The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

A spatial modelling framework for assessing climate change impacts on freshwater ecosystems: Response of brown trout (Salmo trutta L.) biomass to warming water temperature

Mountain regions worldwide are particularly sensitive to on-going climate change. Specifically in the Alps in Switzerland, the temperature has increased twice as fast than in the rest of the Northern hemisphere. Water temperature closely follows the annual air temperature cycle, severely impacting streams and freshwater ecosystems. In the last 20 years, brown trout (Salmo trutta L) catch has declined by approximately 40-50% in many rivers in Switzerland. Increasing water temperature has been suggested as one of the most likely cause of this decline. Temperature has a direct effect on trout population dynamics through developmental and disease control but can also indirectly impact dynamics via food-web interactions such as resource availability. We developed a spatially explicit modelling framework that allows spatial and temporal projections of trout biomass using the Aare river catchment as a model system, in order to assess the spatial and seasonal patterns of trout biomass variation. Given that biomass has a seasonal variation depending on trout life history stage, we developed seasonal biomass variation models for three periods of the year (Autumn-Winter, Spring and Summer). Because stream water temperature is a critical parameter for brown trout development, we first calibrated a model to predict water temperature as a function of air temperature to be able to further apply climate change scenarios. We then built a model of trout biomass variation by linking water temperature to trout biomass measurements collected by electro-fishing in 21 stations from 2009 to 2011. The different modelling components of our framework had overall a good predictive ability and we could show a seasonal effect of water temperature affecting trout biomass variation. Our statistical framework uses a minimum set of input variables that make it easily transferable to other study areas or fish species but could be improved by including effects of the biotic environment and the evolution of demographical parameters over time. However, our framework still remains informative to spatially highlight where potential changes of water temperature could affect trout biomass. (C) 2015 Elsevier B.V. All rights reserved.-

What Role Does Sleep Play in Weight Gain in the First Semester of University?

We hypothesized that shorter sleep durations and greater variability in sleep patterns are associated with weight gain in the first semester of university. Students (N = 132) completed daily sleep diaries for 9 weeks, completed the MEQ (chronotype) and CES-D (depressed mood) at week 9, and self-reported weight/height (weeks 1 & 9). Mean and variability scores were calculated for sleep duration (TST, TSTv), bedtime (BT, BTv), and wake time (WT, WTv). An initial hierarchical regression evaluated (block 1) sex, ethnicity; (block 2) depressed mood, chronotype; (block 3) TST; (block 4) BT, WT; and (block 5; R(2) change = 0.09, p = 0.005) TSTv, BTv, WTv with weight change. A sex-by-TSTv interaction was found. A final model showed that ethnicity, TST, TSTv, and BTv accounted for 31% of the variance in weight change for males; TSTv was the most significant contributor (R(2) change = 0.21, p < 0.001). Daily variability in sleep duration contributes to males' weight gain. Further investigation needs to examine sex-specific outcomes for sleep and weight.

Estimation of reference curves for the urinary steroid metabolome in the first year of life in healthy children : Tracing the complexity of human postnatal steroidogenesis.

CONTEXT: Complex steroid disorders such as P450 oxidoreductase deficiency or apparent cortisone reductase deficiency may be recognized by steroid profiling using chromatographic mass spectrometric methods. These methods are highly specific and sensitive, and provide a complete spectrum of steroid metabolites in a single measurement of one sample which makes them superior to immunoassays. The steroid metabolome during the fetal-neonatal transition is characterized by (a) the metabolites of the fetal-placental unit at birth, (b) the fetal adrenal androgens until its involution 3-6 months postnatally, and (c) the steroid metabolites produced by the developing endocrine organs. All these developmental events change the steroid metabolome in an age- and sex-dependent manner during the first year of life. OBJECTIVE: The aim of this study was to provide normative values for the urinary steroid metabolome of healthy newborns at short time intervals in the first year of life. METHODS: We conducted a prospective, longitudinal study to measure 67 urinary steroid metabolites in 21 male and 22 female term healthy newborn infants at 13 time-points from week 1 to week 49 of life. Urine samples were collected from newborn infants before discharge from hospital and from healthy infants at home. Steroid metabolites were measured by gas chromatography-mass spectrometry (GC-MS) and steroid concentrations corrected for urinary creatinine excretion were calculated. RESULTS: 61 steroids showed age and 15 steroids sex specificity. Highest urinary steroid concentrations were found in both sexes for progesterone derivatives, in particular 20α-DH-5α-DH-progesterone, and for highly polar 6α-hydroxylated glucocorticoids. The steroids peaked at week 3 and decreased by ∼80% at week 25 in both sexes. The decline of progestins, androgens and estrogens was more pronounced than of glucocorticoids whereas the excretion of corticosterone and its metabolites and of mineralocorticoids remained constant during the first year of life. CONCLUSION: The urinary steroid profile changes dramatically during the first year of life and correlates with the physiologic developmental changes during the fetal-neonatal transition. Thus detailed normative data during this time period permit the use of steroid profiling as a powerful diagnostic tool.

