Investigation of the Genetics of Obesity through Single Nucleotide Polymorphisms of the Glucocorticoid Pathway

The stress hormone cortisol is responsible for aspects of metabolism and visceral fat formation that are hypothesized to be linked to obesity. Cortisol directly and indirectly influences metabolism by stimulating lipolysis as well as gluconeogenesis, the breakdown of fat and creation of glucose respectively. By interacting with abdominal organs such as the liver and pancreas, cortisol also increases metabolism through downstream hormones, such as glucagon and epinephrine. Cortisol intersects a variety of pathways that influence the breakdown of sugar, making it an important target for metabolic studies. This study investigates the correlation of mutations in proteins responsible for cortisol action in target tissues, individually and collectively, to clinical measurements of patients with obesity who are seeking or have already sought out bariatric surgery. DNA samples and clinical information were collected from patients of the Ellis Hospital Bariatric Care who were recruited for the study under the supervision of the Ellis Hospital Institutional Review Board. Genotyping of patient samples was done by performing allele specific-polymerase chain reactions (AS_PCR) which were then analyzed through agarose gel electrophoresis to look for single nucleotide polymorphisms (SNPs). It was found that the mutations throughout the glucocorticoid pathway are present at comparable rates in both the bariatric population and general population. Therefore, it cannot be concluded that there is an increase of mutations in the study population compared to the values for the general public found in literature. There are strong correlations between a mutation in the glucocorticoid receptor (GR) and excess body weight. This mutation causes conversion of an aspartic acid to a serine (N363S) in the protein sequence which has previously been shown to cause increased sensitivity to cortisol. As more SNPs are analyzed in combination with each other, more conclusions may be drawn between SNPs and physiological parameters of the patients. High correlations may provide evidence that select bariatric surgeries may be more effective in patients with specific genotypes. If this is the case, bariatric surgery can adopt precision medicine that caters treatment to the patient