Schizophrenia Polygenic Risk Scores Research Articles

Polygenic Risk and Episode Polarity Among Individuals With Bipolar Disorder.

The authors investigated associations between polygenic liabilities for bipolar disorder, major depression, and schizophrenia and episode polarity among individuals with bipolar disorder. The sample consisted of 2,705 individuals diagnosed with bipolar disorder at Danish psychiatric hospitals between January 1995 and March 2017. DNA was obtained from dried blood spots collected at birth as part of routine screening. Polygenic risk scores (PRSs) for bipolar disorder, major depression, and schizophrenia were generated using a meta-PRS method combining internally and externally trained components. Associations between PRS and polarity at first episode, polarity at any episode, and number of episodes with a given polarity were evaluated for each disorder-specific PRS using logistic and negative binominal regressions adjusted for the other two PRSs, age, sex, genotype platform, and five ancestral principal components. PRS for bipolar disorder was positively associated with any manic episodes (odds ratio=1.23, 95% CI=1.09-1.38). PRS for depression was positively associated with any depressive (odds ratio=1.11, 95% CI=1.01-1.23) and mixed (odds ratio=1.15, 95% CI=1.03-1.28) episodes and negatively associated with any manic episodes (odds ratio=0.76, 95% CI=0.69-0.84). PRS for schizophrenia was positively associated with any manic episodes (odds ratio=1.13, 95% CI=1.01-1.27), but only when psychotic symptoms were present (odds ratio for psychotic mania: 1.27, 95% CI=1.05-1.54; odds ratio for nonpsychotic mania: 1.06, 95% CI=0.93-1.20). These patterns were similar for first-episode polarity and for the number of episodes within each pole. PRSs for bipolar disorder, major depression, and schizophrenia are associated with episode polarity and psychotic symptoms in a congruent manner among individuals with bipolar disorder.

Polygenic risk scores for schizophrenia and treatment resistance: New data, systematic review and meta-analysis

Although treatment-resistant schizophrenia (TRS) is an important and frequent problem with a specific treatment, clozapine, its biological determinants are poorly understood. At the genetic level, most studies of association between schizophrenia polygenic risk score (SCZ PRS) and TRS did not reach statistical significance. However, no systematic review or meta-analysis of this type of study has been conducted. In this work, we first performed an association study between SCZ PRS and TRS in a sample of 427 patients with schizophrenia. Then, we carried out a systematic review and meta-analysis of all available data. PubMed was searched for articles reporting association between SCZ PRS and TRS, defined as use of clozapine or failure of two sequentially prescribed antipsychotics. The association in our sample was not statistically significant. Five studies met the inclusion criteria, involving 7309 patients, 2386 (33 %) with TRS. Fixed effect model meta-analysis revealed a statistically significant association with TRS status (OR = 1.090, 95 % CI = 1.030–1.154; P = 0.0027; I2 = 0.00 %). The robustness of the result was demonstrated by maintaining a statistically significant association in all sensitivity analyses, such as a leave-one-out approach or use of a random effects model. Therefore, at least part of the genetic susceptibility to TRS is shared with that of schizophrenia. However, our results did not support the clinical utility of the SCZ PRS in its current stage due to the small effect size. Improvements in PRS estimation and combination with other predictors may lead to future use in stratification of patients.

Effect of polygenic risk for schizophrenia on cardiac structure and function: a UK Biobank observational study

