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

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.

scholarly journals Molecular Genetic Risk for Psychosis Is Associated With Psychosis Risk Symptoms in a Population-Based UK Cohort: Findings From Generation Scotland

2020 ◽  
Vol 46 (5) ◽  
pp. 1045-1052
Author(s):  
Anna R Docherty ◽  
Andrey A Shabalin ◽  
Daniel E Adkins ◽  
Frank Mann ◽  
Robert F Krueger ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Molecular Genetic ◽  
Large Population ◽  
Genetic Data ◽  
Population Based ◽  
Health Study ◽  
Polygenic Risk ◽  
Generation Scotland ◽  
Common Genetic Variants ◽  
Psychosis Risk

Abstract Objective Subthreshold psychosis risk symptoms in the general population may be associated with molecular genetic risk for psychosis. This study sought to optimize the association of risk symptoms with genetic risk for psychosis in a large population-based cohort in the UK (N = 9104 individuals 18–65 years of age) by properly accounting for population stratification, factor structure, and sex. Methods The newly expanded Generation Scotland: Scottish Family Health Study includes 5391 females and 3713 males with age M [SD] = 45.2 [13] with both risk symptom data and genetic data. Subthreshold psychosis symptoms were measured using the Schizotypal Personality Questionnaire-Brief (SPQ-B) and calculation of polygenic risk for schizophrenia was based on 11 425 349 imputed common genetic variants passing quality control. Follow-up examination of other genetic risks included attention-deficit hyperactivity disorder (ADHD), autism, bipolar disorder, major depression, and neuroticism. Results Empirically derived symptom factor scores reflected interpersonal/negative symptoms and were positively associated with polygenic risk for schizophrenia. This signal was largely sex specific and limited to males. Across both sexes, scores were positively associated with neuroticism and major depressive disorder. Conclusions A data-driven phenotypic analysis enabled detection of association with genetic risk for schizophrenia in a population-based sample. Multiple polygenic risk signals and important sex differences suggest that genetic data may be useful in improving future phenotypic risk assessment.

scholarly journals Two schizophrenia imaging signatures and their associations with cognition, psychopathology, and genetics in the general population

2022 ◽  
Author(s):  
Ganesh B Chand ◽  
Pankhuri Singhal ◽  
Dominic B Dwyer ◽  
Junhao Wen ◽  
Guray Erus ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Gray Matter Volume ◽  
Control Sample ◽  
Population Level ◽  
Population Based ◽  
Risk Scores ◽  
Support Vector ◽  
Cross Sectional ◽  
Polygenic Risk ◽  
Independent Population

The prevalence and significance of schizophrenia-related phenotypes at the population-level are debated in the literature. Here we assess whether two recently reported neuroanatomical signatures of schizophrenia, signature 1 with widespread reduction of gray matter volume, and signature 2 with increased striatal volume, could be replicated in an independent schizophrenia sample, and investigate whether expression of these signatures can be detected at the population-level and how they relate to cognition, psychosis spectrum symptoms, and schizophrenia genetic risk. This cross-sectional study used an independent schizophrenia-control sample (n=347; age 16-57 years) for replication of imaging signatures, and then examined two independent population-level datasets: Philadelphia Neurodevelopmental Cohort [PNC; n=359 typically developing (TD) and psychosis-spectrum symptoms (PS) youth] and UK Biobank (UKBB; n=836; age 44-50 years) adults. We quantified signature expression using support-vector machine learning, and compared cognition, psychopathology, and polygenic risk between signatures. Two neuroanatomical signatures of schizophrenia were replicated. Signature 1 but not signature 2 was significantly more common in youth with PS than TD youth, whereas signature 2 frequency was similar. In both youth and adults, signature 1 had worse cognitive performance than signature 2. Compared to adults with neither signature, adults expressing signature 1 had elevated schizophrenia polygenic risk scores, but this was not seen for signature 2. We successfully replicate two neuroanatomical signatures of schizophrenia, and describe their prevalence in population-based samples of youth and adults. We further demonstrate distinct relationships of these signatures with psychosis symptoms, cognition, and genetic risk, potentially reflecting underlying neurobiological vulnerability.

