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 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.

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 F31. POLYGENIC RISK SCORES AND EARLY RISK ENDOPHENOTYPES IN CHILDREN AT GENETIC RISK OF SCHIZOPHRENIA AND BIPOLAR DISORDER: IMPLICATIONS FOR THE DEFINITION OF THE CHILDHOOD RISK STATUS

2018 ◽  
Vol 44 (suppl_1) ◽  
pp. S230-S231
Author(s):  
Thomas Paccalet ◽  
Alexandre Bureau ◽  
Elsa Gilbert ◽  
Nicolas Berthelot ◽  
Pierre Marquet ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Genetic Risk ◽  
Risk Scores ◽  
Risk Status ◽  
Polygenic Risk ◽  
Early Risk ◽  
Definition Of

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 The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: A systematic review

2018 ◽  
Vol 234 ◽  
pp. 148-155 ◽  
Author(s):  
Sumit Mistry ◽  
Judith R. Harrison ◽  
Daniel J. Smith ◽  
Valentina Escott-Price ◽  
Stanley Zammit
Keyword(s):  
Systematic Review ◽  
Bipolar Disorder ◽  
Genetic Risk ◽  
Risk Scores ◽  
Polygenic Risk

scholarly journals Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Joshua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Prediction Accuracy ◽  
Genetic Risk Score ◽  
Low Risk ◽  
Risk Scores ◽  
Sample Mean ◽  
Polygenic Risk ◽  
Reliable Identification

AbstractPolygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals’ scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals’ scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.

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
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