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Clarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems.
The study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse (‘baseline’) and the longitudinal Vietnam Era Twin Study of Aging (‘follow-up’). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)].
Total depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07–1.57), erectile dysfunction (OR 1.32, 95% CI 1.10–1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04–1.53), and sleep apnea (OR 1.40, 95% CI 1.13–1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09–1.60).
A history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.
Conventional longitudinal behavioral genetic models estimate the relative contribution of genetic and environmental factors to stability and change of traits and behaviors. Longitudinal models rarely explain the processes that generate observed differences between genetically and socially related individuals. We propose that exchanges between individuals and their environments (i.e., phenotype–environment effects) can explain the emergence of observed differences over time. Phenotype–environment models, however, would require violation of the independence assumption of standard behavioral genetic models; that is, uncorrelated genetic and environmental factors. We review how specification of phenotype–environment effects contributes to understanding observed changes in genetic variability over time and longitudinal correlations among nonshared environmental factors. We then provide an example using 30 days of positive and negative affect scores from an all-female sample of twins. Results demonstrate that the phenotype–environment effects explain how heritability estimates fluctuate as well as how nonshared environmental factors persist over time. We discuss possible mechanisms underlying change in gene–environment correlation over time, the advantages and challenges of including gene–environment correlation in longitudinal twin models, and recommendations for future research.
Despite being identified as a pervasive emotion in the modern workplace (Pfeffer & Sutton, 2000), fear oddly has not received a corresponding amount of attention among management researchers. In fact, Kish-Gephart, Detert, Treviño, and Edmondson (2009, p. 163) observe that we still have much to learn about the nature of fear in workplace settings, including “what it is, how and why it is experienced, and to what effects.” Bennis (1966) notes further that fear has always been a part of the work environment (see also Connelly & Turner, 2018), but it remains an especially important issue in today’s workplaces because of the effects of rapid and ongoing organizational change, which are often linked to uncertain outcomes (Bordia, Hobman, Jones, Gallois, & Callan, 2004; Tiedens & Linton, 2001). Our aim in this chapter is to provide an overview of fear (arising from uncertainty) as a discrete emotion, to identify stimuli that may trigger fear at work, and to identify the potential positive and negative outcomes that can be linked to employees’ fear. We also outline potential pathways for future research on fear of uncertainty in the workplace.
Weed management is an important issue for nursery crop and Christmas tree producers, as well as for those maintaining turfgrass or ornamental species in landscape plantings. PRE and POST herbicides are important weed management tools for these industries. Reports of herbicide-resistant weeds increased from fewer than 100 cases in 1985 to nearly 500 cases globally in 2019, including ones found in turfgrass or ornamental systems. The evolution, persistence, and management of herbicide-resistant weeds are an ongoing educational process. We must keep our stakeholders aware of improved weed control technology and provide them information on resistant weeds. A symposium at the 2019 Weed Science Society of America meeting was conducted with presentations and discussions by invited speakers in relation to current research and potential management strategies for resistant weeds in turfgrass, landscape ornamental, and nursery crops. To prepare for the symposium, a survey was prepared for nursery producers and landscapers on the issues of herbicide-resistant weeds and offsite movement of herbicides used to control herbicide-resistant weeds. Overall, most respondents felt herbicide-resistant weeds are a serious problem and most had personally observed herbicide resistance on properties they maintain. Resistance to glyphosate was the herbicide cited by most respondents, followed by resistance to triazine herbicides. Most felt their weed-control costs had increased because of resistant weeds. Approximately 20% of respondents had their operation affected by drift of herbicides from nearby farm fields, with most reporting no damage from spray or vapor drift, but a few reported greater than 50% of the crop damaged.