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

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.  

Suicide and Psychosis: Results From a Population-Based Cohort of Suicide Death (N = 4380)

2021 ◽  
Author(s):  
Anna R Docherty ◽  
Amanda V Bakian ◽  
Emily DiBlasi ◽  
Andrey A Shabalin ◽  
Danli Chen ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Large Population ◽  
Population Based ◽  
Suicide Death ◽  
Genetics Research ◽  
Affective Symptoms ◽  
Genome Wide ◽  
Increased Risk ◽  
Genetic Risks ◽  
Genome Wide Data

Abstract Approximately 5% of individuals with schizophrenia die from suicide. However, suicide in psychosis is still poorly characterized, partly due to a lack of adequate population-based clinical or genetic data on suicide death. The Utah Suicide Genetics Research Study (USGRS) provides a large population-based cohort of suicide deaths with medical record and genome-wide data (N = 4380). Examination of this cohort identified medical and genetic risks associated with type of suicide death and investigated the relative contributions of psychotic and affective symptoms to method of suicide. Key differences in method of suicide (common vs. atypical methods) were tested in relation to lifetime psychosis and genome-wide genetic risk for schizophrenia, major depressive disorder, and neuroticism. Consistent with previous studies, psychosis-spectrum disorders were observed to be common in suicide (15% of the cohort). Individuals with psychosis more frequently died from atypical methods, with rates of atypical suicide increasing across the schizophrenia spectrum. Genetic risk for schizophrenia was also associated with atypical suicide, regardless of clinical diagnosis, though this association weakened when filtering individuals with schizophrenia from the analysis. Follow-up examination indicated that high rates of atypical suicide observed in schizophrenia are not likely accounted for by restricted access to firearms. Overall, better accounting for the increased risk of atypical suicide methods in psychosis could lead to improved prevention strategies in a large portion of the suicide risk population.

scholarly journals Exploring Various Polygenic Risk Scores for Skin Cancer in the Phenomes of the Michigan Genomics Initiative and the UK Biobank with a Visual Catalog:PRSWeb

2018 ◽  
Author(s):  
Lars G. Fritsche ◽  
Lauren J. Beesley ◽  
Peter VandeHaar ◽  
Robert B. Peng ◽  
Maxwell Salvatore ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Cell Carcinoma ◽  
Genetic Risk ◽  
Population Based ◽  
Risk Scores ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Cancer Subtypes ◽  
Construction Methods ◽  
The Uk

AbstractPolygenic risk scores (PRS) are designed to serve as a single summary measure, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The construction of a PRS often depends on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. In this paper, we consider several choices for constructing a PRS using summary data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict outcomes derived from electronic health records (EHR). Weexamine the three most common skin cancer subtypes in the USA: basal cellcarcinoma, cutaneous squamous cell carcinoma, and melanoma. The genetic risk profiles of subtypes may consist of both shared and unique elements and we construct PRS to understand the common versus distinct etiology. This study is conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate their association with secondary traits. PheWAS results are then replicated using population-based UK Biobank data. We develop an accompanying visual catalog calledPRSwebthat provides detailed PheWAS results and allows users to directly compare different PRS construction methods. The results of this study can provide guidance regarding PRS construction in future PRS-PheWAS studies using EHR data involving disease subtypes.Author summaryIn the study of genetically complex diseases, polygenic risk scores synthesize information from multiple genetic risk factors to provide insight into a patient’s risk of developing a disease based on his/her genetic profile. These risk scores can be explored in conjunction with health and disease information available in the electronic medical records. They may be associated with diseases that may be related to or precursors of the underlying disease of interest. Limited work is available guiding risk score construction when the goal is to identify associations across the medical phenome. In this paper, we compare different polygenic risk score construction methods in terms of their relationships with the medical phenome. We further propose methods for using these risk scores to decouple the shared and unique genetic profiles of related diseases and to explore related diseases’ shared and unique secondary associations. Leveraging and harnessing the rich data resources of the Michigan Genomics Initiative, a biorepository effort at Michigan Medicine, and the larger population-based UK Biobank study, we investigated the performance of genetic risk profiling methods for the three most common types of skin cancer: melanoma, basal cell carcinoma and squamous cell carcinoma.

