Disentangling Tissue and Ome Shared and Private Effects of Exercise

Project Summary/Abstract Exercise is a powerful intervention against many chronic diseases but the molecular mechanisms of this protection remain unclear. We propose an innovative, integrative approach to analyze the complex effects of exercise on multiple biological levels using the extensive data collected by the Molecular Transducers of Physical Activity Consortium (MoTrPAC). This dataset includes multiomic, multi-tissue, and multi-time point profiling after endurance exercise training in both rats and humans, offering an unprecedented opportunity to explore the mechanisms underlying the health benefits of exercise. Existing studies analyze individual omes and tissues separately, which risks missing subtle shared signals and conflating differences in statistical power with true biological variation. To overcome these limitations, we propose an integrative analysis based on our recently published Multiset Correlation and Factor Analysis (MCFA). Our first aim is to extend MCFA to handle tensor-valued data, creating a new model we call tensor-MCFA (tMCFA). This model will explicitly account for multimodal, multi-tissue data by dividing variation into four categories: (tissue, ome)-tuple private, tissue-private, ome-private, and shared. We will design tMCFA to handle and impute missing data pairs and explore linking related features across omes using a graph-guidance strategy. In our second aim, we will apply tMCFA to the Preclinical Animal Study Site (PASS) dataset from MoTrPAC. We will incorporate alternative splicing as an additional modality for analysis and assess the proportion of variance explained by each of the four categories. To interpret these components, we will use gene set enrichment analysis and protein-protein interaction enrichment. By relating our findings to human expression data and various metabolic diseases, we aim to identify how exercise-related changes observed in rats correspond to protective effects against human diseases. This comprehensive analysis across tissues and omes will allow us to pinpoint the key drivers of exercise's protective effects. Through this work, we hope to provide novel insights into the molecular mechanisms underlying the health benefits of physical activity. Our findings could pave the way for new therapeutic strategies and personalized exercise interventions that maximize these protective effects.