Rat Clu(Clusterin) ELISA Kit

Clusterin (Clu), an extracellular chaperone, exhibits characteristics of soluble innate immunity receptors, as assessed by its ability to bind some bacteria strains. In this study, we report that Clu also binds specifically to late apoptotic cells but not to live, early apoptotic, or necrotic cells. Histones, which accumulate on blebs during the apoptotic process, represent privileged Clu-binding motifs at the surface of late apoptotic cells. As a consequence, Clu potentiates, both in vitro and in vivo, the phagocytosis of late apoptotic cells by macrophages. Moreover, the increased phagocytosis of late apoptotic cells induced by Clu favors the presentation and cross-presentation of apoptotic cell-associated antigens. Finally, we observed that, in a model of apoptotic cell-induced autoimmunity, and relative to control mice, Clu(-/-) mice develop symptoms of autoimmunity, including the generation of anti-dsDNA antibodies, deposition of immunoglobulins and complement components within kidneys, and splenomegaly. These results identify Clu as a new molecule partner involved in apoptotic cell efferocytosis and suggest a protective role for Clu in inflammation and autoimmune diseases.

Background: Epigenome-wide association studies (EWAS) based on human brain samples allow a deep and direct understanding of epigenetic dysregulation in Alzheimer's disease (AD).However, strong variation of cell-type proportions across brain tissue samples represents a significant source of data noise.Here, we report the first EWAS based on sorted neuronal and non-neuronal (mostly glia) nuclei from postmortem human brain tissues. Results: We show that cell sorting strongly enhances the robust detection of disease-related DNA methylation changes even in a relatively small cohort.We identify numerous genes with eell-type-specific methylation signatures and document differential methylation dynamics associated with aging specifically in neurons such as CLU, SYNJ2 and NCOR2 or in glia RAI1,CXXC5 and INPP5A.Further, we found neuron or glia-specific associations with AD Braak stage progression at genes such as MCF2L,ANK1, MAP2, LRRC8B, STK32C and S100B.A comparison of our study with previous tissue-based EWAS validates multiple AD-associated DNA methylation signals and additionally specifies their origin to neuron, e.g., HOXA3 or glia (ANK1). In a meta-analysis, we reveal two novel previously unrecognized methylation changes at the key AD risk genes APP and ADAM17. Conclusions: Our data highlight the complex interplay between disease, age and cell-type-specific methylation changes in AD risk genes thus offering new perspectives for the validation and interpretation of large EWAS results.