Associations between sleep health and obesity and weight change in adults: The Daily24 Multisite Cohort Study.

OBJECTIVES: To examine cross-sectional and longitudinal associations of individual sleep domains and multidimensional sleep health with current overweight or obesity and 5-year weight change in adults. METHODS: We estimated sleep regularity, quality, timing, onset latency, sleep interruptions, duration, and napping using validated questionnaires. We calculated multidimensional sleep health using a composite score (total number of "good" sleep health indicators) and sleep phenotypes derived from latent class analysis. Logistic regression was used to examine associations between sleep and overweight or obesity. Multinomial regression was used to examine associations between sleep and weight change (gain, loss, or maintenance) over a median of 1.66 years. RESULTS: The sample included 1016 participants with a median age of 52 (IQR = 37-65), who primarily identified as female (78%), White (79%), and college-educated (74%). We identified 3 phenotypes: good, moderate, and poor sleep. More regularity of sleep, sleep quality, and shorter sleep onset latency were associated with 37%, 38%, and 45% lower odds of overweight or obesity, respectively. The addition of each good sleep health dimension was associated with 16% lower adjusted odds of having overweight or obesity. The adjusted odds of overweight or obesity were similar between sleep phenotypes. Sleep, individual or multidimensional sleep health, was not associated with weight change. CONCLUSIONS: Multidimensional sleep health showed cross-sectional, but not longitudinal, associations with overweight or obesity. Future research should advance our understanding of how to assess multidimensional sleep health to understand the relationship between all aspects of sleep health and weight over time.

Association of Eating and Sleeping Intervals With Weight Change Over Time: The Daily24 Cohort.

Background We aim to evaluate the association between meal intervals and weight trajectory among adults from a clinical cohort. Methods and Results This is a multisite prospective cohort study of adults recruited from 3 health systems. Over the 6-month study period, 547 participants downloaded and used a mobile application to record the timing of meals and sleep for at least 1 day. We obtained information on weight and comorbidities at each outpatient visit from electronic health records for up to 10 years before until 10 months after baseline. We used mixed linear regression to model weight trajectories. Mean age was 51.1 (SD 15.0) years, and body mass index was 30.8 (SD 7.8) kg/m2; 77.9% were women, and 77.5% reported White race. Mean interval from first to last meal was 11.5 (2.3) hours and was not associated with weight change. The number of meals per day was positively associated with weight change. The average difference in annual weight change (95% CI) associated with an increase of 1 daily meal was 0.28 kg (0.02-0.53). Conclusions Number of daily meals was positively associated with weight change over 6 years. Our findings did not support the use of time-restricted eating as a strategy for long-term weight loss in a general medical population.

Electronic Health Record-Based Recruitment and Retention and Mobile Health App Usage: Multisite Cohort Study.

BACKGROUND: To address the obesity epidemic, there is a need for novel paradigms, including those that address the timing of eating and sleep in relation to circadian rhythms. Electronic health records (EHRs) are an efficient way to identify potentially eligible participants for health research studies. Mobile health (mHealth) apps offer available and convenient data collection of health behaviors, such as timing of eating and sleep. OBJECTIVE: The aim of this descriptive analysis was to report on recruitment, retention, and app use from a 6-month cohort study using a mobile app called Daily24. METHODS: Using an EHR query, adult patients from three health care systems in the PaTH clinical research network were identified as potentially eligible, invited electronically to participate, and instructed to download and use the Daily24 mobile app, which focuses on eating and sleep timing. Online surveys were completed at baseline and 4 months. We described app use and identified predictors of app use, defined as 1 or more days of use, versus nonuse and usage categories (ie, immediate, consistent, and sustained) using multivariate regression analyses. RESULTS: Of 70,661 patients who were sent research invitations, 1021 (1.44%) completed electronic consent forms and online baseline surveys; 4 withdrew, leaving a total of 1017 participants in the analytic sample. A total of 53.79% (n=547) of the participants were app users and, of those, 75.3% (n=412), 50.1% (n=274), and 25.4% (n=139) were immediate, consistent, and sustained users, respectively. Median app use was 28 (IQR 7-75) days over 6 months. Younger age, White race, higher educational level, higher income, having no children younger than 18 years, and having used 1 to 5 health apps significantly predicted app use (vs nonuse) in adjusted models. Older age and lower BMI predicted early, consistent, and sustained use. About half (532/1017, 52.31%) of the participants completed the 4-month online surveys. A total of 33.5% (183/547), 29.3% (157/536), and 27.1% (143/527) of app users were still using the app for at least 2 days per month during months 4, 5, and 6 of the study, respectively. CONCLUSIONS: EHR recruitment offers an efficient (ie, high reach, low touch, and minimal participant burden) approach to recruiting participants from health care settings into mHealth research. Efforts to recruit and retain less engaged subgroups are needed to collect more generalizable data. Additionally, future app iterations should include more evidence-based features to increase participant use.

