General vs. Specific Vulnerabilities: Polygenic Risk Scores and Higher-Order Psychopathology Dimensions in the Adolescent Brain Cognitive Development (ABCD) Study

2020 ◽  
Author(s):  
Monika Waszczuk ◽  
Jiaju Miao ◽  
Anna Docherty ◽  
Andrey Shabalin ◽  
Giorgia Michelini ◽  
...  
Keyword(s):  
Externalizing Behavior ◽  
Higher Order ◽  
Genetic Effects ◽  
European Ancestry ◽  
Risk Scores ◽  
General Factor ◽  
Childhood Psychopathology ◽  
Polygenic Risk ◽  
Genetic Vulnerability ◽  
Specific Factors

Background. Polygenic risk scores (PRS) capture genetic vulnerability to psychiatric conditions and promise to advance our understanding of mental health etiology in children. Emerging evidence suggests that PRSs may be associated with higher-order dimensions of childhood psychopathology. The current study delineated a pattern of associations of major PRSs with an overarching general factor of psychopathology (p-factor), and five specific factors: externalizing, internalizing, neurodevelopmental, somatoform, and detachment.Method. The sample consisted of 4,717 unrelated children (mean age=9.92, SD=.62; 47.1% female; all European ancestry). Psychopathology was conceptualized hierarchically as empirically-derived general factor and five specific factors. Partial correlations explored associations between psychopathology factors and major psychopathology-related PRSs originally discovered in large samples (Ns>100,000). Regressions tested which level of the psychopathology hierarchy was most strongly associated with each PRS.Results. Four PRSs were associated primarily with the general factor (>60% of genetic effects were general): Depression-PRS, Neuroticism-PRS, PTSD-PRS, and Insomnia-PRS. Two PRS contributed comparably to general and specific psychopathology: Smoking-PRS and Number of Sexual Partners-PRS. Five PRSs contributed primary to specific factors (<40% of genetic effects were general): Adventurousness-PRS, Disinhibition-PRS, Educational Attainment-PRSs, BMI-PRS, and Intelligence-PRS. The incremental associations with specific factors were mainly driven by the externalizing dimension. Conclusion. The PRSs for internalizing problems predominantly captured non-specific genetic vulnerability to psychopathology in children. Conversely, PRSs for externalizing problems contributed to more specific psychopathology outcomes, most notably externalizing behavior. Overall, many major PRSs captured both general and specific genetic vulnerability to childhood psychopathology.

General v. specific vulnerabilities: polygenic risk scores and higher-order psychopathology dimensions in the Adolescent Brain Cognitive Development (ABCD) Study

2021 ◽  
pp. 1-10
Author(s):  
Monika A. Waszczuk ◽  
Jiaju Miao ◽  
Anna R. Docherty ◽  
Andrey A. Shabalin ◽  
Katherine G. Jonas ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Behavioral Problems ◽  
Mental Health Problems ◽  
Chronic Back Pain ◽  
European Ancestry ◽  
Risk Scores ◽  
General Factor ◽  
Childhood Psychopathology ◽  
Polygenic Risk ◽  
Partial Correlations

Abstract Background Polygenic risk scores (PRSs) capture genetic vulnerability to psychiatric conditions. However, PRSs are often associated with multiple mental health problems in children, complicating their use in research and clinical practice. The current study is the first to systematically test which PRSs associate broadly with all forms of childhood psychopathology, and which PRSs are more specific to one or a handful of forms of psychopathology. Methods The sample consisted of 4717 unrelated children (mean age = 9.92, s.d. = 0.62; 47.1% female; all European ancestry). Psychopathology was conceptualized hierarchically as empirically derived general factor (p-factor) and five specific factors: externalizing, internalizing, neurodevelopmental, somatoform, and detachment. Partial correlations explored associations between psychopathology factors and 22 psychopathology-related PRSs. Regressions tested which level of the psychopathology hierarchy was most strongly associated with each PRS. Results Thirteen PRSs were significantly associated with the general factor, most prominently Chronic Multisite Pain-PRS (r = 0.098), ADHD-PRS (r = 0.079), and Depression-PRS (r = 0.078). After adjusting for the general factor, Depression-PRS, Neuroticism-PRS, PTSD-PRS, Insomnia-PRS, Chronic Back Pain-PRS, and Autism-PRS were not associated with lower order factors. Conversely, several externalizing PRSs, including Adventurousness-PRS and Disinhibition-PRS, remained associated with the externalizing factor (|r| = 0.040–0.058). The ADHD-PRS remained uniquely associated with the neurodevelopmental factor (r = 062). Conclusions PRSs developed to predict vulnerability to emotional difficulties and chronic pain generally captured genetic risk for all forms of childhood psychopathology. PRSs developed to predict vulnerability to externalizing difficulties, e.g. disinhibition, tended to be more specific in predicting behavioral problems. The results may inform translation of existing PRSs to pediatric research and future clinical practice.

