Genetic risk for neurodegenerative disorders, and its overlap with cognitive ability and physical function

AbstractINTRODUCTIONIt is unclear whether polygenic risk for neurodegenerative disease is associated with cognitive performance and physical health.METHODSThis study tested whether polygenic scores for Alzheimer’s disease (AD), Amyotrophic Lateral Sclerosis (ALS), or frontotemporal dementia (FTD) are associated with cognitive performance and physical health. Group-based analyses were performed to compare associations with cognitive and physical function outcomes in the top and bottom 10% for the three neurodegenerative polygenic risk scores.RESULTSHigher polygenic risk scores for AD, ALS, and FTD were associated with lower cognitive performance. Higher polygenic risk scores for FTD was also associated with increased forced expiratory volume in 1s and peak expiratory flow. A significant group difference was observed on the symbol digit substitution task between individuals with high polygenic risk for FTD and high polygenic risk for ALS.DISCUSSIONOur results suggest overlap between polygenic risk for neurodegenerative disorders, cognitive function and physical health.

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The power of pathway-based polygenic risk scores

10.21203/rs.3.rs-643696/v1 ◽

2021 ◽

Author(s):

Paul O’Reilly ◽

Shing Choi ◽

Judit Garcia-Gonzalez ◽

Yunfeng Ruan ◽

Hei Man Wu ◽

...

Keyword(s):

Complex Disease ◽

Predictive Accuracy ◽

Risk Scores ◽

Distinct Advantage ◽

Genetic Profile ◽

Genetic Liability ◽

Polygenic Risk ◽

Individual Level ◽

Genome Wide ◽

Polygenic Scores

Abstract Polygenic risk scores (PRSs) have been among the leading advances in biomedicine in recent years. As a proxy of genetic liability, PRSs are utilised across multiple fields and applications. While numerous statistical and machine learning methods have been developed to optimise their predictive accuracy, all of these distil genetic liability to a single number based on aggregation of an individual’s genome-wide alleles. This results in a key loss of information about an individual’s genetic profile, which could be critical given the functional sub-structure of the genome and the heterogeneity of complex disease. Here we evaluate the performance of pathway-based PRSs, in which polygenic scores are calculated across genomic pathways for each individual, and we introduce a software, PRSet, for computing and analysing pathway PRSs. We find that pathway PRSs have similar power for evaluating pathway enrichment of GWAS signal as the leading methods, with the distinct advantage of providing estimates of pathway genetic liability at the individual-level. Exemplifying their utility, we demonstrate that pathway PRSs can stratify diseases into subtypes in the UK Biobank with substantially greater power than genome-wide PRSs. Compared to genome-wide PRSs, we expect pathway-based PRSs to offer greater insights into the heterogeneity of complex disease and treatment response, generate more biologically tractable therapeutic targets, and provide a more powerful path to precision medicine.

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Stressful Life Events and Self-Control: Testing Gene x Environment Interaction with a Polygenic Approach

10.31234/osf.io/jhbqd ◽

2019 ◽

Author(s):

Yayouk Willems ◽

Jouke-Jan Hottenga ◽

Lannie Ligthart ◽

Gonneke WIllemsen ◽

Dorret Boomsma ◽

...

Keyword(s):

Complex Traits ◽

Large Population ◽

Self Control ◽

Risk Scores ◽

Life Stressors ◽

Control Problems ◽

Environment Interaction ◽

Polygenic Risk ◽

Polygenic Scores ◽

Low Self Control

Background: Ill decisions and reckless behaviors due to low self-control are concurrently and longitudinally costly, and revealing possible factors contributing to individual differences in self-control is necessary. It is hypothesized that genetically sensitivity interacts with life stressors in the prediction of the development of low self-control (gene environment interaction), yet attempts to test this hypothesis mostly concern candidate gene studies yielding inconclusive results. The goal of this research was to bring findings from large scale gene identification studies into the developmental psychology framework, taking the polygenic nature of complex traits into account. Methods: Using data of a large population-based twin sample, we tested whether polygenic risk scores for self-control problems – based on the most recent ADHD GWAS – predict self-control problems in adults, and whether this polygenic risk scores interact with the presence of environmental stressors. Results: While polygenic scores and life stressors significantly predicted low self-control, we did not find a significant interaction effect. Conclusions: Empirically, finding statistical evidence for this hypothesis remains a challenge, and more research is needed to investigate how to better detect G x E.

