scholarly journals Evidence that polygenic risk for psychotic disorder is expressed in the domain of neurodevelopment, emotion regulation and attribution of salience

2017 ◽  
Vol 47 (14) ◽  
pp. 2421-2437 ◽  
Author(s):  
J. van Os ◽  
Y. van der Steen ◽  
Md. A. Islam ◽  
S. Gülöksüz ◽  
B. P. Rutten ◽  
...  
Keyword(s):  
Emotion Regulation ◽  
Psychotic Disorder ◽  
Repeated Measures ◽  
Threshold Model ◽  
Structured Interview ◽  
Self Report ◽  
Polygenic Risk Score ◽  
Genetic Associations ◽  
Polygenic Risk ◽  
The One

BackgroundThe liability-threshold model of psychosis risk predicts stronger phenotypic manifestation of the polygenic risk score (PRS) in the healthy relatives of patients, as compared with healthy comparison subjects.MethodsFirst-degree relatives of patients with psychotic disorder (871 siblings and 812 parents) and healthy comparison subjects (n= 523) were interviewed three times in 6 years. Repeated measures of two psychosis phenotypes, the Community Assessment of Psychic Experiences (CAPE; self-report – subscales of positive, negative and depressive symptoms) and the Structured Interview for Schizotypy – Revised (SIS-R; clinical interview – subscales of positive and negative schizotypy), were examined for association with PRS. Interview-based lifetime rate of depressive and manic episodes were also examined, as was association with repeated measures of intelligence quotient (IQ).ResultsIn the relatives, PRS was associated with CAPE/SIS-R total score (respectively,B= 0.12, 95% CI 0.02–0.22 andB= 0.11, 95% CI 0.02–0.20), the SIS-R positive subscale (B= 0.16, 95% CI 0.04–0.28), the CAPE depression subscale (B= 0.21, 95% CI 0.07–0.34), any lifetime affective episode (OR 3.1, 95% CI 1.04–9.3), but not with IQ (B= −1.8, 95% CI −8.0 to 4.4). In the controls, similar associations were apparent between PRS on the one hand and SIS-R total score, SIS-R positive, SIS-R negative, any lifetime affective episode and, in contrast, lower IQ (B= −8.5, 95% CI −15.5 to −1.6).ConclusionsIn non-ill people, polygenic risk for psychotic disorder is expressed pleiotropically in the domain of neurodevelopment, emotion regulation and attribution of salience. In subjects at elevated genetic risk, emerging expression of neurodevelopmental alterations may create floor effects, obscuring genetic associations.

scholarly journals Interplay between Schizophrenia Polygenic Risk Score and Childhood Adversity in First-Presentation Psychotic Disorder: A Pilot Study

PLoS ONE ◽  
2016 ◽  
Vol 11 (9) ◽  
pp. e0163319 ◽  
Author(s):  
Antonella Trotta ◽  
Conrad Iyegbe ◽  
Marta Di Forti ◽  
Pak C. Sham ◽  
Desmond D. Campbell ◽  
...  
Keyword(s):  
Pilot Study ◽  
Psychotic Disorder ◽  
Risk Score ◽  
Childhood Adversity ◽  
Polygenic Risk Score ◽  
Polygenic Risk

scholarly journals Polygenic risk modeling with latent trait-related genetic components

2019 ◽  
Author(s):  
Matthew Aguirre ◽  
Yosuke Tanigawa ◽  
Guhan Ram Venkataraman ◽  
Rob Tibshirani ◽  
Trevor Hastie ◽  
...  
Keyword(s):  
Fat Mass ◽  
Genetic Risk ◽  
Complex Traits ◽  
Fat Free Mass ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genetic Associations ◽  
Polygenic Risk ◽  
Genetic Components ◽  
Mass Component

AbstractPolygenic risk models have led to significant advances in understanding complex diseases and their clinical presentation. While models like polygenic risk scores (PRS) can effectively predict outcomes, they do not generally account for disease subtypes or pathways which underlie within-trait diversity. Here, we introduce a latent factor model of genetic risk based on components from Decomposition of Genetic Associations (DeGAs), which we call the DeGAs polygenic risk score (dPRS). We compute DeGAs using genetic associations for 977 traits in the UK Biobank and find that dPRS performs comparably to standard PRS while offering greater interpretability. We show how to decompose an individual’s genetic risk for a trait across DeGAs components, highlighting specific results for body mass index (BMI), myocardial infarction (heart attack), and gout in 337,151 white British individuals, with replication in a further set of 25,486 non-British white individuals from the Biobank. We find that BMI polygenic risk factorizes into components relating to fat-free mass, fat mass, and overall health indicators like physical activity measures. Most individuals with high dPRS for BMI have strong contributions from both a fat mass component and a fat-free mass component, whereas a few ‘outlier’ individuals have strong contributions from only one of the two components. Overall, our method enables fine-scale interpretation of the drivers of genetic risk for complex traits.

