Associations between Gut Microbiota, Plasma Metabolites, and Metabolic Syndrome Traits

点击翻译按钮获取中文摘要

PROJECT SUMMARY The goal of this proposal is to understand the relationship between the gut microbiome, gut derived metabolites, and metabolic syndrome traits. Metabolic syndrome is a cluster of risk factors including central obesity, dyslipidemia, hypertension, and insulin resistance with a range of secondary sequelae such as cardiovascular disease (CVD), cerebrovascular disease, and diabetes. Metabolic syndrome has been identified as one of the greatest world health challenges of the 21st century. There are emerging data that the gut microbiota have an important role for the development of metabolic syndrome and directly influences host phenotypes. A detailed understanding of the factors underlying metabolic syndrome will be useful in developing effective prevention strategies and appropriate intervention strategies for at risk individuals. In order to better understand the relationship between the gut microbiome and metabolic syndrome traits, we will perform a secondary analysis of data from the Metabolic Syndrome in Men (METSIM) study. This is a population-based cohort of 10,197 men aged 45-73 years, randomly selected from the population register of Kuopio, Eastern Finland, from 2005 to 2010. This population has been uniquely characterized for cardiovascular clinical traits such as coronary artery disease, stroke, heart failure, and metabolic syndrome traits. This proposal extends the impact of the parent study, which aimed to investigate nongenetic and genetic factors associated with metabolic syndrome and CVD in both cross sectional and longitudinal analysis. We will analyze a subset of approximately 1000 subjects who participated in a 7-year follow-up. Our hypothesis is that gut microbes contribute to metabolic syndrome traits in part through their metabolites and their metabolites are associated with major cardiovascular events. We will first determine the gut derived metabolites that have association with metabolic syndrome traits. Once we identify the subset of metabolites, we will identify individual and clusters of microbes that may influence the levels of certain plasma metabolites. We will also determine the association of plasma concentrations of the gut microbe-generated metabolite with major adverse cardiovascular events. Data will be analyzed using Lasso regression, latent class analysis, path analysis, and Cox proportional hazards regression. Results from this project will inform research on developing patient-centered prevention strategies and interventions. Understanding of the host-microbiome inter- relationships may result in novel therapeutic approaches for prevention, diagnosis, and treatment of metabolic disorders.