Effect of Preheating and Post-Heating on the Microstructures and Mechanical Properties of TC17-Ti2AlNb Joint with Electron Beam Welding.

To enhance welding quality and performance, preheating and post-heating are usually employed on high-temperature materials, concurrently with welding. This is a novel technique in vacuum chamber electron beam welding (EBW). TC17 and Ti2AlNb alloys are the hot topics in aero-engine parts, and the welding of dissimilar materials is also a broad prospect. To settle welding cracks of Ti2AlNb, EBW with preheating and post-heating was investigated on TC17 and Ti2AlNb dissimilar alloy, which improved the manufacturing technology on high-temperature materials. The dissimilar joint no longer had cracks after preheating, which exhibited excellent welding stability and metallurgical homogeneity, and preheating and annealing had an important effect on mechanical properties. The joint strength after 630 °C annealing is higher than that of TC17 alloy base metal (BM) and other annealing temperatures, reaching 1169 MPa at room temperature and 894 MPa at 450 °C tensile condition. The joint plasticity after 740 °C annealing is equivalent to TC17 BM. EBW with preheating improved the microstructure characteristics and enhanced the plasticity of Ti2AlNb alloy weld and dissimilar joint, which would contribute to the application of Ti2AlNb alloy and Ti2AlNb dissimilar parts.

Clustering Schizophrenia Genes by Their Temporal Expression Patterns Aids Functional Interpretation.

BACKGROUND: Schizophrenia is a highly heritable brain disorder with a typical symptom onset in early adulthood. The 2-hit hypothesis posits that schizophrenia results from differential early neurodevelopment, predisposing an individual, followed by a disruption of later brain maturational processes that trigger the onset of symptoms. STUDY DESIGN: We applied hierarchical clustering to transcription levels of 345 genes previously linked to schizophrenia, derived from cortical tissue samples from 56 donors across the lifespan. We subsequently calculated clustered-specific polygenic risk scores for 743 individuals with schizophrenia and 743 sex- and age-matched healthy controls. STUDY RESULTS: Clustering revealed a set of 183 genes that was significantly upregulated prenatally and downregulated postnatally and 162 genes that showed the opposite pattern. The prenatally upregulated set of genes was functionally annotated to fundamental cell cycle processes, while the postnatally upregulated set was associated with the immune system and neuronal communication. We found an interaction between the 2 scores; higher prenatal polygenic risk showed a stronger association with schizophrenia diagnosis at higher levels of postnatal polygenic risk. Importantly, this finding was replicated in an independent clinical cohort of 3233 individuals. CONCLUSIONS: We provide genetics-based evidence that schizophrenia is shaped by disruptions of separable biological processes acting at distinct phases of neurodevelopment. The modeling of genetic risk factors that moderate each other's effect, informed by the timing of their expression, will aid in a better understanding of the development of schizophrenia.

Gene-environment interaction study on the polygenic risk score for neuroticism, childhood adversity, and parental bonding.

The present study examines whether neuroticism is predicted by genetic vulnerability, summarized as polygenic risk score for neuroticism (PRSN), in interaction with bullying, parental bonding, and childhood adversity. Data were derived from a general population adolescent and young adult twin cohort. The final sample consisted of 202 monozygotic and 436 dizygotic twins and 319 twin pairs. The Short Eysenck Personality questionnaire was used to measure neuroticism. PRSN was trained on the results from the Genetics of Personality Consortium (GPC) and United Kingdom Biobank (UKB) cohorts, yielding two different PRSN. Multilevel mixed-effects models were used to analyze the main and interacting associations of PRSN, childhood adversity, bullying, and parental bonding style with neuroticism. We found no evidence of gene-environment correlation. PRSN thresholds of .005 and .2 were chosen, based on GPC and UKB datasets, respectively. After correction for confounders, all the individual variables were associated with the expression of neuroticism: both PRSN from GPC and UKB, childhood adversity, maternal bonding, paternal bonding, and bullying in primary school and secondary school. However, the results indicated no evidence for gene-environment interaction in this cohort. These results suggest that genetic vulnerability on the one hand and negative life events (childhood adversity and bullying) and positive life events (optimal parental bonding) on the other represent noninteracting pathways to neuroticism.

