Schizophrenia Polygenic Risk Scores Research Articles

Interaction between visual impairment and genetic risk of dementia and psychosis in older adults.

Visual impairment (VI) is associated with dementia and other neuropsychiatric outcomes, but previous studies have not considered genetic sources of confounding or effect modification. We analysed data from the Health and Retirement Study, an ongoing nationally representative survey of older US adults, a subset of whom underwent genetic testing from 2006 to 2012 (n = 13465). Using discrete time proportional hazards models and generalised estimating equations, we measured the association between VI and dementia, depression and hallucinations adjusting for demographics and comorbidities, ancestry-specific principal components and polygenic risk scores (PRS) for Alzheimer's disease, major depressive disorder or schizophrenia. Effect modification was assessed using VI-PRS interaction terms and stratified analyses. VI was associated with dementia, depression and hallucinations after adjusting polygenic risk and other confounders. There was no VI-PRS interaction for dementia or depression. However, the association between VI and hallucinations varied by genetic risk of schizophrenia. Within the bottom four quintiles of schizophrenia PRS, VI was not associated with hallucinations among White (OR 1.16, 95% CI: 0.87-1.55) or Black participants (OR 0.96, 95% CI: 0.49-1.89). In contrast, VI was strongly associated with hallucinations among White (OR 2.08, 95% CI: 1.17-3.71) and Black (OR 10.63, 95% CI: 1.74-65.03) participants in the top quintile of schizophrenia PRS. The association between VI and neuropsychiatric outcomes is not explained by shared genetic risk factors, and there is a significant interaction between VI and polygenic risk of hallucinations in older adults.

Clinical segmentation in 22q11.2 deletion syndrome: Cognitive impairments and additional genetic load

The 22q11.2 deletion syndrome (22q11.2DS) is associated with high psychiatric morbidity. However, large phenotypic heterogeneity hampers early detection of 22q11.2DS individuals at highest risk. Here, we investigated whether individuals with 22q11.2DS can be subdivided into clinically relevant subgroups based on their severity of cognitive impairments and whether such subgroups differ in polygenic risk. Using a cross-sectional design, we examined the number of lifetime psychiatric diagnoses and polygenic risk scores for schizophrenia in an unselected nationwide biobank cohort of individuals with 22q11.2DS (n = 183). Approximately 35% of this sample, aged 10–30 years, had a history with one or more psychiatric diagnosis. In a representative nested subgroup of 28 children and youth, we performed additional comprehensive cognitive evaluation and assessed psychiatric symptoms. Unsupervised hierarchical cluster analysis was performed to divide the subgroup of 22q11.2DS individuals, based on their performance on the cognitive testing battery. This produced two groups that did not differ in mean age or gender composition, but were characterized by low cognitive (LF) and high cognitive (HF) functional levels. The LF group, which had significantly lower global cognitive functioning scores, also displayed higher negative symptom scores; whereas, the HF group displayed lower rate of current psychiatric disorders than the LF group and the reminder of the biobank cohort. The polygenic risk score for schizophrenia was insignificantly lower for the low functioning group than for the high functioning group, after adjustment. Cognitive functioning may provide useful information on psychiatric risk.

Associations between residential environments and late-onset schizophrenia in UK Biobank: Interaction with genetic risk factor

