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Cultural effects can influence the results of causal genetic analyses, such as Mendelian randomisation, but the potential influences of culture on genotype–phenotype associations are not currently well understood. Different genetic variants could be associated with different phenotypes in different populations, or culture could confound or influence the direction of the association between genotypes and phenotypes in different populations.
This study sought to examine current national disaster risk management capacities, and identify governance barriers to strengthening national preparedness for responding to public health emergencies, associated with the anticipated climate-driven intensification of natural disaster cycles.
A mixed-methods online survey, assessing broader governance constraints to climate change adaptation (CCA) for public health, was distributed to representatives of national public health associations, and societies of 82 member countries under the World Federation of Public Health Associations. Specific questions relevant to disaster risk management capacities and barriers were analyzed as part of a narrowed focus on the CCA subdomain of emergency preparedness.
Existence of some technology, infrastructure, and/ or human resources, necessary to develop early warning and other surveillance systems for climate-related health risks was reported by 9 out of 11 responding countries. However, 7 reported persistent limitations and/ or regional discrepancies. Most significant identified barriers to strengthening emergency preparedness at the national level included governance coordination challenges, and, in the case of many developing countries, technical, medical, and human resource shortages.
The development of new frameworks for intersectoral governance and large-scale resource mobilization will prove crucial to ongoing efforts to strengthen national climate-health resiliency and prepare for disaster-associated health threats.
Observational studies have found associations between smoking and both poorer cognitive ability and lower educational attainment; however, evaluating causality is challenging. We used two complementary methods to explore this.
We conducted observational analyses of up to 12 004 participants in a cohort study (Study One) and Mendelian randomisation (MR) analyses using summary and cohort data (Study Two). Outcome measures were cognitive ability at age 15 and educational attainment at age 16 (Study One), and educational attainment and fluid intelligence (Study Two).
Study One: heaviness of smoking at age 15 was associated with lower cognitive ability at age 15 and lower educational attainment at age 16. Adjustment for potential confounders partially attenuated findings (e.g. fully adjusted cognitive ability β −0.736, 95% CI −1.238 to −0.233, p = 0.004; fully adjusted educational attainment β −1.254, 95% CI −1.597 to −0.911, p < 0.001). Study Two: MR indicated that both smoking initiation and lifetime smoking predict lower educational attainment (e.g. smoking initiation to educational attainment inverse-variance weighted MR β −0.197, 95% CI −0.223 to −0.171, p = 1.78 × 10−49). Educational attainment results were robust to sensitivity analyses, while analyses of general cognitive ability were less so.
We find some evidence of a causal effect of smoking on lower educational attainment, but not cognitive ability. Triangulation of evidence across observational and MR methods is a strength, but the genetic variants associated with smoking initiation may be pleiotropic, suggesting caution in interpreting these results. The nature of this pleiotropy warrants further study.
Despite the early promise of behavioral genetic research, efforts to disentangle the genetic contribution to individual differences in behavior (e.g., personality traits) have been slow. Early studies relied on a candidate gene approach to identify genes influencing these traits; however, many of these failed to replicate, despite having a plausible biological mechanism. More recent studies have used whole genome approaches to investigate the genetic architecture of behavioral traits. However, unlike many other complex traits such as height (Marouli et al., 2017; Wood et al., 2014) and schizophrenia (Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014), relatively few genetic variants have been identified which are robustly associated with temperament and individual differences in personality.
It is not clear to what extent associations between schizophrenia, cannabis use and cigarette use are due to a shared genetic etiology. We, therefore, examined whether schizophrenia genetic risk associates with longitudinal patterns of cigarette and cannabis use in adolescence and mediating pathways for any association to inform potential reduction strategies.
Associations between schizophrenia polygenic scores and longitudinal latent classes of cigarette and cannabis use from ages 14 to 19 years were investigated in up to 3925 individuals in the Avon Longitudinal Study of Parents and Children. Mediation models were estimated to assess the potential mediating effects of a range of cognitive, emotional, and behavioral phenotypes.
The schizophrenia polygenic score, based on single nucleotide polymorphisms meeting a training-set p threshold of 0.05, was associated with late-onset cannabis use (OR = 1.23; 95% CI = 1.08,1.41), but not with cigarette or early-onset cannabis use classes. This association was not mediated through lower IQ, victimization, emotional difficulties, antisocial behavior, impulsivity, or poorer social relationships during childhood. Sensitivity analyses adjusting for genetic liability to cannabis or cigarette use, using polygenic scores excluding the CHRNA5-A3-B4 gene cluster, or basing scores on a 0.5 training-set p threshold, provided results consistent with our main analyses.
Our study provides evidence that genetic risk for schizophrenia is associated with patterns of cannabis use during adolescence. Investigation of pathways other than the cognitive, emotional, and behavioral phenotypes examined here is required to identify modifiable targets to reduce the public health burden of cannabis use in the population.
There is a wealth of literature on the observed association between childhood trauma and psychotic illness. However, the relationship between childhood trauma and psychosis is complex and could be explained, in part, by gene–environment correlation.
