Future management of human obesity: understanding the meaning of genetic susceptibility

Abstract

Gene-environment interactions are central to the expression of obesity. The condition is strongly heritable (ie, genetic), and most of the variation in obesity levels between countries and between individuals can be explained by the effects of obesogenic environments on individual genetic susceptibilities. The nature of the obesogenic environmental influences is not clear in detail, but they correlate closely with measures of affluence. The causes of variation in genetic susceptibility are also not clearly defined, but their general nature has become clearer. The failure of genome-wide association studies or large linkage studies to identify or replicate causative genetic variants, together with the segregation of obesity-related traits in families, implicates a heterogenetic mechanism in which rare, dominantly or additively expressed genetic variants are responsible for most of common obesity. The search for rare causative variants continues with some successes, but those identified contribute very little to the overall burden and, assuming heterogenetics, there are many more to find. The time when genomic risk factors provide more information than do currently available markers, such as family history, is a long way off. Genomic studies to date have contributed little, if anything, to the prevention and treatment of common obesity and its associated disorders. This contrasts with the obvious and immediate potential implications of the well-established overall genetic basis of obesity, which have not yet been exploited in the clinical or public health arenas. Genomic studies, which have helped to define the genetic basis of common obesity mainly by exclusion, will in the future play an increasingly important role in understanding and managing obesity, but only with parallel studies of the physiological, behavioral, and economic influences. Keywords: obesity phenotypes, obesogenic environment, genomics, pathophysiology, treatment, prevention Background and aimsAccording to the World Health Organization projections, by 2015 about 2.3 billion adults in the world will be overweight and over 700 million will be obese, and economic costing predicts that obesity-related expenditure in USA will approach US$100 billion per annum.1 It is now widely, if not universally, accepted that the rising national and global prevalence of overweight and obesity since the 1980s can be understood as the effects of increasingly obesogenic environments (OEs), which are correlated with measures of affluence and food availability, 2 in genetically predisposed individuals. 3,4 Obesity is assessed by the body mass index (BMI, kg/m 2 ) in most epidemiological and genetic studies, often together with measures of central fat distribution such as waist circumference because of adverse metabolic and health associations. However, neither BMI nor other anthropometric measurements are by themselves sufficiently accurate

Population-level trends in the distribution of body mass index in Canada, 2000–2014

“…Other theories have been proposed and discussed to explain increasing dispersion at the individual level (Jenkins and Campbell 2015;Frohlich and Potvin 2008;Kivimäki et al 2015), and many suggest this may be the result of the interaction between the individuals' genetic susceptibility and environment factors (Jenkins and Campbell 2014;Razak et al 2015). These new findings put forward several unanswered questions.…”

Baseline characteristics associated with different BMI trajectories in weight loss trials: a case for better targeting of interventions

“…However associations between success of initial weight loss and baseline leptin levels have been demonstrated 27 . Many genes may be involved in causing and/or promoting obesity and so it is not unexpected that the phenotypic presentation and response to treatments may vary substantially 28 . Growth mixture models provide a method for examining the effects of these different causal factors on the weight loss trajectory overtime.…”

Preventing Long-Term Complications of Obesity, Type 2 Diabetes, and Metabolic Syndrome

“…Thus, the unutilized stored fat gradually increase, leading to obesity. In spite of hopes, genomic studies however, have contributed little to date with reference to identifying new drug targets and generating drugs to prevent or treat obesity and its associated disorders [28].…”