The combined effects of reactant kinetics and enzyme stability explain the temperature dependence of metabolic rates

A mechanistic understanding of the response of metabolic rate to temperature is essential for understanding thermal ecology and metabolic adaptation. Although the Arrhenius equation has been used to describe the effects of temperature on reaction rates and metabolic traits, it does not adequately describe two aspects of the thermal performance curve (TPC) for metabolic rate—that metabolic rate is a unimodal function of temperature often with maximal values in the biologically relevant temperature range and that activation energies are temperature dependent. We show that the temperature dependence of metabolic rate in ectotherms is well described by an enzyme-assisted Arrhenius (EAAR) model that accounts for the temperature-dependent contribution of enzymes to decreasing the activation energy required for reactions to occur. The model is mechanistically derived using the thermodynamic rules that govern protein stability. We contrast our model with other unimodal functions that also can be used to describe the temperature dependence of metabolic rate to show how the EAAR model provides an important advance over previous work. We fit the EAAR model to metabolic rate data for a variety of taxa to demonstrate the model’s utility in describing metabolic rate TPCs while revealing significant differences in thermodynamic properties across species and acclimation temperatures. Our model advances our ability to understand the metabolic and ecological consequences of increases in the mean and variance of temperature associated with global climate change. In addition, the model suggests avenues by which organisms can acclimate and adapt to changing thermal environments. Furthermore, the parameters in the EAAR model generate links between organismal level performance and underlying molecular processes that can be tested for in future work

Multi-Polygenic Analysis of Nicotine Dependence in Individuals of European Ancestry

Introduction: Heritability estimates of nicotine dependence (ND) range from 40% to 70%, but discovery GWAS of ND are underpowered and have limited predictive utility. In this work, we leverage genetically correlated traits and diseases to increase the accuracy of polygenic risk prediction. Methods: We employed a multi-trait model using summary statistic-based best linear unbiased predictors (SBLUP) of genetic correlates of DSM-IV diagnosis of ND in 6394 individuals of European Ancestry (prevalence = 45.3%, %female = 46.8%, mu(age) = 40.08 [s.d. = 10.43]) and 3061 individuals from a nationally-representative sample with Fagerstrom Test for Nicotine Dependence symptom count (FTND; 51.32% female, mean age = 28.9 [s.d. = 1.70]). Polygenic predictors were derived from GWASs known to be phenotypically and genetically correlated with ND (i.e., Cigarettes per Day [CPD], the Alcohol Use Disorders Identification Test [AUDIT-Consumption and AUDIT-Problems], Neuroticism, Depression, Schizophrenia, Educational Attainment, Body Mass Index [BMI], and Self-Perceived Risk-Taking); including Height as a negative control. Analyses controlled for age, gender, study site, and the first 10 ancestral principal components. Results: The multi-trait model accounted for 3.6% of the total trait variance in DSM-IV ND. Educational Attainment (beta = -0.125; 95% CI: [-0.149,-0.101]), CPD (0.071 [0.047,0.095]), and Self-Perceived Risk-Taking (0.051 [0.026,0.075]) were the most robust predictors. PGS effects on FTND were limited. Conclusions: Risk for ND is not only polygenic, but also pleiotropic. Polygenic effects on ND that are accessible by these traits are limited in size and act additively to explain risk.Peer reviewe

Multi-omic and multi-species meta-analyses of nicotine consumption.

Cross-species translational approaches to human genomic analyses are lacking. The present study uses an integrative framework to investigate how genes associated with nicotine use in model organisms contribute to the genetic architecture of human tobacco consumption. First, we created a model organism geneset by collecting results from five animal models of nicotine exposure (RNA expression changes in brain) and then tested the relevance of these genes and flanking genetic variation using genetic data from human cigarettes per day (UK BioBank N = 123,844; all European Ancestry). We tested three hypotheses: (1) DNA variation in, or around, the \u27model organism geneset\u27 will contribute to the heritability to human tobacco consumption, (2) that the model organism genes will be enriched for genes associated with human tobacco consumption, and (3) that a polygenic score based off our model organism geneset will predict tobacco consumption in the AddHealth sample (N = 1667; all European Ancestry). Our results suggested that: (1) model organism genes accounted for ~5-36% of the observed SNP-heritability in human tobacco consumption (enrichment: 1.60-31.45), (2) model organism genes, but not negative control genes, were enriched for the gene-based associations (MAGMA, H-MAGMA, SMultiXcan) for human cigarettes per day, and (3) polygenic scores based on our model organism geneset predicted cigarettes per day in an independent sample. Altogether, these findings highlight the advantages of using multiple species evidence to isolate genetic factors to better understand the etiological complexity of tobacco and other nicotine consumption

