Obesity Genetics and Cardiometabolic Health: Potential for Risk Prediction - Sanghera, Dharambir K. (Diabetes Obes Metab, 2019)
Increasing burden of obesity world-wide and its effect on cardiovascular disease (CVD) risk is an opportunity for evaluation of preventive approaches. Both obesity and CVD have a genetic background and polymorphisms within genes that enhance expression of variant proteins that influence CVD in obesity, thus genome-based prediction may be a feasible strategy. However, identification of genetically driven risk factors for CVD manifesting as clinically recognized phenotypes is a major challenge. Clusters of such risk factors include hyperglycemia, hypertension, ectopic liver fat, and inflammation. All involve multiple genetic pathways having complex interactions with variable environmental influences. The factors that make significant contributions to CVD risk include altered carbohydrate homeostasis, ectopic deposition of fat in muscle and liver, and inflammation with contributions from the gut microbiome. Futuristic model depends on harnessing the predictive power of plausible genetic variants, phenotype reversibility, and effective therapeutic choices based on genotype–phenotype interactions. Inverting disease phenotypes into ideal cardiovascular health metrics could improve genetic and epigenetic assessment, and form the basis of a futuristic model for risk detection and early intervention.