We developed a bioinformatics framework which uses multi-tissue expression arrays and publicly available resources to statistically rank and functionally annotate endocrine axes. By applying this method to expression profiles within the Hybrid Mouse Diversity Panel (HMDP), we identify many known and several novel inter-tissue circuits. We further show the utility of this approach by uncovering a new adipose-to-skeletal muscle endocrine axis which shows promise as a therapeutic target for metabolic syndrome in both mice and humans. Functional experiments show adipose-derived Lipocalin-5 (LCN5) is sufficient to enhance skeletal muscle mitochondrial activity and gene expression. When overexpressed in a mouse model, the secreted peptide prevents and rescues diet-induced metabolic syndrome as measured by insulin- and glucose- tolerance. We also show that the human orthologue of the protein is sufficient to enhance expression of similar oxidation and biogenesis genes in human muscle cells. We further expand this method to identify adipose-derived Inter ?-trypsin inhibitor 5 (Itih5) as a conserved regulator of cardiomyocyte function. Specifically, correlative data in mice and humans and mechanistic studies show ITIH5 as a suppressor of cardiomyocyte hypertrophy. The goal of this proposal is to 1) Mechanistically dissect how Lipocalin-5/6 enhances skeletal muscle mitochondrial activity in mice and humans and 2) Utilize both global and targeted studies to understand biologic processes by which ITIH5 reduces cardiac hypertrophy in a physiologic and pathophysiologic state.
- RELEVANCE TO PUBLIC HEALTH Significant efforts over the past decades have shown axes of inter-tissue communication as both causal and contributory for metabolic syndrome and consequent development of cardiovascular disease and diabetes. Continuing to understand novel mechanisms of endocrine communication could serve as both a platform for discovery which informs mechanisms of biology, as well as translate directly to therapeutic targets. This proposal discusses a method to rank, screen and annotate axes of tissue-tissue interaction, then highlights two examples of utilizing this method to develop a novel therapeutic for systemic metabolic syndrome and cardiomyocyte hypertrophy.