The importance of triglycerides (TG) level as a risk factor for cardiovascular diseases (CVD) has been extensively investigated in the general population; however, their relationship in patients with type 2 diabetes mellitus (T2DM) is uncertain. We aimed to assess the association of TG with CVD in T2DM individuals. We searched bibliographic databases for studies published until June 2018, reporting on the relationship between TG and CVD in T2DM people. A random-effects model with inverse variance weighting was used to compute pooled estimates of the most fully adjusted risk ratios (RR) and corresponding 95% confidence intervals (CI) according to TG categories, unit TG, and logarithm (log) of TG for CVD. A total of 31 studies were included, involving 132,044 T2DM patients with 10,733 incident cardiovascular events. The pooled RR (95% CI) of CVD for an increase in baseline TG, log TG by 1-mmol/l and categorized in the highest vs. the lowest TG in T2DM were 1.06 (1.02, 1.09), 1.30 (1.18, 1.42) and 1.30 (1.16, 1.46), corresponding to a CVD risk increase of 6%, 30% and 30%, respectively. The pooled RR (95% CI) of CVD for per 1-mmol/L TG increment in eight studies and TG categories in three studies were 1.03 (0.98, 1.08) and 1.39 (0.92, 2.1) in T2DM patients adjusted for other lipids parameter, respectively. In T2DM patients, an elevated triglyceride level cannot serve as an independent marker for an increased risk of cardiovascular events, but still, the higher serum TG levels tend to be associated with increased risks of CVD.

Objective . Fulminant type 1 diabetes (FT1D) is a type of type 1 diabetes, which is characterized by rapid onset of disease and severe metabolic disorders. We intend to screen for crucial genes and potential molecular mechanisms in FT1D in this study. Method . We downloaded GSE44314, which includes six healthy controls and five patients with FT1D, from the GEO database. Identification of differentially expressed genes (DEGs) was performed by NetworkAnalyst. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were screened by an online tool—Database for Annotation, Visualization, and Integration Discovery (DAVID). Protein‐protein interaction (PPI) network and hub genes among DEGs were analyzed by NetworkAnalyst. And we also use NetworkAnalyst to find out the microRNAs (miRNAs) and transcription factors (TFs) which regulate the expression of DEGs. Result . We identified 130 DEGs (60 upregulated and 70 downregulated DEGs) between healthy controls and FT1D patients. GO analysis results revealed that DEGs were mostly enriched in generation of precursor metabolites and energy, neurohypophyseal hormone activity, and mitochondrial inner membrane. KEGG pathway analysis demonstrated that DEGs were mostly involved in nonalcoholic fatty liver disease. Results indicated that NCOA1, SRF, ERBB3, EST1, TOP1, UBE2S, INO80, COX7C, ITGAV, and COX6C were the top hub genes in the PPI network. Furthermore, we recognized that LDLR, POTEM, IFNAR2, BAZ2A, and SRF were the top hub genes in the miRNA‐target gene network, and SRF, TSPAN4, CD59, ETS1, and SLC25A25 were the top hub genes in the TF‐target gene network. Conclusion . Our study pinpoints key genes and pathways associated with FT1D by a sequence of bioinformatics analysis on DEGs. These identified genes and pathways provide more detailed molecular mechanisms of FT1D and may provide novel therapeutic targets.

Endometriosis is referred to as a “benign cancer,” severely impacting women’s reproductive health. However, the pathogenesis of endometriosis remains unclear. This study aims to investigate the potential roles of lipid metabolism-related genes (LMRGs) and immune infiltration in the diagnosis and pathogenesis of endometriosis. Four microarray datasets (GSE6364, GSE51981, GSE153740, and GSE232713) with eutopic endometrium samples of the midsecretory phase were downloaded from the Gene Expression Omnibus database. Seven hundred forty LMRGs were obtained from the Reactome database. The GSE6364 and GSE51981 datasets were merged and differentially expressed genes (DEGs) were identified between endometriosis patients and normal controls. Lipid metabolism-related DEGs were detected by intersecting the DEGs and LMRGs. Functional enrichment analysis, protein–protein interaction analysis, and receiver operating characteristic analysis of lipid metabolism-related DEGs were performed. Additionally, immune cell infiltration was compared between endometriosis patients and normal controls, and associations with lipid metabolism-related DEGs were assessed. Fifty-eight lipid metabolism-related DEGs were identified in endometriosis patients compared with normal controls, which enriched in glycerolipids, fatty acyls, sphingolipids, glycerophospholipids, and sterol lipids metabolism, especially steroid hormone metabolism and arachidonic acid metabolism. Additionally, 11 core genes were identified, with HMGCR and CYP27A1 validated as potential markers for diagnosing endometriosis and assessing its severity, respectively. Immune infiltration analysis revealed that fibroblasts and B lineage cells were predominantly abnormal in the endometrium of the midsecretory phase in endometriosis. Correlation analysis suggested that core genes were closely related to immune cells. In conclusion, HMGCR and CYP27A1 were identified as potential markers for endometriosis and its severity, respectively. Fibroblasts and B lineage cells may significantly contribute to the reduced endometrial receptivity observed in endometriosis. These findings provide new insights into the diagnostic and pathogenic roles of LMRGs in endometriosis and highlight their implications for infertility and pregnancy complications related to endometriosis.