Anti-CLU polyclonal antibody

Clusterin (CLU) is a stress-responding protein associated with cytoprotection in a broad range of pathological processes. However, clusterin's function in diabetes-induced endothelial dysfunction has not been defined. Herein, using two diabetes models, we investigated the role of clusterin in endothelial dysfunction triggered by diabetes and the molecular mechanisms involved. The results revealed that clusterin overexpression inhibited ICAM-1/VCAM-1 expression in aortas and improved endothelium-dependent vasodilatation in db/db diabetic mice and streptozotocin (STZ)-induced diabetes models. Consistently, in vitro, adenoviral clusterin overexpression reduced the expression of a range of pro-inflammatory cytokines and suppressed monocyte adhesion to endothelial cells subjected to high glucose and high palmitate. Further study indicated that clusterin overexpression mitigated mitochondrial excessive fission and reduced mitochondrial ROS production. Conversely, silencing clusterin aggravated mitochondrial fission and endothelial inflammatory activation in high glucose-exposed endothelial cells. Accumulating evidence indicates that impaired mitochondrial dynamics plays a considerable role in promoting endothelial dysfunction in diabetic subjects. Therefore, treatments targeting mitochondrial undue fission may be promising measures to prevent vascular complications of diabetes. Furthermore, AMP-activated protein kinase (AMPK) activation contributed to the modulation of mitochondrial dynamics executed by clusterin. Mechanistically, clusterin promoted the phosphorylation of AMPK alpha and its downstream target acetyl-CoA carboxylase (ACC), while the inhibition of AMPK alpha negated the improvement in mitochondrial dynamics provided by clusterin overexpression. Over all, these findings suggest that clusterin exerts beneficial effects in endothelial cells under diabetic conditions via inhibiting mitochondrial fragmentation mediated by AMPK.

Most of the loci identified by genome-wide association studies (GWAS) for late-onset Alzheimer's disease (LOAD) are in strong linkage disequilibrium (LD) with nearby variants all of which could be the actual functional variants, often in non-protein-coding regions and implicating underlying gene regulatory mechanisms. We set out to characterize the causal variants, regulatory mechanisms, tissue contexts, and target genes underlying these associations. We applied our INFERNO algorithm to the top 19 non-APOE loci from the IGAP GWAS study. INFERNO annotated all LD-expanded variants at each locus with tissue-specific regulatory activity. Bayesian co-localization analysis of summary statistics and eQTL data was performed to identify tissue-specific target genes. INFERNO identified enhancer dysregulation in all 19 tag regions analyzed, significant enrichments of enhancer overlaps in the immune-related blood category, and co-localized eQTL signals overlapping enhancers from the matching tissue class in ten regions (ABCA7, BIN1, CASS4, CD2AP, CD33, CELE], CLU, EPHAL FERMT2, ZCWPW1). In several cases, we identified dysregulation of long noncoding RNA (lncRNA) transcripts and applied the lncRNA target identification algorithm from INFERNO to characterize their downstream biological effects. We also validated the allele-specific effects of several variants on enhancer function using luciferase expression assays. By integrating functional genomics with GWAS signals, our analysis yielded insights into the regulatory mechanisms, tissue contexts, genes, and biological processes affected by noncoding genetic variation associated with LOAD risk.