Binge Eating Disorder Mediates Links between Symptoms of Depression and Anxiety and Caloric Intake in Obese Women

Despite considerable comorbidity between mood disorders, binge eating disorder (BED), and obesity, the underlying mechanisms remain unresolved. Therefore, the purpose of this study was to examine models by which internalizing behaviors of depression and anxiety influence food intake in overweight/obese women. Thirty-two women (15 BED, 17 controls) participated in a laboratory eating-episode and completed questionnaires assessing symptoms of anxiety and depression. Path analysis was used to test mediation and moderation models to determine the mechanisms by which internalizing symptoms influenced kilocalorie (kcal) intake. The BED group endorsed significantly more symptoms of depression (10.1 versus 4.8, P=0.005 ) and anxiety (8.5 versus 2.7, P=0.003). Linear regression indicated that BED diagnosis and internalizing symptoms accounted for 30% of the variance in kcal intake. Results from path analysis suggested that BED mediates the influence of internalizing symptoms on total kcal intake. The associations between internalizing symptoms and food intake are best described as operating indirectly through a BED diagnosis. This suggests that symptoms of depression and anxiety influence whether one engages in binge eating, which influences kcal intake. Greater understanding of the mechanisms underlying the associations between mood, binge eating, and food intake will facilitate the development of more effective prevention and treatment strategies for both BED and obesity

Incorporating Genetics into Your Studies: A Guide for Social Scientists

There has been a surge of interest in recent years in incorporating genetic components into on-going longitudinal, developmental studies and related psychological studies. While this represents an exciting new direction in developmental science, much of the research on genetic topics in developmental science does not reflect the most current practice in genetics. This is likely due, in part, to the rapidly changing landscape of the field of genetics, and the difficulty this presents for developmental scientists who are trying to learn this new area. In this review, we present an overview of the paradigm shifts that have occurred in genetics and we introduce the reader to basic genetic methodologies. We present our view of the current stage of research ongoing at the intersection of genetics and social science, and we provide recommendations for how we could do better. We also address a number of issues that social scientists face as they integrate genetics into their projects, including choice of a study design (candidate gene versus genome-wide association versus sequencing), different methods of DNA collection, and special considerations involved in the analysis of genotypic data. Through this review, we hope to equip social scientists with a deeper understanding of the many considerations that go into genetics research, in an effort to foster more meaningful cross-disciplinary initiatives

Modeling Longitudinal Change in Cervical Length Across Pregnancy

Introduction: A short cervix (cervical length \u3c 25 mm) in the mid-trimester (18 to 24 weeks) of pregnancy is a powerful predictor of spontaneous preterm delivery (gestational age at delivery \u3c 37 weeks). Although the biological mechanisms of cervical remodeling have been the subject of extensive investigation, very little is known about the rate of change in cervical length over the course of a pregnancy, or the extent to which rapid cervical shortening increases maternal risk for spontaneous preterm delivery. Methods: A cohort of 5,160 unique women carrying 5,971 singleton pregnancies provided two or more measurements of cervical length during pregnancy. Cervical length was measured in millimeters using a transvaginal 12-3 MHz ultrasound endocavity probe (SuperSonic Imagine). Maternal characteristics, including relevant medical history and birth outcome data, were collected for each participant. Gestational age at delivery was measured from the first day of each woman’s last menstrual period and confirmed by ultrasound. Repeated measurements of cervical length during pregnancy were modeled as a longitudinal, multilevel growth curve in MPlus. A three-level variance structure was used to account for non-independence of repeated measurements clustered within pregnancies, which are clustered within participants. Results: The average number of cervical length measurements per pregnancy is 6. Shorter mid-trimester cervical lengths and accelerated rates of cervical shortening are associated with shorter gestational duration. A smaller initial cervical length (p \u3c 1*10-4) and a faster rate of change in cervical change length during pregnancy (p \u3c 1*10-4) are significantly associated with an earlier gestational age at delivery. A higher pre-pregnancy body mass index (BMI) is associated with shorter initial cervical length in early pregnancy (p \u3c 1*10-4), while maternal age is associated with a more rapid rate of change in cervical length (p \u3c 1*10-4). Parameters describing cervical length and its rate change during pregnancy (i.e., intercept, linear slope, and quadratic slope parameters) explained 59% more variance in gestational age at delivery than a single mid-rimester cervical length measurement, which is the current gold standard in clinical practice. However, a significant amount of residual variance in individual estimates of cervical length growth parameters remains (p \u3c 1*10-4), which could be accounted for, in part, by common variation in the population. Conclusion: We have developed longitudinal models of cervical length that describe individual and group level trajectories of cervical change across pregnancy. Extensions of this model incorporating genomic data, can be used to estimate the heritability of cervical length and its role in mediating the timing of birth.https://scholarscompass.vcu.edu/gradposters/1141/thumbnail.jp

