The use of Polygenic Risk Scores to Inform Aetiology of Mood and Psychotic Disorders

2017 ◽  
Vol 41 (S1) ◽  
pp. S166-S166
Author(s):  
J. Harrison ◽  
S. Mistry
Keyword(s):  
Bipolar Disorder ◽  
Genetic Basis ◽  
Psychotic Disorders ◽  
Mental Illnesses ◽  
Risk Scores ◽  
Psychotic Symptoms ◽  
Polygenic Risk ◽  
Genetic Overlap ◽  
Competing Interest

IntroductionPolygenic risk scores (PRS) incorporate many small genetic markers that are associated with conditions. This technique was first used to investigate mental illnesses in 2009. Since then, it has been widely used.ObjectivesWe wanted to explore how PRS have been used to the study the aetiology of psychosis, schizophrenia, bipolar disorder and depression.AimsWe aimed to conduct a systematic review, identifying studies that have examined associations between PRS for bipolar disorder, schizophrenia/psychosis and depression and psychopathology-related outcome measures.MethodsWe searched EMBASE, Medline and PsychInfo from 06/08/2009 to 14/03/2016. We hand-searched the reference lists of related papers.ResultsAfter removing duplicates, the search yielded 1043 publications. When irrelevant articles were excluded, 33 articles remained. We found 24 studies using schizophrenia PRS, three using bipolar PRS and nine using depression PRS. Many studies successfully used PRS to predict case/control status. Some studies showed associations between PRS and diagnostic sub-categories. A range of clinical phenotypes and symptoms has been explored. For example, specific PRS are associated with cognitive performance in schizophrenia, psychotic symptoms in bipolar disorder, and frequency of episodes of depression. PRS have also demonstrated genetic overlap between mental illnesses. It was difficult to assess the quality of some studies as not all reported sufficient methodological detail.ConclusionsPRS have enabled us to explore the polygenic architecture of mental illness and demonstrate a genetic basis for some observed features. However, they have yet to give insights into the biology, which underpin mental illnesses.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Genetic risk for bipolar disorder and schizophrenia predicts structure and function of the ventromedial prefrontal cortex

2021 ◽  
Vol 46 (4) ◽  
pp. E441-E450
Author(s):  
Christoph Abé ◽  
Predrag Petrovic ◽  
William Ossler ◽  
William H. Thompson ◽  
Benny Liberg ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Prefrontal Cortex ◽  
Genetic Risk ◽  
Psychotic Disorders ◽  
Structure And Function ◽  
Ventromedial Prefrontal Cortex ◽  
Risk Scores ◽  
Polygenic Risk ◽  
And Function ◽  
Structural Brain

Background: Bipolar disorder is highly heritable and polygenic. The polygenic risk for bipolar disorder overlaps with that of schizophrenia, and polygenic scores are normally distributed in the population. Bipolar disorder has been associated with structural brain abnormalities, but it is unknown how these are linked to genetic risk factors for psychotic disorders. Methods: We tested whether polygenic risk scores for bipolar disorder and schizophrenia predict structural brain alterations in 98 patients with bipolar disorder and 81 healthy controls. We derived brain cortical thickness, surface area and volume from structural MRI scans. In post-hoc analyses, we correlated polygenic risk with functional hub strength, derived from resting-state functional MRI and brain connectomics. Results: Higher polygenic risk scores for both bipolar disorder and schizophrenia were associated with a thinner ventromedial prefrontal cortex (vmPFC). We found these associations in the combined group, and separately in patients and drug-naive controls. Polygenic risk for bipolar disorder was correlated with the functional hub strength of the vmPFC within the default mode network. Limitations: Polygenic risk is a cumulative measure of genomic burden. Detailed genetic mechanisms underlying brain alterations and their cognitive consequences still need to be determined. Conclusion: Our multimodal neuroimaging study linked genomic burden and brain endophenotype by demonstrating an association between polygenic risk scores for bipolar disorder and schizophrenia and the structure and function of the vmPFC. Our findings suggest that genetic factors might confer risk for psychotic disorders by influencing the integrity of the vmPFC, a brain region involved in self-referential processes and emotional regulation. Our study may also provide an imaging–genetics vulnerability marker that can be used to help identify individuals at risk for developing bipolar disorder.