Construct validation using multitrait‐multimethod‐twin data: The case of a general factor of personality

2010 ◽  
Vol 24 (3) ◽  
pp. 258-277 ◽  
Author(s):  
Rainer Riemann ◽  
Christian Kandler
Keyword(s):  
Study Design ◽  
Convergent Validity ◽  
Structural Equation ◽  
Twin Studies ◽  
Higher Order ◽  
Genetic Effects ◽  
Order Structure ◽  
General Factor ◽  
General Factor Of Personality ◽  
Peer Report

We describe a behavioural genetic extension of the classic multitrait‐multimethod study design that allows estimating genetic and environmental influences on method effects in twin studies (MTMM‐T). Genetic effects and effects of the environment shared by siblings are interpreted as indicators of convergent validity. In an application of the MTMM study design, we used self‐ and peer report data to examine the higher‐order structure of the NEO‐PI‐R. Structural equation modelling did not support a general factor of personality in multimethod data. The higher‐order factor Stability turns out to be, at most, a weak trait factor. Genetic effects on method factors indicate that especially self‐reports but also peer reports show convergent validity between twins but not between methods. Copyright © 2010 John Wiley & Sons, Ltd.

scholarly journals Using Genetics to Examine a General Liability to Childhood Psychopathology

2019 ◽  
Vol 50 (4) ◽  
pp. 213-220 ◽  
Author(s):  
Lucy Riglin ◽  
Ajay K. Thapar ◽  
Beate Leppert ◽  
Joanna Martin ◽  
Alexander Richards ◽  
...  
Keyword(s):  
Association Studies ◽  
Full Range ◽  
Population Based ◽  
Autism Spectrum ◽  
Developmental Changes ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Childhood Psychopathology ◽  
Specific Factors ◽  
P Factor

AbstractPsychiatric disorders show phenotypic as well as genetic overlaps. There are however also marked developmental changes throughout childhood. We investigated the extent to which, for a full range of early childhood psychopathology, a general “p” factor was explained by genetic liability, as indexed by multiple different psychiatric polygenic risk scores (PRS) and whether these relationships altered with age. The sample was a UK, prospective, population-based cohort with psychopathology data at age 7 (N = 8161) and age 13 (N = 7017). PRS were generated from large published genome-wide association studies. At both ages, we found evidence for a childhood “p” factor as well as for specific factors. Schizophrenia and attention-deficit/hyperactivity disorder (ADHD) PRS were associated with this general “p” factor at both ages but depression and autism spectrum disorder (ASD) PRS were not. We also found some evidence of associations between schizophrenia, ADHD and depression PRS with specific factors, but these were less robust and there was evidence for developmental changes.

scholarly journals Polygenic Risk Scores Augment Stroke Subtyping

2021 ◽  
Vol 7 (2) ◽  
pp. e560
Author(s):  
Jiang Li ◽  
Durgesh P. Chaudhary ◽  
Ayesha Khan ◽  
Christoph Griessenauer ◽  
David J. Carey ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Genetic Correlation ◽  
Genome Wide Association Study ◽  
Low Frequency ◽  
European Ancestry ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Large Artery ◽  
Polygenic Risk ◽  
Gene Sets

ObjectiveTo determine whether the polygenic risk score (PRS) derived from MEGASTROKE is associated with ischemic stroke (IS) and its subtypes in an independent tertiary health care system and to identify the PRS derived from gene sets of known biological pathways associated with IS.MethodsControls (n = 19,806/7,484, age ≥69/79 years) and cases (n = 1,184/951 for discovery/replication) of acute IS with European ancestry and clinical risk factors were identified by leveraging the Geisinger Electronic Health Record and chart review confirmation. All Geisinger MyCode patients with age ≥69/79 years and without any stroke-related diagnostic codes were included as low risk control. Genetic heritability and genetic correlation between Geisinger and MEGASTROKE (EUR) were calculated using the summary statistics of the genome-wide association study by linkage disequilibrium score regression. All PRS for any stroke (AS), any ischemic stroke (AIS), large artery stroke (LAS), cardioembolic stroke (CES), and small vessel stroke (SVS) were constructed by PRSice-2.ResultsA moderate heritability (10%–20%) for Geisinger sample as well as the genetic correlation between MEGASTROKE and the Geisinger cohort was identified. Variation of all 5 PRS significantly explained some of the phenotypic variations of Geisinger IS, and the R2 increased by raising the cutoff for the age of controls. PRSLAS, PRSCES, and PRSSVS derived from low-frequency common variants provided the best fit for modeling (R2 = 0.015 for PRSLAS). Gene sets analyses highlighted the association of PRS with Gene Ontology terms (vascular endothelial growth factor, amyloid precursor protein, and atherosclerosis). The PRSLAS, PRSCES, and PRSSVS explained the most variance of the corresponding subtypes of Geisinger IS suggesting shared etiologies and corroborated Geisinger TOAST subtyping.ConclusionsWe provide the first evidence that PRSs derived from MEGASTROKE have value in identifying shared etiologies and determining stroke subtypes.