Night eating, weight, and health behaviors in adults participating in the Daily24 study.

BACKGROUND: Night eating syndrome (NES) is associated with adverse health outcomes. This study evaluated the relationship between night eating severity, weight, and health behaviors. METHODS: Participants (N = 1017; 77.6% female, mean Body Mass Index (BMI) = 30.5, SD = 7.8 kg/m2, age = 51.1, SD = 15.0 years) were recruited from three health systems. Participants completed the Night Eating Questionnaire (NEQ) and questionnaires assessing sleep, chronotype, physical activity, diet, weight, and napping. RESULTS: In the overall sample, higher NEQ scores were associated with higher BMI (p < .001) and consumption of sugar-sweetened beverages (p < .001), as well as lower fruit/vegetable consumption (p = .001). Higher NEQ scores were associated with increased odds of having overweight/obesity (p < .001), eating fast food (p < .001), moderate-vigorous physical activity (p = .005), and smoking (p = .004). Participants who exceeded the screening threshold for NES (n = 48, 4.7%) reported elevated BMI (p = .014), an increased likelihood of overweight/obesity (p = .004), greater sugar-sweetened beverages consumption (p < .001), napping less than twice per week (p = .029), shorter sleep duration (p = .012), and a later chronotype (M = 4:55, SD = 2:45). CONCLUSION: Night eating severity was associated with obesity and intake of fast food and sugar-sweetened beverages. Interventions to address night eating and associated behaviors may enhance the efficacy of weight management interventions and promote engagement in positive health behaviors.

Development of a Mobile App for Ecological Momentary Assessment of Circadian Data: Design Considerations and Usability Testing.

BACKGROUND: Collecting data on daily habits across a population of individuals is challenging. Mobile-based circadian ecological momentary assessment (cEMA) is a powerful frame for observing the impact of daily living on long-term health. OBJECTIVE: In this paper, we (1) describe the design, testing, and rationale for specifications of a mobile-based cEMA app to collect timing of eating and sleeping data and (2) compare cEMA and survey data collected as part of a 6-month observational cohort study. The ultimate goal of this paper is to summarize our experience and lessons learned with the Daily24 mobile app and to highlight the pros and cons of this data collection modality. METHODS: Design specifications for the Daily24 app were drafted by the study team based on the research questions and target audience for the cohort study. The associated backend was optimized to provide real-time data to the study team for participant monitoring and engagement. An external 8-member advisory board was consulted throughout the development process, and additional test users recruited as part of a qualitative study provided feedback through in-depth interviews. RESULTS: After ≥4 days of at-home use, 37 qualitative study participants provided feedback on the app. The app generally received positive feedback from test users for being fast and easy to use. Test users identified several bugs and areas where modifications were necessary to in-app text and instructions and also provided feedback on the engagement strategy. Data collected through the mobile app captured more variability in eating windows than data collected through a one-time survey, though at a significant cost. CONCLUSIONS: Researchers should consider the potential uses of a mobile app beyond the initial data collection when deciding whether the time and monetary expenditure are advisable for their situation and goals.

What influences the "when" of eating and sleeping?A qualitative interview study.

