Metabolic Profiling of Diabetes: From Black-Box Epidemiology to Systems Epidemiology

Abstract

Type 2 diabetes (T2D)2 is a heterogeneous condition that is characterized by increased insulin resistance and impaired insulin secretion. A progressive disorder with an insidious onset, T2D typically progresses from an early asymptomatic insulin resistance state to mild glucose intolerance and eventually to frank T2D that requires pharmacologic interventions. Whether insulin resistance or impaired insulin secretion is the primary defect in the pathogenesis of T2D remains a matter of debate. Interestingly, most genetic variants identified from recent genome-wide association studies are related to decreased β-cell function or impaired insulin secretion, which implicates a key role for β-cell dysfunction in the development of T2D. Still, obesity, with its fundamental influence on insulin resistance, is the single most important risk factor for T2D. Although T2D is largely predictable through anthropometric, lifestyle, and clinical factors and is preventable through diet and exercise, the metabolic pathways underlying the progression from normal glycemia to a prediabetes state and later to T2D are not completely understood. Classic epidemiology typically relates lifestyle and environmental exposures to chronic disease end points, such as T2D. This approach (sometimes referred to as “black-box epidemiology”) has identified many important lifestyle and environmental risk factors for chronic diseases, but it often does not illuminate biological mechanisms that underlie observed associations. Recent advances in “omics” technology, however, have enabled epidemiologists to incorporate novel biomarkers at multiple levels into human observational studies, with the potential to shift the research paradigm from the traditional black-box strategy to a systems approach (1, 2). This new model integrates a wide range of information—genetic predisposition (genome), epigenetic changes (epigenome), the expression of genes (transcriptome), proteins (proteome), metabolites (metabolome), and gut microbiota (microbiome)—into population-based studies to improve our understanding of the biological mechanisms that underlie disease pathophysiology in humans. Systems epidemiology is at the intersection of …