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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.
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.
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.
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.
DSM-5 includes two conceptualizations of personality disorders (PDs). The classification in Section II is identical to the one found in DSM-IV, and includes 10 categorical PDs. The Alternative Model (Section III) includes criteria for dimensional measures of maladaptive personality traits organized into five domains. The degree to which the two conceptualizations reflect the same etiological factors is not known.
We use data from a large population-based sample of adult twins from the Norwegian Institute of Public Health Twin Panel on interview-based DSM-IV PDs and a short self-report inventory that indexes the five domains of the DSM-5 Alternative Model plus a domain explicitly targeting compulsivity. Schizotypal, Paranoid, Antisocial, Borderline, Avoidant, and Obsessive-compulsive PDs were assessed at the same time as the maladaptive personality traits and 10 years previously. Schizoid, Histrionic, Narcissistic, and Dependent PDs were only assessed at the first interview. Biometric models were used to estimate overlap in genetic and environmental risk factors.
When measured concurrently, there was 100% genetic overlap between the maladaptive trait domains and Paranoid, Schizotypal, Antisocial, Borderline, and Avoidant PDs. For OCPD, 43% of the genetic variance was shared with the domains. Genetic correlations between the individual domains and PDs ranged from +0.21 to +0.91.
The pathological personality trait domains, which are part of the Alternative Model for classification of PDs in DSM-5 Section III, appears to tap, at an aggregate level, the same genetic risk factors as the DSM-5 Section II classification for most of the PDs.
Sequence-based association studies are at a critical inflexion point with the increasing availability of exome-sequencing data. A popular test of association is the sequence kernel association test (SKAT). Weights are embedded within SKAT to reflect the hypothesized contribution of the variants to the trait variance. Because the true weights are generally unknown, and so are subject to misspecification, we examined the efficiency of a data-driven weighting scheme. We propose the use of a set of theoretically defensible weighting schemes, of which, we assume, the one that gives the largest test statistic is likely to capture best the allele frequency–functional effect relationship. We show that the use of alternative weights obviates the need to impose arbitrary frequency thresholds. As both the score test and the likelihood ratio test (LRT) may be used in this context, and may differ in power, we characterize the behavior of both tests. The two tests have equal power, if the weights in the set included weights resembling the correct ones. However, if the weights are badly specified, the LRT shows superior power (due to its robustness to misspecification). With this data-driven weighting procedure the LRT detected significant signal in genes located in regions already confirmed as associated with schizophrenia — the PRRC2A (p = 1.020e-06) and the VARS2 (p = 2.383e-06) — in the Swedish schizophrenia case-control cohort of 11,040 individuals with exome-sequencing data. The score test is currently preferred for its computational efficiency and power. Indeed, assuming correct specification, in some circumstances, the score test is the most powerful test. However, LRT has the advantageous properties of being generally more robust and more powerful under weight misspecification. This is an important result given that, arguably, misspecified models are likely to be the rule rather than the exception in weighting-based approaches.
Government transparency is widely promoted, yet little is known about transparency’s effects. Survey experiments reported here, made on the streets of Lima, Peru, investigate a simple question: what are the effects of government-sponsored transparency websites, and the information revealed by those efforts, on attitudes about the Peruvian political system? Like many developing countries, Peru lacks much system support, making it more difficult to improve governance and democracy; transparency itself has little impact on political attitudes. However, some dimensions of the information provided by transparency matter: endorsement by a credible third party or framing that associates comparatively good community well-being with government performance. These conditions substantively increase Peruvians’ approval of the national political community, the regime’s performance, institutions, and local government.
To compare two front-of-pack nutrition labelling systems for the assessment of packaged foods and drinks with Australian Dietary Guidelines.
A cross-sectional nutrient profiling assessment. Food and drink products (n 20 225) were categorised into scoring levels using criteria for the Institute of Medicine (IOM) three-star system and the five-star Australian Health Star Rating (HSR). The effectiveness of these systems to categorise foods in accordance with Australian Dietary Guidelines was explored.
The study was conducted in Australia, using a comprehensive food database.
Packaged food and drink products (n 20 225) available in Australia.
Using the IOM three-star system, the majority (55 %) of products scored the minimum 0 points and 25·5 % scored the maximum 3 points. Using HSR criteria, the greatest proportion of products (15·2 %) scored three-and-a-half stars from a possible five and 12·5 % received the lowest rating of a half-star. Very few products (4·1 %) scored five stars. Products considered core foods and drinks in Australian Dietary Guidelines received higher scores than discretionary foods in all food categories for both labelling systems (all P<0·05; Mann–Whitney U test), with the exception of fish products using IOM three-star criteria (P=0·603). The largest discrepancies in median score between the two systems were for the food categories edible oils, convenience foods and dairy.