BackgroundEnvironment and genes both contribute to schizophrenia. However, the impact of different natural environments surrounding residential addresses on schizophrenia in urban settings remains unknown. This study aimed to investigate the association of urbanisation, measured by residential environments, with late-onset schizophrenia and explore whether genetic risk for schizophrenia modified the associations. MethodsWe examined the associations between residential environments and late-onset schizophrenia and its interaction with genetic risk factors in UK Biobank, followed from 2006 to 2010 (baseline) to Dec 2021. Residential environments, including greenspace, domestic garden, blue space, and total natural environment, were evaluated using land use coverage percentage. The polygenic risk score (PRS) of schizophrenia was derived using a Bayesian approach and adjusted it against ancestry. Cox proportional hazard regression model was used to assess the associations between per interquartile (IQR) increase of each type of residential environments and late-onset schizophrenia. Interactive effects of PRS and residential environments on late-onset schizophrenia were assessed on both additive and multiplicative scales. ResultsA total of 393,680 participants were included in the analysis, with 844 cases of late-onset schizophrenia being observed after 12.8 years of follow-up. Within 300 m buffer surrounding the residential addresses, per interquartile increase in greenspace (31.5 %) and total natural environment (34.4 %) were both associated with an 11 % (HR = 0.89, 95 % CI 0.80, 0.99) lower risk of late-onset schizophrenia. Domestic garden and blue space did not show significant protective effects on late-onset schizophrenia. A strong dose-response relationship between schizophrenia PRS and schizophrenia was found, while no additive or multiplicative interaction effects were present between residential environments and PRS on late-onset schizophrenia. ConclusionResidential greenspace and total natural environment may protect against late-onset schizophrenia in older people regardless of genetic risk. These findings shed light on the prevention of schizophrenia and urban planning to optimise ecosystem benefits linked to schizophrenia.

Factor analysis of lifetime psychopathology and its brain morphometric and genetic correlates in a transdiagnostic sample

There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.

Exploring intra-diagnosis heterogeneity and inter-diagnosis commonality in genetic architectures of bipolar disorders: association of polygenic risks of major psychiatric illnesses and lifetime phenotype dimensions.

Bipolar disorder (BD) shows heterogeneous illness presentation both cross-sectionally and longitudinally. This phenotypic heterogeneity might reflect underlying genetic heterogeneity. At the same time, overlapping characteristics between BD and other psychiatric illnesses are observed at clinical and biomarker levels, which implies a shared biological mechanism between them. Incorporating these two issues in a single study design, this study investigated whether phenotypically heterogeneous subtypes of BD have a distinct polygenic basis shared with other psychiatric illnesses. Six lifetime phenotype dimensions of BD identified in our previous study were used as target phenotypes. Associations between these phenotype dimensions and polygenic risk scores (PRSs) of major psychiatric illnesses from East Asian (EA) and other available populations were analyzed. Each phenotype dimension showed a different association pattern with PRSs of mental illnesses. PRS for EA schizophrenia showed a significant negative association with the cyclicity dimension (p = 0.044) but a significant positive association with the psychotic/irritable mania dimension (p = 0.001). PRS of EA major depressive disorder demonstrated a significant negative association with the elation dimension (p = 0.003) but a significant positive association with the comorbidity dimension (p = 0.028). This study demonstrates that well-defined phenotype dimensions of lifetime-basis in BD have distinct genetic risks shared with other major mental illnesses. This finding supports genetic heterogeneity in BD and suggests a pleiotropy among BD subtypes and other psychiatric disorders beyond BD. Further genomic analyses adopting deep phenotyping across mental illnesses in ancestrally diverse populations are warranted to clarify intra-diagnosis heterogeneity and inter-diagnoses commonality issues in psychiatry.

Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo

The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.

Schizophrenia polygenic risk scores, clinical variables and genetic pathways as predictors of phenotypic traits of bipolar I disorder

AimWe investigated the predictive value of polygenic risk scores (PRS) derived from the schizophrenia GWAS (Trubetskoy et al., 2022) (SCZ3) for phenotypic traits of bipolar disorder type-I (BP-I) in 1878 BP-I cases and 2751 controls from Romania and UK. MethodsWe used PRSice-v2.3.3 and PRS-CS for computing SCZ3-PRS for testing the predictive power of SCZ3-PRS alone and in combination with clinical variables for several BP-I subphenotypes and for pathway analysis. Non-linear predictive models were also used. ResultsSCZ3-PRS significantly predicted psychosis, incongruent and congruent psychosis, general age-of-onset (AO) of BP-I, AO-depression, AO-Mania, rapid cycling in univariate regressions. A negative correlation between the number of depressive episodes and psychosis, mainly incongruent and an inverse relationship between increased SCZ3-SNP loading and BP-I-rapid cycling were observed. In random forest models comparing the predictive power of SCZ3-PRS alone and in combination with nine clinical variables, the best predictions were provided by combinations of SCZ3-PRS-CS and clinical variables closely followed by models containing only clinical variables. SCZ3-PRS performed worst. Twenty-two significant pathways underlying psychosis were identified. LimitationsThe combined RO-UK sample had a certain degree of heterogeneity of the BP-I severity: only the RO sample and partially the UK sample included hospitalized BP-I cases. The hospitalization is an indicator of illness severity. Not all UK subjects had complete subphenotype information. ConclusionOur study shows that the SCZ3-PRS have a modest clinical value for predicting phenotypic traits of BP-I. For clinical use their best performance is in combination with clinical variables.

