified in lung tissue of silicotic rats by quantitative polymerase chain reaction (qPCR). Secreted phosphoprotein 1 (SPP1) was measured in serum from silicosis patients, lungs of silicotic rats and NR8383 macrophages treated with silica. A total of 1,338 mRNAs were revealed to be differentially expressed in silicotic rat lungs, including 912 upregulated and 426 downregulated mRNAs. In GO analysis of significant changes in mRNAs, the most affected processes were the defense response, extracellular space and chemokine activity in terms of biological process, cellular component and molecular function. In KEGG pathway analysis, dysregulated mRNAs were involved in systemic lupus erythematosus, staphylococcus aureus infection, complement and coagulation cascades, alcoholism and pertussis. qPCR demonstrated that expression of Spp1, Mmp12, Ccl7, Defb5, Fabp4 and Slc26a4 was increased in silicotic rats, while Lpo, Itln1, Lcn2 and Dlk1 expression was decreased. It was also found that SPP1 was increased in serum from silicosis patients, silicotic rats and silica-treated NR8383 macrophages. The expression of mRNAs was altered significantly in silicotic rats, which suggested that certain genes are novel targets for the diagnosis and treatment of silicosis.