Dietary animal and plant protein intakes and their associations with obesity and cardio-metabolic indicators in European adolescents: the HELENA cross-sectional study

Background: Previous studies suggest that dietary protein might play a beneficial role in combating obesity and its related chronic diseases. Total, animal and plant protein intakes and their associations with anthropometry and serum biomarkers in European adolescents using one standardised methodology across European countries are not well documented. Objectives: To evaluate total, animal and plant protein intakes in European adolescents stratified by gender and age, and to investigate their associations with cardio-metabolic indicators (anthropometry and biomarkers). Methods: The current analysis included 1804 randomly selected adolescents participating in the HELENA study (conducted in 2006-2007) aged 12.5-17.5 y (47% males) who completed two non-consecutive computerised 24-h dietary recalls. Associations between animal and plant protein intakes, and anthropometry and serum biomarkers were examined with General linear Model multivariate analysis. Results: Average total protein intake exceeded the recommendations of World Health Organization and European Food Safety Authority. Mean total protein intake was 96 g/d (59% derived from animal protein). Total, animal and plant protein intakes (g/d) were significantly lower in females than in males and total and plant protein intakes were lower in younger participants (12.5-14.9 y). Protein intake was significantly lower in underweight subjects and higher in obese ones; the direction of the relationship was reversed after adjustments for body weight (g/(kg.d)). The inverse association of plant protein intakes was stronger with BMI z-score and body fat percentage (BF%) compared to animal protein intakes. Additionally, BMI and BF% were positively associated with energy percentage of animal protein. Conclusions: This sample of European adolescents appeared to have adequate total protein intake. Our findings suggest that plant protein intakes may play a role in preventing obesity among European adolescents. Further longitudinal studies are needed to investigate the potential beneficial effects observed in this study in the prevention of obesity and related chronic diseases.

Framingham Heart Study 100K project: genome-wide associations for cardiovascular disease outcomes

BACKGROUND:Cardiovascular disease (CVD) and its most common manifestations - including coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF) - are major causes of morbidity and mortality. In many industrialized countries, cardiovascular disease (CVD) claims more lives each year than any other disease. Heart disease and stroke are the first and third leading causes of death in the United States. Prior investigations have reported several single gene variants associated with CHD, stroke, HF, and AF. We report a community-based genome-wide association study of major CVD outcomes.METHODS:In 1345 Framingham Heart Study participants from the largest 310 pedigrees (54% women, mean age 33 years at entry), we analyzed associations of 70,987 qualifying SNPs (Affymetrix 100K GeneChip) to four major CVD outcomes: major atherosclerotic CVD (n = 142; myocardial infarction, stroke, CHD death), major CHD (n = 118; myocardial infarction, CHD death), AF (n = 151), and HF (n = 73). Participants free of the condition at entry were included in proportional hazards models. We analyzed model-based deviance residuals using generalized estimating equations to test associations between SNP genotypes and traits in additive genetic models restricted to autosomal SNPs with minor allele frequency [greater than or equal to]0.10, genotype call rate [greater than or equal to]0.80, and Hardy-Weinberg equilibrium p-value [greater than or equal to] 0.001.RESULTS:Six associations yielded p <10-5. The lowest p-values for each CVD trait were as follows: major CVD, rs499818, p = 6.6 x 10-6; major CHD, rs2549513, p = 9.7 x 10-6; AF, rs958546, p = 4.8 x 10-6; HF: rs740363, p = 8.8 x 10-6. Of note, we found associations of a 13 Kb region on chromosome 9p21 with major CVD (p 1.7 - 1.9 x 10-5) and major CHD (p 2.5 - 3.5 x 10-4) that confirm associations with CHD in two recently reported genome-wide association studies. Also, rs10501920 in CNTN5 was associated with AF (p = 9.4 x 10-6) and HF (p = 1.2 x 10-4). Complete results for these phenotypes can be found at the dbgap website http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.CONCLUSION:No association attained genome-wide significance, but several intriguing findings emerged. Notably, we replicated associations of chromosome 9p21 with major CVD. Additional studies are needed to validate these results. Finding genetic variants associated with CVD may point to novel disease pathways and identify potential targeted preventive therapies.

Serotonin synthesis, release and reuptake in terminals: a mathematical model.