Rates of perinatal environment risk factors in schizophrenia patients with higher and lower schizophrenia polygenic risk scores

IntroductionUnderstanding the relations between genetic (G) and environmental (E) factors in the development of schizophrenia is important for psychosis prevention. These relations may vary from G x E correlations to G x E interactions and independent additive effects of genetic load and environment. The G x E interactions mean that genetic variants associated with schizophrenia make an individual vulnerable to specific environmental exposures thus enhancing the risk of disease manifestation in those who possess such genetic variants. In the case of independent effects, environmental exposure might serve as the main cause or an additional to genetic load external trigger which is needed for the illness development. Thus, the rate of independent environmental risk factors is expected to be higher in patients with a lower genetic liability to schizophrenia.ObjectivesThe study aimed to confirm this hypothesis by comparing schizophrenia patients with higher and lower polygenic risk scores for schizophrenia (SZ-PRS) on the rate of urbanicity, winter birth and obstetric complications (OC), as previous data suggested their independence from the genetic burden of the disease.MethodsSZ-PRS were calculated for 861 patients with schizophrenia spectrum diagnoses (ICD-10, F2), predominantly of Slavic decent, based on the latest GWAS. For patients comprising the highest and lowest SZ-PRS deciles, information on the environmental risk factors was extracted from medical records. Each environmental factor was coded as present/absent. The presence were defined as being born in the most urban environment (a city’s population > 5 million), in winter months and having at least one OC from a predefined list (Alfimova et al. Int J Mol Sci 2022; 23: 12629). In addition, hypoxia/asphyxia, and low birth weight were analyzed separately. Polyenvirommental risk scores (PERS) aggregating the three factors were calculated using natural logarithms of the odds ratios (OR) from an umbrella review (Radua et al. World Psychiatry 2018; 17: 49-66). Logistic regression adjusted for ancestry-related principal components, demographic, and technical variables was applied to compare the SZ-PRS deciles on each factor and PERS.ResultsNone of the factors alone or PERS predicted SZ-PRS decile membership.ConclusionsThe results did not support the hypothesis. Future research needs reliable data on the frequency of the studied factors in the general population where the patients come from.The study was supported by the Russian Science Foundation, grant no. 21-15-00124.Disclosure of InterestNone Declared

Genetic and Phenotypic Features of Schizophrenia in the UK Biobank

Large-scale biobanks provide important opportunities for mental health research, but selection biases raise questions regarding the comparability of individuals with those in clinical research settings. To compare the genetic liability to psychiatric disorders in individuals with schizophrenia in the UK Biobank with individuals in the Psychiatric Genomics Consortium (PGC) and to compare genetic liability and phenotypic features with participants recruited from clinical settings. This cross-sectional study included participants from the population-based UK Biobank and schizophrenia samples recruited from clinical settings (CLOZUK, CardiffCOGS, Cardiff F-Series, and Cardiff Affected Sib-Pairs). Data were collected between January 1993 and July 2021. Data analysis was conducted between July 2021 and June 2023. A genome-wide association study of UK Biobank schizophrenia case-control status was conducted, and the results were compared with those from the PGC via genetic correlations. To test for differences with the clinical samples, polygenic risk scores (PRS) were calculated for schizophrenia, bipolar disorder, depression, and intelligence using PRS-CS. PRS and phenotypic comparisons were conducted using pairwise logistic regressions. The proportions of individuals with copy number variants associated with schizophrenia were compared using Firth logistic regression. The sample of 517 375 participants included 1438 UK Biobank participants with schizophrenia (550 [38.2%] female; mean [SD] age, 54.7 [8.3] years), 499 475 UK Biobank controls (271 884 [54.4%] female; mean [SD] age, 56.5 [8.1] years), and 4 schizophrenia research samples (4758 [28.9%] female; mean [SD] age, 38.2 [21.0] years). Liability to schizophrenia in UK Biobank was highly correlated with the latest genome-wide association study from the PGC (genetic correlation, 0.98; SE, 0.18) and showed the expected patterns of correlations with other psychiatric disorders. The schizophrenia PRS explained 6.8% of the variance in liability for schizophrenia case status in UK Biobank. UK Biobank participants with schizophrenia had significantly lower schizophrenia PRS than 3 of the clinically ascertained samples and significantly lower rates of schizophrenia-associated copy number variants than the CLOZUK sample. UK Biobank participants with schizophrenia had higher educational attainment and employment rates than the clinically ascertained schizophrenia samples, lower rates of smoking, and a later age of onset of psychosis. Individuals with schizophrenia in the UK Biobank, and likely other volunteer-based biobanks, represent those less severely affected. Their inclusion in wider studies should enhance the representation of the full spectrum of illness severity.