Type 2 diabetes mellitus is a chronic disease increasing in global prevalence. Although habitual consumption of walnuts is associated with reduced risk of CVD, there is inconsistent evidence for the impact of walnut consumption on markers of glycaemic control. This systematic review and meta-analysis aimed to examine the effect of walnut consumption on markers of blood glucose control. A systematic search of Medline, PubMed, CINAHL and Cochrane databases (to 2 March 2019) was conducted. Inclusion criteria were randomised controlled trials conducted with adults which assessed the effect of walnut consumption on fasting blood glucose and insulin, glycated Hb and homeostatic model assessment of insulin resistance. Random effects meta-analyses were conducted to assess the weighted mean differences (WMD) for each outcome. Risk of bias in studies was assessed using the Cochrane Risk of Bias tool 2.0. Sixteen studies providing eighteen effect sizes were included in the review. Consumption of walnuts did not result in significant changes in fasting blood glucose levels (WMD: 0·331 mg/dl; 95 % CI −0·817, 1·479) or other outcome measures. Studies were determined to have either ‘some concerns’ or be at ‘high risk’ of bias. There was no evidence of an effect of walnut consumption on markers of blood glucose control. These findings suggest that the known favourable effects of walnut intake on CVD are not mediated via improvements in glycaemic control. Given the high risk of bias observed in the current evidence base, there is a need for further high-quality randomised controlled trials.
The volume of evidence from scientific research and wider observation is greater than ever before, but much is inconsistent and scattered in fragments over increasingly diverse sources, making it hard for decision-makers to find, access and interpret all the relevant information on a particular topic, resolve seemingly contradictory results or simply identify where there is a lack of evidence. Evidence synthesis is the process of searching for and summarising a body of research on a specific topic in order to inform decisions, but is often poorly conducted and susceptible to bias. In response to these problems, more rigorous methodologies have been developed and subsequently made available to the conservation and environmental management community by the Collaboration for Environmental Evidence. We explain when and why these methods are appropriate, and how evidence can be synthesised, shared, used as a public good and benefit wider society. We discuss new developments with potential to address barriers to evidence synthesis and communication and how these practices might be mainstreamed in the process of decision-making in conservation.
Dr Nick Martin has made enormous contributions to the field of behavior genetics over the past 50 years. Of his many seminal papers that have had a profound impact, we focus on his early work on the power of twin studies. He was among the first to recognize the importance of sample size calculation before conducting a study to ensure sufficient power to detect the effects of interest. The elegant approach he developed, based on the noncentral chi-squared distribution, has been adopted by subsequent researchers for other genetic study designs, and today remains a standard tool for power calculations in structural equation modeling and other areas of statistical analysis. The present brief article discusses the main aspects of his seminal paper, and how it led to subsequent developments, by him and others, as the field of behavior genetics evolved into the present era.
Nut consumption is associated with a range of health benefits. The current study aimed to examine nut consumption in the 2011–2012 National Nutrition and Physical Activity Survey (NNPAS) and to investigate associations between nut intake, nutrient intake and anthropometric and blood pressure measurements.
Secondary analysis of the 2011–2012 NNPAS. Usual consumption of nuts in the 2011–2012 NNPAS was determined, and nut consumption was compared with population recommendations of 30 g nuts per day. The relationship between nut consumption and intakes of key nutrients, anthropometric outcomes (weight, BMI and waist circumference) and blood pressure was examined using linear regression for participants aged over 18 years.
Australians (2 years and older, n 12 153) participating in the representative 2011–2012 NNPAS.
Mean nut intake was 4·61 (95 % CI: 4·36, 4·86) g/d, with only 5·6 % of nut consumers consuming 30 g of nuts per day. Nut consumption was associated with significantly greater intakes of fibre, vitamin E, Fe, Mg and P. There was no association between nut consumption and body weight, BMI, waist circumference, or blood pressure.
Exploration of nut consumption in a representative sample of Australians identified that nut intake does not meet recommendations. Higher nut consumption was not adversely associated with higher body weight, aligning with the current evidence base. Given the current levels of nut consumption in Australia, strategies to increase nut intake to recommended levels are required.
An improved understanding of diagnostic and treatment practices for patients with rare primary mitochondrial disorders can support benchmarking against guidelines and establish priorities for evaluative research. We aimed to describe physician care for patients with mitochondrial diseases in Canada, including variation in care.
