The role of Alzheimer's disease risk genes in endolysosomal pathways

Abstract

There is ample pathological and biological evidence for endo-lysosomal dysfunction in Alzheimer's disease (AD) and emerging genetic studies repeatedly implicate endo-lysosomal genes as associated with increased AD risk. The endo-lysosomal network (ELN) is essential for all cell types of the central nervous system (CNS), yet each unique cell type utilizes cellular trafficking differently (see Fig. 1). Challenges ahead involve defining the role of AD associated genes in the functionality of the endo-lysosomal network (ELN) and understanding how this impacts the cellular dysfunction that occurs in AD. This is critical to the development of new therapeutics that will impact, and potentially reverse, early disease phenotypes. Here we review some early evidence of ELN dysfunction in AD pathogenesis and discuss the role of selected AD-associated risk genes in this pathway. In particular, we review genes that have been replicated in multiple genome-wide association studies(Andrews et al., 2020; Jansen et al., 2019; Kunkle et al., 2019; Lambert et al., 2013; Marioni et al., 2018) and reviewed in(Andrews et al., 2020) that have defined roles in the endo-lysosomal network. These genes include SORL1, an AD risk gene harboring both rare and common variants associated with AD risk and a role in trafficking cargo, including APP, through the ELN; BIN1, a regulator of clathrin-mediated endocytosis whose expression correlates with Tau pathology; CD2AP, an AD risk gene with roles in endosome morphology and recycling; PICALM, a clathrin-binding protein that mediates trafficking between the trans-Golgi network and endosomes; and Ephrin Receptors, a family of receptor tyrosine kinases with AD associations and interactions with other AD risk genes. Finally, we will discuss how human cellular models can elucidate cell-type specific differences in ELN dysfunction in AD and aid in therapeutic development.

Keywords: AD risk genes; Endolysosomal network; Human cellular model.