ABSTRACT
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.
Subject(s)
Schizophrenia , Humans , Adult , Schizophrenia/genetics , Brain , Genetic Risk Score , Multifactorial Inheritance , Cluster Analysis , Genetic Predisposition to DiseaseABSTRACT
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.
Subject(s)
Cognition , Exposome , Schizophrenic Psychology , Adult , Humans , Cross-Sectional Studies , Schizophrenia/epidemiology , Siblings/psychology , Case-Control Studies , Cognition Disorders/epidemiology , Male , FemaleABSTRACT
Importance: Understanding the origins of clinical heterogeneity in bipolar disorder (BD) will inform new approaches to stratification and studies of underlying mechanisms. Objective: To identify components of genetic liability that are shared between BD, schizophrenia, and major depressive disorder (MDD) and those that differentiate each disorder from the others and to examine associations between heterogeneity for key BD symptoms and each component. Design, Setting, and Participants: Using data from the Bipolar Disorder Research Network in the United Kingdom, components of liability were identified by applying genomic structural equation modeling to genome-wide association studies of schizophrenia, BD, and MDD. Polygenic risk scores (PRS) representing each component were tested for association with symptoms in an independent BD data set. Adults with DSM-IV BD or schizoaffective disorder, bipolar type, were included. Data were collected from January 2000 to December 2013, and data were analyzed from June 2020 to February 2022. Main Outcomes and Measures: PRS representing the components of liability were tested for association with mania and depression, psychosis, and mood incongruence of psychosis in participants with BD, measured using the Bipolar Affective Disorder Dimensional Scale. Results: Of 4429 included participants, 3012 (68.0%) were female, and the mean (SD) age was 46.2 (12.3) years. Mania and psychosis were associated with the shared liability component (mania ß = 0.29; 95% CI, 0.23-0.34; P = 3.04 × 10-25; psychosis ß = 0.05; 95% CI, 0.04-0.07; P = 2.33 × 10-13) and the components that differentiate each of schizophrenia (mania ß = 0.08; 95% CI, 0.03-0.14; P = .002; psychosis ß = 0.03; 95% CI, 0.01-0.04; P = 1.0 × 10-4) and BD (mania ß = 0.14; 95% CI, 0.09-0.20; P = 1.99 × 10-7; psychosis ß = 0.02; 95% CI, 0.01-0.03; P = .006) from the other disorders. The BD differentiating component was associated with mania independently of effects on psychosis (ß = 0.14; 95% CI, 0.08-0.20; P = 4.32 × 10-6) but not with psychosis independently of mania. Conversely, the schizophrenia differentiating component was associated with psychosis independently of effects on mania (ß = 0.01; 95% CI, 0.003-0.03; P = .02), but not with mania independently of psychosis. Mood incongruence of psychosis was associated only with the schizophrenia differentiating component (ß = 0.03; 95% CI, 0.01-0.05; P = .005). Depression was associated with higher MDD differentiating component (ß = 0.07; 95% CI, 0.01-0.12; P = .01) but lower BD differentiating component (ß = -0.11; 95% CI, -0.17 to -0.06; P = 7.06 × 10-5). Conclusions and Relevance: In this study of BD, clinical heterogeneity reflected the burden of liability to BD and the contribution of alleles that have differentiating effects on risk for other disorders; mania, psychosis, and depression were associated with the components of genetic liability differentiating BD, MDD, and schizophrenia, respectively. Understanding the basis of this etiological heterogeneity will be critical for identifying the different pathophysiological processes underlying BD, stratifying patients, and developing precision therapeutics.
Subject(s)
Bipolar Disorder , Depressive Disorder, Major , Schizophrenia , Adult , Bipolar Disorder/diagnosis , Bipolar Disorder/genetics , Bipolar Disorder/psychology , Depressive Disorder, Major/diagnosis , Depressive Disorder, Major/genetics , Female , Genome-Wide Association Study , Humans , Male , Mania , Middle Aged , Schizophrenia/diagnosis , Schizophrenia/geneticsABSTRACT
Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.
Subject(s)
Genome-Wide Association Study , Schizophrenia , Alleles , Genetic Predisposition to Disease/genetics , Genomics , Humans , Polymorphism, Single Nucleotide/genetics , Schizophrenia/geneticsABSTRACT
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.
