Human IL1R2 blocking peptide

Background-Many different genetic and clinical factors have been identified as causes or contributors to atherosclerosis. We present a model of preclinical atherosclerosis based on genetic and clinical data that predicts the presence of coronary artery calcification in healthy Americans of European descent 45 to 84 years of age in the Multi-Ethnic Study of Atherosclerosis (MESA). Methods and Results-We assessed 712 individuals for the presence or absence of coronary artery calcification and assessed their genotypes for 2882 single-nucleotide polymorphisms. With the use of these single-nucleotide polymorphisms and relevant clinical data, a Bayesian network that predicts the presence of coronary calcification was constructed. The model contained 13 single-nucleotide polymorphisms (from genes AGTR1, ALOX15, INSR, PRKAB1, IL1R2, ESR2, KCNK1, FBLN5, PPARA, VEGFA, PON1, TDRD6, PLA2G7, and 1 ancestry informative marker) and 5 clinical variables (sex, age, weight, smoking, and diabetes mellitus) and achieved 85% predictive accuracy, as measured by area under the receiver operating characteristic curve. This is a significant (P<0.001) improvement on models that use just the single-nucleotide polymorphism data or just the clinical variables. Conclusions-We present an investigation of joint genetic and clinical factors associated with atherosclerosis that shows predictive results for both cases, as well as enhanced performance for their combination. (Circulation. 2009; 120: 2448-2454.)

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal human malignant tumor, with a dismal 5-year survival rate of less than 5%. The lack of specific symptoms at early tumor stages and the paucity of biomarkers contribute to the poor diagnosis of pancreatic ductal adenocarcinoma. To improve prognosis, a screening biomarker for early diagnosis of pancreatic cancer is in urgent need. We searched the databases of expression profiling by array on GEO, aiming at comparing gene expression profile of matched pairs of pancreatic tumor and adjacent non-tumor tissues, and we screen out 4 suitable series of gene expression microarray data ("GSE15471", "GSE18670", "GSE28735" and "GSE58561"). After carefully analyzing, 13 DEGs (MYOF, SLC6A6, S100P, HK2, IFI44L, OSBPL3, IGF2BP3, PDK4, IL1R2, ERO1A, EGLN3, PLAC8 and ACSL5) are significantly differentially expressed in four microarray databases in common. After analyzing mRNA expression data and clinical follow-up survey provided in the TCGA database and clinicopathological data of 137 pancreatic ductal adenocarcinoma patients, we carefully demonstrated that three of these differentially expressed genes (ERO1A, OSBPL3 and IFI44L) are correlated with poor prognosis of pancreatic ductal adenocarcinoma patients. In addition, we revealed that cell-matrix adhesion and extracellular matrix were top significantly regulated pathways in pancreatic ductal adenocarcinoma and depicted two protein-protein interactions networks of extracellular matrix related Genes which are dysregulated according to 4 gene expression microarray data mentioned above ("GSE15471", "GSE18670", "GSE28735" and "GSE58561"), hoping to shed light on the etiology of PDAC and mechanisms of drug resistance in PDAC in this study.