Genetic variability and the hypothalamic control of energy balance

Background. Obesity is a major health problem throughout the industrialized world. Despite numerous attempts to curtail the rapid growth of obesity, its incidence continues to rise. Therefore, it is crucial to better understand the etiology of obesity beyond the concept of energy balance.^ Aims. The first aim of this study was to first investigate the relationship between eating behaviors and body size. The second goal was to identify genetic variation associated with eating behaviors. Thirdly, this study aimed to examine the joint relationships between eating behavior, body size and genetic variation.^ Methods. This study utilized baseline data ascertained in young adults from the Training Interventions and Genetics of Exercise (TIGER) Study. Variables assessed included eating behavior (Emotional Eating Scale, Eating Attitudes Test-26, and the Block98 Food Frequency Questionnaire), body size (body mass index, waist and hip circumference, waist/hip ratio, and percent body fat), genetic variation in genes implicated related to the hypothalamic control of energy balance, and appropriate covariates (age, gender, race/ethnicity, smoking status, and physical activity. For the genetic association analyses, genotypes were collapsed by minor allele frequency, and haplotypes were estimated for each gene. Additionally, Bayesian networks were constructed in order to determine the relationships between genetic variation, eating behavior and body size.^ Results. We report that the EAT-26 score, Caloric intake, percent fat, fiber intake, HEAT index, and daily servings of vegetables, meats, grains, and fats were significantly associated with at least one body size measure. Multiple SNPs in 17 genes and haplotypes from 12 genes were tested for their association with body size. Variation within both DRD4 and HTR2A was found to be associated with EAT-26 score. In addition, variation in the ghrelin gene (GHRL) was significantly associated with daily Caloric intake. A significant interaction between daily servings of grains and the HEAT index and variation within the leptin receptor gene (LEPR) was shown to influence body size.^ Conclusion. This study has shown that there is a substantial genetic component to eating behavior and that genetic variation interacts with eating behavior to influence body size.^

EVALUATION OF THE EFFECTIVENESS OF ANISOTROPIC ANALYTICAL ALGORITHM IN FLATTENED AND FLATTENING-FILTER-FREE BEAMS FOR HIGH ENERGY LUNG DOSE DELIVERY USING THE RADIOLOGICAL PHYSICS CENTER LUNG PHANTOM

The effectiveness of the Anisotropic Analytical Algorithm (AAA) implemented in the Eclipse treatment planning system (TPS) was evaluated using theRadiologicalPhysicsCenteranthropomorphic lung phantom using both flattened and flattening-filter-free high energy beams. Radiation treatment plans were developed following the Radiation Therapy Oncology Group and theRadiologicalPhysicsCenterguidelines for lung treatment using Stereotactic Radiation Body Therapy. The tumor was covered such that at least 95% of Planning Target Volume (PTV) received 100% of the prescribed dose while ensuring that normal tissue constraints were followed as well. Calculated doses were exported from the Eclipse TPS and compared with the experimental data as measured using thermoluminescence detectors (TLD) and radiochromic films that were placed inside the phantom. The results demonstrate that the AAA superposition-convolution algorithm is able to calculate SBRT treatment plans with all clinically used photon beams in the range from 6 MV to 18 MV. The measured dose distribution showed a good agreement with the calculated distribution using clinically acceptable criteria of ±5% dose or 3mm distance to agreement. These results show that in a heterogeneous environment a 3D pencil beam superposition-convolution algorithms with Monte Carlo pre-calculated scatter kernels, such as AAA, are able to reliably calculate dose, accounting for increased lateral scattering due to the loss of electronic equilibrium in low density medium. The data for high energy plans (15 MV and 18 MV) showed very good tumor coverage in contrast to findings by other investigators for less sophisticated dose calculation algorithms, which demonstrated less than expected tumor doses and generally worse tumor coverage for high energy plans compared to 6MV plans. This demonstrates that the modern superposition-convolution AAA algorithm is a significant improvement over previous algorithms and is able to calculate doses accurately for SBRT treatment plans in the highly heterogeneous environment of the thorax for both lower (≤12 MV) and higher (greater than 12 MV) beam energies.

Targeting AKT/mTOR Signaling Pathways During Murine Skin Tumor Promotion and the Impact of Dietary Energy Balance Manipulation

The prevalence of obesity has continued to rise over the last several decades in the United States lending to overall increases in risk for chronic diseases including many types of cancer. In contrast, reduction in energy consumption via calorie restriction (CR) has been shown to be a potent inhibitor of carcinogenesis across a broad range of species and tumor types. Previous data has demonstrated differential signaling through Akt and mTOR via the IGF-1R and other growth factor receptors across the diet-induced obesity (DIO)/CR spectrum. Furthermore, mTORC1 is known to be regulated directly via nutrient availability, supporting its role in the link between epithelial carcinogenesis and diet-induced obesity. In an effort to better understand the importance of mTORC1 in the context of both positive and negative energy balance during epithelial carcinogenesis, we have employed the use of specific pharmacological inhibitors, rapamycin (mTORC1 inhibitor) and metformin (AMPK activator) to target mTORC1 or various components of this pathway during skin tumor promotion. Two-stage skin carcinogenesis studies demonstrated that mTORC1 inhibition via rapamycin, metformin or combination treatments greatly inhibited skin tumor development in normal, overweight and obese mice. Furthermore, mechanisms by which these chemopreventive agents may be exerting their anti-tumor effects were explored. In addition, the effect of these compounds on the epidermal proliferative response was analyzed and drastic decreases in epidermal hyperproliferation and hyperplasia were found. Rapamycin also inhibited dermal inflammatory cell infiltration in a dose-dependent manner. Both compounds also blocked or attenuated TPA-induced signaling through epidermal mTORC1 as well as several downstream targets. In addition, inhibition of this pathway by metformin appeared to be, at least in part, dependent on AMPK activation in the skin. Overall, the data indicate that pharmacological strategies targeting this pathway offset the tumor-enhancing effects of DIO and may serve as possible CR mimetics. They suggest that mTORC1 contributes significantly to the process of skin tumor promotion, specifically during dietary energy balance effects. Exploiting the mechanistic information underlying dietary energy balance responsive pathways will help translate decades of research into effective strategies for prevention of epithelial carcinogenesis.