Transcriptional level of inflammation markers associates with short-term brain structural changes in first-episode schizophrenia.

BACKGROUND: Inflammation has been implicated in the pathology of schizophrenia and may cause neuronal cell death and dendrite loss. Neuroimaging studies have highlighted longitudinal brain structural changes in patients with schizophrenia, yet it is unclear whether this is related to inflammation. We aim to address this question, by relating brain structural changes with the transcriptional profile of inflammation markers in the early stage of schizophrenia. METHODS: Thirty-eight patients with first-episode schizophrenia and 51 healthy controls were included. High-resolution T1-weighted magnetic resonance imaging (MRI) and clinical assessments were performed at baseline and 2 ~ 6 months follow-up for all subjects. Changes in the brain structure were analyzed using surface-based morphological analysis and correlated with the expression of immune cells-related gene sets of interest reported by previous reviews. Transcriptional data were retrieved from the Allen Human Brain Atlas. Furthermore, we examined the brain structural changes and peripheral inflammation markers in association with behavioral symptoms and cognitive functioning in patients. RESULTS: Patients exhibited accelerated cortical thickness decrease in the left frontal cortices, less decrease or an increase in the superior parietal lobule and right lateral occipital lobe, and increased volume in the bilateral pallidum, compared with controls. Changes in cortical thickness correlated with the transcriptional level of monocyte across cortical regions in patients (r = 0.54, p < 0.01), but not in controls (r = - 0.05, p = 0.76). In addition, cortical thickness change in the left superior parietal lobule positively correlated with changes in digital span-backward test scores in patients. CONCLUSIONS: Patients with schizophrenia exhibit regional-specific cortical thickness changes in the prefrontal and parietooccipital cortices, which is related to their cognitive impairment. Inflammation may be an important factor contributing to cortical thinning in first-episode schizophrenia. Our findings suggest that the immunity-brain-behavior association may play a crucial role in the pathogenesis of schizophrenia.

The association between polygenic risk scores for mental disorders and social cognition: A scoping review.

People with mental disorders, such as psychosis or autism spectrum disorder (ASD), often present impairments in social cognition (SC), which may cause significant difficulties in real-world functioning. SC deficits are seen also in unaffected relatives, indicating a genetic substratum. The present review evaluated the evidence on the association between SC and the polygenic risk score (PRS), a single metric of the molecular genetic risk to develop a specific disorder. In July 2022, we conducted systematic searches in Scopus and PubMed following the PRISMA-ScR guidelines. We selected original articles written in English reporting results on the association between PRSs for any mental disorder and domains of SC either in people with mental disorders or controls. The search yielded 244 papers, of which 13 were selected for inclusion. Studies tested mainly PRSs for schizophrenia, ASD, and attention-deficit hyperactivity disorder. Emotion recognition was the most investigated domain of SC. Overall, evidence revealed that currently available PRSs for mental disorders do not explain variation in SC performances. To enhance the understanding of mechanisms underlying SC in mental disorders, future research should focus on the development of transdiagnostic PRSs, study their interaction with environmental risk factors, and standardize outcome measurement.

Context v. algorithm: evidence that a transdiagnostic framework of contextual clinical characterization is of more clinical value than categorical diagnosis.

BACKGROUND: A transdiagnostic and contextual framework of 'clinical characterization', combining clinical, psychopathological, sociodemographic, etiological, and other personal contextual data, may add clinical value over and above categorical algorithm-based diagnosis. METHODS: Prediction of need for care and health care outcomes was examined prospectively as a function of the contextual clinical characterization diagnostic framework in a prospective general population cohort (n = 6646 at baseline), interviewed four times between 2007 and 2018 (NEMESIS-2). Measures of need, service use, and use of medication were predicted as a function of any of 13 DSM-IV diagnoses, both separately and in combination with clinical characterization across multiple domains: social circumstances/demographics, symptom dimensions, physical health, clinical/etiological factors, staging, and polygenic risk scores (PRS). Effect sizes were expressed as population attributable fractions. RESULTS: Any prediction of DSM-diagnosis in relation to need and outcome in separate models was entirely reducible to components of contextual clinical characterization in joint models, particularly the component of transdiagnostic symptom dimensions (a simple score of the number of anxiety, depression, mania, and psychosis symptoms) and staging (subthreshold, incidence, persistence), and to a lesser degree clinical factors (early adversity, family history, suicidality, slowness at interview, neuroticism, and extraversion), and sociodemographic factors. Clinical characterization components in combination predicted more than any component in isolation. PRS did not meaningfully contribute to any clinical characterization model. CONCLUSION: A transdiagnostic framework of contextual clinical characterization is of more value to patients than a categorical system of algorithmic ordering of psychopathology.