BACKGROUND: Serotonin is a neurotransmitter that has been linked to a wide variety of behaviors including feeding and body-weight regulation, social hierarchies, aggression and suicidality, obsessive compulsive disorder, alcoholism, anxiety, and affective disorders. Full understanding of serotonergic systems in the central nervous system involves genomics, neurochemistry, electrophysiology, and behavior. Though associations have been found between functions at these different levels, in most cases the causal mechanisms are unknown. The scientific issues are daunting but important for human health because of the use of selective serotonin reuptake inhibitors and other pharmacological agents to treat disorders in the serotonergic signaling system. METHODS: We construct a mathematical model of serotonin synthesis, release, and reuptake in a single serotonergic neuron terminal. The model includes the effects of autoreceptors, the transport of tryptophan into the terminal, and the metabolism of serotonin, as well as the dependence of release on the firing rate. The model is based on real physiology determined experimentally and is compared to experimental data. RESULTS: We compare the variations in serotonin and dopamine synthesis due to meals and find that dopamine synthesis is insensitive to the availability of tyrosine but serotonin synthesis is sensitive to the availability of tryptophan. We conduct in silico experiments on the clearance of extracellular serotonin, normally and in the presence of fluoxetine, and compare to experimental data. We study the effects of various polymorphisms in the genes for the serotonin transporter and for tryptophan hydroxylase on synthesis, release, and reuptake. We find that, because of the homeostatic feedback mechanisms of the autoreceptors, the polymorphisms have smaller effects than one expects. We compute the expected steady concentrations of serotonin transporter knockout mice and compare to experimental data. Finally, we study how the properties of the the serotonin transporter and the autoreceptors give rise to the time courses of extracellular serotonin in various projection regions after a dose of fluoxetine. CONCLUSIONS: Serotonergic systems must respond robustly to important biological signals, while at the same time maintaining homeostasis in the face of normal biological fluctuations in inputs, expression levels, and firing rates. This is accomplished through the cooperative effect of many different homeostatic mechanisms including special properties of the serotonin transporters and the serotonin autoreceptors. Many difficult questions remain in order to fully understand how serotonin biochemistry affects serotonin electrophysiology and vice versa, and how both are changed in the presence of selective serotonin reuptake inhibitors. Mathematical models are useful tools for investigating some of these questions.

Application description and policy model in collaborative environment for sharing of information on epidemiological and clinical research data sets.

BACKGROUND: Sharing of epidemiological and clinical data sets among researchers is poor at best, in detriment of science and community at large. The purpose of this paper is therefore to (1) describe a novel Web application designed to share information on study data sets focusing on epidemiological clinical research in a collaborative environment and (2) create a policy model placing this collaborative environment into the current scientific social context. METHODOLOGY: The Database of Databases application was developed based on feedback from epidemiologists and clinical researchers requiring a Web-based platform that would allow for sharing of information about epidemiological and clinical study data sets in a collaborative environment. This platform should ensure that researchers can modify the information. A Model-based predictions of number of publications and funding resulting from combinations of different policy implementation strategies (for metadata and data sharing) were generated using System Dynamics modeling. PRINCIPAL FINDINGS: The application allows researchers to easily upload information about clinical study data sets, which is searchable and modifiable by other users in a wiki environment. All modifications are filtered by the database principal investigator in order to maintain quality control. The application has been extensively tested and currently contains 130 clinical study data sets from the United States, Australia, China and Singapore. Model results indicated that any policy implementation would be better than the current strategy, that metadata sharing is better than data-sharing, and that combined policies achieve the best results in terms of publications. CONCLUSIONS: Based on our empirical observations and resulting model, the social network environment surrounding the application can assist epidemiologists and clinical researchers contribute and search for metadata in a collaborative environment, thus potentially facilitating collaboration efforts among research communities distributed around the globe.

BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES.

Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally "validated" in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.

A population model of folate-mediated one-carbon metabolism.

BACKGROUND: Previous mathematical models for hepatic and tissue one-carbon metabolism have been combined and extended to include a blood plasma compartment. We use this model to study how the concentrations of metabolites that can be measured in the plasma are related to their respective intracellular concentrations. METHODS: The model consists of a set of ordinary differential equations, one for each metabolite in each compartment, and kinetic equations for metabolism and for transport between compartments. The model was validated by comparison to a variety of experimental data such as the methionine load test and variation in folate intake. We further extended this model by introducing random and systematic variation in enzyme activity. OUTCOMES AND CONCLUSIONS: A database of 10,000 virtual individuals was generated, each with a quantitatively different one-carbon metabolism. Our population has distributions of folate and homocysteine in the plasma and tissues that are similar to those found in the NHANES data. The model reproduces many other sets of clinical data. We show that tissue and plasma folate is highly correlated, but liver and plasma folate much less so. Oxidative stress increases the plasma S-adenosylmethionine/S-adenosylhomocysteine (SAM/SAH) ratio. We show that many relationships among variables are nonlinear and in many cases we provide explanations. Sampling of subpopulations produces dramatically different apparent associations among variables. The model can be used to simulate populations with polymorphisms in genes for folate metabolism and variations in dietary input.

