During the present cycle of our PPG, we have developed a novel approach, which we term "integrative genetics", to help identify genes and pathways associated with the Metabolic Syndrome (MetSyn). We have also developed a new mapping tool in mice, which we term a "mouse diversity panel" (MDP), which allows high resolution mapping of traits such as gene-by-environment interactions. In the present proposal, we will apply these tools to two basic questions concerning the metabolic syndrome. The first question has to do with the nature ofthe molecular networks underlying human MetSyn traits. In our previous "integrative genetics" studies, we examined both molecular phenotypes (transcript levels) and clinical phenotypes in segregating mouse populations. This allowed us to identify genetic loci controlling transcript levels and model co-expression networks. We will now extend this approach to human populations. In collaboration with Dr. Markku Laakso, we will examine DNA variation and transcript levels in fat biopsies from 1,000 individuals in a MetSyn study population that has been typed for the major MetSyn traits. We will then identify genes and co-expression networks related to clinical traits. Gene-by-diet interactions are critically important in MetSyn, but they are notoriously difficult to study directly in human populations. We will use our mouse diversity panel to examine differences in biologic networks and clinical traits in mice maintained on either a chow diet or a high fat diet for 8 weeks. This will allow us to map genes controlled dietary responsiveness of MetSyn traits and to medol to co-expression networks perturbed by these genes. The mouse and human data will be integrated and aspects relevant to this program validated in collaborative studies with other Projects and the Cores.
MetSyn is a primary cause of cardiovascular disease and diabetes. Our integrative genetics approach provides a means of understanding the biologic networks that underlie the complex interactions in MetSyn traits. One particularly important interaction is that between genetics and diet, and this will be addressed using our mouse diversity panel. The results will be relevant to disease prevention, diagnosis, and treatment.
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