Independent contribution of polygenic risk for schizophrenia and cannabis use in predicting psychotic-like experiences in young adulthood: testing gene × environment moderation and mediation.

BACKGROUND: It has not yet been determined if the commonly reported cannabis-psychosis association is limited to individuals with pre-existing genetic risk for psychotic disorders. METHODS: We examined whether the relationship between polygenic risk score for schizophrenia (PRS-Sz) and psychotic-like experiences (PLEs), as measured by the Community Assessment of Psychic Experiences-42 (CAPE-42) questionnaire, is mediated or moderated by lifetime cannabis use at 16 years of age in 1740 of the individuals of the European IMAGEN cohort. Secondary analysis examined the relationships between lifetime cannabis use, PRS-Sz and the various sub-scales of the CAPE-42. Sensitivity analyses including covariates, including a PRS for cannabis use, were conducted and results were replicated using data from 1223 individuals in the Dutch Utrecht cannabis cohort. RESULTS: PRS-Sz significantly predicted cannabis use (p = 0.027) and PLE (p = 0.004) in the IMAGEN cohort. In the full model, considering PRS-Sz and covariates, cannabis use was also significantly associated with PLE in IMAGEN (p = 0.007). Results remained consistent in the Utrecht cohort and through sensitivity analyses. Nevertheless, there was no evidence of a mediation or moderation effects. CONCLUSIONS: These results suggest that cannabis use remains a risk factor for PLEs, over and above genetic vulnerability for schizophrenia. This research does not support the notion that the cannabis-psychosis link is limited to individuals who are genetically predisposed to psychosis and suggests a need for research focusing on cannabis-related processes in psychosis that cannot be explained by genetic vulnerability.

Adjusting for population stratification in polygenic risk score analyses: a guide for model specifications in the UK Biobank.

The current study was conducted to provide a general guidance for model specifications in polygenic risk score (PRS) analyses of the UK Biobank, such as adjusting for covariates (i.e. age, sex, recruitment centers, and genetic batch) and the number of principal components (PCs) that need to be included. To cover behavioral, physical and mental health outcomes, we evaluated three continuous outcomes (BMI, smoking, drinking) and two binary outcomes (Major Depressive Disorder and educational attainment). We applied 3280 (656 per phenotype) different models including different sets of covariates. We evaluated these different model specifications by comparing regression parameters such as R2, coefficients, and P values, as well as ANOVA tests. Findings suggest that only up to three PCs appears to be sufficient for controlling population stratification for most outcomes, whereas including other covariates (particularly age and sex) appears to be more essential for model performance.

Examining the association between exposome score for schizophrenia and cognition in schizophrenia, siblings, and healthy controls: Results from the EUGEI study.

BACKGROUND: People with schizophrenia spectrum disorders (SSD) frequently present cognitive impairments. Here, we investigated whether the exposome score for schizophrenia (ES-SCZ) - a cumulative environmental exposure score - was associated with impairments of neurocognition, social cognition, and perception in patients with SSD, their unaffected siblings, and healthy controls. METHODS: This cross-sectional sample consisted of 1200 patients, 1371 siblings, and 1564 healthy controls. Neurocognition, social cognition, and perception were assesed using a short version of the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III), the Degraded Facial Affect Recognition Task (DFAR), and the Benton Facial Recognition Test (BFR), respectively. Regression models were used to analyze the association between ES-SCZ and cognitive domains in each group. RESULTS: There were no statistically significant associations between ES-SCZ and cognitive domains in SSD. ES-SCZ was negatively associated with T-score of cognition in siblings (B=-0.40, 95% CI -0.76 to -0.03) and healthy controls (B=-0.63, 95% CI -1.06 to -0.21). Additionally, ES-SCZ was positively associated with DFAR-total in siblings (B=0.83, 95% CI 0.26 to 1.40). Sensitivity analyses excluding cannabis use history from ES-SCZ largely confirmed the main findings. CONCLUSIONS: Longitudinal cohorts may elucidate how environmental exposures influence the onset and course of cognitive impairments in trans-syndromic psychosis spectrum.