Fear learning circuitry is biased toward generalization of fear associations in posttraumatic stress disorder.

Fear conditioning is an established model for investigating posttraumatic stress disorder (PTSD). However, symptom triggers may vaguely resemble the initial traumatic event, differing on a variety of sensory and affective dimensions. We extended the fear-conditioning model to assess generalization of conditioned fear on fear processing neurocircuitry in PTSD. Military veterans (n=67) consisting of PTSD (n=32) and trauma-exposed comparison (n=35) groups underwent functional magnetic resonance imaging during fear conditioning to a low fear-expressing face while a neutral face was explicitly unreinforced. Stimuli that varied along a neutral-to-fearful continuum were presented before conditioning to assess baseline responses, and after conditioning to assess experience-dependent changes in neural activity. Compared with trauma-exposed controls, PTSD patients exhibited greater post-study memory distortion of the fear-conditioned stimulus toward the stimulus expressing the highest fear intensity. PTSD patients exhibited biased neural activation toward high-intensity stimuli in fusiform gyrus (P<0.02), insula (P<0.001), primary visual cortex (P<0.05), locus coeruleus (P<0.04), thalamus (P<0.01), and at the trend level in inferior frontal gyrus (P=0.07). All regions except fusiform were moderated by childhood trauma. Amygdala-calcarine (P=0.01) and amygdala-thalamus (P=0.06) functional connectivity selectively increased in PTSD patients for high-intensity stimuli after conditioning. In contrast, amygdala-ventromedial prefrontal cortex (P=0.04) connectivity selectively increased in trauma-exposed controls compared with PTSD patients for low-intensity stimuli after conditioning, representing safety learning. In summary, fear generalization in PTSD is biased toward stimuli with higher emotional intensity than the original conditioned-fear stimulus. Functional brain differences provide a putative neurobiological model for fear generalization whereby PTSD symptoms are triggered by threat cues that merely resemble the index trauma.

Quantifying pursuit diving seabirds' associations with fine-scale physical features in a high tidal energy environment

The rapid increase in the number of tidal stream turbine arrays will create novel and unprecedented levels of anthropogenic activity within habitats characterized by horizontal current speeds exceeding 2 ms−1. However, the potential impacts on pursuit‐diving seabirds exploiting these tidal stream environments remain largely unknown. Identifying similarities between the fine‐scale physical features (100s of metres) suitable for array installations, and those associated with foraging pursuit‐diving seabirds, could identify which species are most vulnerable to either collisions with moving components, or displacement from these installations. A combination of vessel‐based observational surveys, Finite Volume Community Ocean Model outputs and hydroacoustic seabed surveys provided concurrent measures of foraging distributions and physical characteristics at a fine temporal (15 min) and spatial (500 m) resolution across a tidal stream environment suitable for array installations, during both breeding and non‐breeding seasons. These data sets were then used to test for associations between foraging pursuit‐diving seabirds (Atlantic puffins Fratercula arctica, black guillemots Cepphus grylle, common guillemots Uria aalge, European shags Phalacrocorax aristotelis) and physical features. These species were associated with areas of fast horizontal currents, slow horizontal currents, high turbulence, downward vertical currents and also hard–rough seabeds. The identity and strength of associations differed among species, and also within species between seasons, indicative of interspecific and intraspecific variations in habitat use. However, Atlantic puffins were associated particularly strongly with areas of fast horizontal currents during breeding seasons, and European shags with areas of rough–hard seabeds and downward vertical currents during non‐breeding seasons. Synthesis and applications. Atlantic puffins’ strong association with fast horizontal current speeds indicates that they are particularly likely to interact with installations during breeding seasons. Any post‐installation monitoring and mitigation measures should therefore focus on this species and season. The multi‐species associations with high turbulence and downward vertical currents, which often coincide with fast horizontal current speeds, also highlight useful pre‐installation mitigation measures via the omission of devices from these areas, reducing the overall likelihood of interactions. Environmental impact assessments (EIA) generally involve once‐a‐month surveys across 2‐year periods. However, the approaches used in this study show that more focussed surveys can greatly benefit management strategies aiming to reduce the likelihood of negative impacts by facilitating the development of targeted mitigation measures. It is therefore recommended that these approaches contribute towards EIA within development sites.

