Is reduction in appetite beneficial for body weight management in the context of overweight and obesity? Yes, according to the SATIN (Satiety Innovation) study

New dietary-based concepts are needed for treatment and effective prevention of overweight and obesity. The primary objective was to investigate if reduction in appetite is associated with improved weight loss maintenance. This cohort study was nested within the European Commission project Satiety Innovation (SATIN). Participants achieving ≥8% weight loss during an initial 8-week low-energy formula diet were included in a 12-week randomised double-blind parallel weight loss maintenance intervention. The intervention included food products designed to reduce appetite or matching controls along with instructions to follow national dietary guidelines. Appetite was assessed by ad libitum energy intake and self-reported appetite evaluations using visual analogue scales during standardised appetite probe days. These were evaluated at the first day of the maintenance period compared with baseline (acute effects after a single exposure of intervention products) and post-maintenance compared with baseline (sustained effects after repeated exposures of intervention products) regardless of randomisation. A total of 181 participants (forty-seven men and 134 women) completed the study. Sustained reduction in 24-h energy intake was associated with improved weight loss maintenance (R 0·37; P = 0·001), whereas the association was not found acutely (P = 0·91). Suppression in self-reported appetite was associated with improved weight loss maintenance both acutely (R −0·32; P = 0·033) and sustained (R −0·33; P = 0·042). Reduction in appetite seems to be associated with improved body weight management, making appetite-reducing food products an interesting strategy for dietary-based concepts

Menopause accelerates biological aging

Although epigenetic processes have been linked to aging and disease in other systems, it is not yet known whether they relate to reproductive aging. Recently, we developed a highly accurate epigenetic biomarker of age (known as the “epigenetic clock”), which is based on DNA methylation levels. Here we carry out an epigenetic clock analysis of blood, saliva, and buccal epithelium using data from four large studies: the Women's Health Initiative (n = 1,864); Invecchiare nel Chianti (n = 200); Parkinson's disease, Environment, and Genes (n = 256); and the United Kingdom Medical Research Council National Survey of Health and Development (n = 790). We find that increased epigenetic age acceleration in blood is significantly associated with earlier menopause (P = 0.00091), bilateral oophorectomy (P = 0.0018), and a longer time since menopause (P = 0.017). Conversely, epigenetic age acceleration in buccal epithelium and saliva do not relate to age at menopause; however, a higher epigenetic age in saliva is exhibited in women who undergo bilateral oophorectomy (P = 0.0079), while a lower epigenetic age in buccal epithelium was found for women who underwent menopausal hormone therapy (P = 0.00078). Using genetic data, we find evidence of coheritability between age at menopause and epigenetic age acceleration in blood. Using Mendelian randomization analysis, we find that two SNPs that are highly associated with age at menopause exhibit a significant association with epigenetic age acceleration. Overall, our Mendelian randomization approach and other lines of evidence suggest that menopause accelerates epigenetic aging of blood, but mechanistic studies will be needed to dissect cause-and-effect relationships further

Longitudinal variability of time-location/activity patterns of population at different ages: a longitudinal study in California

<p>Abstract</p> <p>Background</p> <p>Longitudinal time-activity data are important for exposure modeling, since the extent to which short-term time-activity data represent long-term activity patterns is not well understood. This study was designed to evaluate longitudinal variations in human time-activity patterns.</p> <p>Method</p> <p>We report on 24-hour recall diaries and questionnaires collected via the internet from 151 parents of young children (mostly under age 55), and from 55 older adults of ages 55 and older, for both a weekday and a weekend day every three months over an 18-month period. Parents also provided data for their children. The self-administrated diary and questionnaire distinguished ~30 frequently visited microenvironments and ~20 activities which we selected to represent opportunities for exposure to toxic environmental compounds. Due to the non-normal distribution of time-location/activity data, we employed generalized linear mixed-distribution mixed-effect models to examine intra- and inter-individual variations. Here we describe variation in the likelihood of and time spent engaging in an activity or being in a microenvironment by age group, day-type (weekday/weekend), season (warm/cool), sex, employment status, and over the follow-up period.</p> <p>Results</p> <p>As expected, day-type and season influence time spent in many location and activity categories. Longitudinal changes were also observed, e.g., young children slept less with increasing follow-up, transit time increased, and time spent on working and shopping decreased during the study, possibly related to human physiological changes with age and changes in macro-economic factors such as gas prices and the economic recession.</p> <p>Conclusions</p> <p>This study provides valuable new information about time-activity assessed longitudinally in three major age groups and greatly expands our knowledge about intra- and inter-individual variations in time-location/activity patterns. Longitudinal variations beyond weekly and seasonal patterns should be taken into account in simulating long-term time-activity patterns in exposure modeling.</p

Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics

The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves.The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats.We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data

Thrombin Induces Macrophage Migration Inhibitory Factor Release and Upregulation in Urothelium: A Possible Contribution to Bladder Inflammation

Macrophage migration inhibitory factor (MIF) is a pro-inflammatory cytokine expressed by urothelial cells that mediates bladder inflammation. We investigated the effect of stimulation with thrombin, a Protease Activated Receptor-1 (PAR1) agonist, on MIF release and MIF mRNA upregulation in urothelial cells.MIF and PAR1 expression was examined in normal human immortalized urothelial cells (UROtsa) using real-time RT-PCR, Western blotting and dual immunostaining. MIF and PAR1 immunostaining was also examined in rat urothelium. The effect of thrombin stimulation (100 nM) on urothelial MIF release was examined in UROtsa cells (in vitro) and in rats (in vivo). UROtsa cells were stimulated with thrombin, culture media were collected at different time points and MIF amounts were determined by ELISA. Pentobarbital anesthetized rats received intravesical saline (control), thrombin, or thrombin +2% lidocaine (to block nerve activity) for 1 hr, intraluminal fluid was collected and MIF amounts determined by ELISA. Bladder or UROtsa MIF mRNA was measured using real time RT-PCR.UROtsa cells constitutively express MIF and PAR1 and immunostaining for both was observed in these cells and in the basal and intermediate layers of rat urothelium. Thrombin stimulation of urothelial cells resulted in a concentration- and time-dependent increase in MIF release both in vitro (UROtsa; 2.8-fold increase at 1 hr) and in vivo (rat; 4.5-fold) while heat-inactivated thrombin had no effect. In rats, thrombin-induced MIF release was reduced but not abolished by intravesical lidocaine treatment. Thrombin also upregulated MIF mRNA in UROtsa cells (3.3-fold increase) and in the rat bladder (2-fold increase) where the effect was reduced (1.4-fold) by lidocaine treatment.Urothelial cells express both MIF and PAR1. Activation of urothelial PAR1 receptors, either by locally generated thrombin or proteases present in the urine, may mediate bladder inflammation by inducing urothelial MIF release and upregulating urothelial MIF expression

Genome-Wide Gene-Environment Study Identifies Glutamate Receptor Gene GRIN2A as a Parkinson's Disease Modifier Gene via Interaction with Coffee

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df = 10−6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10−7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication = 0.59, PReplication = 10−3; ORPooled = 0.51, PPooled = 7×10−8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10−3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10−13). Imputation revealed a block of SNPs that achieved P2df<5×10−8 in GWAIS, and OR = 0.41, P = 3×10−8 in heavy coffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify genes that are missed in GWAS. Both adenosine antagonists (caffeine-like) and glutamate antagonists (GRIN2A-related) are being tested in clinical trials for treatment of PD. GRIN2A may be a useful pharmacogenetic marker for subdividing individuals in clinical trials to determine which medications might work best for which patients

Endophytic fungi from the roots of horseradish (Armoracia rusticana) and their interactions with the defensive metabolites of the glucosinolate myrosinase – isothiocyanate system

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