scholarly journals Associations between polygenic liability for schizophrenia and level of psychosis and mood-incongruence in bipolar disorder

2017 ◽  
Author(s):  
Judith Allardyce ◽  
Ganna Leonenko ◽  
Marian Hamshere ◽  
Antonio F. Pardiñas ◽  
Liz Forty ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Logistic Regression ◽  
Multinomial Logistic Regression ◽  
Bipolar Affective Disorder ◽  
Research Network ◽  
Risk Scores ◽  
Psychotic Symptoms ◽  
P Value ◽  
Polygenic Risk ◽  
Psychotic Features

AbstractImportanceBipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes/mechanisms.ObjectivesTo investigate the relationship between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRS) and psychotic presentations of BD, using clinical descriptions which consider both occurrence and level of mood-incongruent psychotic features.DesignCase-control design: using multinomial logistic regression, to estimate differential associations of PRS across categories of cases and controls.Settings & Participants4399 BDcases, mean [sd] age-at-interview 46[12] years, of which 2966 were woman (67%) from the BD Research Network (BDRN) were included in the final analyses, with data for 4976 schizophrenia cases and 9012 controls from the Type-1 diabetes genetics consortium and Generation Scotland included for comparison.ExposureStandardised PRS, calculated using alleles with an association p-value threshold < 0.05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, adjusted for the first 10 population principal components and genotyping-platform.Main outcome measureMultinomial logit models estimated PRS associations with BD stratified by (1) Research Diagnostic Criteria (RDC) BD subtypes (2) Lifetime occurrence of psychosis.(3) Lifetime mood-incongruent psychotic features and (4) ordinal logistic regression examined PRS associations across levels of mood-incongruence. Ratings were derived from the Schedule for Clinical Assessment in Neuropsychiatry interview (SCAN) and the Bipolar Affective Disorder Dimension Scale (BADDS).ResultsAcross clinical phenotypes, there was an exposure-response gradient with the strongest PRS association for schizophrenia (RR=1.94, (95% C.1.1.86, 2.01)), then schizoaffective BD (RR=1.37, (95% C.I. 1.22, 1.54)), BD I (RR= 1.30, (95% C.I. 1.24, 1.36)) and BD II (RR=1.04, (95% C.1. 0.97, 1.11)). Within BD cases, there was an effect gradient, indexed by the nature of psychosis, with prominent mood-incongruent psychotic features having the strongest association (RR=1.46, (95% C.1.1.36, 1.57)), followed by mood-congruent psychosis (RR= 1.24, (95% C.1. 1.17, 1.33)) and lastly, BD cases with no history of psychosis (RR= 1.09, (95% C.1. 1.04, 1.15)).ConclusionWe show for the first time a polygenic-risk gradient, across schizophrenia and bipolar disorder, indexed by the occurrence and level of mood-incongruent psychotic symptoms.

scholarly journals A Longitudinal Approach to Biological Psychiatric Research: The PsyCourse Study

2017 ◽  
Author(s):  
Monika Budde ◽  
Heike Anderson-Schmidt ◽  
Katrin Gade ◽  
Daniela Reich-Erkelenz ◽  
Kristina Adorjan ◽  
...  
Keyword(s):  
Psychotic Disorders ◽  
Diagnostic Group ◽  
Psychiatric Research ◽  
Risk Scores ◽  
Psychotic Symptoms ◽  
Diagnostic Systems ◽  
Global Functioning ◽  
Polygenic Risk ◽  
First Results ◽  
Present Design