Cardiovascular disease is a major cause of excess mortality in people with schizophrenia. Several factors are responsible, including lifestyle and metabolic effects of antipsychotics. However, variations in cardiac structure and function are seen in people with schizophrenia in the absence of cardiovascular disease risk factors and after accounting for lifestyle and medication. Therefore, we aimed to explore whether shared genetic causes contribute to these cardiac variations. For this observational study, we used data from the UK Biobank and included White British or Irish individuals without diagnosed schizophrenia with variable polygenic risk scores for the condition. To test the association between polygenic risk score for schizophrenia and cardiac phenotype, we used principal component analysis and regression. Robust regression was then used to explore the association between the polygenic risk score for schizophrenia and individual cardiac phenotypes. We repeated analyses with fibro-inflammatory pathway-specific polygenic risk scores for schizophrenia. Last, we investigated genome-wide sharing of common variants between schizophrenia and cardiac phenotypes using linkage disequilibrium score regression. The primary outcome was principal component regression. Of 33 353 individuals recruited, 32 279 participants had complete cardiac MRI data and were included in the analysis, of whom 16 625 (51·5%) were female and 15 654 (48·5%) were male. 1074 participants were excluded on the basis of incomplete cardiac MRI data (for all phenotypes). A model regressing polygenic risk scores for schizophrenia onto the first five cardiac principal components of the principal components analysis was significant (F=5·09; p=0·00012). Principal component 1 captured a pattern of increased cardiac volumes, increased absolute peak diastolic strain rates, and reduced ejection fractions; polygenic risk scores for schizophrenia and principal component 1 were negatively associated (β=-0·01 [SE 0·003]; p=0·017). Similar to the principal component analysis results, for individual cardiac phenotypes, we observed negative associations between polygenic risk scores for schizophrenia and indexed right ventricular end-systolic volume (β=-0·14 [0·04]; p=0·0013, pFDR=0·015), indexed right ventricular end-diastolic volume (β=-0·17 [0·08]); p=0·025; pFDR=0·082), and absolute longitudinal peak diastolic strain rates (β=-0·01 [0·003]; p=0·0024, pFDR=0·015), and a positive association between polygenic risk scores for schizophrenia and right ventricular ejection fraction (β=0·09 [0·03]; p=0·0041, pFDR=0·015). Models examining the transforming growth factor-β (TGF-β)-specific and acute inflammation-specific polygenic risk scores for schizophrenia found significant associations with the first five principal components (F=2·62, p=0·022; F=2·54, p=0·026). Using linkage disequilibrium score regression, we observed genetic overlap with schizophrenia for right ventricular end-systolic volume and right ventricular ejection fraction (p=0·0090, p=0·0077). High polygenic risk scores for schizophrenia are associated with decreased cardiac volumes, increased ejection fractions, and decreased absolute peak diastolic strain rates. TGF-β and inflammatory pathways might be implicated, and there is evidence of genetic overlap for some cardiac phenotypes. Reduced absolute peak diastolic strain rates indicate increased myocardial stiffness and diastolic dysfunction, which increases risk of cardiac disease. Thus, genetic risk for schizophrenia is associated with cardiac structural changes that can worsen cardiac outcomes. Further work is required to determine whether these associations are specific to schizophrenia or are also seen in other psychiatric conditions. National Institute for Health Research, Maudsley Charity, Wellcome Trust, Medical Research Council, Academy of Medical Sciences, Edmond J Safra Foundation, British Heart Foundation.

Associations Between Cannabis Use, Polygenic Liability for Schizophrenia, and Cannabis-related Experiences in a Sample of Cannabis Users.

Risk for cannabis use and schizophrenia is influenced in part by genetic factors, and there is evidence that genetic risk for schizophrenia is associated with subclinical psychotic-like experiences (PLEs). Few studies to date have examined whether genetic risk for schizophrenia is associated with cannabis-related PLEs. We tested whether measures of cannabis involvement and polygenic risk scores (PRS) for schizophrenia were associated with self-reported cannabis-related experiences in a sample ascertained for alcohol use disorders (AUDs), the Collaborative Study on the Genetics of Alcoholism (COGA). We analyzed 4832 subjects (3128 of European ancestry and 1704 of African ancestry; 42% female; 74% meeting lifetime criteria for an AUD). Cannabis use disorder (CUD) was prevalent in this analytic sample (70%), with 40% classified as mild, 25% as moderate, and 35% as severe. Polygenic risk for schizophrenia was positively associated with cannabis-related paranoia, feeling depressed or anhedonia, social withdrawal, and cognitive difficulties, even when controlling for duration of daily cannabis use, CUD, and age at first cannabis use. The schizophrenia PRS was most robustly associated with cannabis-related cognitive difficulties (β = 0.22, SE = 0.04, P = 5.2e-7). In an independent replication sample (N = 1446), associations between the schizophrenia PRS and cannabis-related experiences were in the expected direction and not statistically different in magnitude from those in the COGA sample. Among individuals who regularly use cannabis, genetic liability for schizophrenia-even in those without clinical features-may increase the likelihood of reporting unusual experiences related to cannabis use.

Relationship between polygenic risk scores and symptom dimensions of schizophrenia and schizotypy in multiplex families with schizophrenia.