Both the IOM three-star and Australian HSR front-of-pack labelling systems rated packaged foods and drinks broadly in line with Australian Dietary Guidelines by assigning core foods higher ratings and discretionary foods lower ratings.
Observational studies have suggested that 25-hydroxyvitamin D (25(OH)D) levels are associated with inflammatory markers. Most trials reporting significant associations between vitamin D intake and inflammatory markers used specific patient groups. Thus, we aimed to determine the effect of supplementary vitamin D using secondary data from a population-based, randomised, placebo-controlled, double-blind trial (Pilot D-Health trial 2010/0423). Participants were 60- to 84-year-old residents of one of the four eastern states of Australia. They were randomly selected from the electoral roll and were randomised to one of three trial arms: placebo (n 214), 750 μg (n 215) or 1500 μg (n 215) vitamin D3, each taken once per month for 12 months. Post-intervention blood samples for the analysis of C-reactive protein (CRP), IL-6, IL-10, leptin and adiponectin levels were available for 613 participants. Associations between intervention group and biomarker levels were evaluated using quantile regression. There were no statistically significant differences in distributions of CRP, leptin, adiponectin, leptin:adiponectin ratio or IL-10 levels between the placebo group and either supplemented group. The 75th percentile IL-6 level was 2·8 pg/ml higher (95 % CI 0·4, 5·8 pg/ml) in the 1500 μg group than in the placebo group (75th percentiles:11·0 v. 8·2 pg/ml), with a somewhat smaller, non-significant difference in 75th percentiles between the 750 μg and placebo groups. Despite large differences in serum 25(OH)D levels between the three groups after 12 months of supplementation, we found little evidence of an effect of vitamin D supplementation on cytokine or adipokine levels, with the possible exception of IL-6.
Previous studies have shown significant within-person changes in binge eating and emotional eating across the menstrual cycle, with substantial increases in both phenotypes during post-ovulation. Increases in both estradiol and progesterone levels appear to account for these changes in phenotypic risk, possibly via increases in genetic effects. However, to date, no study has examined changes in genetic risk for binge phenotypes (or any other phenotype) across the menstrual cycle. The goal of the present study was to examine within-person changes in genetic risk for emotional eating scores across the menstrual cycle.
Participants were 230 female twin pairs (460 twins) from the Michigan State University Twin Registry who completed daily measures of emotional eating for 45 consecutive days. Menstrual cycle phase was coded based on dates of menstrual bleeding and daily ovarian hormone levels.
Findings revealed important shifts in genetic and environmental influences, where estimates of genetic influences were two times higher in post- as compared with pre-ovulation. Surprisingly, pre-ovulation was marked by a predominance of environmental influences, including shared environmental effects which have not been previously detected for binge eating phenotypes in adulthood.
Our study was the first to examine within-person shifts in genetic and environmental influences on a behavioral phenotype across the menstrual cycle. Results highlight a potentially critical role for these shifts in risk for emotional eating across the menstrual cycle and underscore the need for additional, large-scale studies to identify the genetic and environmental factors contributing to menstrual cycle effects.
Antisocial personality disorder (ASPD) and borderline personality disorder (BPD) share genetic and environmental risk factors. Little is known about the temporal stability of these etiological factors in adulthood.
DSM-IV criteria for ASPD and BPD were assessed using structured interviews in 2282 Norwegian twins in early adulthood and again approximately 10 years later. Longitudinal biometric models were used to analyze the number of endorsed criteria.
The mean criterion count for ASPD and BPD decreased 40% and 28%, respectively, from early to middle adulthood. Rank-order stability was 0.58 for ASPD and 0.45 for BPD. The best-fitting longitudinal twin model included only genetic and individual-specific environmental factors. Genetic effects, both those shared by ASPD and BPD, and those specific to each disorder remained completely stable. The unique environmental effects, however, changed substantially, with a correlation across time of 0.19 for the shared effects, and 0.39 and 0.15, respectively, for those specific to ASPD and BPD. Genetic effects accounted for 71% and 72% of the stability over time for ASPD and BPD, respectively. The genetic and environmental correlations between ASPD and BPD were 0.73, and 0.43, respectively, at both time points.
ASPD and BPD traits were moderately stable from early to middle adulthood, mostly due to genetic risk factors which did not change over the 10-year assessment period. Environmental risk factors were mostly transient, and appear to be the main source of phenotypic change. Genetic liability factors were, to a large extent, shared by ASPD and BPD.
Mixed anxiety–depression (MAD) has been under scrutiny to determine its potential place in psychiatric nosology. The current study sought to investigate its prevalence, clinical characteristics, course and potential validators.