LEARNING IMPULSE CONTROL IN A NOVEL ANIMAL MODEL: SYNAPTIC, CELLULAR, AND PHARMACOLOGICAL SUBSTRATES

Impulse control, an executive process that restrains inappropriate actions, is impaired in numerous psychiatric conditions. This thesis reports three experiments that utilized a novel animal model of impulse control, the response inhibition (RI) task, to examine the substrates that underlie learning this task. In the first experiment, rats were trained to withhold responding on the RI task, and then euthanized for electrophysiological testing. Training in the RI task increased the AMPA/NMDA ratio at the synapses of pyramidal neurons in the prelimbic, but not infralimbic, region of the medial prefrontal cortex. This enhancement paralleled performance as subjects underwent acquisition and extinction of the inhibitory response. AMPA/NMDA was elevated only in neurons that project to the ventral striatum. Thus, this experiment identified a synaptic correlate of impulse control. In the second experiment, a separate group of rats were trained in the RI task prior to electrophysiological testing. Training in the RI task produced a decrease in membrane excitability in prelimbic, but not infralimbic, neurons as measured by maximal spiking evoked in response to increasing current injection. Importantly, this decrease was strongly correlated with successful inhibition in the task. Fortuitously, subjects trained in an operant control condition showed elevated infralimbic, but not prelimbic, excitability, which was produced by learning an anticipatory signal that predicted imminent reward availability. These experiments revealed two cellular correlates of performance, corresponding to learning two different associations under distinct task conditions. In the final experiment, rats were trained on the RI task under three conditions: Short (4-s), long (60-s), or unpredictable (1-s to 60-s) premature phases. These conditions produced distinct errors on the RI task. Interestingly, amphetamine increased premature responding in the short and long conditions, but decreased premature responding in the unpredictable condition. This dissociation may arise from interactions between amphetamine and underlying cognitive processes, such as attention, timing, and conditioned avoidance. In summary, this thesis showed that learning to inhibit a response produces distinct synaptic, cellular, and pharmacological changes. It is hoped that these advances will provide a starting point for future therapeutic interventions of disorders of impulse control.

Chemical composition of B-type supergiants in the OB 8, OB 10, OB 48, OB 78 associations of M 31

Absolute and differential chemical abundances are presented for the largest group of massive stars in M31 studied to date. These results were derived from intermediate resolution spectra of seven B-type supergiants, lying within four OB associations covering a galactocentric distance of 5-12 kpc. The results are mainly based on an LTE analysis, and we additionally present a full non-LTE, unified model atmosphere analysis of one star (OB 78-277) to demonstrate the reliability of the differential LTE technique. A comparison of the stellar oxygen abundance with that of previous nebular results shows that there is an off set of between similar to0.15-0.4 dex between the two methods which is critically dependent on the empirical calibration adopted for the R 23 parameter with [O/H]. However within the typical errors of the stellar and nebular analyses (and given the strength of dependence of the nebular results on the calibration used) the oxygen abundances determined in each method are fairly consistent. We determine the radial oxygen abundance gradient from these stars, and do not detect any systematic gradient across this galactocentric range. We find that the inner regions of M31 are not, as previously thought, very "metal rich". Our abundances of C, N, O, Mg, Si, Al, S and Fe in the M31 supergiants are very similar to those of massive stars in the solar neighbourhood.

Associations between Mothers' Experiences with the Troubles in Northern Ireland and Mothers' and Childrens' Psychological Functioning: The Moderating Role of Social Identity.

Relatively little research has examined the relations between growing up in a community with a history of protracted violent political conflict and subsequent generations' well-being. The current article examines relations between mothers' self-report of the impact that the historical political violence in Northern Ireland (known, as the Troubles) has on her and her child's current mental health. These relations are framed within the social identity model of stress, which provides a framework for understanding coping responses within societies that have experienced intergroup conflict. Mother-child dyads (N = 695) living in Belfast completed interviews. Results suggest that the mother-reported impact of the Troubles continue to be associated with mothers' mental health, which, in, turn, is associated with her child's adjustment. The strength of mothers' social identity moderated pathways between the impact of the Troubles and her mental health, consistent with the social identity model of stress. (C) 2010 Wiley Periodicals, Inc.

Associations between maternal characteristics and pregnancy-related stress among low-risk mothers: An observational cross-sectional study

Background: Pregnancy is viewed as a major life event and, while the majority of healthy, low-risk women adapt well to pregnancy, there are those whose levels of stress are heightened by the experience.

Objectives: To determine the level of pregnancy-related stress experienced by a group of healthy, low-risk pregnant women and to relate the level of stress with a number of maternal characteristics.

Design: An observational cross-sectional study.

Setting: A large, urban maternity centre in Northern Ireland.