scholarly journals Sleep Deficits and Cannabis Use Behaviors: An Analysis of Shared Genetics Using Linkage Disequilibrium Score Regression and Polygenic Risk Prediction

2020 ◽  
Author(s):  
Evan A. Winiger ◽  
Jarrod M. Ellingson ◽  
Claire L. Morrison ◽  
Robin P. Corley ◽  
Joëlle A. Pasman ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
Sleep Duration ◽  
Association Studies ◽  
Genetic Correlations ◽  
Cannabis Use ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Short Sleep Duration ◽  
Polygenic Risk

AbstractStudy ObjectivesEstimate the genetic relationship of cannabis use with sleep deficits and eveningness chronotype.MethodsWe used linkage disequilibrium score regression (LDSC) to analyze genetic correlations between sleep deficits and cannabis use behaviors. Secondly, we generated sleep deficit polygenic risk scores (PRSs) and estimated their ability to predict cannabis use behaviors using logistic regression. Summary statistics came from existing genome wide association studies (GWASs) of European ancestry that were focused on sleep duration, insomnia, chronotype, lifetime cannabis use, and cannabis use disorder (CUD). A target sample for PRS prediction consisted of high-risk participants and participants from twin/family community-based studies (n = 796, male = 66%; mean age = 26.81). Target data consisted of self-reported sleep (sleep duration, feeling tired, and taking naps) and cannabis use behaviors (lifetime use, number of lifetime uses, past 180-day use, age of first use, and lifetime CUD symptoms).ResultsSignificant genetic correlation between lifetime cannabis use and eveningness chronotype (rG = 0.24, p < 0.01), as well as between CUD and both short sleep duration (<7 h) (rG = 0.23, p = 0.02) and insomnia (rG = 0.20, p = 0.02). Insomnia PRS predicted earlier age of first cannabis use (β = −0.09, p = 0.02) and increased lifetime CUD symptom count use (β = 0.07, p = 0.03).ConclusionCannabis use is genetically associated with both sleep deficits and an eveningness chronotype, suggesting that there are genes that predispose individuals to both cannabis use and sleep deficits.

scholarly journals Polygenic transcriptome risk scores (PTRS) can improve portability of polygenic risk scores across ancestries

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Yanyu Liang ◽  
Milton Pividori ◽  
Ani Manichaikul ◽  
Abraham A. Palmer ◽  
Nancy J. Cox ◽  
...  
Keyword(s):  
Association Studies ◽  
Poor Performance ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Transcript Levels ◽  
Polygenic Risk ◽  
Genome Wide

Abstract Background Polygenic risk scores (PRS) are valuable to translate the results of genome-wide association studies (GWAS) into clinical practice. To date, most GWAS have been based on individuals of European-ancestry leading to poor performance in populations of non-European ancestry. Results We introduce the polygenic transcriptome risk score (PTRS), which is based on predicted transcript levels (rather than SNPs), and explore the portability of PTRS across populations using UK Biobank data. Conclusions We show that PTRS has a significantly higher portability (Wilcoxon p=0.013) in the African-descent samples where the loss of performance is most acute with better performance than PRS when used in combination.

scholarly journals Global biobank analyses provide lessons for computing polygenic risk scores across diverse cohorts

2021 ◽  
Author(s):  
Ying Wang ◽  
Shinichi Namba ◽  
Esteban Lopera ◽  
Sini Kerminen ◽  
Kristin Tsuo ◽  
...  
Keyword(s):  
Best Practices ◽  
Prediction Accuracy ◽  
Disease Risk ◽  
Association Studies ◽  
Meta Analysis ◽  
European Ancestry ◽  
Risk Scores ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Polygenic Risk