Subject(s)
Facial Recognition/physiology , Phenotype , Psychotic Disorders/physiopathology , Siblings , Adult , Female , Genomics , Humans , Interviews as Topic , Male , Psychotic Disorders/genetics , Risk FactorsABSTRACT
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.
Subject(s)
Psychotic Disorders , Schizophrenia , Bias , Decision Making , Delusions/psychology , Hallucinations , Humans , Psychotic Disorders/psychology , Schizophrenia/geneticsABSTRACT
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.
Subject(s)
Psychotic Disorders , Schizophrenia , Humans , Psychotic Disorders/etiology , Psychotic Disorders/genetics , Hallucinations/etiology , Hallucinations/genetics , Schizophrenia/etiology , Schizophrenia/genetics , Multifactorial Inheritance , Risk , Delusions/diagnosisABSTRACT
BACKGROUND: A cumulative environmental exposure score for schizophrenia (exposome score for schizophrenia [ES-SCZ]) may provide potential utility for risk stratification and outcome prediction. Here, we investigated whether ES-SCZ was associated with functioning in patients with schizophrenia spectrum disorder, unaffected siblings, and healthy controls. METHODS: This cross-sectional sample consisted of 1,261 patients, 1,282 unaffected siblings, and 1,525 healthy controls. The Global Assessment of Functioning (GAF) scale was used to assess functioning. ES-SCZ was calculated based on our previously validated method. The association between ES-SCZ and the GAF dimensions (symptom and disability) was analyzed by applying regression models in each group (patients, siblings, and controls). Additional models included polygenic risk score for schizophrenia (PRS-SCZ) as a covariate. RESULTS: ES-SCZ was associated with the GAF dimensions in patients (symptom: B = -1.53, p-value = 0.001; disability: B = -1.44, p-value = 0.001), siblings (symptom: B = -3.07, p-value < 0.001; disability: B = -2.52, p-value < 0.001), and healthy controls (symptom: B = -1.50, p-value < 0.001; disability: B = -1.31, p-value < 0.001). The results remained the same after adjusting for PRS-SCZ. The degree of associations of ES-SCZ with both symptom and disability dimensions were higher in unaffected siblings than in patients and controls. By analyzing an independent dataset (the Genetic Risk and Outcome of Psychosis study), we replicated the results observed in the patient group. CONCLUSIONS: Our findings suggest that ES-SCZ shows promise for enhancing risk prediction and stratification in research practice. From a clinical perspective, ES-SCZ may aid in efforts of clinical characterization, operationalizing transdiagnostic clinical staging models, and personalizing clinical management.
Subject(s)
Exposome , Psychotic Disorders , Schizophrenia , Cross-Sectional Studies , Humans , Schizophrenia/genetics , SiblingsABSTRACT
We performed a systematic analysis of blood DNA methylation profiles from 4483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia, and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia.
Subject(s)
DNA Methylation , Epigenome , Psychotic Disorders/physiopathology , Schizophrenia, Treatment-Resistant/physiopathology , Adult , Aged , England , Female , Humans , Ireland , Male , Middle Aged , Psychotic Disorders/genetics , Schizophrenia, Treatment-Resistant/genetics , Scotland , Sweden , Young AdultABSTRACT
Schizophrenia is a highly polygenic disorder with important contributions from both common and rare risk alleles. We analyzed exome sequencing data for de novo variants (DNVs) in a new sample of 613 schizophrenia trios and combined this with published data to give a total of 3,444 trios. In this new data, loss-of-function (LoF) DNVs were significantly enriched among 3,471 LoF-intolerant genes, which supports previous findings. In the full dataset, genes associated with neurodevelopmental disorders (n = 159) were significantly enriched for LoF DNVs. Within these neurodevelopmental disorder genes, SLC6A1, which encodes a γ-aminobutyric acid transporter, was associated with missense-damaging DNVs. In 1,122 trios for which genome-wide common variant data were available, schizophrenia and bipolar disorder polygenic risk were significantly overtransmitted to probands. Probands carrying LoF or deletion DNVs in LoF-intolerant or neurodevelopmental disorder genes had significantly less overtransmission of schizophrenia polygenic risk than did non-carriers, which provides a second robust line of evidence that these DNVs increase liability to schizophrenia.
