Associations Between Genetic Risk For Psychiatric Disorders and Childhood Neurodevelopment: Investigating Polygenic Risk Scores For Psychiatric Disorders and Traits In General Population Samples

Psychiatric disorders place a huge burden on those affected and their families, as well as society. Nearly all psychiatric disorders have a heritable component and lifetime prevalence rates of several disorders are higher among first degree biological relatives of individuals with a diagnosis. Given that many psychiatric disorders have their onset in adolescence, estimating genetic risk during childhood may identify at-risk individuals for early intervention that can reduce this burden. Here we measured genetic risk for psychopathology using both polygenic risk scores (PRS) and family history in a large typically developing sample of 9-10 year old children from the Adolescent Brain and Cognitive Development (ABCD) StudySM and determined associations with a large battery of behavioural phenotypes. By including all genetic risk predictors in the same model, we were able to delineate unique behavioral associations across these measures. Polygenic risk for Attention Deficit Hyperactivity Disorder (ADHD) and depression (DEP) was associated with unique patterns of both externalizing and internalizing behaviors. Family history of conduct problems, depression and anxiety/stress additionally predicted unique behavioral variance across similar measures. These findings provide important insight into the potential predictive utility of PRS and family history in early adolescence and suggest that they may be signaling differential, additive information that could be useful for quantifying risk during development.

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Polygenic risk for psychiatric disorder reveals distinct association profiles across social behaviour in the general population

10.1101/2021.06.28.21259532 ◽

2021 ◽

Author(s):

Fenja Schlag ◽

Andrea Giuseppe Allegrini ◽

Jan Buitelaar ◽

Ellen Verhoef ◽

Marjolein van Donkelaar ◽

...

Keyword(s):

General Population ◽

Psychiatric Disorders ◽

Social Behaviour ◽

Negative Binomial ◽

Random Effect ◽

Population Based ◽

Autism Spectrum ◽

Risk Scores ◽

Polygenic Risk ◽

Shared Genetic

Many complex psychiatric disorders are characterised by a spectrum of social difficulties. These symptoms lie on a behavioural dimension that is shared with social behaviour in the general population, with substantial contributions of genetic factors. However, shared genetic links may vary across psychiatric disorders and social symptoms. Here, we systematically investigate heterogeneity in shared genetic liabilities with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), bipolar disorder (BP), major depression (MD) and schizophrenia, across a spectrum of different social symptoms. Specifically, longitudinally assessed low-prosociality and peer-problem scores in two UK population-based/community-based cohorts (ALSPAC, N ≤ 6174, 4-17 years; TEDS, N ≤ 7112, 4-16 years; parent- and teacher-reports) were regressed on polygenic risk scores for ADHD, ASD, BP, MD, and schizophrenia, as informed by genome-wide summary statistics from large consortia, using negative binomial regression models. Across ALSPAC and TEDS, we replicated univariate polygenic associations between social behaviour and risk for ADHD, MD, and schizophrenia. Modelling univariate genetic effects across both cohorts with random-effect meta-regression revealed evidence for polygenic links between social behaviour and ADHD, ASD, MD, and schizophrenia risk, but not BP, where differences in age, reporter and social trait captured 45-88% in univariate effect variation. For ADHD, MD, and ASD polygenic risk, we identified stronger association with peer problems than low prosociality, while schizophrenia polygenic risk was solely associated with low prosociality. The identified association profiles suggest marked differences in the social genetic architecture underlying different psychiatric disorders when investigating population-based social symptoms across 13 years of child and adolescent development.

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Distribution of 54 polygenic risk scores for common diseases in long lived individuals and their offspring

10.1101/2021.06.23.21257874 ◽

2021 ◽

Author(s):

Sophia Gunn ◽

Michael Wainberg ◽

Zeyuan Song ◽

Stacy Andersen ◽

Robert Boudreau ◽

...

