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Observational studies suggest that 25-hydroxy vitamin D (25(OH)D) concentration is inversely associated with pain. However, findings from intervention trials are inconsistent. We assessed the effect of vitamin D supplementation on pain using data from a large, double-blind, population-based, placebo-controlled trial (the D-Health Trial). 21 315 participants (aged 60–84 years) were randomly assigned to a monthly dose of 60 000 IU vitamin D3 or matching placebo. Pain was measured using the six-item Pain Impact Questionnaire (PIQ-6), administered 1, 2 and 5 years after enrolment. We used regression models (linear for continuous PIQ-6 score and log-binomial for binary categorisations of the score, namely ‘some or more pain impact’ and ‘presence of any bodily pain’) to estimate the effect of vitamin D on pain. We included 20 423 participants who completed ≥1 PIQ-6. In blood samples collected from 3943 randomly selected participants (∼800 per year), the mean (sd) 25(OH)D concentrations were 77 (sd 25) and 115 (sd 30) nmol/l in the placebo and vitamin D groups, respectively. Most (76 %) participants were predicted to have 25(OH)D concentration >50 nmol/l at baseline. The mean PIQ-6 was similar in all surveys (∼50·4). The adjusted mean difference in PIQ-6 score (vitamin D cf placebo) was 0·02 (95 % CI (−0·20, 0·25)). The proportion of participants with some or more pain impact and with the presence of bodily pain was also similar between groups (both prevalence ratios 1·01, 95 % CI (0·99, 1·03)). In conclusion, supplementation with 60 000 IU of vitamin D3/month had negligible effect on bodily pain.
To determine associations of alcohol use with cognitive aging among middle-aged men.
1,608 male twins (mean 57 years at baseline) participated in up to three visits over 12 years, from 2003–2007 to 2016–2019. Participants were classified into six groups based on current and past self-reported alcohol use: lifetime abstainers, former drinkers, very light (1–4 drinks in past 14 days), light (5–14 drinks), moderate (15–28 drinks), and at-risk drinkers (>28 drinks in past 14 days). Linear mixed-effects regressions modeled cognitive trajectories by alcohol group, with time-based models evaluating rate of decline as a function of baseline alcohol use, and age-based models evaluating age-related differences in performance by current alcohol use. Analyses used standardized cognitive domain factor scores and adjusted for sociodemographic and health-related factors.
Performance decreased over time in all domains. Relative to very light drinkers, former drinkers showed worse verbal fluency performance, by –0.21 SD (95% CI –0.35, –0.07), and at-risk drinkers showed faster working memory decline, by 0.14 SD (95% CI 0.02, –0.20) per decade. There was no evidence of protective associations of light/moderate drinking on rate of decline. In age-based models, light drinkers displayed better memory performance at advanced ages than very light drinkers (+0.14 SD; 95% CI 0.02, 0.20 per 10-years older age); likely attributable to residual confounding or reverse association.
Alcohol consumption showed minimal associations with cognitive aging among middle-aged men. Stronger associations of alcohol with cognitive aging may become apparent at older ages, when cognitive abilities decline more rapidly.
Alzheimer’s disease (AD) is highly heritable, and AD polygenic risk scores (AD-PRSs) have been derived from genome-wide association studies. However, the nature of genetic influences very early in the disease process is still not well known. Here we tested the hypothesis that an AD-PRSs would be associated with changes in episodic memory and executive function across late midlife in men who were cognitively unimpaired at their baseline midlife assessment..
We examined 1168 men in the Vietnam Era Twin Study of Aging (VETSA) who were cognitively normal (CN) at their first of up to three assessments across 12 years (mean ages 56, 62, and 68). Latent growth models of episodic memory and executive function were based on 6–7 tests/subtests. AD-PRSs were based on Kunkle et al. (Nature Genetics, 51, 414–430, 2019), p < 5×10−8 threshold.
AD-PRSs were correlated with linear slopes of change for both cognitive abilities. Men with higher AD-PRSs had steeper declines in both memory (r = −.19, 95% CI [−.35, −.03]) and executive functioning (r = −.27, 95% CI [−.49, −.05]). Associations appeared driven by a combination of APOE and non-APOE genetic influences.