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A comprehensive analysis of methods for assessing polygenic burden on Alzheimer’s disease pathology and risk beyond APOE

Brain Communications ◽

10.1093/braincomms/fcz047 ◽

2019 ◽

Vol 2 (1) ◽

Cited By ~ 2

Author(s):

Andre Altmann ◽

Marzia A Scelsi ◽

Maryam Shoai ◽

Eric de Silva ◽

Leon M Aksman ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Clinical Diagnosis ◽

Risk Scores ◽

Imaging Biomarkers ◽

Cross Sectional ◽

Polygenic Risk ◽

Apoe Ε4 ◽

Polygenic Scores ◽

Apoe Locus

Abstract Genome-wide association studies have identified dozens of loci that alter the risk to develop Alzheimer’s disease. However, with the exception of the APOE-ε4 allele, most variants bear only little individual effect and have, therefore, limited diagnostic and prognostic value. Polygenic risk scores aim to collate the disease risk distributed across the genome in a single score. Recent works have demonstrated that polygenic risk scores designed for Alzheimer’s disease are predictive of clinical diagnosis, pathology confirmed diagnosis and changes in imaging biomarkers. Methodological innovations in polygenic risk modelling include the polygenic hazard score, which derives effect estimates for individual single nucleotide polymorphisms from survival analysis, and methods that account for linkage disequilibrium between genomic loci. In this work, using data from the Alzheimer’s disease neuroimaging initiative, we compared different approaches to quantify polygenic disease burden for Alzheimer’s disease and their association (beyond the APOE locus) with a broad range of Alzheimer’s disease-related traits: cross-sectional CSF biomarker levels, cross-sectional cortical amyloid burden, clinical diagnosis, clinical progression, longitudinal loss of grey matter and longitudinal decline in cognitive function. We found that polygenic scores were associated beyond APOE with clinical diagnosis, CSF-tau levels and, to a minor degree, with progressive atrophy. However, for many other tested traits such as clinical disease progression, CSF amyloid, cognitive decline and cortical amyloid load, the additional effects of polygenic burden beyond APOE were of minor nature. Overall, polygenic risk scores and the polygenic hazard score performed equally and given the ease with which polygenic risk scores can be derived; they constitute the more practical choice in comparison with polygenic hazard scores. Furthermore, our results demonstrate that incomplete adjustment for the APOE locus, i.e. only adjusting for APOE-ε4 carrier status, can lead to overestimated effects of polygenic scores due to APOE-ε4 homozygous participants. Lastly, on many of the tested traits, the major driving factor remained the APOE locus, with the exception of quantitative CSF-tau and p-tau measures.

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Improving reporting standards for polygenic scores in risk prediction studies

10.1101/2020.04.23.20077099 ◽

2020 ◽

Author(s):

Hannah Wand ◽

Samuel A. Lambert ◽

Cecelia Tamburro ◽

Michael A. Iacocca ◽

Jack W. O’Sullivan ◽

...

Keyword(s):

Complex Disease ◽

Public Health Practice ◽

Internal Validity ◽

Risk Scores ◽

Polygenic Risk Score ◽

Reporting Standards ◽

Polygenic Risk ◽

Genome Wide ◽

Polygenic Scores ◽

Study Population

SummaryIn recent years, polygenic risk scores (PRS) have become an increasingly studied tool to capture the genome-wide liability underlying many human traits and diseases, hoping to better inform an individual’s genetic risk. However, a lack of adherence to previous reporting standards has hindered the translation of this important tool into clinical and public health practice with the heterogeneous underreporting of details necessary for benchmarking and reproducibility. To address this gap, the ClinGen Complex Disease Working Group and Polygenic Score (PGS) Catalog have collaborated to develop the 33-item Polygenic Risk Score Reporting Statement (PRS-RS). This framework provides the minimal information expected of authors to promote the internal validity, transparency, and reproducibility of PRS by requiring authors to detail the study population, statistical methods, and clinical utility of a published score. The widespread adoption of this framework will encourage rigorous methodological consideration and facilitate benchmarking to ensure high quality scores are translated into the clinic.

