Psychiatric Polygenic Risk Scores Research Articles

Psychiatric Polygenic Risk Scores Across Youth With Bipolar Disorder, Youth at High Risk for Bipolar Disorder, and Controls

There is a pronounced gap in knowledge regarding polygenic underpinnings of youth bipolar disorder (BD). This study aimed to compare polygenic risk scores (PRSs) in youth with BD, youth at high clinical and/or familial risk for BD (HR), and controls. Participants were 344 youths of European ancestry (13-20 years old), including 136 youths with BD, 121 HR youths, and 87 controls. PRSs for BD, schizophrenia), major depressive disorder, and attention-deficit/hyperactivity disorder were constructed using independent genome-wide summary statistics from adult cohorts. Multinomial logistic regression was used to examine the association between each PRS and diagnostic status (BD vs HR vs controls). All genetic analyses controlled for age, sex, and 2 genetic principal components. The BD group showed significantly higher BD-PRS than the control group (odds ratio= 1.54, 95% CI= 1.13-2.10, p= .006), with the HR group numerically intermediate. BD-PRS explained 7.9% of phenotypic variance. PRSs for schizophrenia, major depressive disorder, and attention-deficit/hyperactivity disorder were not significantly different among groups. In the BD group, BD-PRS did not significantly differ in relation to BD subtype, age of onset, psychosis, or family history of BD. BD-PRS derived from adult genome-wide summary statistics is elevated in youth with BD. Absence of significant between-group differences in PRSs for other psychiatric disorders supports the specificity of BD-PRS in youth. These findings add to the biological validation of BD in youth and could have implications for early identification and diagnosis. To enhance clinical utility, future genome-wide association studies that focus specifically on early-onset BD are warranted, as are studies integrating additional genetic and environmental factors. We worked to ensure sex and gender balance in the recruitment of human participants. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. We actively worked to promote sex and gender balance in our author group. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

Multiple psychiatric polygenic risk scores predict associations between childhood adversity and bipolar disorder

BackgroundIt remains unclear how adverse childhood experiences (ACE) and increased genetic risk for bipolar disorder (BD) interact to influence BD symptom outcomes. Here we calculated multiple psychiatric polygenic risk scores (PRS) and used the measures of ACE to understand these gene-environment interactions. Method885 BD subjects were included for analyses. BD, ADHD, MDD and SCZ PRSs were calculated using the PRS-CS-auto method. ACEs were evaluated using the Children Life Event Questionnaire (CLEQ). Participants were divided into groups based on the presence of ACE and the total number of ACEs. The associations between total ACE number, PRSs and their interactions were evaluated using multiple linear and logistic regressions. Secondary analyses were performed to evaluate the influence of ACE and PRS on sub-phenotypes of BD. ResultsThe number of ACEs increased with the ADHD PRS. BD participants who had ACEs showed an earlier age of BD onset and higher odds of having rapid cycling. Increased BD PRS was associated with increased odds of developing psychotic symptoms. Higher ADHD PRS was associated with increased odds of having rapid cycling. No prediction effect was observed from MDD and SCZ PRS. And, we found no significant interaction between ACE numbers and any of the PRSs in predicting any selected BD sub-phenotypes. LimitationsThe study was limited by sample size, ACE definition, and cross-sectional data collection method. ConclusionsThe findings consolidate the importance of considering multiple psychiatric PRSs in predicting symptom outcomes among BD patients.

