Metabolic dysfunctions are not only highly correlated with insulin resistance and diabetes, but are also associated with a 10 fold higher risk to develop Alzheimer’s disease. The proposed project joins forces between two Leibniz institutions with different expertise to establish a unique research platform for Translational Neuroscience. Here, we will break ground by introducing lipidomics to the field of synapse biology, by investigating insulin resistance in conjunction with high Abeta­load and by studying the effect whether synaptic disease states result in an altered lipid composition that in turn leads to synaptic dysfunction in brain.

Phenotypes at cellular and organism level are a result of a multitude of different molecular species. Thereby, interconnected networks are at the heart of both signaling pathways and complex traits that mediate adaptive plasticity and determine phenotypes. To answer the question how different molecular layers are connected and to gain deeper insights into the underlying mechanisms that determine a certain phenotype, a comprehensive and representative analysis of the molecular species involved is necessary [2]. Historically, each molecule class (e.g. DNA, RNA, proteins, metabolites, and lipids) has been studied separately in large scale omics experiments to look for relationships within biological processes. Using this strategy, we have assembled some of the molecular pieces related to signaling networks, but many interactions between them are still unrevealed or unexplained due to the restrictive single‐data‐type study designs. Therefore, multimolecular approaches on the sample processing as well as on the data analysis side are a prerequisite to obtain an integrated perspective. Read more in our recent publications SIMPLEX a multiomics for systems biology (https://www.ncbi.nlm.nih.gov/pubmed/26814187).