In current diagnostic systems, schizophrenia and bipolar disorder are still conceptualized as distinct categorical entities. Recently, both clinical and genetic evidence have challenged this Kraepelinian dichotomy. There are only few longitudinal studies addressing the potential overlaps between these conditions. Here, we present design and first results of the PsyCourse study, an ongoing transdiagnostic study of the affective-to-psychotic continuum that combines longitudinal deep phenotyping and dimensional assessment of psychopathology with an extensive collection of biomaterial. Within the DSM-IV framework, we compare two broad diagnostic groups: one consisting of predominantly affective and one of predominantly psychotic disorders. Depressive, manic, and psychotic symptoms as well as global functioning over time were analyzed. Furthermore, we explore the effects of polygenic risk scores for schizophrenia on diagnostic group membership and address their effects on non-participation in follow-up visits. While phenotypic results show differences in both current psychotic and manic symptoms, depressive symptoms did not vary between both groups. Polygenic risk scores for schizophrenia significantly explained part of the variability of the diagnostic group. Furthermore, there was a trend that a higher polygenic loading for schizophrenia was associated with attrition. Because of its unique properties, the PsyCourse study presents a prime resource for the interrogation of complex genotype-phenotype relationships.

scholarly journals Use of schizophrenia and bipolar disorder polygenic risk scores to identify psychotic disorders

2018 ◽  
Vol 213 (3) ◽  
pp. 535-541 ◽  
Author(s):  
Maria Stella Calafato ◽  
Johan H. Thygesen ◽  
Siri Ranlund ◽  
Eirini Zartaloudi ◽  
Wiepke Cahn ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Predictive Models ◽  
Genetic Variants ◽  
Psychotic Disorders ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Early Interventions ◽  
Polygenic Risk ◽  
Increases In Risk ◽  
Shared Genetic

BackgroundThere is increasing evidence for shared genetic susceptibility between schizophrenia and bipolar disorder. Although genetic variants only convey subtle increases in risk individually, their combination into a polygenic risk score constitutes a strong disease predictor.AimsTo investigate whether schizophrenia and bipolar disorder polygenic risk scores can distinguish people with broadly defined psychosis and their unaffected relatives from controls.MethodUsing the latest Psychiatric Genomics Consortium data, we calculated schizophrenia and bipolar disorder polygenic risk scores for 1168 people with psychosis, 552 unaffected relatives and 1472 controls.ResultsPatients with broadly defined psychosis had dramatic increases in schizophrenia and bipolar polygenic risk scores, as did their relatives, albeit to a lesser degree. However, the accuracy of predictive models was modest.ConclusionsAlthough polygenic risk scores are not ready for clinical use, it is hoped that as they are refined they could help towards risk reduction advice and early interventions for psychosis.Declaration of interestR.M.M. has received honoraria for lectures from Janssen, Lundbeck, Lilly, Otsuka and Sunovian.

scholarly journals Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity

2021 ◽  
pp. 1-12
Author(s):  
Simon Schmitt ◽  
Tina Meller ◽  
Frederike Stein ◽  
Katharina Brosch ◽  
Kai Ringwald ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Mental Disorders ◽  
Cortical Thickness ◽  
Genetic Risk ◽  
Right Hemisphere ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Grey Matter Volume ◽  
Polygenic Risk ◽  
Risk For Depression

Abstract Background MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. Methods We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. Results The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. Conclusions Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

Association between Polygenic Risk Scores for ADHD and Asthma: A Birth Cohort Investigation

2021 ◽  
pp. 108705472110201
Author(s):  
Douglas Teixeira Leffa ◽  
Bernardo Horta ◽  
Fernando C. Barros ◽  
Ana M. B. Menezes ◽  
Thais Martins-Silva ◽  
...  
Keyword(s):  
Birth Cohort ◽  
Genetic Background ◽  
Adult Adhd ◽  
Risk Scores ◽  
Asthma Diagnosis ◽  
Polygenic Risk ◽  
Increased Risk ◽  
Genetic Overlap ◽  
Genetic Mechanisms ◽  
Shared Genetic

