scholarly journals Genetic liability in individuals at ultra-high risk of psychosis: A comparison study of 9 psychiatric traits

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243104
Author(s):  
Keane Lim ◽  
Max Lam ◽  
Hailiang Huang ◽  
Jianjun Liu ◽  
Jimmy Lee
Keyword(s):  
High Risk ◽  
Large Scale ◽  
Association Studies ◽  
Predictive Ability ◽  
Risk Scores ◽  
Psychotic Symptoms ◽  
Genome Wide Association Studies ◽  
Healthy Controls ◽  
Genetic Liability ◽  
Ultra High Risk

Individuals at ultra-high risk (UHR) of psychosis are characterised by the emergence of attenuated psychotic symptoms and deterioration in functioning. In view of the high non-psychotic comorbidity and low rates of transition to psychosis, the specificity of the UHR status has been called into question. This study aims to (i) investigate if the UHR construct is associated with the genetic liability of schizophrenia or other psychiatric conditions; (ii) examine the ability of polygenic risk scores (PRS) to discriminate healthy controls from UHR, remission and conversion status. PRS was calculated for 210 youths (nUHR = 102, nControl = 108) recruited as part of the Longitudinal Youth at Risk Study (LYRIKS) using nine psychiatric traits derived from twelve large-scale psychiatric genome-wide association studies as discovery datasets. PRS was also examined to discriminate UHR-Healthy control status, and healthy controls from UHR remission and conversion status. Result indicated that schizophrenia PRS appears to best index the genetic liability of UHR, while trend level associations were observed for depression and cross-disorder PRS. Schizophrenia PRS discriminated healthy controls from UHR (R2 = 7.9%, p = 2.59 x 10−3, OR = 1.82), healthy controls from non-remitters (R2 = 8.1%, p = 4.90 x 10−4, OR = 1.90), and converters (R2 = 7.6%, p = 1.61 x 10−3, OR = 1.82), with modest predictive ability. A trend gradient increase in schizophrenia PRS was observed across categories. The association between schizophrenia PRS and UHR status supports the hypothesis that the schizophrenia polygenic liability indexes the risk for developing psychosis.

scholarly journals An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

2018 ◽  
Author(s):  
Tom G. Richardson ◽  
Sean Harrison ◽  
Gibran Hemani ◽  
George Davey Smith
Keyword(s):  
Web Application ◽  
Large Scale ◽  
Complex Disease ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Polygenic Risk ◽  
The Uk

AbstractThe age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (P<5×l0 05) derived from GWAS and 551 heritable traits from the UK Biobank study (N=334,398). Findings can be investigated using a web application (http://mrcieu.mrsoftware.org/PRS_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility.To demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to unravel the causal determinants of complex disease.

scholarly journals An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Tom G Richardson ◽  
Sean Harrison ◽  
Gibran Hemani ◽  
George Davey Smith
Keyword(s):  
Web Application ◽  
Large Scale ◽  
Complex Disease ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Polygenic Risk ◽  
The Uk

The age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (p<5×10−05) derived from GWAS and 551 heritable traits from the UK Biobank study (N = 334,398). Findings can be investigated using a web application (http:‌//‌mrcieu.‌mrsoftware.org/‌PRS‌_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility. To demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to unravel the causal determinants of complex disease.

Discriminative Analysis of Symptom Severity and Ultra-High Risk of Schizophrenia Using Intrinsic Functional Connectivity

2020 ◽  
Vol 30 (09) ◽  
pp. 2050047
Author(s):  
Lubin Wang ◽  
Xianbin Li ◽  
Yuyang Zhu ◽  
Bei Lin ◽  
Qijing Bo ◽  
...  
Keyword(s):  
High Risk ◽  
Functional Connectivity ◽  
Symptom Severity ◽  
Large Scale ◽  
Brain Networks ◽  
Brain Regions ◽  
Support Vector ◽  
Healthy Controls ◽  
Intrinsic Functional Connectivity ◽  
Ultra High Risk