Associations between genetic liabilities to smoking behavior and schizophrenia symptoms in patients with a psychotic disorder, their siblings and healthy controls.

It is unknown how smoking behavior polygenic scores (PRS) relate to psychosis and psychotic symptoms. To elucidate this, genotype and phenotype data were collected from patients with schizophrenia, their unaffected siblings, and healthy controls in a six-year follow-up prospective cohort study. Associations between smoking behaviors, PRS and schizophrenia symptoms were explored using linear mixed-effect models. The mean number of cigarettes smoked per day were 18 for patients, 13 for siblings and 12 for controls. In the overall sample, PRSs-smoking initiation (i.e., ever smoking as a binary phenotype, PRS-SI) were positively associated with positive symptoms, negative symptoms, and depressive symptoms, whereas PRSs-AI (age at regular smoking initiation) were negatively associated with all symptom dimensions, with similar effect sizes. When considering groups separately, PRS were only associated with psychotic symptoms in siblings and controls. In conclusion, unaffected siblings show smoking behaviors at an intermediate level between patients and healthy controls. Additionally, PRS-SI and PRS-AI are associated with all symptom dimensions only in unaffected siblings and healthy controls, possibly owing to the dominant role of other (genetic) risk factors in patients. Future studies may examine mechanisms via which genetic risk for smoking affects mental health symptoms.

Associations Between Polygenic Risk Score Loading, Psychosis Liability, and Clozapine Use Among Individuals With Schizophrenia.

Importance: Predictors consistently associated with psychosis liability and course of illness in schizophrenia (SCZ) spectrum disorders (SSD), including the need for clozapine treatment, are lacking. Longitudinally ascertained medication use may empower studies examining associations between polygenic risk scores (PRSs) and pharmacotherapy choices. Objective: To examine associations between PRS-SCZ loading and groups with different liabilities to SSD (individuals with SSD taking clozapine, individuals with SSD taking other antipsychotics, their parents and siblings, and unrelated healthy controls) and between PRS-SCZ and the likelihood of receiving a prescription of clozapine relative to other antipsychotics. Design, Setting, and Participants: This genetic association study was a multicenter, observational cohort study with 6 years of follow-up. Included were individuals diagnosed with SSD who were taking clozapine or other antipsychotics, their parents and siblings, and unrelated healthy controls. Data were collected from 2004 until 2021 and analyzed between October 2021 and September 2022. Exposures: Polygenic risk scores for SCZ. Main Outcomes and Measures: Multinomial logistic regression was used to examine possible differences between groups by computing risk ratios (RRs), ie, ratios of the probability of pertaining to a particular group divided by the probability of healthy control status. We also computed PRS-informed odd ratios (ORs) for clozapine use relative to other antipsychotics. Results: Polygenic risk scores for SCZ were generated for 2344 participants (mean [SD] age, 36.95 years [14.38]; 994 female individuals [42.4%]) who remained after quality control screening (557 individuals with SSD taking clozapine, 350 individuals with SSD taking other antipsychotics during the 6-year follow-up, 542 parents and 574 siblings of individuals with SSD, and 321 unrelated healthy controls). All RRs were significantly different from 1; RRs were highest for individuals with SSD taking clozapine (RR, 3.24; 95% CI, 2.76-3.81; P = 2.47 × 10-46), followed by individuals with SSD taking other antipsychotics (RR, 2.30; 95% CI, 1.95-2.72; P = 3.77 × 10-22), parents (RR, 1.44; 95% CI, 1.25-1.68; P = 1.76 × 10-6), and siblings (RR, 1.40; 95% CI, 1.21-1.63; P = 8.22 × 10-6). Polygenic risk scores for SCZ were positively associated with clozapine vs other antipsychotic use (OR, 1.41; 95% CI, 1.22-1.63; P = 2.98 × 10-6), suggesting a higher likelihood of clozapine prescriptions among individuals with higher PRS-SCZ. Conclusions and Relevance: In this study, PRS-SCZ loading differed between groups of individuals with SSD, their relatives, and unrelated healthy controls, with patients taking clozapine at the far end of PRS-SCZ loading. Additionally, PRS-SCZ was associated with a higher likelihood of clozapine prescribing. Our findings may inform early intervention and prognostic studies of the value of using PRS-SCZ to personalize antipsychotic treatment.