The association between schizophrenia polygenic scores (PGS) and experiencing childhood trauma was investigated using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Norwegian Mother, Father and Child Cohort Study (MoBa). Schizophrenia PGS were derived in each cohort for children, mothers, and fathers where genetic data were available. Measures of trauma exposure were derived based on data collected throughout childhood and adolescence (0–17 years; ALSPAC) and at age 8 years (MoBa).
Within ALSPAC, we found a positive association between schizophrenia PGS and exposure to trauma across childhood and adolescence; effect sizes were consistent for both child or maternal PGS. We found evidence of an association between the schizophrenia PGS and the majority of trauma subtypes investigated, with the exception of bullying. These results were comparable with those of MoBa. Within ALSPAC, genetic liability to a range of additional psychiatric traits was also associated with a greater trauma exposure.
Results from two international birth cohorts indicate that genetic liability for a range of psychiatric traits is associated with experiencing childhood trauma. Genome-wide association study of psychiatric phenotypes may also reflect risk factors for these phenotypes. Our findings also suggest that youth at higher genetic risk might require greater resources/support to ensure they grow-up in a healthy environment.
Smoking prevalence is higher amongst individuals with schizophrenia and depression compared with the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).
We conducted two-sample MR to explore the bi-directional effects of smoking on schizophrenia and depression. For smoking behaviour, we used (1) smoking initiation GWAS from the GSCAN consortium and (2) we conducted our own GWAS of lifetime smoking behaviour (which captures smoking duration, heaviness and cessation) in a sample of 462690 individuals from the UK Biobank. We validated this instrument using positive control outcomes (e.g. lung cancer). For schizophrenia and depression we used GWAS from the PGC consortium.
There was strong evidence to suggest smoking is a risk factor for both schizophrenia (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.67–3.08, p < 0.001) and depression (OR 1.99, 95% CI 1.71–2.32, p < 0.001). Results were consistent across both lifetime smoking and smoking initiation. We found some evidence that genetic liability to depression increases smoking (β = 0.091, 95% CI 0.027–0.155, p = 0.005) but evidence was mixed for schizophrenia (β = 0.022, 95% CI 0.005–0.038, p = 0.009) with very weak evidence for an effect on smoking initiation.
These findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking, providing further evidence for the detrimental consequences of smoking on mental health.
Galileo participated in exchanges of encrypted correspondence at key moments in his life. In 1610–11, following the publication of the “Sidereal Messenger,” ciphers helped Galileo to diplomatically reveal what he was observing through his telescope. After his Inquisition trial of 1633, Galileo and his closest allies relied on a substitution code (gergo) to protect the privacy of his conversations and to facilitate the removal of his library and manuscripts at Arcetri. Throughout this article, we position Galileo's use of codes within the rich contemporary literature about communicating securely and reflect on cryptic writing as a strategy of communication and dissimulation.
There is increasing evidence that smoking is a risk factor for severe mental illness, including bipolar disorder. Conversely, patients with bipolar disorder might smoke more (often) as a result of the psychiatric disorder.
We conducted a bidirectional Mendelian randomisation (MR) study to investigate the direction and evidence for a causal nature of the relationship between smoking and bipolar disorder.
We used publicly available summary statistics from genome-wide association studies on bipolar disorder, smoking initiation, smoking heaviness, smoking cessation and lifetime smoking (i.e. a compound measure of heaviness, duration and cessation). We applied analytical methods with different, orthogonal assumptions to triangulate results, including inverse-variance weighted (IVW), MR-Egger, MR-Egger SIMEX, weighted-median, weighted-mode and Steiger-filtered analyses.
Across different methods of MR, consistent evidence was found for a positive effect of smoking on the odds of bipolar disorder (smoking initiation ORIVW = 1.46, 95% CI 1.28–1.66, P = 1.44 × 10−8, lifetime smoking ORIVW = 1.72, 95% CI 1.29–2.28, P = 1.8 × 10−4). The MR analyses of the effect of liability to bipolar disorder on smoking provided no clear evidence of a strong causal effect (smoking heaviness betaIVW = 0.028, 95% CI 0.003–0.053, P = 2.9 × 10−2).
These findings suggest that smoking initiation and lifetime smoking are likely to be a causal risk factor for developing bipolar disorder. We found some evidence that liability to bipolar disorder increased smoking heaviness. Given that smoking is a modifiable risk factor, these findings further support investment into smoking prevention and treatment in order to reduce mental health problems in future generations.
Despite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop tailored smoking interventions that could lead to both improved uptake and efficacy.
Recent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to individual-level data from UK Biobank to investigate the link between smoking and personality. We first estimate genetic overlap between traits using LD score regression and then use bidirectional Mendelian randomisation methods to unpick the nature of this relationship.
We found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion. We found some evidence that personality traits are causally linked to certain smoking phenotypes: among current smokers each additional neuroticism risk allele was associated with smoking an additional 0.07 cigarettes per day (95% CI 0.02–0.12, p = 0.009), and each additional extraversion effect allele was associated with an elevated odds of smoking initiation (OR 1.015, 95% CI 1.01–1.02, p = 9.6 × 10−7).
We found some evidence for specific causal pathways from personality to smoking phenotypes, and weaker evidence of an association from smoking initiation to personality. These findings could be used to inform future smoking interventions or to tailor existing schemes.
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