scholarly journals Estimating the Prevalence and Genetic Risk Mechanisms of ARFID in a Large Autism Cohort

2021 ◽  
Vol 12 ◽  
Author(s):  
Tanner Koomar ◽  
Taylor R. Thomas ◽  
Natalie R. Pottschmidt ◽  
Michael Lutter ◽  
Jacob J. Michaelson
Keyword(s):  
Disordered Eating ◽  
Genetic Risk ◽  
Risk Scores ◽  
Clinical Samples ◽  
Common Variants ◽  
Narrow Sense Heritability ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Current Sample

This study is the first genetically-informed investigation of avoidant/restrictive food intake disorder (ARFID), an eating disorder that profoundly impacts quality of life for those affected. ARFID is highly comorbid with autism, and we provide the first estimate of its prevalence in a large and phenotypically diverse autism cohort (a subsample of the SPARK study, N = 5,157 probands). This estimate, 21% (at a balanced accuracy 80%), is at the upper end of previous estimates from studies based on clinical samples, suggesting under-diagnosis and potentially lack of awareness among caretakers and clinicians. Although some studies suggest a decrease of disordered eating symptoms by age 6, our estimates indicate that up to 17% (at a balanced accuracy 87%) of parents of autistic children are also at heightened risk for ARFID, suggesting a lifelong risk for disordered eating. We were also able to provide the first estimates of narrow-sense heritability (h2) for ARFID risk, at 0.45. Genome-wide association revealed a single hit near ZSWIM6, a gene previously implicated in neurodevelopmental conditions. While, the current sample was not well-powered for GWAS, effect size and heritability estimates allowed us to project the sample sizes necessary to more robustly discover ARFID-linked loci via common variants. Further genetic analysis using polygenic risk scores (PRS) affirmed genetic links to autism as well as neuroticism and metabolic syndrome.

scholarly journals Integrating genome-wide polygenic risk scores and non-genetic risk factors to develop and validate risk prediction models for colorectal cancer

2021 ◽  
Author(s):  
Sarah EW Briggs ◽  
Philip Law ◽  
James E East ◽  
Sarah Wordsworth ◽  
Malcolm Dunlop ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Factors ◽  
Risk Prediction ◽  
Genetic Risk ◽  
Prediction Models ◽  
Fold Increase ◽  
Risk Scores ◽  
Risk Prediction Models ◽  
Polygenic Risk ◽  
Genome Wide

Objective While population screening programs for cancer colorectal (CRC) have proven benefit, risk-stratified approaches may improve screening outcomes further. To date, genome-wide polygenic risk scores (PRS) for CRC have not been integrated with non-genetic risk factors. We aimed to evaluate several genome-wide approaches, and the benefit of adding PRS to the QCancer-10 (colorectal cancer) non-genetic risk model, to identify those at highest risk of CRC. Design Using UK Biobank we developed and compared six different PRS for CRC. The top-performing genome-wide and GWAS-significant PRS were then combined with QCancer-10 and performance compared to QCancer-10 alone. Results PRS derived using LDpred2 software performed best, with an odds-ratio per standard deviation of 1.58, and top age- and sex-adjusted C-statistic of 0.733 in logistic regression and 0.724 in Cox regression models in the Geographic Validation Cohort. Integrated QCancer-10+PRS models out-performed QCancer-10, with C-statistics of 0.730 and 0.693, and explained variation of 28.1% and 21.0% from QCancer-10+LDpred2 and QCancer-10 respectively in men; performance improvements in women were similar. Men in the top 20% of risk accounted for 47.6% of cases, and women 42.5% using QCancer-10+LDpred2 models, with a 3.49-fold increase in risk in men and 2.75-fold increase in women in the top 5% of risk, compared to average risk. Decision curve analysis showed that adding PRS to QCancer-10 improved net-benefit and interventions avoided across most probability thresholds. Conclusion Integrated QCancer-10+PRS models out-perform existing CRC risk prediction models. Evaluation of risk stratified screening using this approach in a bowel screening population could be warranted.