Past studies have consistently shown functional dysconnectivity of large-scale brain networks in schizophrenia. In this study, we aimed to further assess whether multivariate pattern analysis (MVPA) could yield a sensitive predictor of patient symptoms, as well as identify ultra-high risk (UHR) stage of schizophrenia from intrinsic functional connectivity of whole-brain networks. We first combined rank-based feature selection and support vector machine methods to distinguish between 43 schizophrenia patients and 52 healthy controls. The constructed classifier was then applied to examine functional connectivity profiles of 18 UHR individuals. The classifier indicated reliable relationship between MVPA measures and symptom severity, with higher classification accuracy in more severely affected schizophrenia patients. The UHR subjects had classification scores falling between those of healthy controls and patients, suggesting an intermediate level of functional brain abnormalities. Moreover, UHR individuals with schizophrenia-like connectivity profiles at baseline presented higher rate of conversion to full-blown illness in the follow-up visits. Spatial maps of discriminative brain regions implicated increases of functional connectivity in the default mode network, whereas decreases of functional connectivity in the cerebellum, thalamus and visual areas in schizophrenia. The findings may have potential utility in the early diagnosis and intervention of schizophrenia.

scholarly journals Dissociable influences of APOE ε4 and polygenic risk of AD dementia on amyloid and cognition

Neurology ◽  
2018 ◽  
Vol 90 (18) ◽  
pp. e1605-e1612 ◽  
Author(s):  
Tian Ge ◽  
Mert R. Sabuncu ◽  
Jordan W. Smoller ◽  
Reisa A. Sperling ◽  
Elizabeth C. Mormino ◽  
...  
Keyword(s):  
Cognitive Decline ◽  
Genetic Risk ◽  
Large Scale ◽  
Association Studies ◽  
Specific Effect ◽  
Hippocampal Volume ◽  
Risk Scores ◽  
Hippocampal Atrophy ◽  
Genome Wide Association Studies ◽  
Polygenic Risk

ObjectiveTo investigate the effects of genetic risk of Alzheimer disease (AD) dementia in the context of β-amyloid (Aβ) accumulation.MethodsWe analyzed data from 702 participants (221 clinically normal, 367 with mild cognitive impairment, and 114 with AD dementia) with genetic data and florbetapir PET available. A subset of 669 participants additionally had longitudinal MRI scans to assess hippocampal volume. Polygenic risk scores (PRSs) were estimated with summary statistics from previous large-scale genome-wide association studies of AD dementia. We examined relationships between APOE ε4 status and PRS with longitudinal Aβ and cognitive and hippocampal volume measurements.ResultsAPOE ε4 was strongly related to baseline Aβ, whereas only weak associations between PRS and baseline Aβ were present. APOE ε4 was additionally related to greater memory decline and hippocampal atrophy in Aβ+ participants. When APOE ε4 was controlled for, PRS was related to cognitive decline in Aβ+ participants. Finally, PRSs were associated with hippocampal atrophy in Aβ− participants and weakly associated with baseline hippocampal volume in Aβ+ participants.ConclusionsGenetic risk factors of AD dementia demonstrate effects related to Aβ, as well as synergistic interactions with Aβ. The specific effect of faster cognitive decline in Aβ+ individuals with higher genetic risk may explain the large degree of heterogeneity in cognitive trajectories among Aβ+ individuals. Consideration of genetic variants in conjunction with baseline Aβ may improve enrichment strategies for clinical trials targeting Aβ+ individuals most at risk for imminent cognitive decline.

scholarly journals Human demographic history impacts genetic risk prediction across diverse populations

2016 ◽  
Author(s):  
Alicia R. Martin ◽  
Christopher R. Gignoux ◽  
Raymond K. Walters ◽  
Genevieve L. Wojcik ◽  
Benjamin M. Neale ◽  
...  
Keyword(s):  
Risk Prediction ◽  
Large Scale ◽  
Disease Risk ◽  
Association Studies ◽  
Demographic History ◽  
Population History ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Medical Genomics

AbstractThe vast majority of genome-wide association studies are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g. linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely-used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWAS, we used published summary statistics to calculate polygenic risk scores for six well-studied traits and diseases. We identified directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk were typically highest in the population from which summary statistics were derived. We demonstrated that scores inferred from European GWAS were biased by genetic drift in other populations even when choosing the same causal variants, and that biases in any direction were possible and unpredictable. This work cautions that summarizing findings from large-scale GWAS may have limited portability to other populations using standard approaches, and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.

scholarly journals Large uncertainty in individual PRS estimation impacts PRS-based risk stratification