Integrating Electronic Health Records and Polygenic Risk to Identify Genetically Unrelated Comorbidities of Schizophrenia That May Be Modifiable

BackgroundPatients with schizophrenia have substantial comorbidity that contributes to reduced life expectancy of 10 to 20 years. Identifying modifiable comorbidities could improve rates of premature mortality. Conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore are enriched for potentially modifiable associations. MethodsPhenome-wide comorbidity was calculated from electronic health records of 250,000 patients across 2 independent health care institutions (Vanderbilt University Medical Center and Mass General Brigham); associations with schizophrenia polygenic risk scores were calculated across the same phenotypes in linked biobanks. ResultsSchizophrenia comorbidity was significantly correlated across institutions (r = 0.85), and the 77 identified comorbidities were consistent with prior literature. Overall, comorbidity and polygenic risk score associations were significantly correlated (r = 0.55, p = 1.29 × 10−118). However, directly testing for the absence of genetic effects identified 36 comorbidities that had significantly equivalent schizophrenia polygenic risk score distributions between cases and controls. This set included phenotypes known to be consequences of antipsychotic medications (e.g., movement disorders) or of the disease such as reduced hygiene (e.g., diseases of the nail), thereby validating the approach. It also highlighted phenotypes with less clear causal relationships and minimal genetic effects such as tobacco use disorder and diabetes. ConclusionsThis work demonstrates the consistency and robustness of electronic health record–based schizophrenia comorbidities across independent institutions and with the existing literature. It identifies known and novel comorbidities with an absence of shared genetic risk, indicating other causes that may be modifiable and where further study of causal pathways could improve outcomes for patients.

Transdiagnostic dimensions of symptoms and experiences associated with immune proteins in the continuity of psychosis.

There is limited evidence as to whether the immune protein profile is associated with a particular symptomatology pattern across the psychosis continuum. We estimated two bifactor models of general and specific dimensions of psychotic experiences in unaffected siblings of patients (n = 52) and community controls (n = 200), and of psychotic symptoms in first-episode psychosis (FEP) patients (n = 110). We evaluated associations between these transdiagnostic dimensions and trait (TNF-α, IFN-γ), state (IL-6, IL-1β), and regulatory (TGF-β, IL-10, IL-4) cytokines. We explored whether schizophrenia genetic liability (schizophrenia polygenic risk score; SZ-PRS) modified the associations. High levels of trait marker IFN-γ were associated with the severity of general psychosis dimension in the unaffected siblings and community controls, expanding to the depressive dimension in siblings and to the manic dimension in FEP. High TNF-α levels were associated with more positive psychotic experiences in unaffected siblings and manic symptoms in FEP. Low levels of state markers IL-6 and IL-1β were observed in unaffected siblings presenting more depressive experiences. Still, high levels of IL-6 and IL-1β were associated with the severity of the depressive and negative symptom dimensions at FEP. The severity of transdiagnostic dimension scores across the three groups was associated with lower regulatory cytokines. Exploratory analysis suggested that a high SZ-PRS contributed mostly to associations with psychotic dimensions. IFN-γ mapped onto the multidimensional expression of psychosis, reinforcing the trait concept. State markers IL-6 and IL-1β may fluctuate along the spectrum. Dysfunction in the regulatory arm may disinhibit the inflammatory system. Associations with psychotic dimensions may be more prone to SZ-PRS susceptibility.