Memory is most characteristically impaired in AD, but executive functions are one of the first cognitive abilities to decline in midlife in normal aging. This study is among the first to demonstrate that this early decline also relates to AD genetic influences, even in men CN at baseline.
The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.
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.
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.
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.
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.
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.
We introduce the optimizer CSOLNP, which is a C++ implementation of the R package RSOLNP (Ghalanos & Theussl, 2012, Rsolnp: General non-linear optimization using augmented Lagrange multiplier method. R package version, 1) alongside some improvements. CSOLNP solves non-linearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. CSOLNP, NPSOL (a very popular implementation of SQP method in FORTRAN (Gill et al., 1986, User's guide for NPSOL (version 4.0): A Fortran package for nonlinear programming (No. SOL-86-2). Stanford, CA: Stanford University Systems Optimization Laboratory), and SLSQP (another SQP implementation available as part of the NLOPT collection (Johnson, 2014, The NLopt nonlinear-optimization package. Retrieved from http://ab-initio.mit.edu/nlopt)) are three optimizers available in OpenMx package. These optimizers are compared in terms of runtimes, final objective values, and memory consumption. A Monte Carlo analysis of the performance of the optimizers was performed on ordinal and continuous models with five variables and one or two factors. While the relative difference between the objective values is less than 0.5%, CSOLNP is in general faster than NPSOL and SLSQP for ordinal analysis. As for continuous data, none of the optimizers performs consistently faster than the others. In terms of memory usage, we used Valgrind's heap profiler tool, called Massif, on one-factor threshold models. CSOLNP and NPSOL consume the same amount of memory, while SLSQP uses 71 MB more memory than the other two optimizers.
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.
Our aim was to test the direction of causation between self-report parental monitoring (PM) and the liability to illicit drug initiation (DI) as indicated by cannabis, cocaine, and stimulants. We fitted a multiple indicator model to test causal and non-causal models based on a large, genetically informative cross-sectional sample of male twins. The sample comprised 1,778 males aged 24–62 years from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. Data came from self-report measures of lifetime cannabis, stimulants, and cocaine initiation, and retrospective assessment of PM between ages 8–17 years. Multivariate modeling showed that familial aggregation in PM and DI were both explained by a combination of additive genetic and shared environmental effects. Moreover, the significant association between PM and DI was best explained by a correlated liability model versus causal models. PM has typically been assumed to be an environmental, causal risk factor for drug use and has been shown to be among the more salient environmental risk factors for illicit DI. Our data were not consistent with this causal hypothesis. Instead, a correlated liability model in which PM and risk of DI share common genetic and environmental risks provided a better fit to the data.
Excessive internet use has been linked to psychopathology. Therefore, understanding the genetic and environmental risks underpinning internet use and their relation to psychopathology is important. This study aims to explore the genetic and environmental etiology of internet use measures and their associations with internalizing disorders and substance use disorders. The sample included 2,059 monozygotic (MZ) and dizygotic (DZ) young adult twins from the Brisbane Longitudinal Twin Study (BLTS). Younger participants reported more frequent internet use, while women were more likely to use the internet for interpersonal communication. Familial aggregation in ‘frequency of internet use’ was entirely explained by additive genetic factors accounting for 41% of the variance. Familial aggregation in ‘frequency of use after 11 pm’, ‘using the internet to contact peers’, and ‘using the internet primarily to access social networking sites’ was attributable to varying combinations of additive genetic and shared environmental factors. In terms of psychopathology, there were no significant associations between internet use measures and major depression (MD), but there were positive significant associations between ‘frequency of internet use’ and ‘frequency of use after 11 pm’ with social phobia (SP). ‘Using the internet to contact peers’ was positively associated with alcohol abuse, whereas ‘using the internet to contact peers’ and ‘using the internet primarily to access social networking sites’ were negatively associated with cannabis use disorders and nicotine symptoms. Individual differences in internet use can be attributable to varying degrees of genetic and environmental risks. Despite some significant associations of small effect, variation in internet use appears mostly unrelated to psychopathology.
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.