Insight into the pathophysiology of cardiometabolic diseases using multiple omics approaches

Abstract

Cardiometabolic diseases cover a wide spectrum of conditions, including insulin resistance, metabolic syndrome and prediabetes, and clinical conditions such as type 2 diabetes mellitus and cardiovascular diseases. Cardiometabolic diseases pose a major threat to society, contributing to morbidity and mortality globally. To reduce the burden of cardiometabolic diseases, many studies have aimed to identify biomarkers associated with increased risk of developing cardiometabolic disease. Identified biomarkers for increased risk of cardiometabolic diseases include, but are not limited to, dyslipidemia, hyperglycemia, hypertension and obesity. However, the direction of the effect in some of the observed associations and the question whether or not some of associations between biomarkers and diseases are causal are uncertain. In addition, the mechanisms underlying cardiometabolic diseases are complex and are affected by multiple genetic and environmental factors. Recently, the emergence of -omics technologies (e.g., genomics and metabolomics) has provided opportunities to explore the causality of biomarkers of cardiometabolic diseases in observational studies, and to gain insight into the underlying pathways leading to disease onset. The overall aims of this thesis are to examine the directions of effect and to investigate causality of associations between (patho)physiological biomarkers and type 2 diabetes mellitus, and between behavioral risk factors and cardiometabolic traits (i.e., dyslipidemia traits). In addition, a novel framework for further study of treatment-response relationship for (cardiometabolic) diseases is introduced.