Subject(s)
GABA Plasma Membrane Transport Proteins/genetics , Genetic Predisposition to Disease/genetics , Schizophrenia/genetics , Adult , Female , Humans , Male , Mutation, Missense , Exome SequencingABSTRACT
BACKGROUND: Cognitive impairment is a clinically important feature of schizophrenia. Polygenic risk score (PRS) methods have demonstrated genetic overlap between schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), educational attainment (EA), and IQ, but very few studies have examined associations between these PRS and cognitive phenotypes within schizophrenia cases. METHODS: We combined genetic and cognitive data in 3034 schizophrenia cases from 11 samples using the general intelligence factor g as the primary measure of cognition. We used linear regression to examine the association between cognition and PRS for EA, IQ, schizophrenia, BD, and MDD. The results were then meta-analyzed across all samples. A genome-wide association studies (GWAS) of cognition was conducted in schizophrenia cases. RESULTS: PRS for both population IQ (P = 4.39 × 10-28) and EA (P = 1.27 × 10-26) were positively correlated with cognition in those with schizophrenia. In contrast, there was no association between cognition in schizophrenia cases and PRS for schizophrenia (P = .39), BD (P = .51), or MDD (P = .49). No individual variant approached genome-wide significance in the GWAS. CONCLUSIONS: Cognition in schizophrenia cases is more strongly associated with PRS that index cognitive traits in the general population than PRS for neuropsychiatric disorders. This suggests the mechanisms of cognitive variation within schizophrenia are at least partly independent from those that predispose to schizophrenia diagnosis itself. Our findings indicate that this cognitive variation arises at least in part due to genetic factors shared with cognitive performance in populations and is not solely due to illness or treatment-related factors, although our findings are consistent with important contributions from these factors.
Subject(s)
Bipolar Disorder/genetics , Depressive Disorder, Major/genetics , Educational Status , Genome-Wide Association Study , Intelligence/genetics , Psychotic Disorders/genetics , Schizophrenia/genetics , Datasets as Topic , Humans , Multifactorial InheritanceABSTRACT
Psychotic patients with a lifetime history of cannabis use generally show better cognitive functioning than other psychotic patients. Some authors suggest that cannabis-using patients may have been less cognitively impaired and less socially withdrawn in their premorbid life. Using a dataset comprising 948 patients with first-episode psychosis (FEP) and 1313 population controls across 6 countries, we examined the extent to which IQ and both early academic (Academic Factor [AF]) and social adjustment (Social Factor [SF]) are related to the lifetime frequency of cannabis use in both patients and controls. We expected a higher IQ and a better premorbid social adjustment in psychotic patients who had ever used cannabis compared to patients without any history of use. We did not expect such differences in controls. In both patients and controls, IQ was 3 points higher among occasional-users than in never-users (mean difference [Mdiff] = 2.9, 95% CI = [1.2, 4.7]). Both cases and control daily-users had lower AF compared to occasional (Mdiff = -0.3, 95% CI = [-0.5; -0.2]) and never-users (Mdiff = -0.4, 95% CI = [-0.6; -0.2]). Finally, patient occasional (Mdiff = 0.3, 95% CI = [0.1; 0.5]) and daily-users (Mdiff = 0.4, 95% CI = [0.2; 0.6]) had better SF than their never-using counterparts. This difference was not present in controls (Fgroup*frequency(2, 2205) = 4.995, P = .007). Our findings suggest that the better premorbid social functioning of FEP with a history of cannabis use may have contributed to their likelihood to begin using cannabis, exposing them to its reported risk-increasing effects for Psychotic Disorders.