scholarly journals Polygenic risk, lifestyle, and cardiovascular mortality: a prospective population-based UK Biobank study

2021 ◽  
Author(s):  
Jae-Seung Yun ◽  
Sang-Hyuk Jung ◽  
Manu Shivakumar ◽  
Brenda Xiao ◽  
Amit V. Khera ◽  
...  
Keyword(s):  
Cardiovascular Mortality ◽  
Genetic Risk ◽  
Risk Groups ◽  
Population Based ◽  
Risk Scores ◽  
Uk Biobank ◽  
Lifestyle Behavior ◽  
Polygenic Risk ◽  
High Genetic Risk ◽  
Very High

AbstractOBJECTIVETo assess the prognostic ability of polygenic risk scores (PRSs) for coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) for cardiovascular (CV) mortality, independent of traditional risk factors, and further investigate the additive effect between lifestyle behavior and PRS on CV mortality.DESIGNProspective population-based cohort study.SETTINGUK Biobank.PARTICIPANTSA total 377,909 unrelated participants of white British descent were included in the analyses from the UK Biobank cohort.MAIN OUTCOME MEASURESGenome-wide PRSs were constructed using >6 million genetic variants. We stratified patients into four PRS risk groups: low (0 to 19th percentile), intermediate (20 to 79th percentile), high (80 to 98th percentile), and very high (99th percentile). We defined a favorable and unfavorable lifestyle with four modifiable lifestyle components, including smoking, obesity, physical activity, and diet. Cox proportional hazard models were used to analyze the relationship between PRS and CV mortality with stratification by age, sex, disease status, and lifestyle behavior.RESULTSOf 377,909 UK Biobank participants having European ancestry, 3,210 (0.8%) died due to CV disease during a median follow-up of 8.9 years. CV mortality risk was significantly associated with CAD PRS (low vs. very high genetic risk groups, CAD PRS hazard ratio [HR] 2.61 [2.02 to 3.36]) and T2DM PRS (HR 2.08 [1.58 to 2.73]), respectively. These relationships remained significant even after adjustment for a comprehensive range of demographic and clinical factors. In the very high genetic risk group, adherence to an unfavorable lifestyle was further associated with a substantially increased risk of CV mortality (favorable versus unfavorable lifestyle with very high genetic risk for CAD PRS, HR 8.31 [5.12 to 13.49]; T2DM PRS, HR 5.84 [3.39 to 10.04]). Across all genetic risk groups, 32.1% of CV mortality was attributable to lifestyle behavior (population attributable fraction [PAF] 32.1% [95% CI 28.8 to 35.3%]) and 14.1% was attributable to smoking (PAF 14.1% [95% CI 12.4 to 15.7%]). There was no evidence of significant interaction between PRSs and age, sex, or lifestyle behavior in predicting the risk of CV mortality.CONCLUSIONPRSs for CAD or T2DM and lifestyle behaviors are independent predictive factors for future CV mortality in the white, middle-aged population. PRS-based risk assessment could be useful to identify individuals who need intensive behavioral or therapeutic interventions to reduce the risk of CV mortality.Summary BoxWhat is already known on this topicPolygenic risk scores quantify the inherited risk conferred by the cumulative impact of common variants into a quantitative risk estimate.Previous studies primarily targeted the ability of polygenic risk scores to predict a specific disease, and only a few studies have investigated the association between genetic risk scores and cardiovascular mortality.The majority of previous analyses calculated polygenic risk scores from only a small number of genetic variants or adjusted for only a few risk factors, and no studies have examined whether the association of polygenic risk score with cardiovascular mortality differs by lifestyle behavior.What this study addsGenetic risk and lifestyle are independent predictive factors for cardiovascular mortality, even after adjustment for a comprehensive range of demographic and clinical factors.A healthy lifestyle is associated with relative risk reduction for cardiovascular mortality across all genetic risk categories, a finding that indicates the potential benefit of intensive lifestyle modification in overcoming genetic risk for cardiovascular mortality.

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

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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