Psychotic disorders and schizotypal traits aggregate in the relatives of probands with schizophrenia. It is currently unclear how variability in symptom dimensions in schizophrenia probands and their relatives is associated with polygenic liability to psychiatric disorders. To investigate whether polygenic risk scores (PRSs) can predict symptom dimensions in members of multiplex families with schizophrenia. The largest genome-wide data-sets for schizophrenia, bipolar disorder and major depressive disorder were used to construct PRSs in 861 participants from the Irish Study of High-Density Multiplex Schizophrenia Families. Symptom dimensions were derived using the Operational Criteria Checklist for Psychotic Disorders in participants with a history of a psychotic episode, and the Structured Interview for Schizotypy in participants without a history of a psychotic episode. Mixed-effects linear regression models were used to assess the relationship between PRS and symptom dimensions across the psychosis spectrum. Schizophrenia PRS is significantly associated with the negative/disorganised symptom dimension in participants with a history of a psychotic episode (P = 2.31 × 10-4) and negative dimension in participants without a history of a psychotic episode (P = 1.42 × 10-3). Bipolar disorder PRS is significantly associated with the manic symptom dimension in participants with a history of a psychotic episode (P = 3.70 × 10-4). No association with major depressive disorder PRS was observed. Polygenic liability to schizophrenia is associated with higher negative/disorganised symptoms in participants with a history of a psychotic episode and negative symptoms in participants without a history of a psychotic episode in multiplex families with schizophrenia. These results provide genetic evidence in support of the spectrum model of schizophrenia, and support the view that negative and disorganised symptoms may have greater genetic basis than positive symptoms, making them better indices of familial liability to schizophrenia.

Genetic Relationship between Alzheimer’s Disease and Schizophrenia

AbstractBackgroundLarge genome‐wide association studies (GWASs) have demonstrated that common genetic variation contributes to the heritability of brain disorders, including Alzheimer’s disease and schizophrenia. Patients with Alzheimer’s disease and schizophrenia often have similar symptoms such as cognitive decline and hallucinations. Excessive synaptic pruning resulting from neuroinflammation and microglial activation are considered to play an important role in the development of both diseases. However, the genetic correlation between Alzheimer’s disease and schizophrenia is unclear.MethodIn this study, we used genotyping data of Alzheimer’s disease and schizophrenia to examine the genetic relationship between the two diseases. We calculated polygenic risk scores (PRSs) at multiple thresholds for both diseases and tested their relationship using logistic and linear regression.ResultWe found that schizophrenia PRSs were negatively associated with Alzheimer’s disease at multiple thresholds. The most significant association (p = 2.24 x 10‐9) was obtained at GWAS threshold p = 0.5. Vice versa, Alzheimer’s disease PRSs were positively associated with schizophrenia. The most significant signal (p = 4.10 x 10‐8) was obtained at GWAS threshold p = 0.1. Logic regression showed there was a strong correlation between the best schizophrenia PRSs and diagnosis of Alzheimer’s disease. The same held with the best Alzheimer’s disease PRSs and diagnosis of schizophrenia. Further, we found that there was a significant linear correction between the best PRSs of Alzheimer’s disease and schizophrenia in the Alzheimer’s disease dataset (R = 0.27, p < 2.2 x 10‐16).ConclusionOur study indicated that there is a strong genetic correlation between Alzheimer’s disease and schizophrenia, suggesting GWAS data from each disease might help to build a better risk prediction model for clinical risk assessment. Further studies on the shared risk variants/genes/pathways may help to better understand the mechanisms behind the two diseases for earlier disease prediction, diagnosis, and prevention.

A Blueprint for Genetic Determinism

A Blueprint for Genetic Determinism

Polygenic risk scores for schizophrenia and major depression are associated with socio-economic indicators of adversity in two British community samples

Schizophrenia (SCZ) and major depressive disorder (MDD) are complex psychiatric disorders which contribute substantially to the global burden of disease. Both psychopathologies are heritable with some genetic overlap between them. Importantly, SCZ and MDD have also been found to be associated with environmental risk factors. However, rather than being independent of genetic influences, exposure to environmental risk factors may be under genetic control, known as gene-environment correlation (rGE). In this study we investigated rGE in relation to polygenic risk scores for SCZ and MDD in adults, derived from large genome-wide association studies, across two different British community samples: Understanding Society (USoc) and the National Child Development Study (NCDS). We tested whether established environmental risk factors for SCZ and/or MDD are correlated with polygenic scores in adults and whether these associations differ between the two disorders and cohorts. Findings partially overlapped between disorders and cohorts. In NCDS, we identified a significant correlation between the genetic risk for MDD and an indicator of low socio-economic status, but no significant findings emerged for SCZ. In USoc, we replicated associations between indicators of low socio-economic status and the genetic propensity for MDD. In addition, we identified associations between the genetic susceptibility for SCZ and being single or divorced. Results across both studies provide further evidence that the genetic risk for SCZ and MDD were associated with common environmental risk factors, specifically MDD’s association with lower socio-economic status.