2020 ◽  
Author(s):  
Yi Ding ◽  
Kangcheng Hou ◽  
Kathryn S. Burch ◽  
Sandra Lapinska ◽  
Florian Privé ◽  
...  
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Probabilistic Approach ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Single Individual ◽  
Individual Level ◽  
Credible Intervals ◽  
The Uk ◽  
Genetic Value

AbstractLarge-scale genome-wide association studies have enabled polygenic risk scores (PRS), which estimate the genetic value of an individual for a given trait. Since PRS accuracy is typically assessed using cohort-level metrics (e.g., R2), uncertainty in PRS estimates at individual level remains underexplored. Here we show that Bayesian PRS methods can estimate the variance of individual PRS and can yield well-calibrated credible intervals for the genetic value of a single individual. For real traits in the UK Biobank (N=291,273 unrelated “white British”), we observe large variance in individual PRS estimates which impacts interpretation of PRS-based stratification; for example, averaging across 11 traits, only 1.8% (s.d. 2.4%) of individuals with PRS point estimates in the top decile have their entire 95% credible intervals fully contained in the top decile. To account for this uncertainty, we propose a probabilistic approach to PRS-based stratification that estimates the probability of an individual’s genetic value to be above a prespecified threshold. Our results showcase the importance of incorporating uncertainty in individual PRS estimates into subsequent analyses.

scholarly journals Exploring shared genetic bases and causal relationships of schizophrenia and bipolar disorder with 28 cardiovascular and metabolic traits

2018 ◽  
Vol 49 (08) ◽  
pp. 1286-1298 ◽  
Author(s):  
Hon-Cheong So ◽  
Kwan-Long Chau ◽  
Fu-Kiu Ao ◽  
Cheuk-Hei Mo ◽  
Pak-Chung Sham
Keyword(s):  
Bipolar Disorder ◽  
Large Scale ◽  
Association Studies ◽  
Risk Scores ◽  
Exact Nature ◽  
Genome Wide Association Studies ◽  
Inverse Association ◽  
Causal Relationships ◽  
Shared Genetic ◽  
Genetic Bases

AbstractBackgroundCardiovascular diseases represent a major health issue in patients with schizophrenia (SCZ) and bipolar disorder (BD), but the exact nature of cardiometabolic (CM) abnormalities involved and the underlying mechanisms remain unclear. Psychiatric medications are known risk factors, but it is unclear whether there is a connection between the disorders (SCZ/BD) themselves and CM abnormalities.MethodsUsing polygenic risk scores and linkage disequilibrium score regression, we investigated the shared genetic bases of SCZ and BD with 28 CM traits. We performed Mendelian randomization (MR) to elucidate causal relationships between the two groups of disorders. The analysis was based on large-scale meta-analyses of genome-wide association studies. We also identified the potential shared genetic variants and inferred the pathways involved.ResultsWe found tentative polygenic associations of SCZ with glucose metabolism abnormalities, adverse adipokine profiles, increased waist-to-hip ratio and visceral adiposity (false discovery rate or FDR&lt;0.05). However, there was an inverse association with body mass index. For BD, we observed several polygenic associations with favorable CM profiles at FDR&lt;0.05. MR analysis showed that SCZ may be causally linked to raised triglyceride and that lower fasting glucose may be linked to BD. We also identified numerous single nucleotide polymorphisms and pathways shared between SCZ/BD with CM traits, some of which are related to inflammation or the immune system.ConclusionsOur findings suggest that SCZ patients may be genetically predisposed to several CM abnormalities independent of medication side effects. On the other hand, CM abnormalities in BD may be more likely to be secondary. However, the findings require further validation.

scholarly journals Psychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci

2016 ◽  
Vol 47 (6) ◽  
pp. 1116-1125 ◽  
Author(s):  
M. Liu ◽  
S. M. Malone ◽  
U. Vaidyanathan ◽  
M. C. Keller ◽  
G. Abecasis ◽  
...  
Keyword(s):  
Complex Traits ◽  
Large Scale ◽  
Electrodermal Activity ◽  
Association Studies ◽  
Causal Chain ◽  
Event Related Potential ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disorder Risk