scholarly journals Novel polygenic risk score links depression-related cortical transcriptomic changes to brain morphology and symptom severity

2021 ◽  
Author(s):  
Amy E Miles ◽  
Fernanda C Dos Santos ◽  
Enda M Byrne ◽  
Miguel E Renteria ◽  
Andrew M McIntosh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Risk Score ◽  
Symptom Severity ◽  
Self Report ◽  
Brain Morphology ◽  
Polygenic Risk Score ◽  
Depression Diagnosis ◽  
Polygenic Risk ◽  
Depression Risk ◽  
Common Genetic Variants

ABSTRACTOur group developed a transcriptome-based polygenic risk score (T-PRS) that uses common genetic variants to capture ‘depression-like’ shifts in cortical gene expression. Here, we mapped T-PRS onto diagnosis and symptom severity in major depressive disorder (MDD) cases and controls from the Psychiatric Genomics Consortium (PGC). To evaluate potential mechanisms, we further mapped T-PRS onto discrete measures of brain morphology and broad depression risk in healthy young adults. Genetic, self-report, and/or neuroimaging data were available in 29,340 PGC participants (59% women; 12,923 MDD cases, 16,417 controls) and 482 participants in the Duke Neurogenetics Study (DNS: 53% women; aged 19.8±1.2 years). T-PRS was computed from SNP data using PrediXcan to impute cortical expression levels of MDD-related genes from a previous post-mortem transcriptome meta-analysis. Sex-specific regressions were used to test effects of T-PRS on depression diagnosis, symptom severity, and Freesurfer-derived subcortical volume, cortical thickness, surface area, and local gyrification index in the PGC and DNS samples, respectively. T-PRS did not predict depression diagnosis (OR=1.007, 95%CI=[0.997-1.018]); however, it correlated with symptom severity in men (rho=0.175, p=7.957×10−4) in one large PGC cohort (N=762, 48% men). In DNS, T-PRS was associated with smaller amygdala volume in women (β=-0.186, t=-3.478, p=.001) and less prefrontal gyrification (max≤-2.970, p≤.006) in both sexes. In men, prefrontal gyrification mediated an indirect effect of T-PRS on broad depression risk (b=.005, p=.029), indexed using self-reported family history of depression. Depression-like shifts in cortical gene expression predict symptom severity in men and may contribute to disease vulnerability through their effect on cortical gyrification.

scholarly journals Impulsivity and Venturesomeness in an Adult ADHD Sample: Relation to Personality, Comorbidity, and Polygenic Risk

2020 ◽  
Vol 11 ◽  
Author(s):  
Oliver Grimm ◽  
Heike Weber ◽  
Sarah Kittel-Schneider ◽  
Thorsten M. Kranz ◽  
Christian P. Jacob ◽  
...  
Keyword(s):  
Adult Adhd ◽  
Principal Component ◽  
Basic Feature ◽  
Self Report ◽  
Polygenic Risk Score ◽  
Comorbid Disorders ◽  
Psychiatric Comorbidities ◽  
Polygenic Risk ◽  
Different Genetic Background ◽  
Inattentive Type

While impulsivity is a basic feature of attention-deficit/hyperactivity disorder (ADHD), no study explored the effect of different components of the Impulsiveness (Imp) and Venturesomeness (Vent) scale (IV7) on psychiatric comorbidities and an ADHD polygenic risk score (PRS). We used the IV7 self-report scale in an adult ADHD sample of 903 patients, 70% suffering from additional comorbid disorders, and in a subsample of 435 genotyped patients. Venturesomeness, unlike immediate Impulsivity, is not specific to ADHD. We consequently analyzed the influence of Imp and Vent also in the context of a PRS on psychiatric comorbidities of ADHD. Vent shows a distinctly different distribution of comorbidities, e.g., less anxiety and depression. PRS showed no effect on different ADHD comorbidities, but correlated with childhood hyperactivity. In a complementary analysis using principal component analysis with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition ADHD criteria, revised NEO Personality Inventory, Imp, Vent, and PRS, we identified three ADHD subtypes. These are an impulsive–neurotic type, an adventurous–hyperactive type with a stronger genetic component, and an anxious–inattentive type. Our study thus suggests the importance of adventurousness and the differential consideration of impulsivity in ADHD. The genetic risk is distributed differently between these subtypes, which underlines the importance of clinically motivated subtyping. Impulsivity subtyping might give insights into the organization of comorbid disorders in ADHD and different genetic background.