Subject(s)
Intelligence , Marijuana Use/epidemiology , Psychosocial Functioning , Psychotic Disorders/epidemiology , Schizophrenia/epidemiology , Social Adjustment , Adolescent , Adult , Case-Control Studies , Comorbidity , Female , Humans , Intelligence/physiology , Male , Middle Aged , Young AdultABSTRACT
BACKGROUND: First-degree relatives of patients with psychotic disorder have higher levels of polygenic risk (PRS) for schizophrenia and higher levels of intermediate phenotypes. METHODS: We conducted, using two different samples for discovery (n = 336 controls and 649 siblings of patients with psychotic disorder) and replication (n = 1208 controls and 1106 siblings), an analysis of association between PRS on the one hand and psychopathological and cognitive intermediate phenotypes of schizophrenia on the other in a sample at average genetic risk (healthy controls) and a sample at higher than average risk (healthy siblings of patients). Two subthreshold psychosis phenotypes, as well as a standardised measure of cognitive ability, based on a short version of the WAIS-III short form, were used. In addition, a measure of jumping to conclusion bias (replication sample only) was tested for association with PRS. RESULTS: In both discovery and replication sample, evidence for an association between PRS and subthreshold psychosis phenotypes was observed in the relatives of patients, whereas in the controls no association was observed. Jumping to conclusion bias was similarly only associated with PRS in the sibling group. Cognitive ability was weakly negatively and non-significantly associated with PRS in both the sibling and the control group. CONCLUSIONS: The degree of endophenotypic expression of schizophrenia polygenic risk depends on having a sibling with psychotic disorder, suggestive of underlying gene-environment interaction. Cognitive biases may better index genetic risk of disorder than traditional measures of neurocognition, which instead may reflect the population distribution of cognitive ability impacting the prognosis of psychotic disorder.
Subject(s)
Gene-Environment Interaction , Multifactorial Inheritance , Psychotic Disorders/genetics , Schizophrenia/genetics , Siblings , Adult , Case-Control Studies , Endophenotypes , Europe , Female , Genetic Predisposition to Disease , Humans , Male , Middle Aged , Psychotic Disorders/psychology , Risk Factors , Schizophrenic Psychology , Young AdultABSTRACT
Introduction: White noise speech illusions index liability for psychotic disorder in case-control comparisons. In the current study, we examined i) the rate of white noise speech illusions in siblings of patients with psychotic disorder and ii) to what degree this rate would be contingent on exposure to known environmental risk factors (childhood adversity and recent life events) and level of known endophenotypic dimensions of psychotic disorder [psychotic experiences assessed with the Community Assessment of Psychic Experiences (CAPE) scale and cognitive ability]. Methods: The white noise task was used as an experimental paradigm to elicit and measure speech illusions in 1,014 patients with psychotic disorders, 1,157 siblings, and 1,507 healthy participants. We examined associations between speech illusions and increasing familial risk (control -> sibling -> patient), modeled as both a linear and a categorical effect, and associations between speech illusions and level of childhood adversities and life events as well as with CAPE scores and cognitive ability scores. Results: While a positive association was found between white noise speech illusions across hypothesized increasing levels of familial risk (controls -> siblings -> patients) [odds ratio (OR) linear 1.11, 95% confidence interval (CI) 1.02-1.21, p = 0.019], there was no evidence for a categorical association with sibling status (OR 0.93, 95% CI 0.79-1.09, p = 0.360). The association between speech illusions and linear familial risk was greater if scores on the CAPE positive scale were higher (p interaction = 0.003; ORlow CAPE positive scale 0.96, 95% CI 0.85-1.07; ORhigh CAPE positive scale 1.26, 95% CI 1.09-1.46); cognitive ability was lower (p interaction < 0.001; ORhigh cognitive ability 0.94, 95% CI 0.84-1.05; ORlow cognitive ability 1.43, 95% CI 1.23-1.68); and exposure to childhood adversity was higher (p interaction < 0.001; ORlow adversity 0.92, 95% CI 0.82-1.04; ORhigh adversity 1.31, 95% CI 1.13-1.52). A similar, although less marked, pattern was seen for categorical patient-control and sibling-control comparisons. Exposure to recent life events did not modify the association between white noise and familial risk (p interaction = 0.232). Conclusion: The association between white noise speech illusions and familial risk is contingent on additional evidence of endophenotypic expression and of exposure to childhood adversity. Therefore, speech illusions may represent a trait-dependent risk marker.
