Schizophrenia Polygenic Risk Scores Research Articles

A comparison of taxon-like schizotypal clusters of non-clinical individuals on polygenic scores for schizophrenia and related phenotypes

IntroductionSchizotypy is conceptualized to be on the continuum of the risk for psychosis. However, previous studies that used the dimensional approach to schizotypy failed to confirm the expected relations between schizotypal traits and polygenic risk scores (PRS) for schizophrenia. A taxonic approach is an alternative way of looking at schizotypy, but to the best of our knowledge it has not been used to explore the genetic architecture of this construct.ObjectivesThe present study aimed to fill this gap by comparing groups with different profiles of schizotypal traits on PRS for schizophrenia and related phenotypes.MethodsTo find clusters with different combinations of schizotypal traits, we conducted data mining of an ethnically homogeneous cohort of 1377 healthy individuals completed the Schizotypal Personality Questionnaire. Four clusters emerged, termed low, positive, negative, and high mixed schizotypy. Approximately equal groups from each cluster were selected for genotyping. After quality control, PRS for schizophrenia, depression, neuroticism, and educational attainment were calculated for 320 individuals (mean age = 31.74, SD 12.25 years, 59% women) based on the summary statistics of the largest genome-wide association studies of the respective traits. The groups from different clusters were then compared on PRS.ResultsThe schizotypy groups were similar in age and sex composition but differed in educational attainment and neuroticism (as measured by the Eysenck Personality Inventory), with the high mixed schizotypes having the lowest education and highest neuroticism scores among the schizotypy groups. There were no statistically significant differences between the groups in any PRS. However, the high mixed schizotypy group showed the largest PRS for schizophrenia, neuroticism, and depression. At a nominally significant level, it differed from negative and positive schizotypes in schizophrenia PRS and from low schizotypy in neuroticism PRS. The positive and negative schizotypal groups had non-significantly lower schizophrenia PRS than low schizotypy subjects.ConclusionsOur study showed no reliable difference between groups with different schizotypal profiles in PRS of schizophrenia and related phenotypes. At the same time, a number of trends were observed suggesting that only the high mixed schizotypy might be viewed as a condition with an elevated genetic risk of schizophrenia. This is in line with Meehl’s quasi-dimensional model of schizotypy and warrants further investigation in larger samples. This work was supported by the Russian Foundation for Basic Research under Grant 20-013-00230.Disclosure of InterestNone Declared

The use of Polygenic Scores in a family design of First Episode Psychosis

IntroductionA wide variety of traits is heritable and has genetic loading, including schizophrenia spectrum disorders (SSDs) and its associated neurocognitive features. The genetic architecture of SSDs is polygenic, with the contribution of thousands of single nucleotide polymorphisms of small effect with an estimated SNP-heritability of 24%. The same occurs with neurocognitive phenotypes such as intelligence or educational attainment. Therefore, the method of polygenic risk scores (PRS) is useful in estimating the genetic burden of such traits. Moreover, the use of PRS in a sample of genetically related individuals would allow analyzing the contribution of genetic and environmental factors involved in the development of the disorder and its candidate endophenotypes.ObjectivesTo estimate PRS for schizophrenia, and polygenic scores for intelligence and educational attainment in patients with First Episode Psychosis (FEP), their first-degree relatives (siblings and parents), and a group of healthy controls.MethodsThe sample is comprised of 579 participants of the PAFIP-FAMILIAS project in Santander, Spain (133 FEP patients, their 244 first-degree relatives, and 202 healthy controls). All provided sociodemographic information and completed the same neuropsychological battery. Participants’ DNA was extracted from venous blood samples, and genotyping was performed at the Centro Nacional de Investigaciones Oncológicas (CeGen) by the Global Screening Array v.3.0 panel (Illumina). Data quality control, imputation, calculation of PRS, and genetic association analysis are being performed using PLINK, SHAPEIT, IMPUTE2, SPSS and R.ResultsData analysis is currently in progress, at the quality analysis stage, in collaboration with the Institute of Psychiatric Phenomics and Genomics (IPPG) in Munich, Germany. We expect to find higher PRS for schizophrenia in FEP patients, while their first-degree relatives will potentially show intermediate risk scores between patients and healthy controls. A similar finding is expected regarding intelligence and educational attainment, as FEP patients may show more genetic burden for low intelligence and education.ConclusionsThe estimation of PRS has demonstrated to be valuable in studying complex traits such as schizophrenia. We believe that by applying this method in a family design can provide interesting insights on the development of SSDs and its potential endophenotypes, and potentially useful in their prevention.Disclosure of InterestNone Declared