Keyword(s):

General Population ◽

Genetic Risk ◽

Disease Risk ◽

Association Studies ◽

Risk Scores ◽

Human Longevity ◽

Genome Wide Association Studies ◽

Predictive Values ◽

Polygenic Risk ◽

Polygenic Scores

Background: A surprising and well-replicated result in genetic studies of human longevity is that centenarians appear to carry disease-associated variants in numbers similar to the general population. With the proliferation of large genome-wide association studies (GWAS) in recent years, investigators have turned to polygenic scores to leverage GWAS results into a measure of genetic risk that can better predict risk of disease than individual significant variants alone. Methods: We selected 54 polygenic risk scores (PRSs) developed for a variety of outcomes and we calculated their values in individuals from the New England Centenarian Study (NECS, N = 4886) and the Long Life Family Study (LLFS, N = 4577). We compared the distribution of these PRSs among exceptionally long-lived individuals (ELLI), their offspring and controls and we also examined their predictive values, using t-tests and regression models adjusting for sex and principal components reflecting ancestral background of the individuals (PCs). In our analyses we controlled for multiple testing using a Bonferroni-adjusted threshold for 54 traits. Results: We found that only 4 of the 54 PRSs differed between ELLIs and controls in both cohorts. ELLIs had significantly lower mean PRSs for Alzheimer's disease (AD), coronary artery disease (CAD) and systemic lupus than controls, suggesting genetic predisposition to extreme longevity may be mediated by reduced susceptibility to these traits. ELLIs also had significantly higher mean PRSs for improved cognitive function. In addition, the PRS for AD was associated with higher risk of dementia among controls but not ELLIs (p = 0.0004, 0.3 in NECS, p = 0.03, 0.93 in LLFS respectively). Interestingly, ELLIs did not have a larger number of homozygous risk genotypes for AD (TNECS = -1.72, TLLFs = 0.83) and CAD (TNECS = -5.08, TLLFs = -0.31) in both cohorts, but did have significantly larger number of homozygous protective genotypes than controls for the two traits (AD: TNECS =3.10, TLLFs = 2.2, CAD: TNECS = 6.57, TLLFs =2.36, respectively). Conclusions: ELLIs have a similar burden of genetic disease risk as the general population for most traits, but have significantly lower genetic risk of AD, CAD, and lupus. The lack of association between AD PRS and dementia among ELLIs suggests that their genetic risk for AD is somehow buffered by protective genetic or environmental factors.

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Subthreshold psychosis symptoms associated with molecular genetic risk in a population-based cohort: Findings from Generation Scotland

10.1101/821041 ◽

2019 ◽

Author(s):

A.R. Docherty ◽

Andrey A. Shabalin ◽

Daniel E. Adkins ◽

Frank Mann ◽

Robert F. Krueger ◽

...

Keyword(s):

Sex Differences ◽

General Population ◽

Genetic Risk ◽

Molecular Genetic ◽

Population Based ◽

Risk Scores ◽

Factor Scores ◽

Polygenic Risk ◽

Genome Wide ◽

Genetic Risks

AbstractImportanceSubthreshold psychosis symptoms in the general population may be associated with genetic risk for schizophrenia. In this analysis, empirically-derived symptom factor scores led to a detection of significant and robust polygenic signal.ObjectiveThis study sought to optimize genetic association with data-driven symptom factor scores, accounting for cohort factor structure and sex differences.DesignEFA-derived symptom factor scores were regressed onto PRS for schizophrenia in models accounting for age and genetic ancestry principal components. Follow-up examination of symptom factor score associations with other related genetic risks included ADHD, autism, bipolar disorder, major depression, and neuroticism.ParticipantsThis study examined the newly expanded symptom dataset from the Northern European ancestry cohort, Generation Scotland: Scottish Family Health Study (N = 9,105 individuals 18-65 years of age) comprising common variant and subthreshold psychosis symptom data. A total of 5,391 females and 3,713 males with age M[SD] = 45.2 [13] were included in the final analyses.Main Outcome and MeasureSubthreshold psychosis symptoms were measured using the Schizotypal Personality Questionnaire-Brief (SPQ-B). Primary phenotypic factor scores and genome-wide polygenic risk scores (PRS) reflected weighted sum scores and were examined as continuous measures. Polygenic risk scores were calculated from genome-wide association summary statistics using 7,358,674 imputed common genetic variants passing quality control.ResultsIn males, symptom factor scores were positively associated with polygenic risk for schizophrenia alone and implicated primarily interpersonal/negative symptoms. In females, symptom factor scores were positively associated with polygenic risks for ADHD and autism but not schizophrenia. Scores were robustly associated with genetic risk for neuroticism across both males and females.Conclusions and RelevanceThis study detected a significant association of subthreshold psychosis symptoms with genetic risk for schizophrenia and neuroticism in a population-based sample. Furthermore, important sex differences suggest a need for better understanding of schizophrenia risk assessment in females.Key PointsQuestionWhat molecular genetic risks are associated with subthreshold psychosis symptoms in the general population?FindingsIn a large population-based cohort (N = 9,084), significant associations of polygenic risks with symptoms were observed. Symptoms were associated with genetic risk for schizophrenia in males, for ADHD and autism spectrum disorder in females, and for neuroticism across both males and females.MeaningAssociations of genetic risk with symptoms in the general population are highly significant and suggest important sex differences.