ABSTRACT
Exposures constitute a dense network of the environment: exposome. Here, we argue for embracing the exposome paradigm to investigate the sum of nongenetic "risk" and show how predictive modeling approaches can be used to construct an exposome score (ES; an aggregated score of exposures) for schizophrenia. The training dataset consisted of patients with schizophrenia and controls, whereas the independent validation dataset consisted of patients, their unaffected siblings, and controls. Binary exposures were cannabis use, hearing impairment, winter birth, bullying, and emotional, physical, and sexual abuse along with physical and emotional neglect. We applied logistic regression (LR), Gaussian Naive Bayes (GNB), the least absolute shrinkage and selection operator (LASSO), and Ridge penalized classification models to the training dataset. ESs, the sum of weighted exposures based on coefficients from each model, were calculated in the validation dataset. In addition, we estimated ES based on meta-analyses and a simple sum score of exposures. Accuracy, sensitivity, specificity, area under the receiver operating characteristic, and Nagelkerke's R2 were compared. The ESMeta-analyses performed the worst, whereas the sum score and the ESGNB were worse than the ESLR that performed similar to the ESLASSO and ESRIDGE. The ESLR distinguished patients from controls (odds ratio [OR] = 1.94, P < .001), patients from siblings (OR = 1.58, P < .001), and siblings from controls (OR = 1.21, P = .001). An increase in ESLR was associated with a gradient increase of schizophrenia risk. In reference to the remaining fractions, the ESLR at top 30%, 20%, and 10% of the control distribution yielded ORs of 3.72, 3.74, and 4.77, respectively. Our findings demonstrate that predictive modeling approaches can be harnessed to evaluate the exposome.
Subject(s)
Bullying/statistics & numerical data , Child Abuse/statistics & numerical data , Exposome , Hearing Loss/epidemiology , Marijuana Use/epidemiology , Schizophrenia/epidemiology , Siblings , Adult , Adverse Childhood Experiences/statistics & numerical data , Area Under Curve , Bayes Theorem , Case-Control Studies , Child , Child Abuse, Sexual/statistics & numerical data , Female , Humans , Logistic Models , Machine Learning , Male , Models, Statistical , Odds Ratio , ROC Curve , Seasons , Young AdultABSTRACT
Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.
Subject(s)
Bipolar Disorder/genetics , Genetic Loci , Bipolar Disorder/classification , Case-Control Studies , Depressive Disorder, Major/genetics , Female , Genetic Predisposition to Disease , Genome-Wide Association Study , Humans , Male , Polymorphism, Single Nucleotide , Psychotic Disorders/genetics , Schizophrenia/genetics , Systems BiologyABSTRACT
Schizophrenia is a heritable complex phenotype associated with a background risk involving multiple common genetic variants of small effect and a multitude of environmental exposures. Early twin and family studies using proxy-genetic liability measures suggest gene-environment interaction in the etiology of schizophrenia spectrum disorders, but the molecular evidence is scarce. Here, by analyzing the main and joint associations of polygenic risk score for schizophrenia (PRS-SCZ) and environmental exposures in 1,699 patients with a diagnosis of schizophrenia spectrum disorders and 1,542 unrelated controls with no lifetime history of a diagnosis of those disorders, we provide further evidence for gene-environment interaction in schizophrenia. Evidence was found for additive interaction of molecular genetic risk state for schizophrenia (binary mode of PRS-SCZ above 75% of the control distribution) with the presence of lifetime regular cannabis use and exposure to early-life adversities (sexual abuse, emotional abuse, emotional neglect, and bullying), but not with the presence of hearing impairment, season of birth (winter birth), and exposure to physical abuse or physical neglect in childhood. The sensitivity analyses replacing the a priori PRS-SCZ at 75% with alternative cut-points (50% and 25%) confirmed the additive interaction. Our results suggest that the etiopathogenesis of schizophrenia involves genetic underpinnings that act by making individuals more sensitive to the effects of some environmental exposures.