Timing of eating relative to sleep and endogenous circadian rhythm impacts weight and cardiometabolic health. We used qualitative methods to explore what influences the "when" of eating and sleeping. We conducted 37 one-on-one semi-structured interviews among participants with a body mass index (BMI) ≥ 25 kg/m2 recruited from three internal medicine clinics affiliated with an urban academic hospital. Participants (70.3% Female; 51.4% White; Age range: 21-83 years old) completed measures of social jetlag, physical activity, eating habits, and mobile application use and participated in interviews following a guide developed by the study team. Responses were recorded, transcribed and coded sequentially by two trained researchers using editing-style analysis to identify themes. We identified two main themes, each with subthemes: 1) influences on the "when" of eating and sleeping, with subthemes including social jetlag and being overscheduled, and 2) contextualizing beliefs and perceptions about the "when" of eating and sleeping, with subthemes including perceived recommendations for timing of eating and sleeping, and alignment of behaviors with perceived recommendations. Many participants noted being more flexible in their eating and sleeping times on work-free vs work days. The themes this study identified should be considered when designing interventions that influence the timing of eating and sleeping for weight management.

Use of Big Data and Information and Communications Technology in Disasters: An Integrative Review.

ABSTRACTNovel approaches to improving disaster response have begun to include the use of big data and information and communication technology (ICT). However, there remains a dearth of literature on the use of these technologies in disasters. We have conducted an integrative literature review on the role of ICT and big data in disasters. Included in the review were 113 studies that met our predetermined inclusion criteria. Most studies used qualitative methods (39.8%, n=45) over mixed methods (31%, n=35) or quantitative methods (29.2%, n=33). Nearly 80% (n=88) covered only the response phase of disasters and only 15% (n=17) of the studies addressed disasters in low- and middle-income countries. The 4 most frequently mentioned tools were geographic information systems, social media, patient information, and disaster modeling. We suggest testing ICT and big data tools more widely, especially outside of high-income countries, as well as in nonresponse phases of disasters (eg, disaster recovery), to increase an understanding of the utility of ICT and big data in disasters. Future studies should also include descriptions of the intended users of the tools, as well as implementation challenges, to assist other disaster response professionals in adapting or creating similar tools. (Disaster Med Public Health Preparedness. 2019;13:353-367).

Inhibition of bile salt transport by drugs associated with liver injury in primary hepatocytes from human, monkey, dog, rat, and mouse.

Interference of bile salt transport is one of the underlying mechanisms for drug-induced liver injury (DILI). We developed a novel bile salt transport activity assay involving in situ biosynthesis of bile salts from their precursors in primary human, monkey, dog, rat, and mouse hepatocytes in suspension as well as LC-MS/MS determination of extracellular bile salts transported out of hepatocytes. Glycine- and taurine-conjugated bile acids were rapidly formed in hepatocytes and effectively transported into the extracellular medium. The bile salt formation and transport activities were time‒ and bile-acid-concentration‒dependent in primary human hepatocytes. The transport activity was inhibited by the bile salt export pump (BSEP) inhibitors ketoconazole, saquinavir, cyclosporine, and troglitazone. The assay was used to test 86 drugs for their potential to inhibit bile salt transport activity in human hepatocytes, which included 35 drugs associated with severe DILI (sDILI) and 51 with non-severe DILI (non-sDILI). Approximately 60% of the sDILI drugs showed potent inhibition (with IC50 values <50 µM), but only about 20% of the non-sDILI drugs showed this strength of inhibition in primary human hepatocytes and these drugs are associated only with cholestatic and mixed hepatocellular cholestatic (mixed) injuries. The sDILI drugs, which did not show substantial inhibition of bile salt transport activity, are likely to be associated with immune-mediated liver injury. Twenty-four drugs were also tested in monkey, dog, rat and mouse hepatocytes. Species differences in potency were observed with mouse being less sensitive than other species to inhibition of bile salt transport. In summary, a novel assay has been developed using hepatocytes in suspension from human and animal species that can be used to assess the potential for drugs and/or drug-derived metabolites to inhibit bile salt transport and/or formation activity. Drugs causing sDILI, except those by immune-mediated mechanism, are highly associated with potent inhibition of bile salt transport.