More bipolar than bipolar disorder – a polygenic risk score analysis of postpartum psychosis

IntroductionPostpartum psychosis is a rare psychiatric emergency, occurring days to weeks after 1-2 per 1000 deliveries. Its low prevalence makes it difficult to recruit enough participants to investigate the underlying pathophysiology. It is epidemiologically linked to bipolar disorder, which one study also found it to resemble in genetic susceptibility for psychiatric disorders (Di Florio et al. Lancet Psych 2021; 8: 1045–52).ObjectivesIn this study we aim to investigate polygenic liability for psychiatric disorders in two new Swedish postpartum psychosis cohorts.MethodsCases with postpartum psychosis, defined as a psychiatric hospitalization within 6 weeks after delivery, and/or receiving a diagnosis of F53.1 (ICD 10) or 294.40 (ICD 8.), parous women with severe mental illness without postpartum psychosis, and healthy parous controls were identified in two Swedish genetic studies: the Swedish bipolar collection (SWEBIC) and Predictors for ECT (PREFECT). Polygenic risk scores (PRS) were calculated from summary statistics from genome wide studies on bipolar disorder (Mullins et al. Nat Genet 2021; 53 817-829), schizophrenia (Trubetskoy et al. Nature 2022; 604 502-508) and major depression (Wray et al. Nat Genet. 2018; 50 668-681). The p-value thresholds best predicting their respective phenotype were used in logistic regression analyses with the first six principal components and genotyping platform as confounders.ResultsWe identified 176 patients with postpartum psychosis and genetic information (N(SWEBIC)=126, N(PREFECT)=50). Compared with healthy parous women, patients with postpartum psychosis had significantly higher PRS for bipolar disorder (SWEBIC: odds ratio [OR] 2.6 (95% confidence interval [CI] 1.9-3.5), PREFECT: OR 2.4 (95% CI 1.8-3.2), Figure 1.) and schizophrenia (SWEBIC: OR 1.6 (95% CI 1.2-2.2), PREFECT: OR 1.8 (95%; CI 1.3-2.5)). Patients with postpartum psychosis had significantly higher PRS for bipolar disorder (SWEBIC: OR 1.4 (95% CI 1.2-1.8), PREFECT: OR 1.5 (95% CI 1.1-2)) compared with parous women with severe mental illness without postpartum psychosis. We found no associations with major depression PRS in either cohort.Image:ConclusionsWe replicated previous findings of significantly higher PRS for bipolar disorder and schizophrenia in postpartum psychosis compared with healthy controls. In contrast to previous research, we find postpartum psychosis cases to have higher PRS for bipolar disorder than bipolar disorder cases. Our findings highlight the genetic influence in postpartum psychosis and support previous genetic and epidemiological evidence that postpartum psychosis lies on the bipolar spectrum.Disclosure of InterestNone Declared

Polygenic risk score for five major psychiatric disorders associated with volume of distinct brain regions in the general population

Risk genes and abnormal brain structural indices of psychiatric disorders have been extensively studied. However, whether genetic risk influences brain structure in the general population has been rarely studied. The current study enrolled 483 young Chinese adults, calculated their polygenic risk scores (PRS) for psychiatric disorders based on Psychiatric Genomics Consortium GWAS results, and examined the association between PRSs and brain volume. We found that PRSs were associated with the volume of many brain regions, with differences between PRS for different disorder, calculated at different threshold, and calculated using European or East Asian ancestry. Of them, the PRS for Major Depressive Disorder based on European ancestry was positively associated with right temporal gyrus; the PRS for schizophrenia based on East Asian ancestry was negatively associated with right precentral and postcentral gyrus; the PRS for schizophrenia based on European ancestry was positively associated with right superior temporal gyrus. All these brain regions are critical for corresponding disorders. However, no significant associations were found between PRS for Autism Spectrum Disorder / Bipolar Disorder and brain volume; and the association between PRS for Attention Deficit Hyperactivity Disorder at different thresholds and brain volume was inconsistent. These findings suggest distinct brain mechanisms underlying different psychiatric disorders.

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.