Age- and sex-specific associations between risk scores for schizophrenia and self-reported health in the general population.

PURPOSE: The health correlates of polygenic risk (PRS-SCZ) and exposome (ES-SCZ) scores for schizophrenia may vary depending on age and sex. We aimed to examine age- and sex-specific associations of PRS-SCZ and ES-SCZ with self-reported health in the general population. METHODS: Participants were from the population-based Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2). Mental and physical health were measured with the 36-item Short Form Survey 4 times between 2007 and 2018. The PRS-SCZ and ES-SCZ were respectively calculated from common genetic variants and exposures (cannabis use, winter birth, hearing impairment, and five childhood adversity categories). Moderation by age and sex was examined in linear mixed models. RESULTS: For PRS-SCZ and ES-SCZ analyses, we included 3099 and 6264 participants, respectively (age range 18-65 years; 55.7-56.1% female). Age and sex did not interact with PRS-SCZ. Age moderated the association between ES-SCZ and mental (interaction: p = 0.02) and physical health (p = 0.0007): at age 18, + 1.00 of ES-SCZ was associated with - 0.10 of mental health and - 0.08 of physical health, whereas at age 65, it was associated with - 0.21 and - 0.23, respectively (all units in standard deviations). Sex moderated the association between ES-SCZ and physical health (p < .0001): + 1.00 of ES-SCZ was associated with - 0.19 of physical health among female and - 0.11 among male individuals. CONCLUSION: There were larger associations between higher ES-SCZ and poorer health among female and older individuals. Accounting for these interactions may increase ES-SCZ precision and help uncover populational determinants of environmental influences on health.

Polygenic risk, familial liability and stress reactivity in psychosis: an experience sampling study.

BACKGROUND: There is evidence for a polygenic contribution to psychosis. One targetable mechanism through which polygenic variation may impact on individuals and interact with the social environment is stress sensitization, characterized by elevated reactivity to minor stressors in daily life. The current study aimed to investigate whether stress reactivity is modified by polygenic risk score for schizophrenia (PRS) in cases with enduring non-affective psychotic disorder, first-degree relatives of cases, and controls. METHODS: We used the experience sampling method to assess minor stressors, negative affect, positive affect and psychotic experiences in 96 cases, 79 first-degree relatives, i.e. siblings, and 73 controls at wave 3 of the Dutch Genetic Risk and Outcome of Psychosis (GROUP) study. Genome-wide data were collected at baseline to calculate PRS. RESULTS: We found that associations of momentary stress with psychotic experiences, but not with negative and positive affect, were modified by PRS and group (all pFWE<0.001). In contrast to our hypotheses, siblings with high PRS reported less intense psychotic experiences in response to momentary stress compared to siblings with low PRS. No differences in magnitude of these associations were observed in cases with high v. low level of PRS. By contrast, controls with high PRS showed more intense psychotic experiences in response to stress compared to those with low PRS. CONCLUSIONS: This tentatively suggests that polygenic risk may operate in different ways than previously assumed and amplify reactivity to stress in unaffected individuals but operate as a resilience factor in relatives by attenuating their stress reactivity.

The association between cannabis use and facial emotion recognition in schizophrenia, siblings, and healthy controls: Results from the EUGEI study.

