Nϵ-Carboxymethyl-Lysine Deteriorates Vascular Calcification in Diabetic Atherosclerosis Induced by Vascular Smooth Muscle Cell-Derived Foam Cells.

Nϵ-carboxymethyl-lysine (CML), an advanced glycation end product, is involved in vascular calcification (VC) in diabetic atherosclerosis. This study aimed to investigate the effects of CML on VC in diabetic atherosclerosis induced by vascular smooth muscle cell (VSMC)-derived foam cells. Human studies, animal studies and cell studies were performed. The human study results from 100 patients revealed a poor blood glucose and lipid status and more severe coronary lesions and stenosis in patients with coronary artery disease and diabetes mellitus. Intraperitoneal injection of streptozotocin combined with a high-fat diet was used to build a diabetic atherosclerosis model in ApoE-/- mice. The animal study results indicated that CML accelerated VC progression in diabetic atherosclerosis by accelerating the accumulation of VSMC-derived foam cells in ApoE-/- mice. The cell study results illustrated that CML induced VSMC-derived foam cells apoptosis and aggravated foam cells calcification. Consistent with this finding, calcium content and the expression levels of alkaline phosphatase, bone morphogenetic protein 2 and runt-related transcription factor 2 were significantly elevated in A7r5 cells treated with oxidation-low-density lipoprotein and CML. Thus, we concluded that CML promoted VSMC-derived foam cells calcification to aggravate VC in diabetic atherosclerosis, providing evidence for the contribution of foam cells to diabetic VC.

Bioinformatics analysis reveals novel core genes associated with nonalcoholic fatty liver disease and nonalcoholic steatohepatitis.

Nonalcoholic fatty liver disease (NAFLD) is the most frequent liver disease and associated with a wide spectrum of hepatic disorders ranging from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular carcinoma (HCC). NASH is projected to become the most common indication for liver transplantation, and the annual incidence rate of NASH-related HCC is 5.29 cases per 1000 person-years. Owing to the epidemics of NAFLD and the unclear mechanism of NAFLD progression, it is important to elucidate the underlying NAFLD mechanisms in detail. NASH is mainly caused by the development of NAFL Therefore, it is also of great significance to understand the mechanism of progression from NAFL to NASH. Gene expression chip data for NAFLD and NASH were downloaded from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) between NAFLD and normal controls (called DEGs for NAFLD), as well as between NASH and normal tissue (called DEGs for NASH-Normal), and between NASH and NAFL tissue (called DEGs for NASH-NAFL). For DEGs for the NAFLD group, key genes were identified by studying the form of intersection. Potential functions of DEGs for NASH were then analyzed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. A protein-protein interaction network (PPI) was constructed using the STRING database. A total of 249 DEGs and one key gene for NAFLD were identified. For NASH-Normal, 514 DEGs and 11 hub genes were identified, three of which were closely related to the survival analysis of HCC, and potentially closely related to progression from NASH to HCC. One key gene for NASH-NAFL (AKR1B10) was identified. These genes appear to mediate the molecular mechanism underlying NAFLD and may be promising biomarkers for the presence of NASH.

A simpler diagnostic formula for screening nonalcoholic fatty liver disease.

OBJECTIVE: To increase the accuracy of non-invasive diagnosis of nonalcoholic fatty liver disease (NAFLD), clinical and laboratory NAFLD indicators were integrated into a diagnostic formula. METHODS: A total of 141 patients with clinically diagnosed NAFLD and 30 healthy controls were enrolled. We collected case history, body weight, height and mass index (BMI), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma glutamyl transpeptidase, blood urea nitrogen and blood uric acid (UA), serum creatinine, plasma total cholesterol, triglyceride, low density lipoprotein, glycosylated hemoglobin, fasting plasma glucose, fasting insulin, ultrasonic tests, Fibroscans, and other data. Linear correlation, multiple linear regressions, and receiver operating characteristic (ROC) curve methods were used to process and analyze the collected data. The performance of Fibroscan and our diagnostic formula was compared in reference to the findings of liver biopsy. RESULTS: The identified NAFLD diagnostic indices consisted of BMI, ALT, AST and UA. A regression formula was proposed as: CAP = 113.163 + 0.252 * ALT + 6.316 * BMI. Diagnosis of the area under the ROC curve was 0.927, the sensitivity was 87.68%, and specificity was 90%. The cutoff was 277.67 (p < 0.01). The accuracy of the NAFLD diagnosis with the proposed formula was significantly higher than FibroScan (82.6% vs 69.6%; p = 0.005). CONCLUSIONS: NAFLD diagnosis with the proposed formula demonstrated both high sensitivity and specificity, and its accuracy was significantly higher than FibroScan. This formula only utilized non-invasive clinical and laboratory findings and the calculation was simple. It can be conveniently used for clinical diagnosis of NAFLD.

Abnormalities in Plasma Phospholipid Fatty Acid Profiles of Patients with Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related death worldwide. In the present study, we aimed to profile the possible changes in plasma phospholipid fatty acid composition of HCC patients, and to identify the fatty acid biomarkers that could distinguish HCC patients from healthy controls. A total of 37 plasma samples from healthy controls and HCC patients were collected and their phospholipid fatty acid profiles were characterized by gas chromatography-mass spectrometry followed by multivariate statistical analysis. Twenty-five fatty acids were identified and quantified, their proportions varied greatly between two groups, suggesting each group has its own fatty acid pattern. Orthogonal partial least squares discriminant analysis in terms of fatty acid profiles showed that HCC patients could be clearly distinguished from healthy controls. More importantly, linoleic acid (18:2n-6), oleic acid (18:1n-9), arachidonic acid (20:4n-6) and palmitic acid (16:0) were identified as the potential fatty acid biomarkers of HCC patients. Additionally, to further identify the major cause of the abnormality of plasma fatty acid profile, fatty acid distributions of cancerous tissue and its surrounding tissue from 42 HCC patients were also examined. Due to have similar variation trend of major fatty acid biomarkers, linoleic acid (18:2n-6), oleic acid (18:1n-9), abnormalities in plasma phospholipid fatty acid profiles of HCC patients may be mainly attributed to the alternation of intrinsic fatty acid metabolism caused by cancer per se, but not to the differences in dietary factors.