Exploring genetic risk for catatonia in a genome wide association study and polygenic risk score analysis

BackgroundCatatonia is an under-recognized disorder characterized by psychomotor (increased, decreased, or abnormal) changes, affective symptoms, and disturbance of volition, which may arise in the setting of decompensated psychiatric or non-psychiatric medical disorders. Genetic studies of catatonia are limited, and to the best of our knowledge no prior genome wide association studies of catatonia have been performed to date. MethodsFirst we performed a genome wide association study of catatonia regardless of etiology (psychiatric or non-psychiatric). Secondarily we evaluated whether there was an elevated genetic risk profile for predisposing psychiatric disorders (schizophrenia spectrum disorder, bipolar affective disorder, etc.) in patients with catatonia. We used a matched case control design and applied polygenic risk scores to evaluate for a shared polygenetic contribution to catatonia from common psychiatric phenotypes that show a high prevalence of catatonia in their decompensated states. ResultsAnxiety, bipolar affective disorder, schizophrenia spectrum disorder and cross disorder polygenic risk scores were significantly associated with catatonia case status in both unadjusted and adjusted logistic regression models for the European Ancestry set even after correcting for multiple comparisons. Depression, Alzheimer's, Autism Spectrum Disorder and Obsessive Disorder polygenic risk scores were not significantly associated with catatonia status in participants of European Ancestry. In the African Ancestry set, no psychiatric polygenic risk scores were significantly associated with catatonia status in either the unadjusted or adjusted regression models. ConclusionsEven after controlling for relevant covariates, anxiety, bipolar affective disorder, schizophrenia spectrum disorder and cross disorders were significantly associated with catatonia status suggesting that there might be a shared genetic risk for those disorders amongst patients with catatonia.

Psychiatric polygenic risk scores: Child and adolescent psychiatrists' knowledge, attitudes, and experiences.

Psychiatric polygenic risk scores (PRS) have potential utility in psychiatric care and prevention, but there are concerns about their implementation. We surveyed 960 US-based practicing child and adolescent psychiatrists' (CAP) about their experiences, perspectives, and potential uses of psychiatric PRS. While 23% of CAP reported that they had never heard of PRS, 10 % of respondents have had a patient/family bring PRS to them and 4% have generated PRS for patients. Though 25% stated they would request PRS if a patient/caregiver asked, 35% indicated that nothing would prompt them to request PRS. Most respondents (54%) believed psychiatric PRS are currently at least slightly useful and 87% believed they will be so in 5 years. More than 70% indicated they would take action in response to a child with a top fifth percentile psychiatric PRS but no diagnosis: 48% would increase monitoring of symptoms, 42% would evaluate for current symptoms, and 4% would prescribe medications. Yet, most respondents were concerned that high-PRS results could lead to overtreatment and negatively impact patients' emotional well-being. Findings indicate emerging use of psychiatric PRS within child and adolescent psychiatry in the US. It is critical to examine the ethical and clinical challenges that PRS may generate and begin efforts to promote their informed and responsible use.

Associations between psychiatric polygenic risk scores and general and specific psychopathology symptoms in childhood and adolescence between and within dizygotic twin pairs.

Although polygenic risk scores (PRS) predict psychiatric problems, these associations might be attributable to indirect pathways including population stratification, assortative mating, or dynastic effects (mediation via parental environments). The goal of this study was to examine whether PRS-psychiatric symptom associations were attributable to indirect versus direct pathways. The sample consisted of 3,907 dizygotic (DZ) twin pairs. In childhood, their parents rated them on 98 symptoms. In adolescence (n = 2,393 DZ pairs), both the parents and the twins rated themselves on 20 symptoms. We extracted one general and seven specific factors from the childhood data, and one general and three specific factors from the adolescent data. We then regressed each general factor model onto ten psychiatric PRS simultaneously. We first conducted the regressions between individuals (β) and then within DZ twin pairs (βw ), which controls for indirect pathways. In childhood, the PRS for ADHD predicted general psychopathology (β = 0.09, 95% CI: [0.06, 0.12]; βw = 0.07 [0.01, 0.12]). Furthermore, the PRS for ADHD predicted specific inattention (β = 0.04 [0.00, 0.08]; βw = 0.09 [0.01, 0.17]) and specific hyperactivity (β = 0.07 [0.04, 0.11]; βw = 0.09 [0.01, 0.16]); the PRS for schizophrenia predicted specific learning (β = 0.08 [0.03, 0.13]; βw = 0.19 [0.08, 0.30]) and specific inattention problems (β = 0.05 [0.01, 0.09]; βw = 0.10 [0.02, 0.19]); and the PRS for neuroticism predicted specific anxiety (β = 0.06 [0.02, 0.10]; βw = 0.06 [0.00, 0.12]). Overall, the PRS-general factor associations were similar between individuals and within twin pairs, whereas the PRS-specific factors associations amplified by 84% within pairs. This implies that PRS-psychiatric symptom associations did not appear attributable to indirect pathways such as population stratification, assortative mating, or mediation via parental environments. Rather, genetics appeared to directly influence symptomatology.