Schizophrenia is frequently accompanied with social cognitive disturbances. Cannabis represents one established environmental factor associated with the onset and progression of schizophrenia. The present cross-sectional study aimed to investigate the association of facial emotion recognition (FER) performance with cannabis use in 2039 patients with schizophrenia, 2141 siblings, and 2049 healthy controls (HC). FER performance was measured using the Degraded Facial Affect Recognition Task (DFAR). Better FER performance as indicated by higher DFAR-total scores was associated with lifetime regular cannabis use in schizophrenia (B = 1.36, 95% CI 0.02 to 2.69), siblings (B = 2.17, 95% CI 0.79 to 3.56), and HC (B = 3.10, 95% CI 1.14 to 5.06). No associations were found between DFAR-total and current cannabis use. Patients with schizophrenia who started to use cannabis after the age of 16 showed better FER performance than patients who started earlier (B = 2.50, 95% CI 0.15 to 4.84) and non-users (B = 3.72, 95 CI 1.96 to 5.49). Better FER performance was found also in siblings who started to use cannabis after 16 compared to non-users (B = 2.37, 95% CI 0.58 to 4.16), while HC using cannabis performed better than non-users at DFAR-total regardless of the age at onset. Our findings suggest that lifetime regular cannabis use may be associated with better FER regardless of the psychosis risk, but that FER might be moderated by age at first use in people with higher genetic risk. Longitudinal studies may clarify whether there is a cause-and-effect relationship between cannabis use and FER performance in psychotic and non-psychotic samples.

A polygenic-informed approach to a predictive EEG signature empowers antidepressant treatment prediction: A proof-of-concept study.

The treatment of major depressive disorder (MDD) is hampered by low chances of treatment response in each treatment step, which is partly due to a lack of firmly established outcome-predictive biomarkers. Here, we hypothesize that polygenic-informed EEG signatures may help predict antidepressant treatment response. Using a polygenic-informed electroencephalography (EEG) data-driven, data-reduction approach, we identify a brain network in a large cohort (N=1,123), and discover it is sex-specifically (male patients, N=617) associated with polygenic risk score (PRS) of antidepressant response. Subsequently, we demonstrate in three independent datasets the utility of the network in predicting response to antidepressant medication (male, N=232) as well as repetitive transcranial magnetic stimulation (rTMS) and concurrent psychotherapy (male, N=95). This network significantly improves a treatment response prediction model with age and baseline severity data (area under the curve, AUC=0.623 for medicaton; AUC=0.719 for rTMS). A predictive model for MDD patients, aimed at increasing the likelihood of being a responder to antidepressants or rTMS and concurrent psychotherapy based on only this network, yields a positive predictive value (PPV) of 69% for medication and 77% for rTMS. Finally, blinded out-of-sample validation of the network as predictor for psychotherapy response in another independent dataset (male, N=50) results in a within-subsample response rate of 50% (improvement of 56%). Overall, the findings provide a first proof-of-concept of a combined genetic and neurophysiological approach in the search for clinically-relevant biomarkers in psychiatric disorders, and should encourage researchers to incorporate genetic information, such as PRS, in their search for clinically relevant neuroimaging biomarkers.

Nongenetic Factors Associated With Psychotic Experiences Among UK Biobank Participants: Exposome-Wide Analysis and Mendelian Randomization Analysis.

Importance: Although hypothesis-driven research has identified several factors associated with psychosis, this one-exposure-to-one-outcome approach fails to embrace the multiplicity of exposures. Systematic approaches, similar to agnostic genome-wide analyses, are needed to identify genuine signals. Objective: To systematically investigate nongenetic correlates of psychotic experiences through data-driven agnostic analyses and genetically informed approaches to evaluate associations. Design, Setting, Participants: This cohort study analyzed data from the UK Biobank Mental Health Survey from January 1 to June 1, 2021. An exposome-wide association study was performed in 2 equal-sized split discovery and replication data sets. Variables associated with psychotic experiences in the exposome-wide analysis were tested in a multivariable model. For the variables associated with psychotic experiences in the final multivariable model, the single-nucleotide variant-based heritability and genetic overlap with psychotic experiences using linkage disequilibrium score regression were estimated, and mendelian randomization (MR) approaches were applied to test potential causality. The significant associations observed in 1-sample MR analyses were further tested in multiple sensitivity tests, including collider-correction MR, 2-sample MR, and multivariable MR analyses. Exposures: After quality control based on a priori criteria, 247 environmental, lifestyle, behavioral, and economic variables. Main Outcomes and Measures: Psychotic experiences. Results: The study included 155 247 participants (87 896 [57%] female; mean [SD] age, 55.94 [7.74] years). In the discovery data set, 162 variables (66%) were associated with psychotic experiences. Of these, 148 (91%) were replicated. The multivariable analysis identified 36 variables that were associated with psychotic experiences. Of these, 28 had significant genetic overlap with psychotic experiences. One-sample MR analyses revealed forward associations with 3 variables and reverse associations with 3. Forward associations with ever having experienced sexual assault and pleiotropy of risk-taking behavior and reverse associations without pleiotropy of experiencing a physically violent crime as well as cannabis use and the reverse association with pleiotropy of worrying too long after embarrassment were confirmed in sensitivity tests. Thus, associations with psychotic experiences were found with both well-studied and unexplored multiple correlated variables. For several variables, the direction of the association was reversed in the final multivariable and MR analyses. Conclusions and Relevance: The findings of this study underscore the need for systematic approaches and triangulation of evidence to build a knowledge base from ever-growing observational data to guide population-level prevention strategies for psychosis.

