This network was generated as part of the manuscript An integrative systems-biology approach defines mechanisms of Alzheimer’s disease neurodegeneration, Leventhal et al.
A link to the manuscript will be provided when uploaded to a preprint server
Edges are annotated by their degree of confidence in the "weight" column. Nodes can be shaded by their effect size ("magnitude"), importance in the network ("prize"), robustness to edge permutations ("robustness") and how sensitive they are to permutation of the node weights ("specificity"). Nodes can also be grouped according to their membership in subnetworks identified by Louvain clustering ("louvain clusters"). These clusters are annotated by the biological process enriched in these clusters. The shape of the nodes can be changed according to their data type of origin ("general_datatype"). For a more specific description, shape the nodes by "data_source"
Despite years of intense investigation, the mechanisms underlying neuronal death in Alzheimer’s disease, remain incompletely understood. To define relevant pathways, we conducted an unbiased, genome-scale forward genetic screen for age-associated neurodegeneration in Drosophila. We also measured proteomics, phosphoproteomics, and metabolomics in Drosophila models of Alzheimer’s disease and identified Alzheimer’s genetic variants that modify gene expression in disease-vulnerable neurons in humans. We then used a network model to integrate these data with previously published Alzheimer’s disease proteomics, lipidomics and genomics. Here, we computationally predict and experimentally confirm how HNRNPA2B1 and MEPCE enhance toxicity of the tau protein, a pathological feature of Alzheimer’s disease. Furthermore, we demonstrated that the screen hits CSNK2A1 and NOTCH1 regulate DNA damage in Drosophila and human stem cell-derived neural progenitor cells. Our study identifies candidate pathways that could be targeted to ameliorate neurodegeneration in Alzheimer’s disease.