Polygenic heterogeneity in antidepressant treatment and placebo response

The genetic architecture of antidepressant response is poorly understood. Polygenic risk scores (PRS), exploration of placebo response and the use of sub-scales might provide insights. Here, we investigate the association between PRSs for relevant complex traits and response to vortioxetine treatment and placebo using clinical scales, including sub-scales and self-reported assessments. We collected a clinical test sample of Major Depressive Disorder (MDD) patients treated with vortioxetine (N = 907) or placebo (N = 455) from seven randomized, double-blind, clinical trials. In parallel, we obtained data from an observational web-based study of vortioxetine-treated patients (N = 642) with self-reported response. PRSs for antidepressant response, psychiatric disorders, and symptom traits were derived using summary statistics from well-powered genome-wide association studies (GWAS). Association tests were performed between the PRSs and treatment response in each of the two test samples and empirical p-values were evaluated. In the clinical test sample, no PRSs were significantly associated with response to vortioxetine treatment or placebo following Bonferroni correction. However, clinically assessed treatment response PRS was nominally associated with vortioxetine treatment and placebo response given by several secondary outcome scales (improvement on HAM-A, HAM-A Psychic Anxiety sub-scale, CPFQ & PDQ), (P ≤ 0.026). Further, higher subjective well-being PRS (P ≤ 0.033) and lower depression PRS (P = 0.01) were nominally associated with higher placebo response. In the self-reported test sample, higher schizophrenia PRS was significantly associated with poorer self-reported response (P = 0.0001). The identified PRSs explain a low proportion of the variance (1.2–5.3%) in placebo and treatment response. Although the results were limited, we believe that PRS associations bear unredeemed potential as a predictor for treatment response, as more well-powered and phenotypically similar GWAS bases become available.

Gene set enrichment analysis of pathophysiological pathways highlights oxidative stress in psychosis

Polygenic risk prediction remains an important aim of genetic association studies. Currently, the predictive power of schizophrenia polygenic risk scores (PRSs) is not large enough to allow highly accurate discrimination between cases and controls and thus is not adequate for clinical integration. Since PRSs are rarely used to reveal biological functions or to validate candidate pathways, to fill this gap, we investigated whether their predictive ability could be improved by building genome-wide (GW-PRSs) and pathway-specific PRSs, using distance- or expression quantitative trait loci (eQTLs)- based mapping between genetic variants and genes. We focused on five pathways (glutamate, oxidative stress, GABA/interneurons, neuroimmune/neuroinflammation and myelin) which belong to a critical hub of schizophrenia pathophysiology, centred on redox dysregulation/oxidative stress. Analyses were first performed in the Lausanne Treatment and Early Intervention in Psychosis Program (TIPP) study (n = 340, cases/controls: 208/132), a sample of first-episode of psychosis patients and matched controls, and then validated in an independent study, the epidemiological and longitudinal intervention program of First-Episode Psychosis in Cantabria (PAFIP) (n = 352, 224/128). Our results highlighted two main findings. First, GW-PRSs for schizophrenia were significantly associated with early psychosis status. Second, oxidative stress was the only significantly associated pathway that showed an enrichment in both the TIPP (p = 0.03) and PAFIP samples (p = 0.002), and exclusively when gene-variant linking was done using eQTLs. The results suggest that the predictive accuracy of polygenic risk scores could be improved with the inclusion of information from functional annotations, and through a focus on specific pathways, emphasizing the need to build and study functionally informed risk scores.

Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia, Bipolar Disorder, and Depression Among Adults in the US Veterans Affairs Health Care System

Serious mental illnesses, including schizophrenia, bipolar disorder, and depression, are heritable, highly multifactorial disorders and major causes of disability worldwide. To benchmark the penetrance of current neuropsychiatric polygenic risk scores (PRSs) in the Veterans Health Administration health care system and to explore associations between PRS and broad categories of human disease via phenome-wide association studies. Extensive Veterans Health Administration's electronic health records were assessed from October 1999 to January 2021, and an embedded cohort of 9378 individuals with confirmed diagnoses of schizophrenia or bipolar 1 disorder were found. The performance of schizophrenia, bipolar disorder, and major depression PRSs were compared in participants of African or European ancestry in the Million Veteran Program (approximately 400 000 individuals), and associations between PRSs and 1650 disease categories based on ICD-9/10 billing codes were explored. Last, genomic structural equation modeling was applied to derive novel PRSs indexing common and disorder-specific genetic factors. Analysis took place from January 2021 to January 2022. Diagnoses based on in-person structured clinical interviews were compared with ICD-9/10 billing codes. PRSs were constructed using summary statistics from genome-wide association studies of schizophrenia, bipolar disorder, and major depression. Of 707 299 enrolled study participants, 459 667 were genotyped at the time of writing; 84 806 were of broadly African ancestry (mean [SD] age, 58 [12.1] years) and 314 909 were of broadly European ancestry (mean [SD] age, 66.4 [13.5] years). Among 9378 individuals with confirmed diagnoses of schizophrenia or bipolar 1 disorder, 8962 (95.6%) were correctly identified using ICD-9/10 codes (2 or more). Among those of European ancestry, PRSs were robustly associated with having received a diagnosis of schizophrenia (odds ratio [OR], 1.81 [95% CI, 1.76-1.87]; P < 10-257) or bipolar disorder (OR, 1.42 [95% CI, 1.39-1.44]; P < 10-295). Corresponding effect sizes in participants of African ancestry were considerably smaller for schizophrenia (OR, 1.35 [95% CI, 1.29-1.42]; P < 10-38) and bipolar disorder (OR, 1.16 [95% CI, 1.11-1.12]; P < 10-10). Neuropsychiatric PRSs were associated with increased risk for a range of psychiatric and physical health problems. Using diagnoses confirmed by in-person structured clinical interviews and current neuropsychiatric PRSs, the validity of an electronic health records-based phenotyping approach in US veterans was demonstrated, highlighting the potential of PRSs for disentangling biological and mediated pleiotropy.

Association Between Polygenic Risk Scores and Outcome of ECT.

Identifying biomarkers associated with response to electroconvulsive therapy (ECT) may aid clinical decisions. The authors examined whether greater polygenic liabilities for major depressive disorder, bipolar disorder, and schizophrenia are associated with improvement following ECT for a major depressive episode. Between 2013 and 2017, patients who had at least one treatment series recorded in the Swedish National Quality Register for ECT were invited to provide a blood sample for genotyping. The present study included 2,320 participants (median age, 51 years; 62.8% women) who had received an ECT series for a major depressive episode (77.1% unipolar depression), who had a registered treatment outcome, and whose polygenic risk scores (PRSs) could be calculated. Ordinal logistic regression was used to estimate the effect of PRS on Clinical Global Impressions improvement scale (CGI-I) score after each ECT series. Greater PRS for major depressive disorder was significantly associated with less improvement on the CGI-I (odds ratio per standard deviation, 0.89, 95% CI=0.82, 0.96; R2=0.004), and greater PRS for bipolar disorder was associated with greater improvement on the CGI-I (odds ratio per standard deviation, 1.14, 95% CI=1.05, 1.23; R2=0.005) after ECT. PRS for schizophrenia was not associated with improvement. In an overlapping sample (N=1,207) with data on response and remission derived from the self-rated version of the Montgomery-Åsberg Depression Rating Scale, results were similar except that schizophrenia PRS was also associated with remission. Improvement after ECT is associated with polygenic liability for major depressive disorder and bipolar disorder, providing evidence of a genetic component for ECT clinical response. These liabilities may be considered along with clinical predictors in future prediction models of ECT outcomes.