Polygenic effects on brain functional endophenotype for deficit and non-deficit schizophrenia

Deficit schizophrenia (DS) is a subtype of schizophrenia (SCZ). The polygenic effects on the neuroimaging alterations in DS still remain unknown. This study aims to calculate the polygenic risk scores for schizophrenia (PRS-SCZ) in DS, and further explores the potential associations with functional features of brain. PRS-SCZ was calculated according to the Whole Exome sequencing and Genome-wide association studies (GWAS). Resting-state fMRI, as well as biochemical features and neurocognitive data were obtained from 33 DS, 47 NDS and 41 HCs, and association studies of genetic risk with neuroimaging were performed in this sample. The analyses of amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and functional connectivity (FC) were performed to detect the functional alterations between DS and NDS. In addition, correlation analysis was used to investigate the relationships between functional features (ALFF, ReHo, FC) and PRS-SCZ. The PRS-SCZ of DS was significantly lower than that in NDS and HC. Compared to NDS, there was a significant increase in the ALFF of left inferior temporal gyrus (ITG.L) and left inferior frontal gyrus (IFG.L) and a significant decrease in the ALFF of right precuneus (PCUN.R) and ReHo of right middle frontal gyrus (MFG.R) in DS. FCs were widely changed between DS and NDS, mainly concentrated in default mode network, including ITG, PCUN and angular gyrus (ANG). Correlation analysis revealed that the ALFF of left ITG, the ReHo of right middle frontal gyrus, the FC value between insula and ANG, left ITG and right corpus callosum, left ITG and right PCUN, as well as the scores of Trail Making Test-B, were associated with PRS-SCZ in DS. The present study demonstrated the differential polygenic effects on functional changes of brain in DS and NDS, providing a potential neuroimaging-genetic perspective for the pathogenesis of schizophrenia.

The interaction between early life complications and a polygenic risk score for schizophrenia is associated with brain activity during emotion processing in healthy participants.

Previous evidence suggests that early life complications (ELCs) interact with polygenic risk for schizophrenia (SCZ) in increasing risk for the disease. However, no studies have investigated this interaction on neurobiological phenotypes. Among those, anomalous emotion-related brain activity has been reported in SCZ, even if evidence of its link with SCZ-related genetic risk is not solid. Indeed, it is possible this relationship is influenced by non-genetic risk factors. Thus, this study investigated the interaction between SCZ-related polygenic risk and ELCs on emotion-related brain activity. 169 healthy participants (HP) in a discovery and 113 HP in a replication sample underwent functional magnetic resonance imaging (fMRI) during emotion processing, were categorized for history of ELCs and genome-wide genotyped. Polygenic risk scores (PRSs) were computed using SCZ-associated variants considering the most recent genome-wide association study. Furthermore, 75 patients with SCZ also underwent fMRI during emotion processing to verify consistency of their brain activity patterns with those associated with risk factors for SCZ in HP. Results in the discovery and replication samples indicated no effect of PRSs, but an interaction between PRS and ELCs in left ventrolateral prefrontal cortex (VLPFC), where the greater the activity, the greater PRS only in presence of ELCs. Moreover, SCZ had greater VLPFC response than HP. These results suggest that emotion-related VLPFC response lies in the path from genetic and non-genetic risk factors to the clinical presentation of SCZ, and may implicate an updated concept of intermediate phenotype considering early non-genetic factors of risk for SCZ.