We conducted a cross-sectional survey of Canadian physicians involved in the diagnosis and/or ongoing care of patients with mitochondrial diseases. We used snowball sampling to identify potentially eligible participants, who were contacted by mail up to five times and invited to complete a questionnaire by mail or internet. The questionnaire addressed: personal experience in providing care for mitochondrial disorders; diagnostic and treatment practices; challenges in accessing tests or treatments; and views regarding research priorities.
We received 58 survey responses (52% response rate). Most respondents (83%) reported spending 20% or less of their clinical practice time caring for patients with mitochondrial disorders. We identified important variation in diagnostic care, although assessments frequently reported as diagnostically helpful (e.g., brain magnetic resonance imaging, MRI/MR spectroscopy) were also recommended in published guidelines. Approximately half (49%) of participants would recommend “mitochondrial cocktails” for all or most patients, but we identified variation in responses regarding specific vitamins and cofactors. A majority of physicians recommended studies on the development of effective therapies as the top research priority.
While Canadian physicians’ views about diagnostic care and disease management are aligned with published recommendations, important variations in care reflect persistent areas of uncertainty and a need for empirical evidence to support and update standard protocols.
The aggregation of neurocognitive deficits among the non-psychotic first-degree relatives of adult- and childhood-onset schizophrenia patients suggests that there may be a common etiology for these deficits in childhood- and adult-onset illness. However, there is considerable heterogeneity in the presentation of neurobiological abnormalities, and whether there are differences in the extent of familial transmission for specific domains of cognitive function has not been systematically addressed.
We employed variance components analysis, as implemented in SOLAR-Eclipse, to evaluate the evidence of familial transmission for empirically derived composite scores representing attention, working memory, verbal learning, verbal retention, and memory for faces. We contrast estimates for adult- and childhood-onset schizophrenia families and matched community control pedigrees, and compare our findings to previous reports based on analogous neurocognitive assessments.
We observed varying degrees of familial transmission; attention and working memory yielded comparable, significant estimates for adult-onset and community control pedigrees; verbal learning was significant for childhood-onset and community control pedigrees; and facial memory demonstrated significant familial transmission only for childhood-onset schizophrenia. Model-fitting analyses indicated significant differences in familiality between adult- and childhood-onset schizophrenia for attention, working memory, and verbal learning.
By comprehensively assessing a wide range of neurocognitive domains in adult- and childhood-onset schizophrenia families, we provide additional support for specific neurocognitive domains as schizophrenia endophenotypes. Whereas comparable estimates of familial transmission for certain dimensions of cognitive functioning support a shared etiology of adult- and childhood-onset neurocognitive function, observed differences may be taken as preliminary evidence of partially divergent multifactorial architectures.
Structural equation modeling (SEM) is an important research tool, both for path-based model specification (common in the social sciences) and also for matrix-based models (in heavy use in behavior genetics). We developed umx to give more immediate access, relatively concise syntax and helpful defaults for users in these two broad disciplines. umx supports development, modification and comparison of models, as well as both graphical and tabular outputs. The second major focus of umx, behavior genetic models, is supported via functions implementing standard multigroup twin models. These functions support raw and covariance data, including joint ordinal data, and give solutions for ACE models, including support for covariates, common- and independent-pathway models, and gene × environment interaction models. A tutorial site and question forum are also available.
Vulnerability to depression can be measured in different ways. We here examine how genetic risk factors are inter-related for lifetime major depression (MD), self-report current depressive symptoms and the personality trait Neuroticism.
We obtained data from three population-based adult twin samples (Virginia n = 4672, Australia #1 n = 3598 and Australia #2 n = 1878) to which we fitted a common factor model where risk for ‘broadly defined depression’ was indexed by (i) lifetime MD assessed at personal interview, (ii) depressive symptoms, and (iii) neuroticism. We examined the proportion of genetic risk for MD deriving from the common factor v. specific to MD in each sample and then analyzed them jointly. Structural equation modeling was conducted in Mx.
The best fit models in all samples included additive genetic and unique environmental effects. The proportion of genetic effects unique to lifetime MD and not shared with the broad depression common factor in the three samples were estimated as 77, 61, and 65%, respectively. A cross-sample mega-analysis model fit well and estimated that 65% of the genetic risk for MD was unique.