Prospective Longitudinal Study of the Pregnancy DNA Methylome: The US Pregnancy, Race, Environment, Genes (PREG) Study

Purpose The goal of the Pregnancy, Race, Environment, Genes study was to understand how social and environmental determinants of health (SEDH), pregnancy-specific environments (PSE) and biological processes influence the timing of birth and account for the racial disparity in preterm birth. The study followed a racially diverse longitudinal cohort throughout pregnancy and included repeated measures of PSE and DNA methylation (DNAm) over the course of gestation and up to 1 year into the postpartum period. Participants All women were between 18 and 40 years of age with singleton pregnancies and no diagnosis of diabetes or indication of assisted reproductive technology. Both mother and father had to self-identify as either African-American (AA) or European-American (EA). Maternal peripheral blood samples along with self-report questionnaires measuring SEDH and PSE factors were collected at four pregnancy visits, and umbilical cord blood was obtained at birth. A subset of participants returned for two additional postpartum visits, during which additional questionnaires and maternal blood samples were collected. The pregnancy and postpartum extension included n=240 (AA=126; EA=114) and n=104 (AA=50; EA=54), respectively. Findings to date One hundred seventy-seven women (AA=89, EA=88) met full inclusion criteria out of a total of 240 who were initially enrolled. Of the 63 participants who met exclusion criteria after enrolment, 44 (69.8%) were associated with a medical reason. Mean gestational age at birth was significantly shorter for the AA participants by 5.1 days (M=272.5 (SD=10.5) days vs M=277.6 (SD=8.3)). Future plans Future studies will focus on identifying key environmental factors that influence DNAm change across pregnancy and account for racial differences in preterm birth

A Peptide from the Beta-strand Region of CD2 Protein that Inhibits Cell Adhesion and Suppresses Arthritis in a Mouse Model

This is the peer reviewed version of the following article: Satyanarayanajois, S. D., Büyüktimkin, B., Gokhale, A., Ronald, S., Siahaan, T. J. and Latendresse, J. R. (2010), A Peptide from the Beta-strand Region of CD2 Protein that Inhibits Cell Adhesion and Suppresses Arthritis in a Mouse Model. Chemical Biology & Drug Design, 76: 234–244. doi:10.1111/j.1747-0285.2010.01001.x, which has been published in final form at http://doi.org/10.1111/j.1747-0285.2010.01001.x. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Cell adhesion molecules play a central role at every step of the immune response. The function of leukocytes can be regulated by modulating adhesion interactions between cell adhesion molecules to develop therapeutic agents against autoimmune diseases. Among the different cell adhesion molecules that participate in the immunological response, CD2 and its ligand CD58 (LFA-3) are two of the best-characterized adhesion molecules mediating the immune response. To modulate the cell adhesion interaction, peptides were designed from the discontinuous epitopes of the β-strand region of CD2 protein. The two strands were linked by a peptide bond. β-Strands in the peptides were nucleated by inserting a β-sheet-inducing Pro-Gly sequence with key amino acid sequences from CD2 protein that binds to CD58. Using a fluorescence assay, peptides that exhibited potential inhibitory activity in cell adhesion were evaluated for their ability to bind to CD58 protein. A model for peptide binding to CD58 protein was proposed based on docking studies. Administration of one of the peptides, P3 in collagen-induced arthritis (CIA) in the mouse model, indicated that peptide P3 was able to suppress rheumatoid arthritis in mice