BackgroundEndophenotypes are laboratory-based measures hypothesized to lie in the causal chain between genes and clinical disorder, and to serve as a more powerful way to identify genes associated with the disorder. One promise of endophenotypes is that they may assist in elucidating the neurobehavioral mechanisms by which an associated genetic polymorphism affects disorder risk in complex traits. We evaluated this promise by testing the extent to which variants discovered to be associated with schizophrenia through large-scale meta-analysis show associations with psychophysiological endophenotypes.MethodWe genome-wide genotyped and imputed 4905 individuals. Of these, 1837 were whole-genome-sequenced at 11× depth. In a community-based sample, we conducted targeted tests of variants within schizophrenia-associated loci, as well as genome-wide polygenic tests of association, with 17 psychophysiological endophenotypes including acoustic startle response and affective startle modulation, antisaccade, multiple frequencies of resting electroencephalogram (EEG), electrodermal activity and P300 event-related potential.ResultsUsing single variant tests and gene-based tests we found suggestive evidence for an association between contactin 4 (CNTN4) and antisaccade and P300. We were unable to find any other variant or gene within the 108 schizophrenia loci significantly associated with any of our 17 endophenotypes. Polygenic risk scores indexing genetic vulnerability to schizophrenia were not related to any of the psychophysiological endophenotypes after correction for multiple testing.ConclusionsThe results indicate significant difficulty in using psychophysiological endophenotypes to characterize the genetically influenced neurobehavioral mechanisms by which risk loci identified in genome-wide association studies affect disorder risk.

scholarly journals The genetic etiology of childhood insomnia: Longitudinal gene-brain-behavior associations in the ABCD study

2020 ◽  
Author(s):  
Leanna M. Hernandez ◽  
Minsoo Kim ◽  
Cristian Hernandez ◽  
Wesley Thompson ◽  
Chun Chieh Fan ◽  
...  
Keyword(s):  
Sleep Disturbances ◽  
Large Scale ◽  
Sleep Problems ◽  
Association Studies ◽  
Genetic Correlations ◽  
Externalizing Disorders ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Brain Surface ◽  
Brain Behavior

AbstractChildhood sleep problems are common and frequently comorbid with neurodevelopmental, psychiatric disorders. However, little is known about the genetic contributions to sleep-related traits in childhood, their potential relationship with brain development and psychiatric outcomes, or their association with adult sleep disturbance. Using data from the Adolescent Brain and Cognitive Development study, we performed a comprehensive characterization of the genetic and phenotypic relationships between childhood sleep disturbances (SDs; insomnia, arousal, breathing, somnolence, hyperhidrosis, sleep-wake transitions), global and regional measures of brain structure, and multiple dimensions of psychiatric symptomology in 9-10-year-old youth (discovery/replication N=4,428). Among the six SDs assessed, only insomnia showed significant SNP-based heritability (h2=0.15) and had replicable associations with smaller brain surface area (SA). Furthermore, insomnia showed significant positive phenotypic and genetic correlations with externalizing disorders (e.g., attention-deficit/hyperactivity disorder [ADHD]). Polygenic risk scores (PRS) calculated from genome-wide association studies (GWAS) of ADHD predicted insomnia and externalizing symptoms longitudinally, as well as decreased SA at baseline. In contrast, PRS trained using the largest adult insomnia GWAS did not predict childhood insomnia. Together, these findings demonstrate a distinct genetic architecture between childhood and adult SD, and indicate that childhood insomnia should be considered along the dimensional axis of ADHD and externalizing traits. These results highlight the importance of developmental context when interpreting gene-brain-behavior relationships and underscore the need for further large-scale genetic investigations of psychiatric phenotypes in pediatric populations.

scholarly journals Validation of a Trans-Ancestry Polygenic Risk Score for Type 2 Diabetes in Diverse Populations

2021 ◽  
Author(s):  
Tian Ge ◽  
Amit Patki ◽  
Vinodh Srinivasasainagendra ◽  
Yen-Feng Lin ◽  
Marguerite Ryan Irvin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
African American ◽  
Large Scale ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk

ABSTRACTType 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for an equitable deployment of PRS to clinical practice that benefits global populations. Here we integrate T2D GWAS in European, African American and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and evaluate the PRS in the multi-ethnic eMERGE study, four African American cohorts, and the Taiwan Biobank. The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined, and the top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5 fold of increase in T2D risk, suggesting the potential of using the trans-ancestry PRS as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Sign in / Sign up

Export Citation Format

Share Document