A large proportion of genetic risk factors for lifetime MD was not, in the samples studied, captured by a common factor for broadly defined depression utilizing MD and self-report measures of current depressive symptoms and Neuroticism. The genetic substrate for MD may reflect neurobiological processes underlying the episodic nature of its cognitive, motor and neurovegetative manifestations, which are not well indexed by current depressive symptom and neuroticism.
Most studies underline the contribution of heritable factors for psychiatric disorders. However, heritability estimates depend on the population under study, diagnostic instruments, and study designs that each has its inherent assumptions, strengths, and biases. We aim to test the homogeneity in heritability estimates between two powerful, and state of the art study designs for eight psychiatric disorders.
We assessed heritability based on data of Swedish siblings (N = 4 408 646 full and maternal half-siblings), and based on summary data of eight samples with measured genotypes (N = 125 533 cases and 208 215 controls). All data were based on standard diagnostic criteria. Eight psychiatric disorders were studied: (1) alcohol dependence (AD), (2) anorexia nervosa, (3) attention deficit/hyperactivity disorder (ADHD), (4) autism spectrum disorder, (5) bipolar disorder, (6) major depressive disorder, (7) obsessive-compulsive disorder (OCD), and (8) schizophrenia.
Heritability estimates from sibling data varied from 0.30 for Major Depression to 0.80 for ADHD. The estimates based on the measured genotypes were lower, ranging from 0.10 for AD to 0.28 for OCD, but were significant, and correlated positively (0.19) with national sibling-based estimates. When removing OCD from the data the correlation increased to 0.50.
Given the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods. The findings also highlight large differences in genetic and environmental influences between psychiatric disorders, providing future directions for etiological psychiatric research.
Understanding food choices made for meals in overweight and obese individuals may aid strategies for weight loss tailored to their eating habits. However, limited studies have explored food choices at meal occasions. The aim of this study was to identify the usual food choices for meals of overweight and obese volunteers for a weight-loss trial. A cross-sectional analysis was performed using screening diet history data from a 12-month weight-loss trial (the HealthTrack study). A descriptive data mining tool, the Apriori algorithm of association rules, was applied to identify food choices at meal occasions using a nested hierarchical food group classification system. Overall, 432 breakfasts, 428 lunches, 432 dinners and 433 others (meals) were identified from the intake data (n 433 participants). A total of 142 items of closely related food clusters were identified at three food group levels. At the first sub-food group level, bread emerged as central to food combinations at lunch, but unprocessed meat appeared for this at dinner. The dinner meal was characterised by more varieties of vegetables and of foods in general. The definitions of food groups played a pivotal role in identifying food choice patterns at main meals. Given the large number of foods available, having an understanding of eating patterns in which key foods drive overall meal content can help translate and develop novel dietary strategies for weight loss at the individual level.
Background: Considerable evidence from twin and adoption studies indicates that genetic and shared environmental factors play a role in the initiation of smoking behavior. Although twin and adoption designs are powerful to detect genetic and environmental influences, they do not provide information on the processes of assortative mating and parent–offspring transmission and their contribution to the variability explained by genetic and/or environmental factors. Methods: We examined the role of genetic and environmental factors in individual differences for smoking initiation (SI) using an extended kinship design. This design allows the simultaneous testing of additive and non-additive genetic, shared and individual-specific environmental factors, as well as sex differences in the expression of genes and environment in the presence of assortative mating and combined genetic and cultural transmission, while also estimating the regression of the prevalence of SI on age. A dichotomous lifetime ‘ever’ smoking measure was obtained from twins and relatives in the ‘Virginia 30,000’ sample and the ‘Australian 25,000’. Results: Results demonstrate that both genetic and environmental factors play a significant role in the liability to SI. Major influences on individual differences appeared to be additive genetic and unique environmental effects, with smaller contributions from assortative mating, shared sibling environment, twin environment, cultural transmission, and resulting genotype-environment covariance. Age regression of the prevalence of SI was significant. The finding of negative cultural transmission without dominance led us to investigate more closely two possible mechanisms for the lower parent–offspring correlations compared to the sibling and DZ twin correlations in subsets of the data: (1) age × gene interaction, and (2) social homogamy. Neither of the mechanism provided a significantly better explanation of the data. Conclusions: This study showed significant heritability, partly due to assortment, and significant effects of primarily non-parental shared environment on liability to SI.