Evidence, and replication thereof, that molecular-genetic and environmental risks for psychosis impact through an affective pathway.

BACKGROUND: There is evidence that environmental and genetic risk factors for schizophrenia spectrum disorders are transdiagnostic and mediated in part through a generic pathway of affective dysregulation. METHODS: We analysed to what degree the impact of schizophrenia polygenic risk (PRS-SZ) and childhood adversity (CA) on psychosis outcomes was contingent on co-presence of affective dysregulation, defined as significant depressive symptoms, in (i) NEMESIS-2 (n = 6646), a representative general population sample, interviewed four times over nine years and (ii) EUGEI (n = 4068) a sample of patients with schizophrenia spectrum disorder, the siblings of these patients and controls. RESULTS: The impact of PRS-SZ on psychosis showed significant dependence on co-presence of affective dysregulation in NEMESIS-2 [relative excess risk due to interaction (RERI): 1.01, p = 0.037] and in EUGEI (RERI = 3.39, p = 0.048). This was particularly evident for delusional ideation (NEMESIS-2: RERI = 1.74, p = 0.003; EUGEI: RERI = 4.16, p = 0.019) and not for hallucinatory experiences (NEMESIS-2: RERI = 0.65, p = 0.284; EUGEI: -0.37, p = 0.547). A similar and stronger pattern of results was evident for CA (RERI delusions and hallucinations: NEMESIS-2: 3.02, p < 0.001; EUGEI: 6.44, p < 0.001; RERI delusional ideation: NEMESIS-2: 3.79, p < 0.001; EUGEI: 5.43, p = 0.001; RERI hallucinatory experiences: NEMESIS-2: 2.46, p < 0.001; EUGEI: 0.54, p = 0.465). CONCLUSIONS: The results, and internal replication, suggest that the effects of known genetic and non-genetic risk factors for psychosis are mediated in part through an affective pathway, from which early states of delusional meaning may arise.

A replication study of JTC bias, genetic liability for psychosis and delusional ideation.

BACKGROUND: This study attempted to replicate whether a bias in probabilistic reasoning, or 'jumping to conclusions'(JTC) bias is associated with being a sibling of a patient with schizophrenia spectrum disorder; and if so, whether this association is contingent on subthreshold delusional ideation. METHODS: Data were derived from the EUGEI project, a 25-centre, 15-country effort to study psychosis spectrum disorder. The current analyses included 1261 patients with schizophrenia spectrum disorder, 1282 siblings of patients and 1525 healthy comparison subjects, recruited in Spain (five centres), Turkey (three centres) and Serbia (one centre). The beads task was used to assess JTC bias. Lifetime experience of delusional ideation and hallucinatory experiences was assessed using the Community Assessment of Psychic Experiences. General cognitive abilities were taken into account in the analyses. RESULTS: JTC bias was positively associated not only with patient status but also with sibling status [adjusted relative risk (aRR) ratio : 4.23 CI 95% 3.46-5.17 for siblings and aRR: 5.07 CI 95% 4.13-6.23 for patients]. The association between JTC bias and sibling status was stronger in those with higher levels of delusional ideation (aRR interaction in siblings: 3.77 CI 95% 1.67-8.51, and in patients: 2.15 CI 95% 0.94-4.92). The association between JTC bias and sibling status was not stronger in those with higher levels of hallucinatory experiences. CONCLUSIONS: These findings replicate earlier findings that JTC bias is associated with familial liability for psychosis and that this is contingent on the degree of delusional ideation but not hallucinations.