Schizophrenia Polygenic Risk During Typical Development Reflects Multiscale Cortical Organization

BackgroundSchizophrenia is widely recognized as a neurodevelopmental disorder. Abnormal cortical development in otherwise typically developing children and adolescents may be revealed using polygenic risk scores for schizophrenia (PRS-SCZ). MethodsWe assessed PRS-SCZ and cortical morphometry in typically developing children and adolescents (3–21 years, 46.8% female) using whole-genome genotyping and T1-weighted magnetic resonance imaging (n = 390) from the PING (Pediatric Imaging, Neurocognition, and Genetics) cohort. We contextualized the findings using 1) age-matched transcriptomics, 2) histologically defined cytoarchitectural types and functionally defined networks, and 3) case-control differences of schizophrenia and other major psychiatric disorders derived from meta-analytic data of 6 ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) working groups, including a total of 12,876 patients and 15,670 control participants. ResultsHigher PRS-SCZ was associated with greater cortical thickness, which was most prominent in areas with heightened gene expression of dendrites and synapses. PRS-SCZ–related increases in vertexwise cortical thickness were mainly distributed in association cortical areas, particularly the ventral attention network, while relatively sparing koniocortical type cortex (i.e., primary sensory areas). The large-scale pattern of cortical thickness increases related to PRS-SCZ mirrored the pattern of cortical thinning in schizophrenia and mood-related psychiatric disorders derived from the ENIGMA consortium. Age group models illustrate a possible trajectory from PRS-SCZ–associated cortical thickness increases in early childhood toward thinning in late adolescence, with the latter resembling the adult brain phenotype of schizophrenia. ConclusionsCollectively, combining imaging genetics with multiscale mapping, our work provides novel insight into how genetic risk for schizophrenia affects the cortex early in life.

Genetic assortative mating for schizophrenia and bipolar disorder.

Psychiatric disorders are highly polygenic and show patterns of partner resemblance. Partner resemblance has direct population-level genetic implications if it is caused by assortative mating, but not if it is caused by convergence or social homogamy. Using genetics may help distinguish these different mechanisms. Here, we investigated whether partner resemblance for schizophrenia and bipolar disorder is influenced by assortative mating using polygenic risk scores (PRSs). PRSs from The Danish High-Risk and Resilience Study-VIA 7 were compared between parents in three subsamples: population-based control parent pairs (N=198), parent pairs where at least one parent had schizophrenia (N=193), and parent pairs where at least one parent had bipolar disorder (N=115). The PRS for schizophrenia was predictive of schizophrenia in the full sample and showed a significant correlation between parent pairs (r=0.121, p=0.0440), indicative of assortative mating. The PRS for bipolar disorder was also correlated between parent pairs (r=0.162, p=0.0067), but it was not predictive of bipolar disorder in the full sample, limiting the interpretation. Our study provides genetic evidence for assortative mating for schizophrenia, with important implications for our understanding of the genetics of schizophrenia.

Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network

Schizophrenia is a highly heritable psychiatric disorder characterized by widespread functional and structural brain abnormalities. However, previous association studies between MRI and polygenic risk were mostly ROI-based single modality analyses, rather than identifying brain-based multimodal predictive biomarkers. Based on schizophrenia polygenic risk scores (PRS) from healthy white people within the UK Biobank dataset (N = 22,459), we discovered a robust PRS-associated brain pattern with smaller gray matter volume and decreased functional activation in frontotemporal cortex, which distinguished schizophrenia from controls with >83% accuracy, and predicted cognition and symptoms across 4 independent schizophrenia cohorts. Further multi-disease comparisons demonstrated that these identified frontotemporal alterations were most severe in schizophrenia and schizo-affective patients, milder in bipolar disorder, and indistinguishable from controls in autism, depression and attention-deficit hyperactivity disorder. These findings indicate the potential of the identified PRS-associated multimodal frontotemporal network to serve as a trans-diagnostic gene intermediated brain biomarker specific to schizophrenia.

Genome-Transcriptome-Functional Connectivity-Cognition Link Differentiates Schizophrenia From Bipolar Disorder.