In vitro model systems to investigate bile salt export pump (BSEP) activity and drug interactions: A review.

The bile salt export pump protein (BSEP), expressed on the canalicular membranes of hepatocytes, is primarily responsible for the biliary excretion of bile salts. The inhibition of BSEP transport activity can lead to an increase in intracellular bile salt levels and liver injury. This review discusses the various in vitro assays currently available for assessing the effect of drugs or other chemical entities to modulate BSEP transport activity. BSEP transporter assays use one of the following platforms: Xenopus laevis oocytes; canalicular membrane vesicles (CMV); BSEP-expressed membrane vesicles; cell lines expressing BSEP; sandwich cultured hepatocytes (SCH); and hepatocytes in suspension. Two of these, BSEP-expressed insect membrane vesicles and sandwich cultured hepatocytes, are the most commonly used assays. BSEP membrane vesicles prepared from transfected insect cells are useful for assessing BSEP inhibition or substrate specificity and exploring mechanisms of BSEP-associated genetic diseases. This model can be applied in a high-throughput format for discovery-drug screening. However, experimental results from use of membrane vesicles may lack physiological relevance and the model does not allow for investigation of in situ metabolism in modulation of BSEP activity. Hepatocyte-based assays that use the SCH format provide results that are generally more physiologically relevant than membrane assays. The SCH model is useful in detailed studies of the biliary excretion of drugs and BSEP inhibition, but due to the complexity of SCH preparation, this model is used primarily for determining biliary clearance and BSEP inhibition in a limited number of compounds. The newly developed hepatocyte in suspension assay avoids many of the complexities of the SCH method. The use of pooled cryopreserved hepatocytes in suspension minimizes genetic variance and individual differences in BSEP activity and also provides the opportunity for higher throughput screening and cross-species comparisons.

Inhibition of MDR3 Activity in Human Hepatocytes by Drugs Associated with Liver Injury.

MDR3 dysfunction is associated with liver diseases. We report here a novel MDR3 activity assay involving in situ biosynthesis in primary hepatocytes of deuterium (d9)-labeled PC and LC-MS/MS determination of transported extracellular PC-d9. Several drugs associated with DILI such as chlorpromazine, imipramine, itraconazole, haloperidol, ketoconazole, sequinavir, clotrimazole, ritonavir, and troglitazone inhibit MDR3 activity. MDR3 inhibition may play an important role in drug-induced cholestasis and vanishing bile duct syndrome. Several lines of evidence demonstrate that the reported assay is physiologically relevant and can be used to assess the potential of chemical entities and their metabolites to modulate MDR3 activity and/or PC biosynthesis in hepatocytes.

Computing ensembles of transitions with molecular dynamics simulations.

A molecular understanding of conformational change is important for connecting structure and function. Without the ability to sample on the meaningful large-scale conformational changes, the ability to infer biological function and to understand the effect of mutations and changes in environment is not possible. Our Dynamic Importance Sampling method (DIMS), part of the CHARMM simulation package, is a method that enables sampling over ensembles of transition intermediates. This chapter outlines the context for the method and the usage within the program.

Distinct phenotype of a Wilson disease mutation reveals a novel trafficking determinant in the copper transporter ATP7B.

Wilson disease (WD) is a monogenic autosomal-recessive disorder of copper accumulation that leads to liver failure and/or neurological deficits. WD is caused by mutations in ATP7B, a transporter that loads Cu(I) onto newly synthesized cupro-enzymes in the trans-Golgi network (TGN) and exports excess copper out of cells by trafficking from the TGN to the plasma membrane. To date, most WD mutations have been shown to disrupt ATP7B activity and/or stability. Using a multidisciplinary approach, including clinical analysis of patients, cell-based assays, and computational studies, we characterized a patient mutation, ATP7B(S653Y), which is stable, does not disrupt Cu(I) transport, yet renders the protein unable to exit the TGN. Bulky or charged substitutions at position 653 mimic the phenotype of the patient mutation. Molecular modeling and dynamic simulation suggest that the S653Y mutation induces local distortions within the transmembrane (TM) domain 1 and alter TM1 interaction with TM2. S653Y abolishes the trafficking-stimulating effects of a secondary mutation in the N-terminal apical targeting domain. This result indicates a role for TM1/TM2 in regulating conformations of cytosolic domains involved in ATP7B trafficking. Taken together, our experiments revealed an unexpected role for TM1/TM2 in copper-regulated trafficking of ATP7B and defined a unique class of WD mutants that are transport-competent but trafficking-defective. Understanding the precise consequences of WD-causing mutations will facilitate the development of advanced mutation-specific therapies.