scholarly journals Examining temporal interactions between loneliness and depressive symptoms and the mediating role of emotion regulation difficulties among UK residents during the COVID-19 lockdown: Longitudinal results from the COVID-19 Psychological Wellbeing Study

2020 ◽  
Author(s):  
Jenny Groarke ◽  
Emily McGlinchey ◽  
Phoebe McKenna-Plumley ◽  
Emma Berry ◽  
Lisa Graham-Wisener ◽  
...  
Keyword(s):  
Mental Health ◽  
Emotion Regulation ◽  
Depressive Symptoms ◽  
Health Outcomes ◽  
Repeated Measures ◽  
Online Survey ◽  
Self Report ◽  
Mental Health Outcomes ◽  
Temporal Association ◽  
Depression Symptoms

BackgroundLongitudinal studies examining the temporal association between mental health outcomes during the COVID-19 outbreak are needed. It is important to determine how relationships between mental health outcomes, specifically loneliness and depressive symptoms, manifest over a brief timeframe and in a pandemic context.Method Data was gathered over 4 months (March – June 2020) using an online survey with three repeated measures at monthly intervals (N = 1958; 69.8% females; Age 18-87 years, M = 37.01, SD = 12.81). Associations between loneliness, depression symptoms, and emotion regulation difficulty were tested using Pearson’s product moment correlations, and descriptive statistics were calculated for all study variables. Cross-lagged structural equation modelling was used to examine the temporal relationships between variables. Results The longitudinal association between loneliness and depressive symptoms was reciprocal. Loneliness predicted higher depressive symptoms one month later, and depressive symptoms predicted higher loneliness one month later. The relationship was not mediated by emotion regulation difficulties. Emotion regulation difficulties and depressive symptoms were also reciprocally related over time.Limitations Limitations include the reliance on self-report data and the non-representative sample. There was no pre-pandemic assessment limiting the conclusions that can be drawn regarding the mental health impact of the COVID-19 crisis.ConclusionsLoneliness should be considered an important feature of case conceptualisation for depression during this time. Clinical efforts to improve mental health during the pandemic could focus on interventions that target either loneliness, depression, or both. Potential approaches include increasing physical activity or low-intensity cognitive therapies delivered remotely.

scholarly journals Minimal phenotyping yields GWAS hits of reduced specificity for major depression

2018 ◽  
Author(s):  
Na Cai ◽  
Joana A. Revez ◽  
Mark J Adams ◽  
Till F. M. Andlauer ◽  
Gerome Breen ◽  
...  
Keyword(s):  
Association Studies ◽  
Self Report ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Case Identification ◽  
Disease Case ◽  
Psychiatric Conditions ◽  
Cardinal Symptoms

AbstractMinimal phenotyping refers to the reliance on the use of a small number of self-report items for disease case identification. This strategy has been applied to genome-wide association studies (GWAS) of major depressive disorder (MDD). Here we report that the genotype derived heritability (h2SNP) of depression defined by minimal phenotyping (14%, SE = 0.8%) is lower than strictly defined MDD (26%, SE = 2.2%). This cannot be explained by differences in prevalence between definitions or including cases of lower liability to MDD in minimal phenotyping definitions of depression, but can be explained by misdiagnosis of those without depression or with related conditions as cases of depression. Depression defined by minimal phenotyping is as genetically correlated with strictly defined MDD (rG = 0.81, SE = 0.03) as it is with the personality trait neuroticism (rG = 0.84, SE = 0.05), a trait not defined by the cardinal symptoms of depression. While they both show similar shared genetic liability with neuroticism, a greater proportion of the genome contributes to the minimal phenotyping definitions of depression (80.2%, SE = 0.6%) than to strictly defined MDD (65.8%, SE = 0.6%). We find that GWAS loci identified in minimal phenotyping definitions of depression are not specific to MDD: they also predispose to other psychiatric conditions. Finally, while highly predictive polygenic risk scores can be generated from minimal phenotyping definitions of MDD, the predictive power can be explained entirely by the sample size used to generate the polygenic risk score, rather than specificity for MDD. Our results reveal that genetic analysis of minimal phenotyping definitions of depression identifies non-specific genetic factors shared between MDD and other psychiatric conditions. Reliance on results from minimal phenotyping for MDD may thus bias views of the genetic architecture of MDD and may impede our ability to identify pathways specific to MDD.