Can Genetics Predict Response to Complex Behavioral Interventions? Evidence from a Genetic Analysis of the Fast Track Randomized Control Trial

Early interventions are a preferred method for addressing behavioral problems in high-risk children, but often have only modest effects. Identifying sources of variation in intervention effects can suggest means to improve efficiency. One potential source of such variation is the genome. We conducted a genetic analysis of the Fast Track randomized control trial, a 10-year-long intervention to prevent high-risk kindergarteners from developing adult externalizing problems including substance abuse and antisocial behavior. We tested whether variants of the glucocorticoid receptor gene NR3C1 were associated with differences in response to the Fast Track intervention. We found that in European-American children, a variant of NR3C1 identified by the single-nucleotide polymorphism rs10482672 was associated with increased risk for externalizing psychopathology in control group children and decreased risk for externalizing psychopathology in intervention group children. Variation in NR3C1 measured in this study was not associated with differential intervention response in African-American children. We discuss implications for efforts to prevent externalizing problems in high-risk children and for public policy in the genomic era

Epigenetic Alterations in Liver of C57BL/6J Mice after Short-Term Inhalational Exposure to 1,3-Butadiene

Background1,3-Butadiene (BD) is a high-volume industrial chemical and a known human carcinogen. The main mode of BD carcinogenicity is thought to involve formation of genotoxic epoxides.ObjectivesIn this study we tested the hypothesis that BD may be epigenotoxic (i.e., cause changes in DNA and histone methylation) and explored the possible molecular mechanisms for the epigenetic changes.Methods and ResultsWe administered BD (6.25 and 625 ppm) to C57BL/6J male mice by inhalation for 2 weeks (6 hr/day, 5 days a week) and then examined liver tissue from these mice for signs of toxicity using histopathology and gene expression analyses. We observed no changes in mice exposed to 6.25 ppm BD, but glycogen depletion and dysregulation of hepatotoxicity biomarker genes were observed in mice exposed to 625 ppm BD. We detected N-7-(2,3,4-trihydroxybut-1-yl)guanine (THB-Gua) adducts in liver DNA of exposed mice in a dose-responsive manner, and also observed extensive alterations in the cellular epigenome in the liver, including demethylation of global DNA and repetitive elements and a decrease in histone H3 and H4 lysine methylation. In addition, we observed down-regulation of DNA methyltransferase 1 (Dnmt1) and suppressor of variegation 3–9 homolog 1, a histone lysine methyltransferase (Suv39h1), and up-regulation of the histone demethylase Jumonji domain 2 (Jmjd2a), proteins responsible for the accurate maintenance of the epigenetic marks. Although the epigenetic effects were most pronounced in the 625-ppm exposure group, some effects were evident in mice exposed to 6.25 ppm BD.ConclusionsThis study demonstrates that exposure to BD leads to epigenetic alterations in the liver, which may be important contributors to the mode of BD carcinogenicity

MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEv​al/downloads

EcoCyc: a comprehensive database of Escherichia coli biology

EcoCyc (http://EcoCyc.org) is a comprehensive model organism database for Escherichia coli K-12 MG1655. From the scientific literature, EcoCyc captures the functions of individual E. coli gene products; their regulation at the transcriptional, post-transcriptional and protein level; and their organization into operons, complexes and pathways. EcoCyc users can search and browse the information in multiple ways. Recent improvements to the EcoCyc Web interface include combined gene/protein pages and a Regulation Summary Diagram displaying a graphical overview of all known regulatory inputs to gene expression and protein activity. The graphical representation of signal transduction pathways has been updated, and the cellular and regulatory overviews were enhanced with new functionality. A specialized undergraduate teaching resource using EcoCyc is being developed