Adaptable data management for systems biology investigations

<p>Abstract</p> <p>Background</p> <p>Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage.</p> <p>Results</p> <p>The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry). We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents.</p> <p>Conclusion</p> <p>Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community.</p

Comparing the measurement equivalence of EQ-5D-5L across different modes of administration

Background: Interest in collecting Patient Reported Outcomes using electronic methods such as mobile phones has increased in recent years. However there is debate about the level of measurement equivalence between the traditional paper and newer electronic modes. Information about the acceptability of the electronic versions to respondents is also required. The aim of this study is to compare the equivalence of delivering a widely used generic measure of health status (EQ-5D-5L) across two administration modes (paper and mobile phone). Methods: Respondents from a research cohort of people in South Yorkshire were identified, and randomly allocated to one of two administration modes (paper vs. mobile phone) based on stratifications for age and gender (and across a range of self-reported health conditions). A parallel group design was used where each respondent only completed EQ-5D-5L using one of the modes. In total, 70 respondents completed the measure in the mobile phone arm, and 66 completed the standard paper version. Follow up usability questions were also included to assess the acceptability of the mobile version of EQ-5D-5L. Measurement equivalence was compared at the dimension, utility score and visual analogue scale level using chi square analysis and ANOVA, and by comparing mean differences to an estimated minimally important difference value. Results: Response rates were higher in the mobile arm. The mean EQ-5D-5L utility and VAS scores, and the frequency of respondents endorsing individual EQ-5D-5L dimension response levels did not significantly differ across the administration modes. The majority of the mobile arm agreed that the mobile version of EQ-5D-5L was easy to complete, and that the phone was easy to use, and that they would complete mobile health measures again. Conclusions: Completing health status measures such as EQ-5D using mobile phones produces equivalent results to more traditional methods, but with added benefits (for example lessening the burden of data entry). Respondents are positive towards completing questionnaires using these methods. The results provide evidence that electronic measures are valid for use to collect data in a range of settings including clinical trials, routine care, and in health diary settings

Religion's Role in Promoting Health and Reducing Risk Among American Youth

Although past research has long documented religion's salutary impact on adult health-related behaviors and outcomes, relatively little research has examined the relationship between religion and adolescent health. This study uses large, nationally representative samples of high school seniors to examine the relationship between religion and behavioral predictors of adolescent morbidity and mortality. Relative to their peers, religious youth are less likely to engage in behaviors that compromise their health (e.g., carrying weapons, getting into fights, drinking and driving) and are more likely to behave in ways that enhance their health (e.g., proper nutrition, exercise, and rest). Multivariate analyses suggest that these relationships persist even after controlling for demographic factors, and trend analyses reveal that they have existed over time. Particularly important is the finding that religious seniors have been relatively unaffected by past and recent increases in marijuana use.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66995/2/10.1177_109019819802500604.pd

Self-esteem and delinquency revisited

A recent investigation by Rosenberg and Rosenberg used longitudinal data from the Youth in Transition study to explore the causal relationships between delinquency and self-esteem. The present study is based on the same sample of young men in high school and extends Rosenberg and Rosenberg's analysis, first by using the same cross-lagged correlation methods applied over a longer time period, and then by employing a “causal modeling” approach using the LISREL computer program. Each of the analyses was carried out using the total sample as well as two subsamples, the highest and lowest quartiles in initial self-esteem. The causal modeling analyses attempted (a) to take careful account of the actual periods referenced by the measures of delinquency and self-esteem, (b) to control socioeconomic status and ability, and (c) to extend the model to demonstrate ways in which participation in teenage social life and current educational attainment might also influence and be influenced by self-esteem. The analyses suggest that self-esteem plays little part in influencing the teenage behaviors and orientations that follow in time. Consistent with Kaplan's prediction, among young men who enter high school with low self-esteem, the effects of delinquent behavior tend primarily to be self-enhancing.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45258/1/10964_2005_Article_BF02087937.pd

Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background Suboptimal diet is an important preventable risk factor for non-communicable diseases (NCDs); however, its impact on the burden of NCDs has not been systematically evaluated. This study aimed to evaluate the consumption of major foods and nutrients across 195 countries and to quantify the impact of their suboptimal intake on NCD mortality and morbidity

Phylogenetic relationships and molecular evolution in uropeltid snakes (Serpentes: Uropeltidae): allozymes and albumin immunology

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73950/1/j.1095-8312.1990.tb00541.x.pd