scholarly journals 133. Interplay Between Schizophrenia Polygenic Risk Score and Childhood Adversity in First-Presentation Psychotic Disorder: A Pilot Study

2017 ◽  
Vol 43 (suppl_1) ◽  
pp. S72-S72 ◽  
Author(s):  
Antonella Trotta ◽  
Conrad Iyegbe ◽  
Marta Di Forti ◽  
Pak C Sham ◽  
Desmond D Campbell ◽  
...  
Keyword(s):  
Pilot Study ◽  
Psychotic Disorder ◽  
Risk Score ◽  
Childhood Adversity ◽  
Polygenic Risk Score ◽  
Polygenic Risk

scholarly journals Genetic associations with severe COVID-19

2021 ◽  
Author(s):  
Nicholas M Murphy ◽  
Gillian S Dite ◽  
Richard Allman
Keyword(s):  
Risk Prediction ◽  
Risk Score ◽  
Genetic Factors ◽  
Polygenic Risk Score ◽  
Genetic Associations ◽  
Polygenic Risk ◽  
Host Genetic ◽  
The Difference ◽  
Population Controls ◽  
Host Genetic Factors

Identification of host genetic factors that predispose individuals to severe COVID-19 is important, not only for understanding the disease and guiding the development of treatments, but also for risk prediction when combined to form a polygenic risk score (PRS). Using population controls, Pairo-Castineira et al. identified 12 SNPs (a panel of 8 SNPs and a panel of 6 SNPs, with two SNPs in both panels) associated with severe COVID-19. Using controls with asymptomatic or mild COVID-19, we were able to replicate the association with severe COVID-19 for only three of their SNPs and found marginal evidence for an association for one other. When combined as an 8-SNP PRS and a 6-SNP PRS, we found no evidence of association with severe COVID-19. The difference in our results and the results of Pairo-Castineira et al. might be the choice of controls: population controls vs controls with asymptomatic or mild COVID-19.

scholarly journals The independent and combined influence of schizophrenia polygenic risk score and heavy cannabis use on risk for psychotic disorder: A case-control analysis from the EUGEI study.

2019 ◽  
Author(s):  
Marta Di Forti ◽  
Beatrice Wu-Choi ◽  
Diego Quattrone ◽  
Alexander L Richards ◽  
Tom P Freeman ◽  
...  
Keyword(s):  
Psychotic Disorder ◽  
Risk Score ◽  
Case Control ◽  
Cannabis Use ◽  
European Ancestry ◽  
Polygenic Risk Score ◽  
Environment Interaction ◽  
Control Analysis ◽  
Polygenic Risk ◽  
Type Composite

Background: Some recent studies have challenged the direction of causality for the association between cannabis use and psychotic disorder, suggesting that cannabis use initiation is explained by common genetic variants associated with risk of schizophrenia. We used data from the European Union Gene-Environment Interaction consortium (EUGEI) case-control study to test for the independent and combined effect of heavy cannabis use, and of Schizophrenia Polygenic risk score (SZ PRS), on risk for psychotic disorder. Methods: Genome-wide data were obtained from 492 first episode psychosis patients (FEPp) and from 787 controls of European Ancestry, and used to generate SZ PRS from the summary results of an independent meta-analysis. Information on pattern of cannabis use was used to build a 7-level frequency-type composite cannabis use measure that we previously found was a strong predictor of psychotic disorder. Results: SZ PRS did not predict cannabis initiation (b=0.027; p=0.51) or how frequently controls (b=0.027; p=0.06) or FEPp (b=0.006; p=0.91) used it, or the type of cannabis they used (Controls: b = 0.032; p=0.31); FEPp: b= 0.005; p=0.89). The frequency-type composite cannabis use measure (OR=1.32; 95% CI 1.22-1.44) and SZ PRS (OR=2.29; 95%CI 1.71-3.05) showed independent effects from each other on the OR for psychotic disorder. Conclusion: SZ PRS does not predict an individual s propensity to try cannabis, frequency of use, or the potency of the cannabis used. Our findings provide the first evidence that SZ PRS and heavy cannabis use exert effects independent from each other on the risk for psychotic disorder.

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