Drug target genes and molecular mechanism investigation in isoflurane-induced anesthesia based on WGCNA and machine learning methods.

PURPOSE: This study sought to identify drug target genes and their associated molecular mechanisms during isoflurane-induced anesthesia in clinical applications. METHODS: Microarray data (ID: GSE64617; isoflurane-treated vs. normal samples) were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened and hub genes were investigated using weighted correlation network analysis (WGCNA). Protein-protein interactions (PPIs) were constructed among the co-DEGs (common genes between DEGs and hub genes), followed by functional enrichment analyses. Then, three machine learning methods were used to reveal drug targets, followed by validation, nomogram analysis, and gene set enrichment analysis. Finally, an miRNA-target network was constructed. RESULTS: A total of 686 DEGs were identified between the two groups-of which, 183 DEGs integrated with genes revealed by WCGNA were identified as co-genes. These genes, including contactin-associated protein 1 (CNTNAP1), are mainly involved in functions such as action potentials. PPI network analysis revealed three models, with the machine learning analysis exploring four drug target genes: A2H, FAM155B, SCARF2, and SDR16C5. ROC and nomogram analyses demonstrated the ideal diagnostic value of these target genes. Finally, miRNA-mRNA pairs were constructed based on the four mRNAs and associated 174 miRNAs. CONCLUSION: FA2H, FAM155B, SCARF2, and SDR16C5 may be novel drug target genes for isoflurane-induced anesthesia. CNTNAP1 may participate in the progression of isoflurane-induced anesthesia via its action potential function.

Sex Differences at Early Old Stage in Glycolipid Metabolism and Fatty Liver in Offspring Prenatally Exposed to Chinese Great Famine.

Background: About 50 years ago, Chinese Great Famine (CGF) affected the entire population in China, and its long-term influence on the offspring has attracted significant attention for research. However, information on possible metabolic differences between sexes is limited. This study explored whether there might be sex differences in the risks of development of glucolipid metabolic dysfunction and fatty liver following prenatal exposure to CGF. Materials and Methods: There were 11,417 subjects around 55 years of age (6,661 women and 4,756 men). They were divided as the exposed group in which the fetal stage was in CGF, and the unexposed group included those born after CGF. Analysis focused on comparisons between sexes. Results: Compared to the unexposed group, the BMI and triglyceride (P < 0.05) in men were higher in exposed group, while waist circumference and blood sugar (P < 0.05) in the exposed women were significantly higher. With the ages being properly balanced, the risks of glycolipid metabolic dysfunction were significantly higher in both men and women in the exposed than in the unexposed group (P < 0.001). Prenatal exposure to CGF significantly increased risks of abnormal BMI (P < 0.001, 95% CI: 2.305-2.93), blood sugar (P < 0.05, 95% CI: 1.050-1.401), triglycerides (P < 0.05, 95% CI: 1.006-1.245), and fatty liver (P < 0.001, 95% CI: 1.121-1.390) in men, and increased risks of abnormal blood sugar (P < 0.05, 95% CI: 1.024-1.689) and positive urine sugar (P < 0.05, 95% CI: 1.062-6.211) in women. Height and body weight were either the same or higher in the exposed subjects compared with the unexposed ones, regardless of sexes. Conclusion: This study is the first to identify sex differences in the long-term effects of CGF on metabolism and fatty liver. Importance of the findings include the benefits of prescribing medicine for the early prevention of certain diseases for each sex before aging based on the differences revealed. This study also shows "catch-up growth" in the offspring prenatally exposed to CGF as possible mechanisms underlying the long-term effects.