Drinking alcohol is a normal behavior in many societies, and prior studies have demonstrated it has both genetic and environmental sources of variation. Using two very large samples of twins and their first-degree relatives (Australia ≈ 20,000 individuals from 8,019 families; Virginia ≈ 23,000 from 6,042 families), we examine whether there are differences: (1) in the genetic and environmental factors that influence four interrelated drinking behaviors (quantity, frequency, age of initiation, and number of drinks in the last week), (2) between the twin-only design and the extended twin design, and (3) the Australian and Virginia samples. We find that while drinking behaviors are interrelated, there are substantial differences in the genetic and environmental architectures across phenotypes. Specifically, drinking quantity, frequency, and number of drinks in the past week have large broad genetic variance components, and smaller but significant environmental variance components, while age of onset is driven exclusively by environmental factors. Further, the twin-only design and the extended twin design come to similar conclusions regarding broad-sense heritability and environmental transmission, but the extended twin models provide a more nuanced perspective. Finally, we find a high level of similarity between the Australian and Virginian samples, especially for the genetic factors. The observed differences, when present, tend to be at the environmental level. Implications for the extended twin model and future directions are discussed.
Propagation of a strong incident shock through a bed of particles results in complex wave dynamics such as a reflected shock, a transmitted shock, and highly unsteady flow inside the particle bed. In this paper we present three-dimensional numerical simulations of shock propagation in air over a random bed of particles. We assume the flow is inviscid and governed by the Euler equations of gas dynamics. Simulations are carried out by varying the volume fraction of the particle bed at a fixed shock Mach number. We compute the unsteady inviscid streamwise and transverse drag coefficients as a function of time for each particle in the random bed for different volume fractions. We show that (i) there are significant variations in the peak drag for the particles in the bed, (ii) the mean peak drag as a function of streamwise distance through the bed decreases with a slope that increases as the volume fraction increases, and (iii) the deviation from the mean peak drag does not correlate with local volume fraction. We also present the local Mach number and pressure contours for the different volume fractions to explain the various observed complex physical mechanisms occurring during the shock–particle interactions. Since the shock interaction with the random bed of particles leads to transmitted and reflected waves, we compute the average flow properties to characterize the strength of the transmitted and reflected shock waves and quantify the energy dissipation inside the particle bed. Finally, to better understand the complex wave dynamics in a random bed, we consider a simpler approximation of a planar shock propagating in a duct with a sudden area change. We obtain Riemann solutions to this problem, which are used to compare with fully resolved numerical simulations.
Until now, data have not been available to elucidate the genetic and environmental sources of comorbidity between all 10 DSM-IV personality disorders (PDs) and cocaine use. Our aim was to determine which PD traits are linked phenotypically and genetically to cocaine use. Cross-sectional data were obtained in a face-to-face interview between 1999 and 2004. Subjects were 1,419 twins (µage = 28.2 years, range = 19–36) from the Norwegian Institute of Public Health Twin Panel, with complete lifetime cocaine use and criteria for all 10 DSM-IV PDs. Stepwise multiple and Least Absolute Shrinkage and Selection Operator (LASSO) regressions were used to identify PDs related to cocaine use. Twin models were fitted to estimate genetic and environmental associations between the PD traits and cocaine use. In the multiple regression, antisocial (OR = 4.24, 95% CI [2.66, 6.86]) and borderline (OR = 2.19, 95% CI [1.35, 3.57]) PD traits were significant predictors of cocaine use. In the LASSO regression, antisocial, borderline, and histrionic were significant predictors of cocaine use. Antisocial and borderline PD traits each explained 72% and 25% of the total genetic risks in cocaine use, respectively. Genetic risks in histrionic PD were not significantly related to cocaine use. Importantly, after removing criteria referencing substance use, antisocial PD explained 65% of the total genetic variance in cocaine use, whereas borderline explained only 4%. Among PD traits, antisocial is the strongest correlate of cocaine use, for which the association is driven largely by common genetic risks.