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

Psychological Medicine ◽

10.1017/s0033291721001082 ◽

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.

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

Nature Communications ◽

10.1038/s41467-021-24082-z ◽

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.

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Dissecting clinical heterogeneity of bipolar disorder using multiple polygenic risk scores

10.1101/2020.03.31.20044800 ◽

2020 ◽

Author(s):

Brandon J. Coombes ◽

Matej Markota ◽

J. John Mann ◽

Colin Colby ◽

Eli Stahl ◽

...

Keyword(s):

Bipolar Disorder ◽

Psychiatric Disorders ◽

Suicide Attempts ◽

Risk Scores ◽

Rapid Cycling ◽

Clinical Heterogeneity ◽

Polygenic Risk ◽

Clinical Observations ◽

History Of ◽

Dsm Iv

AbstractBipolar disorder (BD) has high clinical heterogeneity, frequent psychiatric comorbidities, and elevated suicide risk. To determine genetic differences between common clinical sub-phenotypes of BD, we performed a systematic PRS analysis using multiple polygenic risk scores (PRSs) from a range of psychiatric, personality, and lifestyle traits to dissect differences in BD sub-phenotypes in two BD cohorts: the Mayo Clinic BD Biobank (N = 968) and Genetic Association Information Network (N = 1001). Participants were assessed for history of psychosis, early-onset BD, rapid cycling (defined as four or more episodes in a year), and suicide attempts using questionnaires and the Structured Clinical Interview for DSM-IV. In a combined sample of 1969 bipolar cases (45.5% male), those with psychosis had higher PRS for SCZ (OR = 1.3 per S.D.; p = 3e-5) but lower PRSs for anhedonia (OR = 0.87; p = 0.003) and BMI (OR = 0.87; p = 0.003). Rapid cycling cases had higher PRS for ADHD (OR = 1.23; p = 7e-5) and MDD (OR = 1.23; p = 4e-5) and lower BD PRS (OR = 0.8; p = 0.004). Cases with a suicide attempt had higher PRS for MDD (OR = 1.26; p = 1e-6) and anhedonia (OR = 1.22; p = 2e-5) as well as lower PRS for educational attainment (OR = 0.87; p = 0.003). The observed novel PRS associations with sub-phenotypes align with clinical observations such as rapid cycling BD patients having a greater lifetime prevalence of ADHD. Our findings confirm that genetic heterogeneity underlies the clinical heterogeneity of BD and consideration of genetic contribution to psychopathologic components of psychiatric disorders may improve genetic prediction of complex psychiatric disorders.

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Neural correlates of polygenic risk score for autism spectrum disorders in general population

Brain Communications ◽

10.1093/braincomms/fcaa092 ◽

2020 ◽

Vol 2 (2) ◽

Author(s):

Budhachandra Khundrakpam ◽

Uku Vainik ◽

Jinnan Gong ◽

Noor Al-Sharif ◽

Neha Bhutani ◽

...

Keyword(s):

Autism Spectrum Disorder ◽

White Matter ◽

General Population ◽

Cortical Thickness ◽

Autism Spectrum ◽

Spectrum Disorder ◽

Risk Scores ◽

Polygenic Risk ◽

Cortical Regions ◽

White Matter Connectivity

Abstract Autism spectrum disorder is a highly prevalent and highly heritable neurodevelopmental condition, but studies have mostly taken traditional categorical diagnosis approach (yes/no for autism spectrum disorder). In contrast, an emerging notion suggests a continuum model of autism spectrum disorder with a normal distribution of autistic tendencies in the general population, where a full diagnosis is at the severe tail of the distribution. We set out to investigate such a viewpoint by investigating the interaction of polygenic risk scores for autism spectrum disorder and Age2 on neuroimaging measures (cortical thickness and white matter connectivity) in a general population (n = 391, with age ranging from 3 to 21 years from the Pediatric Imaging, Neurocognition and Genetics study). We observed that children with higher polygenic risk for autism spectrum disorder exhibited greater cortical thickness for a large age span starting from 3 years up to ∼14 years in several cortical regions localized in bilateral precentral gyri and the left hemispheric postcentral gyrus and precuneus. In an independent case–control dataset from the Autism Brain Imaging Data Exchange (n = 560), we observed a similar pattern: children with autism spectrum disorder exhibited greater cortical thickness starting from 6 years onwards till ∼14 years in wide-spread cortical regions including (the ones identified using the general population). We also observed statistically significant regional overlap between the two maps, suggesting that some of the cortical abnormalities associated with autism spectrum disorder overlapped with brain changes associated with genetic vulnerability for autism spectrum disorder in healthy individuals. Lastly, we observed that white matter connectivity between the frontal and parietal regions showed significant association with polygenic risk for autism spectrum disorder, indicating that not only the brain structure, but the white matter connectivity might also show a predisposition for the risk of autism spectrum disorder. Our findings showed that the fronto-parietal thickness and connectivity are dimensionally related to genetic risk for autism spectrum disorder in general population and are also part of the cortical abnormalities associated with autism spectrum disorder. This highlights the necessity of considering continuum models in studying the aetiology of autism spectrum disorder using polygenic risk scores and multimodal neuroimaging.