Participants: Of the 306 pregnant women who were invited to participate, 278 provided informed consent and were administered one self-complete questionnaire. Due to the withdrawal criteria, 15 questionnaires were removed from the analysis, resulting in a final sample of 263 healthy, low-risk pregnant women.

Methods: Levels of stress were measured using a self-report measure designed to assess specific worries and concerns relating to pregnancy. Maternal characteristics collected included age, marital status, social status, parity, obstetric history, perceived health status and 'wantedness' for the pregnancy. Regression analysis was undertaken using an ordinary linear regression model.

Results: The mean prenatal distress score in the sample was 15.1 (SD = 7.4; range 0-46). The regression model showed that women who had had previous pregnancies, with or without complications, had significantly lower mean prenatal distress scores than primiparous women (p < 0.01). Women reporting poorer physical health had higher mean prenatal distress scores than those who reported at least average health, while women aged 16-20 experienced a mean increase in the reported prenatal distress score (p < 0.05) in comparison to the reference group of 36 years and over.

Conclusions: This study brings to light the prevalence of pregnancy-related stress within a sample representative of healthy, low-risk women. Current antenatal care is ill-equipped to identify women suffering from high levels of stress; yet a growing body of research evidence links stress with adverse pregnancy outcomes. This study emphasises that healthy, low-risk women experience a range of pregnancy-related stress and identification of stress levels, either through the use of a simple stress measurement tool or through the associated factors identified within this research study, provides valuable data on maternal well-being. (C) 2010 Elsevier Ltd. All rights reserved.

Is Use of Optional Attributes and Associations in Conceptual Modeling Always Problematic? Theory and Empirical Tests

Prior research has argued that use of optional properties in conceptual models results in loss of information about the semantics of the domains represented by the models. Empirical research undertaken to date supports this argument. Nevertheless, no systematic analysis has been done of whether use of optional properties is always problematic. Furthermore, prior empirical research might have deliberately or unwittingly employed models where use of optionality always causes problems. Accordingly, we examine analytically whether use of optional properties is always problematic. We employ our analytical results to inform the design of an experiment where we systematically examined the impact of optionality on users’ ability to understand domains represented by different types of conceptual models. We found evidence that use of optionality undermines users’ ability to understand the domain represented by a model but that this effect weakens when use of mandatory properties to replace optional properties leads to more-complex models.

A new statistical framework for the quantification of covariate associations with species distributions

Identifying processes that shape species geographical ranges is a prerequisite for understanding environmental change. Currently, species distribution modelling methods do not offer credible statistical tests of the relative influence of climate factors and typically ignore other processes (e.g. biotic interactions and dispersal limitation). We use a hierarchical model fitted with Markov Chain Monte Carlo to combine ecologically plausible niche structures using regression splines to describe unimodal but potentially skewed response terms. We apply spatially explicit error terms that account for (and may help identify) missing variables. Using three example distributions of European bird species, we map model results to show sensitivity to change in each covariate. We show that the overall strength of climatic association differs between species and that each species has considerable spatial variation in both the strength of the climatic association and the sensitivity to climate change. Our methods are widely applicable to many species distribution modelling problems and enable accurate assessment of the statistical importance of biotic and abiotic influences on distributions.

A HuGE Review and Meta-Analyses of Genetic Associations in New Onset Diabetes after Kidney Transplantation

PURPOSE: New onset diabetes after transplantation (NODAT) is a serious complication following solid organ transplantation. There is a genetic contribution to NODAT and we have conducted comprehensive meta-analysis of available genetic data in kidney transplant populations.

METHODS: Relevant articles investigating the association between genetic markers and NODAT were identified by searching PubMed, Web of Science and Google Scholar. SNPs described in a minimum of three studies were included for analysis using a random effects model. The association between identified variants and NODAT was calculated at the per-study level to generate overall significance values and effect sizes.

RESULTS: Searching the literature returned 4,147 citations. Within the 36 eligible articles identified, 18 genetic variants from 12 genes were considered for analysis. Of these, three were significantly associated with NODAT by meta-analysis at the 5% level of significance; CDKAL1 rs10946398 p = 0.006 OR = 1.43, 95% CI = 1.11-1.85 (n = 696 individuals), KCNQ1 rs2237892 p = 0.007 OR = 1.43, 95% CI = 1.10-1.86 (n = 1,270 individuals), and TCF7L2 rs7903146 p = 0.01 OR = 1.41, 95% CI = 1.07-1.85 (n = 2,967 individuals).

CONCLUSION: Evaluating cumulative evidence for SNPs associated with NODAT in kidney transplant recipients has revealed three SNPs associated with NODAT. An adequately powered, dense genome-wide association study will provide more information using a carefully defined NODAT phenotype.