ABSTRACT
BACKGROUND: The value of the nosological distinction between non-affective and affective psychosis has frequently been challenged. We aimed to investigate the transdiagnostic dimensional structure and associated characteristics of psychopathology at First Episode Psychosis (FEP). Regardless of diagnostic categories, we expected that positive symptoms occurred more frequently in ethnic minority groups and in more densely populated environments, and that negative symptoms were associated with indices of neurodevelopmental impairment. METHOD: This study included 2182 FEP individuals recruited across six countries, as part of the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study. Symptom ratings were analysed using multidimensional item response modelling in Mplus to estimate five theory-based models of psychosis. We used multiple regression models to examine demographic and context factors associated with symptom dimensions. RESULTS: A bifactor model, composed of one general factor and five specific dimensions of positive, negative, disorganization, manic and depressive symptoms, best-represented associations among ratings of psychotic symptoms. Positive symptoms were more common in ethnic minority groups. Urbanicity was associated with a higher score on the general factor. Men presented with more negative and less depressive symptoms than women. Early age-at-first-contact with psychiatric services was associated with higher scores on negative, disorganized, and manic symptom dimensions. CONCLUSIONS: Our results suggest that the bifactor model of psychopathology holds across diagnostic categories of non-affective and affective psychosis at FEP, and demographic and context determinants map onto general and specific symptom dimensions. These findings have implications for tailoring symptom-specific treatments and inform research into the mood-psychosis spectrum.
Subject(s)
Psychopathology , Psychotic Disorders/classification , Psychotic Disorders/psychology , Schizophrenia/classification , Schizophrenic Psychology , Adult , Affective Disorders, Psychotic , Bipolar Disorder/psychology , Depression/psychology , Europe , Female , Humans , Male , Models, Psychological , Psychiatric Status Rating Scales , ROC Curve , Young AdultABSTRACT
BACKGROUND: Sequencing studies have pointed to the involvement in schizophrenia of rare coding variants in neuronally expressed genes, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-D-aspartate receptor (NMDAR) complexes; however, larger samples are required to reveal novel genes and specific biological mechanisms. METHODS: We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5207 cases and 4991 controls. Included among these genes were members of ARC and NMDAR postsynaptic protein complexes, as well as voltage-gated sodium and calcium channels. We performed a rare variant meta-analysis with published sequencing data for a total of 11,319 cases, 15,854 controls, and 1136 trios. RESULTS: While no individual gene was significantly associated with schizophrenia after genome-wide correction for multiple testing, we strengthen the evidence that rare exonic variants in the ARC (p = 4.0 × 10-4) and NMDAR (p = 1.7 × 10-5) synaptic complexes are risk factors for schizophrenia. In addition, we found that loss-of-function variants and missense variants at paralog-conserved sites were enriched in voltage-gated sodium channels, particularly the alpha subunits (p = 8.6 × 10-4). CONCLUSIONS: In one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis and confirm the involvement of ARC and NMDAR postsynaptic complexes.
Subject(s)
Cytoskeletal Proteins/genetics , Nerve Tissue Proteins/genetics , Neurons/physiology , Receptors, N-Methyl-D-Aspartate/genetics , Schizophrenia/genetics , Schizophrenia/physiopathology , Sequence Analysis, DNA , Voltage-Gated Sodium Channels/genetics , Adult , Cohort Studies , Humans , Ireland , Middle Aged , Netherlands , Risk Factors , United KingdomABSTRACT
Studies have suggested that Research Diagnostic Criteria for Schizoaffective Disorder Bipolar type (RDC-SABP) might identify a more genetically homogenous subgroup of bipolar disorder. Aiming to identify loci associated with RDC-SABP, we have performed a replication study using independent RDC-SABP cases (n = 144) and controls (n = 6,559), focusing on the 10 loci that reached a p-value <10-5 for RDC-SABP in the Wellcome Trust Case Control Consortium (WTCCC) bipolar disorder sample. Combining the WTCCC and replication datasets by meta-analysis (combined RDC-SABP, n = 423, controls, n = 9,494), we observed genome-wide significant association at one SNP, rs2352974, located within the intron of the gene TRAIP on chromosome 3p21.31 (p-value, 4.37 × 10-8 ). This locus did not reach genome-wide significance in bipolar disorder or schizophrenia large Psychiatric Genomic Consortium datasets, suggesting that it may represent a relatively specific genetic risk for the bipolar subtype of schizoaffective disorder.