Anxiety, depression, and attachment before and after the first-trimester screening for Down syndrome: comparing couples who undergo ART with those who conceive spontaneously.

OBJECTIVES: This study's aim was to describe the emotional status of parents to be before and after the first-trimester combined prenatal screening test. METHODS: One hundred three couples participated, of which 52 had undergone an in vitro fertilization/intracytoplasmic sperm injection treatment [assisted reproductive technology (ART)] and 51 had conceived spontaneously. Participants completed the state scale of the State-trait Anxiety Inventory, the Edinburgh Depression Scale, and the Maternal and Paternal Antenatal Attachment Questionnaire before the first-trimester combined prenatal screening test at around 12 weeks of gestational age (T1) and just after receiving the results at approximately 14 weeks of gestational age (T2). RESULTS: We observed a significant decrease in anxiety and depression symptoms and a significant increase in attachment from T1 to T2. Results showed no differences between groups at either time point, which suggests that ART parents are more similar to than different from parents conceiving spontaneously. Furthermore, given the importance of anxiety during pregnancy, a subsample of women with clinical anxiety was identified. They had significantly higher rates of clinical depression and lower attachment. CONCLUSIONS: These results indicate that, regardless of whether conception was through ART or spontaneous, clinical anxiety in women over the prenatal testing period is associated with more vulnerability during pregnancy (i.e. clinical depression and less attachment to fetus). © 2015 John Wiley & Sons, Ltd.

A single-blind, randomised controlled trial on the effects of lithium and quetiapine monotherapy on the trajectory of cognitive functioning in first episode mania: A 12-month follow-up study.

BACKGROUND: Cognitive deficits have been reported during the early stages of bipolar disorder; however, the role of medication on such deficits remains unclear. The aim of this study was to compare the effects of lithium and quetiapine monotherapy on cognitive performance in people following first episode mania. METHODS: The design was a single-blind, randomised controlled trial on a cohort of 61 participants following first episode mania. Participants received either lithium or quetiapine monotherapy as maintenance treatment over a 12-month follow-up period. The groups were compared on performance outcomes using an extensive cognitive assessment battery conducted at baseline, month 3 and month 12 follow-up time-points. RESULTS: There was a significant interaction between group and time in phonemic fluency at the 3-month and 12-month endpoints, reflecting greater improvements in performance in lithium-treated participants relative to quetiapine-treated participants. After controlling for multiple comparisons, there were no other significant interactions between group and time for other measures of cognition. CONCLUSION: Although the effects of lithium and quetiapine treatment were similar for most cognitive domains, the findings imply that early initiation of lithium treatment may benefit the trajectory of cognition, specifically verbal fluency in young people with bipolar disorder. Given that cognition is a major symptomatic domain of bipolar disorder and has substantive effects on general functioning, the ability to influence the trajectory of cognitive change is of considerable clinical importance.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

Ecological change predicts population dynamics and genetic diversity over 120 000 years.

While ecological effects on short-term population dynamics are well understood, their effects over millennia are difficult to demonstrate and convincing evidence is scant. Using coalescent methods, we analysed past population dynamics of three lizard species (Psammodromus hispanicus, P. edwardsianus, P. occidentalis) and linked the results with climate change data covering the same temporal horizon (120 000 years). An increase in population size over time was observed in two species, and in P. occidentalis, no change was observed. Temporal changes in temperature seasonality and the maximum temperature of the warmest month were congruent with changes in population dynamics observed for the three species and both variables affected population density, either directly or indirectly (via a life-history trait). These results constitute the first solid link between ecological change and long-term population dynamics. The results moreover suggest that ecological change leaves genetic signatures that can be retrospectively traced, providing evidence that ecological change is a crucial driver of genetic diversity and speciation.