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Clinical laboratory test-wide association scan of polygenic scores identifies biomarkers of complex disease

Genome Medicine ◽

10.1186/s13073-020-00820-8 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Jessica K. Dennis ◽

Julia M. Sealock ◽

Peter Straub ◽

Younga H. Lee ◽

Donald Hucks ◽

...

Keyword(s):

Large Scale ◽

Complex Disease ◽

Clinical Laboratory ◽

Population Level ◽

Risk Scores ◽

Polygenic Risk ◽

Polygenic Scores ◽

Large Populations ◽

Novel Biomarkers ◽

Artery Disease

Abstract Background Clinical laboratory (lab) tests are used in clinical practice to diagnose, treat, and monitor disease conditions. Test results are stored in electronic health records (EHRs), and a growing number of EHRs are linked to patient DNA, offering unprecedented opportunities to query relationships between genetic risk for complex disease and quantitative physiological measurements collected on large populations. Methods A total of 3075 quantitative lab tests were extracted from Vanderbilt University Medical Center’s (VUMC) EHR system and cleaned for population-level analysis according to our QualityLab protocol. Lab values extracted from BioVU were compared with previous population studies using heritability and genetic correlation analyses. We then tested the hypothesis that polygenic risk scores for biomarkers and complex disease are associated with biomarkers of disease extracted from the EHR. In a proof of concept analyses, we focused on lipids and coronary artery disease (CAD). We cleaned lab traits extracted from the EHR performed lab-wide association scans (LabWAS) of the lipids and CAD polygenic risk scores across 315 heritable lab tests then replicated the pipeline and analyses in the Massachusetts General Brigham Biobank. Results Heritability estimates of lipid values (after cleaning with QualityLab) were comparable to previous reports and polygenic scores for lipids were strongly associated with their referent lipid in a LabWAS. LabWAS of the polygenic score for CAD recapitulated canonical heart disease biomarker profiles including decreased HDL, increased pre-medication LDL, triglycerides, blood glucose, and glycated hemoglobin (HgbA1C) in European and African descent populations. Notably, many of these associations remained even after adjusting for the presence of cardiovascular disease and were replicated in the MGBB. Conclusions Polygenic risk scores can be used to identify biomarkers of complex disease in large-scale EHR-based genomic analyses, providing new avenues for discovery of novel biomarkers and deeper understanding of disease trajectories in pre-symptomatic individuals. We present two methods and associated software, QualityLab and LabWAS, to clean and analyze EHR labs at scale and perform a Lab-Wide Association Scan.

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Incorporating Polygenic Risk Scores in the ACE Twin Model to Estimate A–C Covariance

Behavior Genetics ◽

10.1007/s10519-020-10035-7 ◽

2021 ◽

Author(s):

Conor V. Dolan ◽

Roel C. A. Huijskens ◽

Camelia C. Minică ◽

Michael C. Neale ◽

Dorret I. Boomsma

Keyword(s):

Parameter Identification ◽

Environmental Variables ◽

Statistical Power ◽

Risk Scores ◽

Polygenic Risk ◽

Twin Model ◽

Polygenic Scores ◽

Ace Model ◽

Biasing Effects

AbstractThe assumption in the twin model that genotypic and environmental variables are uncorrelated is primarily made to ensure parameter identification, not because researchers necessarily think that these variables are uncorrelated. Although the biasing effects of such correlations are well understood, a method to estimate these parameters in the twin model would be useful. Here we explore the possibility of relaxing this assumption by adding polygenic scores to the (univariate) twin model. We demonstrate that this extension renders the additive genetic (A)—common environmental (C) covariance (σAC) identified. We study the statistical power to reject σAC = 0 in the ACE model and present the results of simulations.

