Biomarkers Screening and Mechanisms Analysis of the Restraint Stress-Induced Myocardial Injury in Hyperlipidemia ApoE-/- Mice.

OBJECTIVES: To explore the biomarkers and potential mechanisms of chronic restraint stress-induced myocardial injury in hyperlipidemia ApoE-/- mice. METHODS: The hyperlipidemia combined with the chronic stress model was established by restraining the ApoE-/- mice. Proteomics and bioinformatics techniques were used to describe the characteristic molecular changes and related regulatory mechanisms of chronic stress-induced myocardial injury in hyperlipidemia mice and to explore potential diagnostic biomarkers. RESULTS: Proteomic analysis showed that there were 43 significantly up-regulated and 58 significantly down-regulated differentially expressed proteins in hyperlipidemia combined with the restraint stress group compared with the hyperlipidemia group. Among them, GBP2, TAOK3, TFR1 and UCP1 were biomarkers with great diagnostic potential. KEGG pathway enrichment analysis indicated that ferroptosis was a significant pathway that accelerated the myocardial injury in hyperlipidemia combined with restraint stress-induced model. The mmu_circ_0001567/miR-7a/Tfr-1 and mmu_circ_0001042/miR-7a/Tfr-1 might be important circRNA-miRNA-mRNA regulatory networks related to ferroptosis in this model. CONCLUSIONS: Chronic restraint stress may aggravate myocardial injury in hyperlipidemia mice via ferroptosis. Four potential biomarkers are selected for myocardial injury diagnosis, providing a new direction for sudden cardiac death (SCD) caused by hyperlipidemia combined with the restraint stress.

Multi-omics analysis unravels dysregulated lysosomal function and lipid metabolism involved in sub-chronic particulate matter-induced pulmonary injury.

Particulate matter (PM) is a huge environmental threat and is of major public concern. Oxidative stress and systemic inflammation are known factors that contribute to PM- related damage; however, a systematic understanding of the deleterious pulmonary effects of PM using multi-omics analysis is lacking. In this study, we performed transcriptomic, proteomic, and metabolomic analyses in a mouse model exposed to PM for three months to identify molecular changes in lung tissues. We identified 1690 genes, 326 proteins, and 67 metabolites exhibiting significant differences between PM-challenged and control mice (p < 0.05). Differentially expressed genes and proteins regulated in PM-challenged mice were involved in lipid metabolism and in the immune and inflammatory response processes. Moreover, a comprehensive analysis of transcript, protein, and metabolite datasets revealed that the genes, proteins, and metabolites in the PM-treated group were involved in lysosomal function and lipid metabolism. Specifically, Cathepsin D (Ctsd), Ferritin light chain (Ftl), Lactotransferrin (Ltf), Lipocalin 2 (Lcn2), and Prosaposin (Psap) were major proteins/genes associated with PM-induced pulmonary damage, while two lipid molecules PC (18:1(11Z)/16:0) and PA (16:0/18:1(11Z)) were major metabolites related to PM-induced pulmonary injury. In summary, lipid metabolism might be used as successful precautions and therapeutic targets in PM-induced pulmonary injury to maintain the stability of cellular lysosomal function.

Expression profiling of circular RNAs and their potential role in early­stage diabetic cardiomyopathy.

Diabetic cardiomyopathy (DCM) is a severe cardiovascular complication of diabetes mellitus (DM). Detecting DCM during the early stages of the disease remains a challenge, as the molecular mechanisms underlying early­stage DCM are not clearly understood. Circular RNA (circRNA), a type of non­coding RNA, has been confirmed to be associated with numerous diseases. However, it is still unclear how circRNAs are involved in early­stage DCM. In the present study, heart tissues harvested from BKS­db/db knock­out mice were identified through high­throughput RNA sequencing technology. A total of 58 significantly differentially expressed circRNAs were identified in the db/db sample. Among these, six upregulated circRNAs and seven downregulated circRNAs were detected by reverse transcription­quantitative PCR and analyzed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Furthermore, based on the predicted binding site with microRNAs (miRNAs) involved in DCM, five circRNAs (mmu_circ_0000652, mmu_circ_0000547, mmu_circ_0001058, mmu_circ_0000680 and novel_circ_0004285) were shown to serve as competing endogenous (ce)RNAs. The corresponding miRNAs and mRNAs of the ceRNAs were also verified, and two promising circRNA­miRNA­mRNA regulatory networks were determined. Finally, internal ribosome entry site prediction combined with open reading frame prediction indicated that it was highly possible that mmu_circ_0001160 encoded a protein. In the present study, a comprehensive analysis of the circRNA expression profile during the early phase of DCM was performed, and two promising circRNA­miRNA­mRNA regulatory networks were identified. These results lay the foundation for unravelling the underlying pathogenesis of DCM, and highlight potential biomarkers and therapeutic targets for the treatment of DCM at an early stage.