Molecular dynamics simulations of transitions for ECD epidermal growth factor receptors show key differences between human and drosophila forms of the receptors.

Recent X-ray structural work on the Drosophila epidermal growth factor receptor (EFGR) has suggested an asymmetric dimer that rationalizes binding affinity measurements that go back decades (Alvarado et al., Cell 2010;142:568-579; Dawson et al., Structure 2007;15:942-954; Lemmon et al., Embo J 1997;16:281-294; Mattoon et al., Proc Natl Acad Sci USA 2004;101:923-928; Mayawala et al., Febs Lett 2005;579:3043-3047; Ozcan et al., Proc Natl Acad Sci USA 2006;103:5735-5740). This type of asymmetric structure has not been seen for the human EGF receptor family and it may or may not be important for function in that realm. We hypothesize that conformational changes in the Drosophila system have been optimized for the transition, whereas the barrier for the same transition is much higher in the human forms. To address our hypothesis we perform dynamic importance sampling (DIMS) (Perilla et al., J Comput Chem 2010;32:196-209) for barrier crossing transitions in both Drosophila and human EFGRs. For each set of transitions, we work from the hypothesis, based on results from the AdK system, that salt-bridge pairs making and breaking connections are central to the conformational change. To evaluate the effectiveness of the salt-bridges as drivers for the conformational change, we use the effective transfer entropy based on stable state MD calculations (Kamberaj and Der Vaart, Biophys J 2009;97:1747-1755) to define a reduced subset of degrees of freedom that seem to be important for driving the transition (Perilla and Woolf, J Chem Phys 2012;136:164101). Our results suggest that salt-bridge making and breaking is not the dominant factor in driving the symmetric to asymmetric transition, but that instead it is a result of more concerted and correlated functional motions within a subset of the dimer structures. Furthermore, the analysis suggests that the set of residues involved in the transitions from the Drosophila relative to the human forms differs and that this difference in substate distributions relates to why the asymmetric form may be more common to Drosophila than to the human forms. We close with a discussion about the residues that may be changed in the human and the Drosophila forms to potentially shift the kinetics of the symmetric to asymmetric transition.

Coarse-grained simulations of transitions in the E2-to-E1 conformations for Ca ATPase (SERCA) show entropy-enthalpy compensation.

SERCA is a membrane transport protein that has been extensively studied. There are a large number of highly resolved X-ray structures and several hundred mutations that have been characterized functionally. Despite this, the molecular details of the catalytic cycle, a cycle that includes large conformational changes, is not fully understood. In this computational study, we provide molecular dynamics descriptions of conformational changes during the E2→E1 transitions. The motivating point for these calculations was a series of insertion mutants in the A-M3 linker region that led to significant shifts in measured rates between the E2 and E1 states, as shown by experimental characterization. Using coarse-grained dynamic importance sampling within the context of a population shift framework, we sample on the intermediates along the transition pathway to address the mechanism for the conformational changes and the effects of the insertion mutations on the kinetics of the transition. The calculations define an approximation for the relative changes in entropy and enthalpy along the transition. These are found to be important for understanding the experimentally observed differences in rates. In particular, the interactions between cytoplasmic domains, water interactions, and the shifts in protein degrees of freedom with the insertion mutations show mutual compensation for the E2→E1 transitions in wild-type and mutant systems.

Multiscale modeling of double-helical DNA and RNA: a unification through Lie groups.