Examining facial emotion recognition as an intermediate phenotype for psychosis: Findings from the EUGEI study.

BACKGROUND: Social cognition impairments, such as facial emotion recognition (FER), have been acknowledged since the earliest description of schizophrenia. Here, we tested FER as an intermediate phenotype for psychosis using two approaches that are indicators of genetic risk for schizophrenia: the proxy-genetic risk approach (family design) and the polygenic risk score for schizophrenia (PRS-SCZ). METHODS: The sample comprised 2039 individuals with schizophrenia, 2141 siblings, and 2049 healthy controls (HC). The Degraded Facial Affect Recognition Task (DFAR) was applied to measure the FER accuracy. Schizotypal traits in siblings and HC were assessed using the Structured Interview for Schizotypy-Revised (SIS-R). The PRS-SCZ was trained using the Psychiatric Genomics Consortium results. Regression models were applied to test the association of DFAR with psychosis risk, SIS-R, and PRS-SCZ. RESULTS: The DFAR-total scores were lower in individuals with schizophrenia than in siblings (RR = 0.97 [95% CI 0.97, 0.97]), who scored lower than HC (RR = 0.99 [95% CI 0.99-1.00]). The DFAR-total scores were negatively associated with SIS-R total scores in siblings (B = -2.04 [95% CI -3.72, -0.36]) and HC (B = -2.93 [95% CI -5.50, -0.36]). Different patterns of association were observed for individual emotions. No significant associations were found between DFAR scores and PRS-SCZ. CONCLUSIONS: Our findings based on a proxy genetic risk approach suggest that FER deficits may represent an intermediate phenotype for schizophrenia. However, a significant association between FER and PRS-SCZ was not found. In the future, genetic mechanisms underlying FER phenotypes should be investigated trans-diagnostically.

Interrogating Associations Between Polygenic Liabilities and Electroconvulsive Therapy Effectiveness.

BACKGROUND: Electroconvulsive therapy (ECT) is the most effective treatment for severe major depressive episodes (MDEs). Nonetheless, firmly established associations between ECT outcomes and biological variables are currently lacking. Polygenic risk scores (PRSs) carry clinical potential, but associations with treatment response in psychiatry are seldom reported. Here, we examined whether PRSs for major depressive disorder, schizophrenia (SCZ), cross-disorder, and pharmacological antidepressant response are associated with ECT effectiveness. METHODS: A total of 288 patients with MDE from 3 countries were included. The main outcome was a change in the 17-item Hamilton Depression Rating Scale scores from before to after ECT treatment. Secondary outcomes were response and remission. Regression analyses with PRSs as independent variables and several covariates were performed. Explained variance (R2) at the optimal p-value threshold is reported. RESULTS: In the 266 subjects passing quality control, the PRS-SCZ was positively associated with a larger Hamilton Depression Rating Scale decrease in linear regression (optimal p-value threshold = .05, R2 = 6.94%, p < .0001), which was consistent across countries: Ireland (R2 = 8.18%, p = .0013), Belgium (R2 = 6.83%, p = .016), and the Netherlands (R2 = 7.92%, p = .0077). The PRS-SCZ was also positively associated with remission (R2 = 4.63%, p = .0018). Sensitivity and subgroup analyses, including in MDE without psychotic features (R2 = 4.42%, p = .0024) and unipolar MDE only (R2 = 9.08%, p < .0001), confirmed the results. The other PRSs were not associated with a change in the Hamilton Depression Rating Scale score at the predefined Bonferroni-corrected significance threshold. CONCLUSIONS: A linear association between PRS-SCZ and ECT outcome was uncovered. Although it is too early to adopt PRSs in ECT clinical decision making, these findings strengthen the positioning of PRS-SCZ as relevant to treatment response in psychiatry.