W57. MENTAL HEALTH DATA COLLECTION IN THE ESTONIAN BIOBANK: INSTRUMENTS, METHODOLOGY AND PRELIMINARY RESULTS

Background: Background: Common psychiatric disorders are clinically heterogeneous and often display many overlapping symptoms as well as comorbidity across psychiatric disorders, hence complicating the genetic investigation of these disorders. To facilitate new discoveries and gain better understanding of the genetics of psychiatric problems, large well-phenotyped biobank samples are greatly needed. The Estonian Biobank (EstBB;N=200,000) is a data-rich national biobank that joins genomic, biomarker, electronic health record (EHR), national registry and questionnaire data to significantly advance the current knowledge of the genetic underpinnings of complex and rare diseases. We aimed to expand the EstBB database with rich phenotypic questionnaire-based information on a broad set of symptoms of common psychiatric disorders and related phenotypes. Methods: Methods: We compiled an online questionnaire “Wellbeing and mental health” which included self-report brief screening instruments to capture a broad range of symptoms on current and/or lifetime depression, anxiety disorders, mania, post-traumatic stress disorder, eating disorders, attention deficit/hyperactivity disorder, psychotic experiences, suicidal thoughts and behavior, cognition, substance (ab)use, problematic gambling and related risk- and protective factors, such as childhood adversity, stressful life events, social support, lifestyle, sociodemographic factors and life satisfaction. In addition, the participants were asked about the side effects, discontinuation and switching of medications prescribed for a mental health problem in their lifetime. Since the start of the data collection coincided with the peak of the second COVID-19 wave in Estonia, we included items related to current perceived stress, burnout and change in mental health during the pandemic. When selecting instruments, preference was given based on 1) reliability and validity of the instruments;2) whether an Estonian adaptation and/or validation has been conducted;3) application in other large biobanks (e.g. the UK Biobank) for future harmonization or replication;4) short length. Results: Results: The invitations to participate in the online mental health study were e-mailed out to all living EstBB participants with available e-mail addresses (N=184,622), followed by two e-mail reminders. The active data collection phase spanned over three months from March to May 2021. The preliminary response rate was 46.7% (N = 86,222) out of all who were contacted. We will present preliminary results on the comparison of respondents and non-respondents based on demographic data, psychiatric diagnoses in EHR and psychiatric polygenic risk scores. Discussion: Discussion: We have significantly expanded the EstBB resource with phenotypic information on a broad range of psychiatric symptoms and related phenotypes to facilitate future research in psychiatric genetics. Disclosure: Nothing to disclose.

Combined polygenic risk scores of different psychiatric traits predict general and specific psychopathology in childhood.

