Control of the GABAA receptor activity in monocytes/macrophages can potently modulate post-infarction inflammation. Topiramate emerges as a promising drug, which may be feasible to translate for MI therapy in the future.
Background Sarcopenia is characterized by the age-associated loss of skeletal muscle mass and strength that develops progressively and plays an important role in the disability of the elderly. It has received growing attention over the last decade and has been implicated as both a cause and consequence of type 2 diabetes mellitus (T2DM). The existence of T2DM could increase the risk of developing sarcopenia through multiple mechanisms including advanced glycation end-product accumulation. Meanwhile, sarcopenia would alter glucose disposal and may contribute to the development and progression of T2DM due to reduced muscle mass. Methods We implemented transcriptomic analysis of skeletal muscle biopsy specimens in sarcopenia patients and proliferating myoblasts or differentiated myotubes from individuals with T2DM. Related microarray data were selected from Gene Expression Omnibus (GEO) to screen the genes, which were differentially expressed for sarcopenia and T2DM. Multiple combinatorial statistical methods and bioinformatics tools were used to analyze the common DEGs. Meanwhile, functional enrichment analysis was also carried out. Furthermore, we constructed the protein-protein interaction (PPI), as well as transcription factor (TF)-gene interactions network and TF-miRNA coregulatory network. Finally, based on the common DEGs, drug compounds were speculated using the Drug Signatures database (DSigDB). Results A total of 1765 and 2155 DEGs of sarcopenia and T2DM were screened, respectively. 15 common genes (LXN, CIB2, PEA15, KANK2, FGD1, NMRK1, PLCB1, SEMA4G, ADARB1, UPF3A, CSTB, COL3A1, CD99, ETV3, FJX1) correlated with sarcopenia and T2DM simultaneously were then identified, and 3 genes (UPF3A, CSTB and PEA15) of them were regarded as hub genes. Functional enrichment analysis revealed several shared pathways between two diseases. In addition, according to the TF-gene interactions network and TF-miRNA coregulatory network, part of TF and miRNA may be identified as key regulator in sarcopenia and T2DM at the same time (e.g., CREM and miR-155). Notably, drug compounds for T2DM and sarcopenia were also suggested, such as coenzyme Q10. Conclusion This study revealed that sarcopenia and T2DM may share similar pathogenesis and provided new biological targets and ideas for early diagnosis and effective treatment of sarcopenia and T2DM.
Ferroptosis is a specific subtype of programmed cell death, which plays an essential role in the immune-associated disease, atherosclerosis (AS). The purpose of this study was to identify potential ferroptosis-related gene biomarkers and its association with immune infiltration characteristics in atherosclerosis with bioinformatics methods. Methods: Differentially expressed genes (DEGs) between AS and control groups were screened from GSE40231, analyzed for functional enrichment and then intersected with ferroptosis-related genes. Then, a random forest model was constructed based on these differentially expressed ferroptosis-related genes (DE-FRGs) and validated with dataset GSE132651. The performance of the models was evaluated with the area under receiver operating characteristic curves (AUC). Finally, we analyzed the correlation between DE-FRGs above and the characteristics of immune infiltration via CIBERSORT method. Results: Six DE-FRGs (IL6, ANGPTL7, CDKN1A, AKR1C3, NOX4 and VLDLR) were detected based on dataset of GSE40231. Furthermore, a random forest model was constructed based on them with a compelling diagnostic performance of AUC = 0.8974 in the validation dataset GSE132651. In addition, the proportion of follicular helper T (Tfh) cells was significantly higher in AS group (P < 0.001). And we found significant correlation relationship between Tfh and expression level of ANGPTL7 (R = 0.35, P < 0.01), CDKN1A (R = 0.4, P < 0.0001), AKR1C3 (R = 0.64, P < 0.0001), NOX4 (R = 0.32, P < 0.01) and VLDLR (R = −0.43, P < 0.0001). Conclusion:This study identified 6 DE-FRGs and validated a predicted model for the early prediction of AS, which also proved the close relationship between ferroptosis and immunity in the pathogenesis of AS.
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