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Age varying polygenic effects on alcohol use in African Americans and European Americans from adolescence to adulthood

Scientific Reports ◽

10.1038/s41598-021-01923-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kit K. Elam ◽

Thao Ha ◽

Zoe Neale ◽

Fazil Aliev ◽

Danielle Dick ◽

...

Keyword(s):

Alcohol Use ◽

Association Studies ◽

Genetic Effects ◽

Risk Scores ◽

Genome Wide Association Studies ◽

Longitudinal Models ◽

Polygenic Risk ◽

Genome Wide ◽

Polygenic Scores ◽

Distal Outcome

AbstractGenetic effects on alcohol use can vary over time but are often examined using longitudinal models that predict a distal outcome at a single time point. The vast majority of these studies predominately examine effects using White, European American (EA) samples or examine the etiology of genetic variants identified from EA samples in other racial/ethnic populations, leading to inconclusive findings about genetic effects on alcohol use. The current study examined how genetic influences on alcohol use varied by age across a 15 year period within a diverse ethnic/racial sample of adolescents. Using a multi-ethnic approach, polygenic risk scores were created for African American (AA, n = 192) and EA samples (n = 271) based on racially/ethnically aligned genome wide association studies. Age-varying associations between polygenic scores and alcohol use were examined from age 16 to 30 using time-varying effect models separately for AA and EA samples. Polygenic risk for alcohol use was found to be associated with alcohol use from age 22–27 in the AA sample and from age 24.50 to 29 in the EA sample. Results are discussed relative to the intersection of alcohol use and developmental genetic effects in diverse populations.

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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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Genetic risk underlying psychiatric and cognitive symptoms in Huntington’s Disease

10.1101/639658 ◽

2019 ◽

Cited By ~ 1

Author(s):

Natalie Ellis ◽

Amelia Tee ◽

Branduff McAllister ◽

Thomas Massey ◽

Duncan McLauchlan ◽

...

Keyword(s):

Cognitive Impairment ◽

Risk Score ◽

Neurodegenerative Disorders ◽

Psychiatric Symptoms ◽

Risk Scores ◽

Polygenic Risk Score ◽

Cognitive Symptoms ◽

Genetic Liability ◽

Polygenic Risk ◽

Increased Risk

AbstractHuntington’s disease (HD) is an inherited neurodegenerative disorder caused by an expanded CAG repeat in the HTT gene. It is diagnosed following a standardized exam of motor control and often presents with cognitive decline and psychiatric symptoms. Recent studies have detected genetic loci modifying the age at onset of motor symptoms in HD, but genetic factors influencing cognitive and psychiatric presentations are unknown. We tested the hypothesis that psychiatric and cognitive symptoms in HD are influenced by the same common genetic variation as in the general population by constructing polygenic risk scores from large genome-wide association studies of psychiatric and neurodegenerative disorders, and of intelligence, and testing for correlation with the presence of psychiatric and cognitive symptoms in a large sample (n=5160) of HD patients. Polygenic risk score for major depression was associated specifically with increased risk of depression in HD, as was schizophrenia risk score with psychosis and irritability. Cognitive impairment and apathy were associated with reduced polygenic risk score for intelligence. In general, polygenic risk scores for psychiatric disorders, particularly depression and schizophrenia, are associated with increased risk of the corresponding psychiatric symptoms in HD, suggesting a common genetic liability. However, the genetic liability to cognitive impairment and apathy appears to be distinct from other psychiatric symptoms in HD. No associations were observed between HD symptoms and risk scores for other neurodegenerative disorders. These data provide a rationale for treatments effective in depression and schizophrenia to be used to treat depression and psychotic symptoms in HD.

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