Mismatch negativity and polygenic risk scores for schizophrenia and bipolar disorder

ObjectiveAuditory mismatch negativity (MMN) impairment is a candidate endophenotype in psychotic disorders, yet the genetic underpinnings remain to be clarified. Here, we examined the relationships between auditory MMN and polygenic risk scores (PRS) for individuals with psychotic disorders, including schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) and in healthy controls (HC). MethodsGenotyped and clinically well-characterized individuals with psychotic disorders (n = 102), including SSD (n = 43) and BD (n = 59), and HC (n = 397) underwent a roving MMN paradigm. In addition MMN, we measured the memory traces of the repetition positivity (RP) and the deviant negativity (DN), which is believed to reflect prediction encoding and prediction error signals, respectively. SCZ and BD PRS were computed using summary statistics from the latest genome-wide association studies. The relationships between the MMN, RP, and DN and the PRSs were assessed with linear regressions. ResultsWe found no significant association between the SCZ or BD PRS and grand average MMN in the psychotic disorders group or in the HCs group (all p > 0.05). SCZ PRS and BD PRS were negatively associated with RP in the psychotic disorders group (β = −0.46, t = −2.86, p = 0.005 and β = −0.29, t = −0.21, p = 0.034, respectively). No significant associations were found between DN and PRS. ConclusionThese findings suggest that genetic variants associated with SCZ and BD may be associated with MMN subcomponents linked to predictive coding among patients with psychotic disorders. Larger studies are needed to confirm these findings and further elucidate the genetic underpinnings of MMN impairment in psychotic disorders.

Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study.

Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.

Studying the relationship between intelligence quotient and schizophrenia polygenic scores in a family design with first-episode psychosis population.

The intelligence quotient (IQ) of patients with first-episode psychosis (FEP) and their unaffected relatives may be related to the genetic burden of schizophrenia (SCZ). The polygenic score approach can be useful for testing this question. To assess the contribution of the polygenic risk scores for SCZ (PGS-SCZ) and polygenic scores for IQ (PGS-IQ) to the individual IQ and its difference from the mean IQ of the family (named family-IQ) through a family-based design in an FEP sample. The PAFIP-FAMILIES sample (Spain) consists of 122 FEP patients, 131 parents, 94 siblings, and 176 controls. They all completed the WAIS Vocabulary subtest for IQ estimation and provided a DNA sample. We calculated PGS-SCZ and PGS-IQ using the continuous shrinkage method. To account for relatedness in our sample, we performed linear mixed models. We controlled for covariates potentially related to IQ, including age, years of education, sex, and ancestry principal components. FEP patients significantly deviated from their family-IQ. FEP patients had higher PGS-SCZ than other groups, whereas the relatives had intermediate scores between patients and controls. PGS-IQ did not differ between groups. PGS-SCZ significantly predicted the deviation from family-IQ, whereas PGS-IQ significantly predicted individual IQ. PGS-SCZ discriminated between different levels of genetic risk for the disorder and was specifically related to patients' lower IQ in relation to family-IQ. The genetic background of the disorder may affect neurocognition through complex pathological processes interacting with environmental factors that prevent the individual from reaching their familial cognitive potential.

Genome-wide DNA methylation risk scores for schizophrenia derived from blood and brain tissues further explain the genetic risk in patients stratified by polygenic risk scores for schizophrenia and bipolar disorder

BackgroundGenetic and environmental factors contribute to the pathogenesis of schizophrenia (SZ) and bipolar disorder (BD). Among genetic risk groups stratified by combinations of Polygenic Risk Score (PRS) deciles for SZ,...

Polygenic risk for schizophrenia predicting social trajectories in a general population sample.

We investigated (a) whether polygenic risk for schizophrenia predicts different trajectories of social development among those who have not developed psychoses and (b) whether possible associations are PRSSCZ-specific or evident also for any polygenic risk for mental disorders, e.g. for major depression. Participants came from the population-based Young Finns Study (n = 2377). We calculated a polygenic risk score for schizophrenia (PRSSCZ) and for major depression (PRSDEP). Diagnoses of psychotic disorders were derived from the hospital care register. Social development from adolescence to middle age was measured by (a) perceived social support from friends, family, and a close other, (b) perceived sociability, and (c) family structure (partnership status, number of children, age of first-time parenthood). Among those without manifest psychoses, high PRSSCZ predicted lower experienced support from friends (B = -0.04, p = 0.009-0.035) and family (B = -0.04, p = 0.009-0.035) especially after early adulthood, and also lower perceived sociability (B = -0.05, p = 0.010-0.026). PRSSCZ was not related to family structure. PRSDEP did not predict any domain of social development. Individuals at high PRSSCZ (not converted to psychosis) seem to experience a lower preference to be with others over being alone. Individuals with high (v. low) PRSSCZ seem to have a similar family structure in terms of partnership status or number of children but, nevertheless, they experience less support from their family. Among those not converted to psychosis in a typical age period, high PRSSCZ may predict a 'later risk phase' and reduced functional resilience when approaching middle age.