Schizophrenia (SZ) and bipolar disorder (BD) share genetic risk factors, yet patients display differential levels of cognitive impairment. We hypothesized a genome-transcriptome-functional connectivity (frontoparietal)-cognition pathway linked to SZ-versus-BD differences, and conducted a multiscale study to delineate this pathway. Large genome-wide studies provided single nucleotide polymorphisms (SNPs) conferring more risk for SZ than BD, and we identified their regulated genes, namely SZ-biased SNPs and genes. We then (a) computed the polygenic risk score for SZ (PRSSZ) of SZ-biased SNPs and examined its associations with imaging-based frontoparietal functional connectivity (FC) and cognitive performances; (b) examined the spatial correlation between ex vivo postmortem expressions of SZ-biased genes and in vivo, SZ-related FC disruptions across frontoparietal regions; (c) investigated SZ-versus-BD differences in frontoparietal FC; and (d) assessed the associations of frontoparietal FC with cognitive performances. PRSSZ of SZ-biased SNPs was significantly associated with frontoparietal FC and working memory test scores. SZ-biased genes' expressions significantly correlated with SZ-versus-BD differences in FC across frontoparietal regions. SZ patients showed more reductions in frontoparietal FC than BD patients compared to controls. Frontoparietal FC was significantly associated with test scores of multiple cognitive domains including working memory, and with the composite scores of all cognitive domains. Collectively, these multiscale findings support the hypothesis that SZ-biased genetic risk, through transcriptome regulation, is linked to frontoparietal dysconnectivity, which in turn contributes to differential cognitive deficits in SZ-versus BD, suggesting that potential biomarkers for more precise patient stratification and treatment.

Ultrarare Coding Variants and Cognitive Function in Schizophrenia

Impaired cognitive function in schizophrenia is associated with poor functional outcomes, but the role of rare coding variants is unclear. To determine whether ultrarare constrained variants (URCVs) are associated with cognition in patients with schizophrenia. Linear regression was used to perform a within-case genetic association study of URCVs and current cognition and premorbid cognitive ability. A multivariable linear regression analysis of the outcomes associated with URCVs, schizophrenia polygenic risk score, polygenic risk score for intelligence and schizophrenia associated copy number variants on cognitive ability was performed. Exome sequencing data from 802 participants with schizophrenia were assessed for current cognition using the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery and for estimated premorbid IQ using the National Adult Reading Test. Individuals were recruited from clinical and voluntary mental health services in the UK. Those with a diagnosis of intellectual disability or a neurological disorder known to affect cognition were excluded. Data collection occurred between 2007 and 2015. Data were analyzed between April 2020 and March 2022. Association between URCVs, current cognition, and current cognition adjusted for premorbid IQ. Of the 802 participants, 499 (62%) were men and 303 (38%) were women; mean (SD) age at interview was 43.36 (11.87) years. Ultrarare constrained variants (n = 400) were associated with lower current cognition scores (β = -0.18; SE = 0.07; P = .005). In the univariable analysis, premorbid IQ was associated with URCVs (β = -0.12; SE = 0.05; P = .02) and partly attenuated the association with current cognition (β = -0.09; SE = 0.05; P = .08). Multivariable analysis showed that measured genetic factors combined accounted for 6.2% of variance in current cognition, 10.3% of variance in premorbid IQ, and supported outcomes of URCVs associated with current cognition independent of premorbid IQ (β = -0.10; SE = 0.05; P = .03). The findings of this study suggest that URCVs contribute to variance in cognitive function in schizophrenia, with partly independent associations before and after onset of the disorder. Although the estimated effect sizes were small, future studies may show that the effect sizes will be greater with better annotation of pathogenic variants. Genomic data may contribute to identifying those at particularly high risk of cognitive impairment in whom early remedial or preventive measures can be implemented.

Polygenic risk for schizophrenia as a moderator of associations between childhood trauma and schizotypy

Recent evidence shows that genetic and environmental risk factors for psychotic disorders are associated with higher levels of schizotypy (or psychosis proneness) in the general population. However, little is known about how these risk factors interact. We specifically examined whether genetic loading for schizophrenia moderates the association between childhood trauma severity and schizotypy. Schizotypy was measured using the Schizotypal Personality Questionnaire (SPQ), and childhood trauma severity was measured with the Childhood Trauma Questionnaire (CTQ) among a total of 168 participants (comprising 51 healthy individuals, 56 diagnosed with schizophrenia, and 61 with bipolar disorder). Polygenic risk scores (PRS) for schizophrenia were calculated for all participants and examined as a potential moderator of associations between total scores on the CTQ and schizotypy total scores and dimensions (i.e., cognitive-perceptual, interpersonal, disorganised). Multiple linear regression models revealed associations between childhood trauma and all dimensions of schizotypy, but no associations between PRS and schizotypy. A significant interaction between PRS and childhood trauma was evident for the interpersonal and disorganised dimensions of schizotypy, as well as the total score, reflecting positive associations between childhood trauma severity and these two schizotypal dimensions, only for individuals with low or average PRS for schizophrenia. This suggests that trauma may be able to increase risk for psychosis independently of any genetic vulnerability. The present findings are consistent with the idea of several risk pathways for the development of psychotic disorders.

