Human AGT(Angiotensinogen) ELISA Kit

Rationale: Chronic obstructive pulmonary disease (COPD) susceptibility is in part related to genetic variants. Most genetic studies have been focused on genome-wide common variants without a specific focus on coding variants, but common and rare coding variants may also affect COPD susceptibility. Objectives: To identify coding variants associated with COPD. Methods: We tested nonsynonymous, splice, and stop variants derived from the Illumina HumanExome array for association with COPD in five study populations enriched for COPD. We evaluated single variants with a minor allele frequency greater than 0.5% using logistic regression. Results were combined using a fixed effects meta-analysis. We replicated novel single-variant associations in three additional COPD cohorts. Measurements and Main Results: We included 6,004 control subjects and 6,161 COPD cases across five cohorts for analysis. Our top result was rs16969968 (P = 1.7 X 10(-14)) in CHRNA5, a locus previously associated with COPD susceptibility and nicotine dependence. Additional top results were found in AGER, MMP3, and SERPINA1. A nonsynonymous variant, rs181206, ina27 (P = 4.7 X 10(-6)) was just below the level of exome-wide significance but attained exome-wick significance (P = 5.7 X 10(-8)) when combined with results from other cohorts. Gene expression datasets revealed an association of rs181206 and the surrounding locus with expression of multiple genes; several were differentially expressed in COPD lung tissue, including TUFM. Conclusions: In an exome array analysis of COPD, we identified nonsynonymous variants at previously described loci and a novel exome-wide significant variant in IL27. This variant is at a locus previously described in genome-wide associations with diabetes, inflammatory bowel disease, and obesity and appears to affect genes potentially related to COPD pathogenesis.

BackgroundA multidirectional relationship has been demonstrated between myocardial infarction (MI) and depression. However, the causal genetic factors and molecular mechanisms underlying this interaction remain unclear. The main purpose of this study was to identify potential candidate genes for the interaction between the two diseases.MethodsUsing a bioinformatics approach and existing gene expression data in the biomedical discovery support system (BITOLA), we defined the starting concept X as Myocardial Infarction and end concept Z as Major Depressive Disorder or Depressive disorder. All intermediate concepts relevant to the Gene or Gene Product for MI and depression were searched. Gene expression data and tissue-specific expression of potential candidate genes were evaluated using the Human eFP (electronic Fluorescent Pictograph) Browser, and intermediate concepts were filtered by manual inspection.ResultsOur analysis identified 128 genes common to both the MI and depression text mining concepts. Twenty-three of the 128 genes were selected as intermediates for this study, 9 of which passed the manual filtering step. Among the 9 genes, LCAT, CD4, SERPINA1, IL6, and PPBP failed to pass the follow-up filter in the Human eFP Browser, due to their low levels in the heart tissue. Finally, four genes (GNB3, CNR1, MTHFR, and NCAM1) remained.ConclusionsGNB3, CNR1, MTHFR, and NCAM1 are putative new candidate genes that may influence the interactions between MI and depression, and may represent potential targets for therapeutic intervention.