Restricted latent-class analyses were fit to 12-month self-reports of depression and anxiety symptom criteria in a large population-based sample of twins. Classes were examined across an array of relevant indicators (demographics, co-morbidity, adverse life events, clinical significance and twin concordance). Longitudinal analyses investigated the stability of, and transitions between, these classes for two time periods approximately 1.5 years apart.
In all analyses, a class exhibiting levels of MAD symptomatology distinctly above the unaffected subjects yet having low prevalence of either major depression (MD) or generalized anxiety disorder (GAD) was identified. A restricted four-class model, constraining two classes to have no prior disorder history to distinguish residual or recurrent symptoms from new onsets in the last year, provided an interpretable classification: two groups with no prior history that were unaffected or had MAD and two with prior history having relatively low or high symptom levels. Prevalence of MAD was substantial (9–11%), and subjects with MAD differed quantitatively but not qualitatively from those with lifetime MD or GAD across the clinical validators examined.
Our findings suggest that MAD is a commonly occurring, identifiable syndromal subtype that warrants further study and consideration for inclusion in future nosologic systems.
While cluster A personality disorders (PDs) have been shown to be moderately heritable, we know little about the temporal stability of these genetic risk factors.
Paranoid PD (PPD) and schizotypal PD (STPD) were assessed using the Structured Interview for DSM-IV Personality in 2793 young adult twins from the Norwegian Institute of Public Health Twin Panel at wave 1 and 2282 twins on average 10 years later at wave 2. Using the program Mx, we fitted a longitudinal latent factor model using the number of endorsed criteria for PPD and STPD.
The stability over time of the criteria counts for PPD and STPD, estimated as polychoric correlations, were +0.34 and +0.40, respectively. The best-fit longitudinal model included only additive genetic and individual-specific environmental factors with parameter estimates constrained to equality across the two waves. The cross-wave genetic and individual-specific environmental correlations for a latent cluster A factor were estimated to equal +1.00 and +0.13, respectively. The cross-time correlations for genetic and environmental effects specific to the individual PDs were estimated at +1.00 and +0.16–0.20, respectively. We found that 68% and 71% of the temporal stability of PPD and STPD derived, respectively, from the effect of genetic factors.
Shared genetic risk factors for two of the cluster A PDs are highly stable in adults over a 10-year period while environmental risk factors are relatively transient. Over two-thirds of the long-term stability of the common cluster A PD liability can be attributed to genetic influences.
To clarify the role of genetic and environmental risk factors in alcohol use disorders (AUDs), we performed a meta-analysis of twin and adoption studies and explored the impact of sex, assessment method (interview v. hospital/population records), and study design (twin v. adoption study) on heritability estimates.
The literature was searched for all unique twin and adoption studies of AUD and identified 12 twin and five adoption studies. The data were then reconstructed and analyzed using ordinal data full information maximum likelihood in the OpenMx program. Heterogeneity was tested with likelihood ratio tests by equating the parameters across studies.
There was no evidence for heterogeneity by study design, sex or assessment method. The best-fit estimate of the heritability of AUD was 0.49 [95% confidence interval (CI) 0.43–0.53], and the proportion of shared environmental variance was 0.10 (95% CI 0.03–0.16). Estimates of unique environmental proportions of variance differed significantly across studies.
AUD is approximately 50% heritable. The multiple genetically informative studies of this syndrome have produced consistent results that support the validity of this heritability estimate, especially given the different potential methodological weaknesses of twin and adoption designs, and of assessments of AUD based on personal interviews v. official records. We also found evidence for modest shared environmental effects suggesting that environmental factors also contribute to the familial aggregation of AUDs.
With the dramatic technological developments of genome-wide association single-nucleotide polymorphism (SNP) chips and next generation sequencing, human geneticists now have the ability to assay genetic variation at ever-rarer allele frequencies. To fully understand the impact of these rare variants on common, complex diseases, we must be able to accurately assess their statistical significance. However, it is well established that classical association tests are not appropriate for the analysis of low-frequency variation, giving spurious findings when observed counts are too few. To further our understanding of the asymptotic properties of traditional association tests, we conducted a range of simulations of a typical rare variant (~1%) under the null hypothesis and tested the allelic χ2, Cochran–Armitage trend, Wald, and Fisher's exact tests. We demonstrate that rare variation shows marked deviation from the expected distributional behavior for each test, with fewer minor alleles corresponding to a greater degree of test statistics deflation. The effect becomes more pronounced at progressively smaller α levels. We also show that the Wald test is particularly deflated at α levels consistent with genome-wide association significance, much more so than the other association tests considered. In general, these classical association tests are inappropriate for the analysis of variants for which the minor allele is observed fewer than 80 times, largely irrespective of sample size.