Genomic Stratification of Clozapine Prescription Patterns Using Schizophrenia Polygenic Scores

BackgroundTreatment-resistant schizophrenia affects approximately 30% of individuals with the disorder. Clozapine is the medication of choice in treatment-resistant schizophrenia, but optimizing administration and dose titration is complex. The identification of factors influencing clozapine prescription and response, including genetics, is of interest in a precision psychiatry framework. MethodsWe used linear regression models accounting for demographic, pharmacological, and clinical covariates to determine whether a polygenic risk score (PRS) for schizophrenia would be associated with the highest dose recorded during clozapine treatment. Analyses were performed across 2 independent multiancestry samples of individuals from a UK patient monitoring system, CLOZUK2 (n = 3133) and CLOZUK3 (n = 909), and a European sample from a Norwegian therapeutic drug monitoring service (n = 417). In a secondary analysis merging both UK cohorts, logistic regression models were used to estimate the relationship between schizophrenia PRSs and clozapine doses classified as low, standard, or high. ResultsAfter controlling for relevant covariates, the schizophrenia PRS was correlated with the highest clozapine dose on record for each individual across all samples: CLOZUK2 (β = 12.22, SE = 3.78, p = .001), CLOZUK3 (β = 12.73, SE = 5.99, p = .034), and the Norwegian cohort (β = 46.45, SE = 18.83, p = .014). In a secondary analysis, the schizophrenia PRS was associated with taking clozapine doses >600 mg/day (odds ratio = 1.279, p = .006). ConclusionsThe schizophrenia PRS was associated with the highest clozapine dose prescribed for an individual in records from 3 independent samples, suggesting that the genetic liability for schizophrenia might index factors associated with therapeutic decisions in cohorts of patients with treatment-resistant schizophrenia.

Связь полигенных показателей риска шизофрении с шизотипией: дименсиональный и таксономический подход

Шизотипию рассматривают как фенотип, отражающий доклинические проявления генетической предрасположенности к шизофрении. Существует два взгляда на природу этой связи - дименсиональный и таксономический. Предыдущие исследования вклада полигенных показателей риска (PRS) шизофрении в выраженность шизотипии были проведены в западноевропейских популяциях, использовали дименсиональную модель и получили отрицательные результаты. Цель настоящего исследования заключалась в оценке связи PRS шизофрении с дименсиями и таксонами шизотипии в русской популяции. Методы. Полногеномные данные были получены для выборки из 290 здоровых испытуемых, принадлежащих к кластерам лиц с низкой, позитивной, негативной и высокой смешанной шизотипией. Шизотипию измеряли с использованием Опросника шизотипической личности (SPQ). Результаты. PRS шизофрении не коррелировали с когнитивно-перцептивным, параноидным, межличностным или дезорганизационным дименсиями SPQ. Таксоноподобные группы (кластеры) различались по PRS на уровне тенденции с максимальными PRS в группе с высоко выраженной смешанной шизотипией. Заключение. Результаты согласуются с предположением таксономической модели о том, что у части здоровых лиц с высокой выраженностью шизотипических личностных черт последние являются отражением генетической предрасположенности к шизофрении. Schizotypy is considered as a phenotype that reflects preclinical manifestations of a genetic predisposition to schizophrenia. There are two views on the nature of this relationship - dimensional and taxonomic. Previous studies on the contribution of schizophrenia polygenic risk scores (PRS) to schizotypy were conducted in Western European populations using the dimensional model and yielded negative results. The objective of this study was to assess the relationship between schizophrenia PRS and dimensions and taxa of schizotypy in the Russian population. Methods. Genome-wide data were obtained from a sample of 290 healthy subjects belonging to the clusters of individuals with low, positive, negative, and high mixed schizotypy. Schizotypy was measured using the Schizotypal Personality Questionnaire (SPQ). Results. The schizophrenia PRS did not correlate with cognitive-perceptual, paranoid, interpersonal, or disorganized SPQ factors. Taxon-like groups (clusters) differed in PRS at a trend level, with the highest PRS being found in the high mixed schizotypy group. Conclusion. The results are consistent with the assumption of the taxonomic model of schizotypy that in some healthy individuals with a high degree of schizotypal personality traits, these traits reflect the genetic predisposition to schizophrenia.