SummaryWith the increasing availability of biobank-scale datasets that incorporate both genomic data and electronic health records, many associations between genetic variants and phenotypes of interest have been discovered. Polygenic risk scores (PRS), which are being widely explored in precision medicine, use the results of association studies to predict the genetic component of disease risk by accumulating risk alleles weighted by their effect sizes. However, limited studies have thoroughly investigated best practices for PRS in global populations across different diseases. In this study, we utilize data from the Global-Biobank Meta-analysis Initiative (GBMI), which consists of individuals from diverse ancestries and across continents, to explore methodological considerations and PRS prediction performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRS using heuristic (pruning and thresholding, P+T) and Bayesian (PRS-CS) methods. We found that the genetic architecture, such as SNP-based heritability and polygenicity, varied greatly among endpoints. For both PRS construction methods, using a European ancestry LD reference panel resulted in comparable or higher prediction accuracy compared to several other non-European based panels; this is largely attributable to European descent populations still comprising the majority of GBMI participants. PRS-CS overall outperformed the classic P+T method, especially for endpoints with higher SNP-based heritability. For example, substantial improvements are observed in East-Asian ancestry (EAS) using PRS-CS compared to P+T for heart failure (HF) and chronic obstructive pulmonary disease (COPD). Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma which has known variation in disease prevalence across global populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using the GBMI and highlight the importance of best practices for PRS in the biobank-scale genomics era.

scholarly journals Assessment of Polygenic Architecture and Risk Prediction based on Common Variants Across Fourteen Cancers

2019 ◽  
Author(s):  
Yan Zhang ◽  
Amber N. Wilcox ◽  
Haoyu Zhang ◽  
Parichoy Pal Choudhury ◽  
Douglas F. Easton ◽  
...  
Keyword(s):  
Association Studies ◽  
Disease Incidence ◽  
Effect Sizes ◽  
European Ancestry ◽  
Risk Scores ◽  
Average Risk ◽  
Genome Wide Association Studies ◽  
Lymphoid Leukemia ◽  
Polygenic Risk ◽  
Wide Range

AbstractWe analyzed summary-level data from genome-wide association studies (GWAS) of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) contributing to risk, as well as the distribution of their associated effect sizes. All cancers evaluated showed polygenicity, involving at a minimum thousands of independent susceptibility variants. For some malignancies, particularly chronic lymphoid leukemia (CLL) and testicular cancer, there are a larger proportion of variants with larger effect sizes than those for other cancers. In contrast, most variants for lung and breast cancers have very small associated effect sizes. For different cancer sites, we estimate a wide range of GWAS sample sizes, required to explain 80% of GWAS heritability, varying from 60,000 cases for CLL to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores, compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that polygenic risk scores have substantial potential for risk stratification for relatively common cancers such as breast, prostate and colon, but limited potential for other cancer sites because of modest heritability and lower disease incidence.

Mapping the genetic architecture of suicide attempt and suicide death using polygenic risk scores for clinically-related psychiatric disorders and traits

2021 ◽  
pp. 1-9
Author(s):  
Ikuo Otsuka ◽  
Hanga Galfalvy ◽  
Jia Guo ◽  
Masato Akiyama ◽  
Dan Rujescu ◽  
...  
Keyword(s):  
Suicide Attempt ◽  
Psychiatric Disorders ◽  
Suicidal Behavior ◽  
Statistical Power ◽  
Small Sample ◽  
European Ancestry ◽  
Risk Scores ◽  
Suicide Attempters ◽  
Polygenic Risk ◽  
Suicide Death

Abstract Background Suicidal behavior is moderately heritable and a consequence of a combination of the diathesis traits for suicidal behavior and suicide-related major psychiatric disorders. Here, we sought to examine shared polygenic effects between various psychiatric disorders/traits and suicidal behavior and to compare the shared polygenic effects of various psychiatric disorders/traits on non-fatal suicide attempt and suicide death. Methods We used our genotyped European ancestry sample of 260 non-fatal suicide attempters, 317 suicide decedents and 874 non-psychiatric controls to test whether polygenic risk scores (PRSs) obtained from large GWASs for 22 suicide-related psychiatric disorders/traits were associated with suicidal behavior. Results were compared between non-fatal suicide attempt and suicide death in a sensitivity analysis. Results PRSs for major depressive disorder, bipolar disorder, schizophrenia, ADHD, alcohol dependence, sensitivity to environmental stress and adversity, educational attainment, cognitive performance, and IQ were associated with suicidal behavior (Bonferroni-corrected p < 2.5 × 10−4). The polygenic effects of all 22 psychiatric disorders/traits had the same direction (p for binomial tests = 4.8 × 10−7) and were correlated (Spearman's ρ = 0.85) between non-fatal suicide attempters and suicide decedents. Conclusions We found that polygenic effects for major psychiatric disorders and diathesis-related traits including stress responsiveness and intellect/cognitive function contributed to suicidal behavior. While we found comparable polygenic architecture between non-fatal suicide attempters and suicide decedents based on correlations with PRSs of suicide-related psychiatric disorders/traits, our analyses are limited by small sample size resulting in low statistical power to detect difference between non-fatal suicide attempt and suicide death.