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SNP-Based Genetic Risk Score Modeling Suggests No Increased Genetic Susceptibility of the Roma Population to Type 2 Diabetes Mellitus

Genes ◽

10.3390/genes10110942 ◽

2019 ◽

Vol 10 (11) ◽

pp. 942 ◽

Cited By ~ 7

Author(s):

Nardos Abebe Werissa ◽

Peter Piko ◽

Szilvia Fiatal ◽

Zsigmond Kosa ◽

Janos Sandor ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

General Population ◽

Genetic Risk ◽

Genetic Risk Score ◽

Risk Scores ◽

Unhealthy Lifestyle ◽

Roma Population

Background: In a previous survey, an elevated fasting glucose level (FG) and/or known type 2 diabetes mellitus (T2DM) were significantly more frequent in the Roma population than in the Hungarian general population. We assessed whether the distribution of 16 single nucleotide polymorphisms (SNPs) with unequivocal effects on the development of T2DM contributes to this higher prevalence. Methods: Genetic risk scores, unweighted (GRS) and weighted (wGRS), were computed and compared between the study populations. Associations between GRSs and FG levels and T2DM status were investigated in separate and combined study populations. Results: The Hungarian general population carried a greater genetic risk for the development of T2DM (GRSGeneral = 15.38 ± 2.70 vs. GRSRoma = 14.80 ± 2.68, p < 0.001; wGRSGeneral = 1.41 ± 0.32 vs. wGRSRoma = 1.36 ± 0.31, p < 0.001). In the combined population models, GRSs and wGRSs showed significant associations with elevated FG (p < 0.001) and T2DM (p < 0.001) after adjusting for ethnicity, age, sex, body mass index (BMI), high-density Lipoprotein Cholesterol (HDL-C), and triglyceride (TG). In these models, the effect of ethnicity was relatively strong on both outcomes (FG levels: βethnicity = 0.918, p < 0.001; T2DM status: ORethnicity = 2.484, p < 0.001). Conclusions: The higher prevalence of elevated FG and/or T2DM among Roma does not seem to be directly linked to their increased genetic load but rather to their environmental/cultural attributes. Interventions targeting T2DM prevention among Roma should focus on harmful environmental exposures related to their unhealthy lifestyle.

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The Prediction of the Course of Minor Psychiatric Disorders

The British Journal of Psychiatry ◽

10.1192/bjp.135.6.535 ◽

1979 ◽

Vol 135 (6) ◽

pp. 535-543 ◽

Cited By ~ 41

Author(s):

P. J. Huxley ◽

D. P. Goldberg ◽

G. P. Maguire ◽

V. A. Kincey

Keyword(s):

Psychiatric Disorder ◽

Psychiatric Disorders ◽

Genetic Risk ◽

Clinical Symptoms ◽

Correlation Factor ◽

Risk Scores ◽

Regression Analyses ◽

Clinical Factors ◽

One Year ◽

Minor Psychiatric Disorders

SummaryRecent studies have suggested that psychosocial factors play an important part in the prediction of the course of minor psychiatric disorders. Fifty-nine new psychiatric out-patients suffering from minor disorders were assessed, using standardized clinical and social interviews, and 52 were followed up after one year and the clinical assessment repeated. Social and clinical factors were equally important predictors of the number of months ill in the survey year, but social and constitutional variables were superior in the prediction of percentage change in symptoms over the year.The results of correlation, factor and multiple regression analyses suggest that the course of minor psychiatric disorder is best predicted by three sets of variables which are, in order of importance, the patient's material social circumstances, his clinical symptoms and his ‘genetic risk’ scores.

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