The impact of genetic risk for schizophrenia on eating disorder clinical presentations

A growing body of literature recognizes associations between eating disorders (EDs) and schizophrenia and suggests that familial liability to schizophrenia in individuals with anorexia nervosa (AN) reveals distinct patterns of clinical outcomes. To further investigate the influence of schizophrenia genetic liability among individuals with EDs, we evaluated the associations between schizophrenia polygenic risk scores (PRS) and clinical presentations of individuals with EDs including their overall health condition and ED-related symptoms. Using data from two previous studies of the genetics of EDs comprising 3,573 Anorexia Nervosa Genetics Initiative (ANGI) cases and 696 Binge Eating Genetics Initiative (BEGIN) cases born after 1973 and linked to the Swedish National Patient Register, we examined the association of schizophrenia PRS on ED clinical features, psychiatric comorbidities, and somatic and mental health burden. Among ANGI cases, higher schizophrenia PRS was statistically significantly associated with higher risk of major depressive disorder (MDD) measured by hazard ratio (HR) with 95% confidence interval (CI) (HR [95% CI]: 1.07 [1.02, 1.13]) and substance abuse disorder (SUD) (HR [95% CI]: 1.14 [1.03, 1.25]) after applying multiple testing correction. Additionally, higher schizophrenia PRS was associated with decreased clinical impairment assessment scores (−0.56, 95% CI: [−1.04, −0.08]) at the conventional significance level (p < 0.05). Further, in BEGIN cases, higher schizophrenia PRS was statistically significantly associated with earlier age at first ED symptom (−0.35 year, 95% CI: [−0.64, −0.06]), higher ED symptom scores (0.16, 95% CI: [0.04, 0.29]), higher risk of MDD (HR [95% CI]: 1.18 [1.04, 1.34]) and SUD (HR [95% CI]: 1.36 [1.07, 1.73]). Similar, but attenuated, patterns held in the subgroup of exclusively AN vs other eating disorder (OED) cases. These results suggest a similar pattern of influence of schizophrenia PRS for AN and OED cases in terms of psychiatric comorbidities, but a different pattern in terms of ED-related clinical features. The disparity of the effect of schizophrenia PRS on AN vs OED merits further investigation.

Association of clinical parameters and polygenic risk scores for body mass index, schizophrenia, and diabetes with antipsychotic-induced weight gain

Antipsychotic-induced weight gain (AIWG) is a common adverse event in schizophrenia. Genome-wide association studies (GWAS) and polygenic risk scores (PRS) for other diseases or traits are recent approaches to disentangling the genetic architecture of AIWG.200 patients with schizophrenia treated monotherapeutically with antipsychotics were included in this study. A multiple linear regression analysis with ten-fold crossvalidation was performed to predict the percentage weight change after five weeks of treatment. Independent variables were sex, age, body mass index (BMI) at baseline, medication-associated risk, and PRSs (BMI, schizophrenia, diabetes, and metabolic syndrome). An explorative GWAS analysis was performed on the same subjects and traits.PRSs for BMI (β = 3.78; p = 0.0041), schizophrenia (β = 5.38; p = 0.021) and diabetes type 2 (β = 13.4; p = 0.046) were significantly associated with AIWG. Other significant factors were sex, baseline BMI and medication. Compared to the model without genetic factors, the addition of PRSs for BMI, schizophrenia, and diabetes type 2 increased the goodness of fit by 6.5 %. The GWAS identified the association of three variants (rs10668573, rs10249381 and rs1988834) with AIWG at a genome-wide level of p < 1 · 10−6.Using PRS for schizophrenia, BMI, and diabetes type 2 increased the explained variation of predicted weight gain, compared to a model without PRSs. For more precise results, PRSs derived from other traits (ideally AIWG) should be investigated. Potential risk variants identified in our GWAS need to be further investigated and replicated in independent samples.