BackgroundPolygenic risk scores (PRSs) operationalize genetic propensity toward a particular mental disorder and hold promise as early predictors of psychopathology, but before a PRS can be used clinically, explanatory power must be increased and the specificity for a psychiatric domain established. To enable early detection, it is crucial to study these psychometric properties in childhood. We examined whether PRSs associate more with general or with specific psychopathology in school‐aged children. Additionally, we tested whether psychiatric PRSs can be combined into a multi‐PRS score for improved performance.MethodsWe computed 16 PRSs based on GWASs of psychiatric phenotypes, but also neuroticism and cognitive ability, in mostly adult populations. Study participants were 9,247 school‐aged children from three population‐based cohorts of the DREAM‐BIG consortium: ALSPAC (UK), The Generation R Study (Netherlands), and MAVAN (Canada). We associated each PRS with general and specific psychopathology factors, derived from a bifactor model based on self‐report and parental, teacher, and observer reports. After fitting each PRS in separate models, we also tested a multi‐PRS model, in which all PRSs are entered simultaneously as predictors of the general psychopathology factor.ResultsSeven PRSs were associated with the general psychopathology factor after multiple testing adjustment, two with specific externalizing and five with specific internalizing psychopathology. PRSs predicted general psychopathology independently of each other, with the exception of depression and depressive symptom PRSs. Most PRSs associated with a specific psychopathology domain, were also associated with general child psychopathology.ConclusionsThe results suggest that PRSs based on current GWASs of psychiatric phenotypes tend to be associated with general psychopathology, or both general and specific psychiatric domains, but not with one specific psychopathology domain only. Furthermore, PRSs can be combined to improve predictive ability. PRS users should therefore be conscious of nonspecificity and consider using multiple PRSs simultaneously, when predicting psychiatric disorders.

Polygenic prediction of PTSD trajectories in 9/11 responders.

Genetics hold promise of predicting long-term post-traumatic stress disorder (PTSD) outcomes following trauma. The aim of the current study was to test whether six hypothesized polygenic risk scores (PRSs) developed to capture genetic vulnerability to psychiatric conditions prospectively predict PTSD onset, severity, and 18-year course after trauma exposure. Participants were 1490 responders to the World Trade Center (WTC) disaster (mean age at 9/11 = 38.81 years, s.d. = 8.20; 93.5% male; 23.8% lifetime WTC-related PTSD diagnosis). Prospective longitudinal data on WTC-related PTSD symptoms were obtained from electronic medical records and modelled as PTSD trajectories using growth mixture model analysis. Independent regression models tested whether six hypothesized psychiatric PRSs (PTSD-PRS, Re-experiencing-PRS, Generalized Anxiety-PRS, Schizophrenia-PRS, Depression-PRS, and Neuroticism-PRS) are predictive of WTC-PTSD outcomes: lifetime diagnoses, average symptom severity, and 18-year symptom trajectory. All analyses were adjusted for population stratification, 9/11 exposure severity, and multiple testing. Depression-PRS predicted PTSD diagnostic status (OR 1.37, CI 1.17-1.61, adjusted p = 0.001). All PRSs, except PTSD-PRS, significantly predicted average PTSD symptoms (β = 0.06-0.10, adjusted p < 0.05). Re-experiencing-PRS, Generalized Anxiety-PRS and Schizophrenia-PRS predicted the high severity PTSD trajectory class (ORs 1.21-1.28, adjusted p < 0.05). Finally, PRSs prediction was independent of 9/11 exposure severity and jointly accounted for 3.7 times more variance in PTSD symptoms than the exposure severity. Psychiatric PRSs prospectively predicted WTC-related PTSD lifetime diagnosis, average symptom severity, and 18-year trajectory in responders to 9/11 disaster. Jointly, PRSs were more predictive of subsequent PTSD than the exposure severity. In the future, PRSs may help identify at-risk responders who might benefit from targeted prevention approaches.

Polygenic Risk of Psychiatric Disorders Exhibits Cross-trait Associations in Electronic Health Record Data From European Ancestry Individuals

