MX1 and UBE2L6 are potential metaflammation gene targets in both diabetes and atherosclerosis.

Background: The coexistence of diabetes mellitus (DM) and atherosclerosis (AS) is widespread, although the explicit metabolism and metabolism-associated molecular patterns (MAMPs) responsible for the correlation are still unclear. Methods: Twenty-four genetically wild-type male Ba-Ma mini pigs were randomly divided into five groups distinguished by different combinations of 90 mg/kg streptozotocin (STZ) intravenous injection and high-cholesterol/lipid (HC) or high-lipid (HL) diet feeding for 9 months in total. Pigs in the STZ+HC and STZ+HL groups were injected with STZ first and then fed the HC or HL diet for 9 months. In contrast, pigs in the HC+STZ and HL+STZ groups were fed the HC or HL diet for 9 months and injected with STZ at 3 months. The controls were only fed a regular diet for 9 months. The blood glucose and abdominal aortic plaque observed through oil red O staining were used as evaluation indicators for successful modelling of DM and AS. A microarray gene expression analysis of all subjects was performed. Results: Atherosclerotic lesions were observed only in the HC+STZ and STZ+HC groups. A total of 103 differentially expressed genes (DEGs) were identified as common between them. The most significantly enriched pathways of 103 common DEGs were influenza A, hepatitis C, and measles. The global and internal protein-protein interaction (PPI) networks of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The top 10 hub proteins, namely, ISG15, IRG6, IRF7, IFIT3, MX1, UBE2L6, DDX58, IFIT2, USP18, and IFI44L, drive aspects of DM and AS. MX1 and UBE2L6 were the intersection of internal and global PPI networks. The expression of MX1 and UBE2L6 was 507.22 ± 342.56 and 96.99 ± 49.92 in the HC+STZ group, respectively, which was significantly higher than others and may be linked to the severity of hyperglycaemia-related atherosclerosis. Further PPI network analysis of calcium/micronutrients, including MX1 and UBE2L6, consisted of 58 and 18 nodes, respectively. The most significantly enriched KEGG pathways were glutathione metabolism, pyrimidine metabolism, purine metabolism, and metabolic pathways. Conclusions: The global and internal PPI network of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The intersection of the nodes of internal and global PPI networks was MX1 and UBE2L6, suggesting their key role in the comorbidity mechanism of DM and AS. This inference was partly verified by the overexpression of MX1 and UBE2L6 in the HC+STZ group but not others. Further calcium- and micronutrient-related enriched KEGG pathway analysis supported that MX1 and UBE2L6 may affect the inflammatory response through micronutrient metabolic pathways, conceptually named metaflammation. Collectively, MX1 and UBE2L6 may be potential common biomarkers for DM and AS that may reveal metaflammatory aspects of the pathological process, although proper validation is still needed to determine their contribution to the detailed mechanism.

Correlation of preoperative seizures with a wide range of tumor molecular markers in gliomas: An analysis of 442 glioma patients from China.

PURPOSE: Epileptic seizures often develop in 40-70 % of glioma patients and have a significant impact on patients' quality of life. Many biomarkers have been suggested to be associated with glioma-related preoperative seizures (GPS). The purpose of the present study was to investigate the possible correlation between GPS and clinicopathological factors and a wide range of glioma-associated molecular markers (GMMs). METHODS: First, a retrospective cohort study of 442 patients with glioma was evaluated at the PLA General Hospital. Univariate and multivariate logistic analyses were used to identify basic factors associated with GPS. Second, 40 pairs of cases who underwent deep sequencing of 68 GMMs were selected from both groups for in-depth analysis. RESULTS: Of the 442 patients examined in this study, 137 (31 %) had GPS. By analyzing the characteristics of these patients, the results showed that patient age (OR: 0.981, p = 0.037, 95 % CI: 0.964-0.999), WHO grade (OR: 0.678, p = 0.008, 95 % CI: 0.509-0.903) and IDH mutations (OR: 1.886, p = 0.013, 95 % CI: 1.143-3.11) in patients were associated with the occurrence of GPS. In our cohort, GPS did not differ by sex, tumor location, histopathological subtype, p53 expression, ARTX loss, MGMT gene promotor methylation, TERT promoter mutation, or 1p/19q co-deletion status. The results of the matching study showed that the paired groups had similar genetic expression profiles, and the mutation of these 68 GMMs was not correlated with the occurrence of GPS. CONCLUSION: The current study updates existing information on GPS and genetic markers in gliomas and explores the correlation of a wide range of GMMs and GPS. These factors may provide insights for developing effective treatment strategies aimed at seizure control.