Objective: Shared genetic mechanisms have been hypothesized to explain the comorbidity between ADHD and asthma. To evaluate their genetic overlap, we relied on data from the 1982 Pelotas birth cohort to test the association between polygenic risk scores (PRSs) for ADHD (ADHD-PRSs) and asthma, and PRSs for asthma (asthma-PRSs) and ADHD. Method: We analyzed data collected at birth, 2, 22, and 30 years from 3,574 individuals. Results: Subjects with ADHD had increased risk of having asthma (OR 1.92, 95% CI 1.01–3.66). The association was stronger for females. Our results showed no evidence of association between ADHD-PRSs and asthma or asthma-PRSs and ADHD. However, an exploratory analysis suggested that adult ADHD might be genetically associated with asthma. Conclusion: Our results do not support a shared genetic background between both conditions. Findings should be viewed in light of important limitations, particularly the sample size and the self-reported asthma diagnosis. Studies in larger datasets are required to better explore the genetic overlap between adult ADHD and asthma.

Psychiatric comorbidities in temporal lobe epilepsy: A case study

2017 ◽  
Vol 41 (S1) ◽  
pp. S474-S474
Author(s):  
L. Jouini ◽  
U. Ouali ◽  
R. Zaouche ◽  
R. Jomli ◽  
Y. Zgueb ◽  
...  
Keyword(s):  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Psychotic Disorders ◽  
Psychiatric Symptoms ◽  
Complete Disappearance ◽  
Therapeutic Implications ◽  
Self Harm ◽  
Competing Interest

IntroductionPsychiatric disorders frequently occur in patients with temporal lobe epilepsy (TLE) (70%). This combination further reduces the quality of life of patients as diagnosis is difficult and therapeutic opportunities are often missed.ObjectivesThe aim of this case study is to show the possible association between TLE and psychiatric semiology and its therapeutic implications.MethodsPresentation of the clinical case of Mr BH who experienced psychosis like symptoms, was finally diagnosed with TLE and put under anti-epileptic drugs.ResultsMr BH, aged 22, with no family or personal history, was admitted for aggressive behavior, self-harm, pyromania, and depression. Three years prior to onset of psychiatric symptoms, he reports episodes of pulsatile- left-temporal headache followed by hypertonic movements of the neck. Symptoms were intermittently followed by total amnesia or impaired consciousness. The patient explained symptoms by an inner presence that he called “his twin” and to whom he attributed those behaviors contrary to his will. The discovery of bilateral hippocampal atrophy in magnetic resonance imaging with a normal electroencephalography suggested the diagnosis of TLE with post-ictal psychotic disorders. Patient was put initially on diazepam and olanzapine with partial improvement. Association of valproate led to progressive but then complete disappearance of symptoms and so confirmed our diagnosis.ConclusionsIt is often difficult to attach psychiatric symptoms to epilepsy. The diagnosis should be done on a set of clinical, radiological and electrical arguments.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Polygenic Risk Scores Derived From Largest Schizophrenia Gwas Are Associated With The Presence Of Psychosis And Level Of Mood Incongruent Psychosis In Bipolar Disorder

2017 ◽  
Vol 27 ◽  
pp. S445-S446
Author(s):  
Judith Allardyce ◽  
Ganna Leonenko ◽  
Marian Hamshere ◽  
Sarah Knott ◽  
Liz Forty ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Risk Scores ◽  
Polygenic Risk

scholarly journals Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank

PLoS Medicine ◽  
2021 ◽  
Vol 18 (10) ◽  
pp. e1003782
Author(s):  
Michael Wainberg ◽  
Samuel E. Jones ◽  
Lindsay Melhuish Beaupre ◽  
Sean L. Hill ◽  
Daniel Felsky ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Sleep Duration ◽  
Sleep Efficiency ◽  
Risk Scores ◽  
Psychiatric Diagnoses ◽  
Uk Biobank ◽  
Major Depressive ◽  
Cross Sectional ◽  
Polygenic Risk ◽  
The Uk

Background Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort. Methods and findings In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures—bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration—were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = −0.11 (95% confidence interval −0.13 to −0.10, p = 3 × 10−56, FDR = 6 × 10−55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry. Conclusions In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.

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