BackgroundPrediction of disease risk is a key component of precision medicine. Common traits such as psychiatric disorders have a complex polygenic architecture, making the identification of a single risk predictor difficult. Polygenic risk scores (PRSs) denoting the sum of an individual’s genetic liability for a disorder are a promising biomarker for psychiatric disorders, but they require evaluation in a clinical setting. MethodsWe developed PRSs for 6 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, cross disorder, attention-deficit/hyperactivity disorder, and anorexia nervosa) and 17 nonpsychiatric traits in more than 10,000 individuals from the Penn Medicine Biobank with accompanying electronic health records. We performed phenome-wide association analyses to test their association across disease categories. ResultsFour of the 6 psychiatric PRSs were associated with their primary phenotypes (odds ratios from 1.2 to 1.6). Cross-trait associations were identified both within the psychiatric domain and across trait domains. PRSs for coronary artery disease and years of education were significantly associated with psychiatric disorders, largely driven by an association with tobacco use disorder. ConclusionsWe demonstrated that the genetic architecture of electronic health record–derived psychiatric diagnoses is similar to ascertained research cohorts from large consortia. Psychiatric PRSs are moderately associated with psychiatric diagnoses but are not yet clinically predictive in naïve patients. Cross-trait associations for these PRSs suggest a broader effect of genetic liability beyond traditional diagnostic boundaries. As identification of genetic markers increases, including PRSs alongside other clinical risk factors may enhance prediction of psychiatric disorders and associated conditions in clinical registries.

Discriminating bipolar depression from major depressive disorder with polygenic risk scores.

Although accurate differentiation between bipolar disorder (BD) and unipolar major depressive disorder (MDD) has important prognostic and therapeutic implications, the distinction is often challenging based on clinical grounds alone. In this study, we tested whether psychiatric polygenic risk scores (PRSs) improve clinically based classification models of BD v. MDD diagnosis. Our sample included 843 BD and 930 MDD subjects similarly genotyped and phenotyped using the same standardized interview. We performed multivariate modeling and receiver operating characteristic analysis, testing the incremental effect of PRSs on a baseline model with clinical symptoms and features known to associate with BD compared with MDD status. We found a strong association between a BD diagnosis and PRSs drawn from BD (R2 = 3.5%, p = 4.94 × 10-12) and schizophrenia (R2 = 3.2%, p = 5.71 × 10-11) genome-wide association meta-analyses. Individuals with top decile BD PRS had a significantly increased risk for BD v. MDD compared with those in the lowest decile (odds ratio 3.39, confidence interval 2.19-5.25). PRSs discriminated BD v. MDD to a degree comparable with many individual symptoms and clinical features previously shown to associate with BD. When compared with the full composite model with all symptoms and clinical features PRSs provided modestly improved discriminatory ability (ΔC = 0.011, p = 6.48 × 10-4). Our study demonstrates that psychiatric PRSs provide modest independent discrimination between BD and MDD cases, suggesting that PRSs could ultimately have utility in subjects at the extremes of the distribution and/or subjects for whom clinical symptoms are poorly measured or yet to manifest.

Polygenic prediction and GWAS of depression, PTSD, and suicidal ideation/self-harm in a Peruvian cohort.

Genome-wide approaches including polygenic risk scores (PRSs) are now widely used in medical research; however, few studies have been conducted in low- and middle-income countries (LMICs), especially in South America. This study was designed to test the transferability of psychiatric PRSs to individuals with different ancestral and cultural backgrounds and to provide genome-wide association study (GWAS) results for psychiatric outcomes in this sample. The PrOMIS cohort (N = 3308) was recruited from prenatal care clinics at the Instituto Nacional Materno Perinatal (INMP) in Lima, Peru. Three major psychiatric outcomes (depression, PTSD, and suicidal ideation and/or self-harm) were scored by interviewers using valid Spanish questionnaires. Illumina Multi-Ethnic Global chip was used for genotyping. Standard procedures for PRSs and GWAS were used along with extra steps to rule out confounding due to ancestry. Depression PRSs significantly predicted depression, PTSD, and suicidal ideation/self-harm and explained up to 0.6% of phenotypic variation (minimum p = 3.9 × 10-6). The associations were robust to sensitivity analyses using more homogeneous subgroups of participants and alternative choices of principal components. Successful polygenic prediction of three psychiatric phenotypes in this Peruvian cohort suggests that genetic influences on depression, PTSD, and suicidal ideation/self-harm are at least partially shared across global populations. These PRS and GWAS results from this large Peruvian cohort advance genetic research (and the potential for improved treatments) for diverse global populations.

Using Genetics to Examine a General Liability to Childhood Psychopathology

Psychiatric disorders show phenotypic as well as genetic overlaps. There are however also marked developmental changes throughout childhood. We investigated the extent to which, for a full range of early childhood psychopathology, a general “p” factor was explained by genetic liability, as indexed by multiple different psychiatric polygenic risk scores (PRS) and whether these relationships altered with age. The sample was a UK, prospective, population-based cohort with psychopathology data at age 7 (N = 8161) and age 13 (N = 7017). PRS were generated from large published genome-wide association studies. At both ages, we found evidence for a childhood “p” factor as well as for specific factors. Schizophrenia and attention-deficit/hyperactivity disorder (ADHD) PRS were associated with this general “p” factor at both ages but depression and autism spectrum disorder (ASD) PRS were not. We also found some evidence of associations between schizophrenia, ADHD and depression PRS with specific factors, but these were less robust and there was evidence for developmental changes.

Psychiatric Polygenic Risk Scores as Predictor for Attention Deficit/Hyperactivity Disorder and Autism Spectrum Disorder in a Clinical Child and Adolescent Sample

Neurodevelopmental disorders such as attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are highly heritable and influenced by many single nucleotide polymorphisms (SNPs). SNPs can be used to calculate individual polygenic risk scores (PRS) for a disorder. We aim to explore the association between the PRS for ADHD, ASD and for Schizophrenia (SCZ), and ADHD and ASD diagnoses in a clinical child and adolescent population. Based on the most recent genome wide association studies of ADHD, ASD and SCZ, PRS of each disorder were calculated for individuals of a clinical child and adolescent target sample (N = 688) and for adult controls (N = 943). We tested with logistic regression analyses for an association with (1) a single diagnosis of ADHD (N = 280), (2) a single diagnosis of ASD (N = 295), and (3) combining the two diagnoses, thus subjects with either ASD, ADHD or both (N = 688). Our results showed a significant association of the ADHD PRS with ADHD status (OR 1.6, P = 1.39 × 10−07) and with the combined ADHD/ASD status (OR 1.36, P = 1.211 × 10−05), but not with ASD status (OR 1.14, P = 1). No associations for the ASD and SCZ PRS were observed. In sum, the PRS of ADHD is significantly associated with the combined ADHD/ASD status. Yet, this association is primarily driven by ADHD status, suggesting disorder specific genetic effects of the ADHD PRS.

Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition.

Psychiatric illnesses are complex and polygenic. They are associated with widespread alterations in the brain, which are partly influenced by genetic factors. There have been some attempts to relate polygenic risk scores (PRS) – a measure of the overall genetic risk an individual carries for a disorder – to brain structure using univariate methods. However, PRS are likely associated with distributed and covarying effects across the brain. We therefore used multivariate machine learning in this proof-of-principle study to investigate associations between brain structure and PRS for four psychiatric disorders; attention deficit-hyperactivity disorder (ADHD), autism, bipolar disorder and schizophrenia. The sample included 213 individuals comprising patients with depression (69), bipolar disorder (33), and healthy controls (111). The five psychiatric PRSs were calculated based on summary data from the Psychiatric Genomics Consortium. T1-weighted magnetic resonance images were obtained and voxel-based morphometry was implemented in SPM12. Multivariate relevance vector regression was implemented in the Pattern Recognition for Neuroimaging Toolbox (PRoNTo). Across the whole sample, a multivariate pattern of grey matter significantly predicted the PRS for autism (r = 0.20, pFDR = 0.03; MSE = 4.20 × 10−5, pFDR = 0.02). For the schizophrenia PRS, the MSE was significant (MSE = 1.30 × 10−5, pFDR = 0.02) although the correlation was not (r = 0.15, pFDR = 0.06). These results lend support to the hypothesis that polygenic liability for autism and schizophrenia is associated with widespread changes in grey matter concentrations. These associations were seen in individuals not affected by these disorders, indicating that this is not driven by the expression of the disease, but by the genetic risk captured by the PRSs.