In Vivo Detection of Vascular Adhesion Protein-1 in Experimental Inflammation

Vascular adhesion protein-1 (VAP-1) is an inflammation-inducible endothelial glycoprotein which mediates leukocyte-endothelial cell interactions. To study the pathogenetic significance of VAP-1 in inflammatory disorders, an in vivo immunodetection method was used to detect the regulation of luminally expressed VAP-1 in experimental skin and joint inflammation in the pig and dog. Moreover, VAP-1 was studied as a potential target to localize inflammation by radioimmunoscintigraphy. Up-regulation of VAP-1 in experimental dermatitis and arthritis could be visualized by specifically targeted immunoscintigraphy. Moreover, the translocation of VAP-1 to the functional position on the endothelial surface was only seen in inflamed tissues. These results suggest that VAP-1 is both an optimal candidate for anti-adhesive therapy and a potential target molecule for imaging inflammation

Genetic architecture of human plasma lipidome and its link to cardiovascular disease

Abstract Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10−8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD