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Neuroticism has societal, mental and physical health relevance, with an etiology involving genetic predisposition, psychological influence, and their interaction.
To understand whether the association between polygenic risk score for neuroticism (PRS-N) and neuroticism is moderated by affective well-being.
Data were derived from TwinssCan, a general population twin cohort (age range=15-35 years, 478 monozygotic twins). Self-report questionnaires were used to measure well-being and neuroticism. PRS-N was trained from the Genetics of Personality Consortium (GPC) and United Kingdom Biobank (UKB). Multilevel mixed-effects models were used to test baseline and changes in well-being and neuroticism.
Baseline wellbeing and neuroticism were associated (β=-1.35, p<0.001). PRSs-N were associated with baseline neuroticism (lowest p-value: 0.008 in GPC, 0.01 in UKB). In interaction models (PRS x wellbeing), GPC PRS-N (β=0.38, p=0.04) and UKB PRS-N (β=0.81, p<0.001) had significant interactions.
PRSs-N were associated with changes in neuroticism (lowest p-value: 0.03 in GPC, 0.3 in UKB). Furthermore, changes in wellbeing and neuroticism were associated (β =-0.66, p<0.001). In interaction models (PRS x change in wellbeing), only UKB PRS-N had a significant interaction (β=0.80, p<0.001).
Interaction between polygenic risk, wellbeing and neuroticism, were observed regarding baselines measures and change over time. Depending on the analysis step, the direction of the effect changed.
Prior evidence suggests that men and women might be differentially susceptible to distinct types of childhood adversity (CA), but research on gender-specific associations between CA subtypes and psychiatric symptoms is limited.
To test the gender-specific associations of CA subtypes and psychiatric symptoms in the general population.
Data from 791 twins and siblings from the TwinssCan project were used. Psychopathology and CA exposure were assessed using the Symptom Checklist-90 Revised (SCL-90) and the Childhood Trauma Questionnaire (CTQ), respectively. The associations between the total CTQ scores and SCL-90 scores (i.e. total SCL-90, psychoticism, paranoid ideation, anxiety, depression, somatization, obsessive-compulsive, interpersonal sensitivity, hostility, and phobic anxiety) were tested in men and women separately. The associations between the five CA subtypes (i.e. physical abuse, emotional abuse, sexual abuse, physical neglect, and emotional neglect) and total SCL-90 were tested in a mutually adjusted model. As exploratory analyses, the associations between all CA subtypes and the nine SCL-90 subdomain scores were similarly tested. The regression coefficients between men and women were compared using Chow’s test. All models were adjusted for age and family structure.
Total CTQ was significantly associated with total SCL-90 in men (B = 0.013, SE = 0.003, P < .001) and women (B = 0.011, SE = 0.002, P < .001). The associations with the nine symptom domains were also significant in both genders (P < .001). No significant gender differences in the regression coefficients of total CTQ were detected. The analyses of CA subtypes showed a significant association between emotional abuse and total SCL-90 in women (B = 0.173, SE = 0.030, P < .001) and men (B = 0.080, SE = 0.035, P = .023), but the association was significantly stronger in women (ꭓ2(1) = 4.10, P = .043). The association of sexual abuse and total SCL-90 was only significant in women (B = 0.217, SE = 0.053, P < .001). The associations of emotional neglect (B = 0.061, SE = 0.027, P = .026) and physical neglect (B = 0.167, SE = 0.043, P < .001) with total SCL-90 were only significant in men. The explorative analyses of SCL-90 subdomains revealed significant associations of emotional abuse with all nine symptom domains and of sexual abuse with seven symptom domains in women. Significant associations of physical neglect with six symptom domains and of emotional neglect with depression were also detected in men. No other significant associations between CT subtypes and total SCL-90 or symptom domain scores were observed in men and women.
CA exposure was associated with diverse psychopathology similarly in both genders. However, women are more sensitive to abuse, but men are more sensitive to neglect. Gender-specific influences of CA subtypes on psychopathology should be considered in future studies.
Gene x environment (G×E) interactions, i.e. genetic modulation of the sensitivity to environmental factors and/or environmental control of the gene expression, have not been reliably established regarding aetiology of psychotic disorders. Moreover, recent studies have shown associations between the polygenic risk scores for schizophrenia (PRS-SZ) and some risk factors of psychotic disorders, challenging the traditional gene v. environment dichotomy. In the present article, we studied the role of GxE interaction between psychosocial stressors (childhood trauma, stressful life-events, self-reported discrimination experiences and low social capital) and the PRS-SZ on subclinical psychosis in a population-based sample.
Data were drawn from the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study, in which subjects without psychotic disorders were included in six countries. The sample was restricted to European descendant subjects (n = 706). Subclinical dimensions of psychosis (positive, negative, and depressive) were measured by the Community Assessment of Psychic Experiences (CAPE) scale. Associations between the PRS-SZ and the psychosocial stressors were tested. For each dimension, the interactions between genes and environment were assessed using linear models and comparing explained variances of ‘Genetic’ models (solely fitted with PRS-SZ), ‘Environmental’ models (solely fitted with each environmental stressor), ‘Independent’ models (with PRS-SZ and each environmental factor), and ‘Interaction’ models (Independent models plus an interaction term between the PRS-SZ and each environmental factor). Likelihood ration tests (LRT) compared the fit of the different models.
There were no genes-environment associations. PRS-SZ was associated with positive dimensions (β = 0.092, R2 = 7.50%), and most psychosocial stressors were associated with all three subclinical psychotic dimensions (except social capital and positive dimension). Concerning the positive dimension, Independent models fitted better than Environmental and Genetic models. No significant GxE interaction was observed for any dimension.
This study in subjects without psychotic disorders suggests that (i) the aetiological continuum hypothesis could concern particularly the positive dimension of subclinical psychosis, (ii) genetic and environmental factors have independent effects on the level of this positive dimension, (iii) and that interactions between genetic and individual environmental factors could not be identified in this sample.
A history of childhood adversity is associated with psychotic disorder, with an increase in risk according to the number of exposures. However, it is not known why only some exposed individuals go on to develop psychosis. One possibility is pre-existing polygenic vulnerability. Here, we investigated, in the largest sample of first-episode psychosis (FEP) cases to date, whether childhood adversity and high polygenic risk scores for schizophrenia (SZ-PRS) combine synergistically to increase the risk of psychosis, over and above the effect of each alone.
We assigned a schizophrenia-polygenic risk score (SZ-PRS), calculated from the Psychiatric Genomics Consortium (PGC2), to all participants in a sample of 384 FEP patients and 690 controls from the case–control component of the EU-GEI study. Only participants of European ancestry were included in the study. A history of childhood adversity was collected using the Childhood Trauma Questionnaire (CTQ). Synergistic effects were estimated using the interaction contrast ratio (ICR) [odds ratio (OR)exposure and PRS − ORexposure − ORPRS + 1] with adjustment for potential confounders.
There was some evidence that the combined effect of childhood adversities and polygenic risk was greater than the sum of each alone, as indicated by an ICR greater than zero [i.e. ICR 1.28, 95% confidence interval (CI) −1.29 to 3.85]. Examining subtypes of childhood adversities, the strongest synergetic effect was observed for physical abuse (ICR 6.25, 95% CI −6.25 to 20.88).
Our findings suggest possible synergistic effects of genetic liability and childhood adversity experiences in the onset of FEP, but larger samples are needed to increase precision of estimates.
Psychosis spectrum disorder has a complex pathoetiology characterised by interacting environmental and genetic vulnerabilities. The present study aims to investigate the role of gene–environment interaction using aggregate scores of genetic (polygenic risk score for schizophrenia (PRS-SCZ)) and environment liability for schizophrenia (exposome score for schizophrenia (ES-SCZ)) across the psychosis continuum.
The sample consisted of 1699 patients, 1753 unaffected siblings, and 1542 healthy comparison participants. The Structured Interview for Schizotypy-Revised (SIS-R) was administered to analyse scores of total, positive, and negative schizotypy in siblings and healthy comparison participants. The PRS-SCZ was trained using the Psychiatric Genomics Consortiums results and the ES-SCZ was calculated guided by the approach validated in a previous report in the current data set. Regression models were applied to test the independent and joint effects of PRS-SCZ and ES-SCZ (adjusted for age, sex, and ancestry using 10 principal components).
Both genetic and environmental vulnerability were associated with case-control status. Furthermore, there was evidence for additive interaction between binary modes of PRS-SCZ and ES-SCZ (above 75% of the control distribution) increasing the odds for schizophrenia spectrum diagnosis (relative excess risk due to interaction = 6.79, [95% confidential interval (CI) 3.32, 10.26], p < 0.001). Sensitivity analyses using continuous PRS-SCZ and ES-SCZ confirmed gene–environment interaction (relative excess risk due to interaction = 1.80 [95% CI 1.01, 3.32], p = 0.004). In siblings and healthy comparison participants, PRS-SCZ and ES-SCZ were associated with all SIS-R dimensions and evidence was found for an interaction between PRS-SCZ and ES-SCZ on the total (B = 0.006 [95% CI 0.003, 0.009], p < 0.001), positive (B = 0.006 [95% CI, 0.002, 0.009], p = 0.002), and negative (B = 0.006, [95% CI 0.004, 0.009], p < 0.001) schizotypy dimensions.
The interplay between exposome load and schizophrenia genetic liability contributing to psychosis across the spectrum of expression provide further empirical support to the notion of aetiological continuity underlying an extended psychosis phenotype.
Daily use of high-potency cannabis has been reported to carry a high risk for developing a psychotic disorder. However, the evidence is mixed on whether any pattern of cannabis use is associated with a particular symptomatology in first-episode psychosis (FEP) patients.
We analysed data from 901 FEP patients and 1235 controls recruited across six countries, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study. We used item response modelling to estimate two bifactor models, which included general and specific dimensions of psychotic symptoms in patients and psychotic experiences in controls. The associations between these dimensions and cannabis use were evaluated using linear mixed-effects models analyses.
In patients, there was a linear relationship between the positive symptom dimension and the extent of lifetime exposure to cannabis, with daily users of high-potency cannabis having the highest score (B = 0.35; 95% CI 0.14–0.56). Moreover, negative symptoms were more common among patients who never used cannabis compared with those with any pattern of use (B = −0.22; 95% CI −0.37 to −0.07). In controls, psychotic experiences were associated with current use of cannabis but not with the extent of lifetime use. Neither patients nor controls presented differences in depressive dimension related to cannabis use.
Our findings provide the first large-scale evidence that FEP patients with a history of daily use of high-potency cannabis present with more positive and less negative symptoms, compared with those who never used cannabis or used low-potency types.
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