Several different mechanical models of double-helical nucleic-acid structures that have been presented in the literature are reviewed here together with a new analysis method that provides a reconciliation between these disparate models. In all cases, terminology and basic results from the theory of Lie groups are used to describe rigid-body motions in a coordinate-free way, and when necessary, coordinates are introduced in a way in which simple equations result. We consider double-helical DNAs and RNAs which, in their unstressed referential state, have backbones that are either straight, slightly precurved, or bent by the action of a protein or other bound molecule. At the coarsest level, we consider worm-like chains with anisotropic bending stiffness. Then, we show how bi-rod models converge to this for sufficiently long filament lengths. At a finer level, we examine elastic networks of rigid bases and show how these relate to the coarser models. Finally, we show how results from molecular dynamics simulation at full atomic resolution (which is the finest scale considered here) and AFM experimental measurements (which is at the coarsest scale) relate to these models.

Towards the prediction of order parameters from molecular dynamics simulations in proteins.

A molecular understanding of how protein function is related to protein structure requires an ability to understand large conformational changes between multiple states. Unfortunately these states are often separated by high free energy barriers and within a complex energy landscape. This makes it very difficult to reliably connect, for example by all-atom molecular dynamics calculations, the states, their energies, and the pathways between them. A major issue needed to improve sampling on the intermediate states is an order parameter--a reduced descriptor for the major subset of degrees of freedom--that can be used to aid sampling for the large conformational change. We present a method to combine information from molecular dynamics using non-linear time series and dimensionality reduction, in order to quantitatively determine an order parameter connecting two large-scale conformationally distinct protein states. This new method suggests an implementation for molecular dynamics calculations that may be used to enhance sampling of intermediate states.

The role of domain: domain interactions versus domain: water interactions in the coarse-grained simulations of the E1P to E2P transitions in Ca-ATPase (SERCA).

SERCA is an important model system for understanding the molecular details of conformational change in membrane transport systems. This reflects the large number of solved X-ray structures and the equally large database of mutations that have been assayed. In this computational study, we provide a molecular dynamics description of the conformational changes during the E1P → E2P transitions. This set of states further changes with insertion mutants in the A-M3 linker region. These mutants were experimentally shown to lead to significant shifts in rates between the E1P → E2P states. Using the population shift framework and dynamic importance sampling method along with coarse-grained representations of the protein, lipid, and water, we suggest why these changes are found. The calculations sample on intermediates and suggest that changes in interactions, individual helix interactions, and water behavior are key elements in the molecular compositions that underlie shifts in kinetics. In particular, as the insertion length grows, it attracts more water and disrupts domain interactions, creating changes as well at the sites of key helix interactions between the A-Domain and the P-Domain. This provides a conceptual picture that aids understanding of the experimental results.

MDAnalysis: a toolkit for the analysis of molecular dynamics simulations.

MDAnalysis is an object-oriented library for structural and temporal analysis of molecular dynamics (MD) simulation trajectories and individual protein structures. It is written in the Python language with some performance-critical code in C. It uses the powerful NumPy package to expose trajectory data as fast and efficient NumPy arrays. It has been tested on systems of millions of particles. Many common file formats of simulation packages including CHARMM, Gromacs, Amber, and NAMD and the Protein Data Bank format can be read and written. Atoms can be selected with a syntax similar to CHARMM's powerful selection commands. MDAnalysis enables both novice and experienced programmers to rapidly write their own analytical tools and access data stored in trajectories in an easily accessible manner that facilitates interactive explorative analysis. MDAnalysis has been tested on and works for most Unix-based platforms such as Linux and Mac OS X. It is freely available under the GNU General Public License from http://mdanalysis.googlecode.com.

Festschrift in the honor of Stephen H. White's 70th Birthday.

The Symposium 'Frontiers in membrane and membrane protein biophysics: experiments and theory', held this year at the University of California, Irvine (August 19-20), celebrated the 70th Birthday of Stephen H. White by bringing together distinguished experimentalists and theoreticians to discuss the state of the art and future challenges in the field of membrane and membrane protein biophysics. The meeting and this special issue highlight the highly interdisciplinary nature of membrane and membrane protein biophysics, and the tremendous contributions that S. H. White and his lab have brought to the field.