O-116 Genetic association analyses identify links between pelvic prolapse (PP) and connective tissue biology, cardiovascular and reproductive health

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
N Pujol Gualdo ◽  
K Läll ◽  
M Lepamets ◽  
R Arffman ◽  
T Piltonen ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Meta Analyses ◽  
Personalized Risk

Abstract Study question Can genome-wide association analysis unravel the biological underpinnings of PP and facilitate personalized risk assessment via genetic risk scores construction? Summary answer We unravel novel links with urogenital development and vascular health in PP and present polygenic risk score as a tool to stratify PP risk. What is known already Prolapse is characterized by a descent of the pelvic organs into the vaginal cavity. PP affects around 40% of women after menopause and is the main indication for major gynecological surgery, having an important health, social and economic burden. Although the etiology and biological mechanisms underlying PP remain poorly understood, prior studies suggest genetic factors might play a role. Recently, a genome-wide association study (GWAS) identified seven genome-wide significant loci, located in or near genes involved in connective tissue metabolism and estrogen exposure in the etiology of PP. Study design, size, duration We conducted a three-stage case-control genome-wide association study. Firstly, in the discovery phase, we meta-analyzed Icelandic, UK Biobank and the FinnGen R3 datasets, comprising a total of 20118 cases and 427426 controls of European ancestry. For replication we used an independent dataset from Estonian Biobank (7968 cases and 118895 controls). Finally, we conducted a joint meta-analysis, containing 28086 cases and 546321 controls, which is the largest GWAS of PP to date. Participants/materials, setting, methods We performed functional annotation on genetic variants unraveled by GWAS and integrated these with expression quantitative trait loci and chromatin interaction data. In addition, we looked at enrichment of association signal on gene-set, tissue and cell type level and analyzed associations with other phenotypes both on genetic and phenotypic level. Colocalisation analyses were conducted to help pinpoint causal genes. We further constructed polygenic risk scores to explore options for personalized risk assessment and prevention. Main results and the role of chance In the discovery phase, we identified 18 genetic loci and 20 genetic variants significantly associated with POP (p &lt; 5 × 10−8) and 75% of the variants show nominal significance association (p &lt; 0.05) in the replication. Notably, the joint meta-analyses detected 20 genetic loci significantly associated with POP, from which 13 loci were novel. Novel genetic variants are located in or near genes involved in gestational duration and preterm birth (rs2687728 p = 2.19x10-9, EEFSEC), cardiovascular health and pregnancy success (rs1247943 p = 5.83x10-18, KLF13), endometriosis (rs12325192 p = 3.72x10-18, CRISPLD2), urogenital tract development (rs7126322, p = 4.35x10-15, WT1 and rs42400, p = 4.8x10-10, ADAMTS16) and regulation of the oxytocin receptor (rs2267372, p = 4.49x10-13, MAFF). Further analyses demonstrated that POP GWAS signals colocalise with several eQTLS (including EEFSEC, MAFF, KLF13, etc.), providing further evidence for mapping associated genes. Tissue and cell enrichment analyses underlined the role of the urogenital system, muscle cells, myocytes and adipocytes (p &lt; 0.00001, FDR&lt;0.05). Furthermore, genetic correlation analyses supported a shared genetic background with gastrointestinal disorders, joint and musculoskeletal disorders and cardiovascular disease. Polygenic risk scores analyses included a total of 125551 people in the target dataset, with 5379 prevalent patients and 2517 incident patients. Analyzing the best GRS as a quintile showed association with incident disease (Harrell c-statistic= 0.603, SD = 0.006). Limitations, reasons for caution This GWAS meta-analyses focused on European ancestry populations, which challenges the generalizability of GWAS findings to non-European populations. Moreover, this study included women with PP from population-based biobanks identified using the ICD-10 code N81, which limits analyses considering different disease stages and severity. Wider implications of the findings Our study provides genetic evidence to improve the current understanding of PP pathogenesis and serves as basis for further functional studies. Moreover, we provide a genetic tool for personalized risk stratification, which could help prevent PP development and improve the quality of a vast quantity of women. Trial registration number not applicable

Sign in / Sign up

Export Citation Format

Share Document