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<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<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 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.

Insights into the genomics of affective disorders

2020 ◽  
Vol 32 (1) ◽  
pp. 9-18
Author(s):  
Andreas J. Forstner ◽  
Per Hoffmann ◽  
Markus M. Nöthen ◽  
Sven Cichon
Keyword(s):  
Bipolar Disorder ◽  
Major Depression ◽  
Affective Disorders ◽  
Association Studies ◽  
Phenotypic Variability ◽  
Genetic Research ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Depression Symptoms ◽  
Genome Wide Association Studies

Abstract Affective disorders, or mood disorders, are a group of neuropsychiatric illnesses that are characterized by a disturbance of mood or affect. Most genetic research in this field to date has focused on bipolar disorder and major depression. Symptoms of major depression include a depressed mood, reduced energy, and a loss of interest and enjoyment. Bipolar disorder is characterized by the occurrence of (hypo)manic episodes, which generally alternate with periods of depression. Formal and molecular genetic studies have demonstrated that affective disorders are multifactorial diseases, in which both genetic and environmental factors contribute to disease development. Twin and family studies have generated heritability estimates of 58–85 % for bipolar disorder and 40 % for major depression. Large genome-wide association studies have provided important insights into the genetics of affective disorders via the identification of a number of common genetic risk factors. Based on these studies, the estimated overall contribution of common variants to the phenotypic variability (single-nucleotide polymorphism [SNP]-based heritability) is 17–23 % for bipolar disorder and 9 % for major depression. Bioinformatic analyses suggest that the associated loci and implicated genes converge into specific pathways, including calcium signaling. Research suggests that rare copy number variants make a lower contribution to the development of affective disorders than to other psychiatric diseases, such as schizophrenia or the autism spectrum disorders, which would be compatible with their less pronounced negative impact on reproduction. However, the identification of rare sequence variants remains in its infancy, as available next-generation sequencing studies have been conducted in limited samples. Future research strategies will include the enlargement of genomic data sets via innovative recruitment strategies; functional analyses of known associated loci; and the development of new, etiologically based disease models. Researchers hope that deeper insights into the biological causes of affective disorders will eventually lead to improved diagnostics and disease prediction, as well as to the development of new preventative, diagnostic, and therapeutic strategies. Pharmacogenetics and the application of polygenic risk scores represent promising initial approaches to the future translation of genomic findings into psychiatric clinical practice.

scholarly journals Genome-Wide Association Studies of Schizophrenia and Bipolar Disorder in a Diverse Cohort of US Veterans

2020 ◽  
Author(s):  
Tim B Bigdeli ◽  
Ayman H Fanous ◽  
Yuli Li ◽  
Nallakkandi Rajeevan ◽  
Frederick Sayward ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Susceptibility Loci ◽  
New Associations ◽  
Genome Wide ◽  
Us Veterans

Abstract Background Schizophrenia (SCZ) and bipolar disorder (BIP) are debilitating neuropsychiatric disorders, collectively affecting 2% of the world’s population. Recognizing the major impact of these psychiatric disorders on the psychosocial function of more than 200 000 US Veterans, the Department of Veterans Affairs (VA) recently completed genotyping of more than 8000 veterans with SCZ and BIP in the Cooperative Studies Program (CSP) #572. Methods We performed genome-wide association studies (GWAS) in CSP #572 and benchmarked the predictive value of polygenic risk scores (PRS) constructed from published findings. We combined our results with available summary statistics from several recent GWAS, realizing the largest and most diverse studies of these disorders to date. Results Our primary GWAS uncovered new associations between CHD7 variants and SCZ, and novel BIP associations with variants in Sortilin Related VPS10 Domain Containing Receptor 3 (SORCS3) and downstream of PCDH11X. Combining our results with published summary statistics for SCZ yielded 39 novel susceptibility loci including CRHR1, and we identified 10 additional findings for BIP (28 326 cases and 90 570 controls). PRS trained on published GWAS were significantly associated with case-control status among European American (P &lt; 10–30) and African American (P &lt; .0005) participants in CSP #572. Conclusions We have demonstrated that published findings for SCZ and BIP are robustly generalizable to a diverse cohort of US veterans. Leveraging available summary statistics from GWAS of global populations, we report 52 new susceptibility loci and improved fine-mapping resolution for dozens of previously reported associations.

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 A large-scale genome-wide association analysis of lung function in the Chinese population identifies novel loci and highlights shared genetic etiology with obesity

2021 ◽  
pp. 2100199
Author(s):  
Zhaozhong Zhu ◽  
Jiachen Li ◽  
Jiahui Si ◽  
Baoshan Ma ◽  
Huwenbo Shi ◽  
...  
Keyword(s):  
Lung Function ◽  
Large Scale ◽  
Causal Effect ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Etiology ◽  
Trait Analysis ◽  
Genome Wide ◽  
Shared Genetic

Lung function is a heritable complex phenotype with obesity being one of its important risk factors. However, the knowledge of their shared genetic basis is limited. Most genome-wide association studies (GWASs) for lung function have been based on European populations, limiting the generalisability across populations. Large-scale lung function GWAS in other populations are lacking.We included 100 285 subjects from China Kadoorie Biobank (CKB). To identify novel loci for lung function, single-trait GWAS were performed on FEV1, FVC, FEV1/FVC in CKB. We then performed genome-wide cross-trait analysis between the lung function and obesity traits (body mass index [BMI], BMI-adjusted waist-to-hip ratio, and BMI-adjusted waist circumference) to investigate the shared genetic effects in CKB. Finally, polygenic risk scores (PRSs) of lung function were developed in CKB and its interaction with BMI's association on lung function were examined. We also conducted cross-trait analysis in parallel with CKB using 457 756 subjects from UK Biobank (UKB) for replication and investigation of ancestry specific effect.We identified 9 genome-wide significant novel loci for FEV1, 6 for FVC and 3 for FEV1/FVC in CKB. FEV1 and FVC showed significant negative genetic correlation with obesity traits in both CKB and UKB. Genetic loci shared between lung function and obesity traits highlighted important pathways, including cell proliferation, embryo and tissue development. Mendelian randomisation analysis suggested significant negative causal effect of BMI on FEV1 and on FVC in both CKB and UKB. Lung function PRSs significantly modified the effect of change-in-BMI on change-in-lung function during an average follow-up of 8 years.This large-scale GWAS of lung function identified novel loci and shared genetic etiology between lung function and obesity. Change-in-BMI might affect change-in-lung function differently according to a subject's polygenic background. These findings may open new avenue for the development of molecular-targeted therapies for obesity and lung function improvement.

scholarly journals Interaction between Genetic Risk Scores for reduced pulmonary function and smoking, asthma and endotoxin

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2020-215624
Author(s):  
Sinjini Sikdar ◽  
Annah B Wyss ◽  
Mi Kyeong Lee ◽  
Thanh T Hoang ◽  
Marie Richards ◽  
...  
Keyword(s):  
Pulmonary Function ◽  
Genetic Risk ◽  
Association Studies ◽  
European Ancestry ◽  
Risk Scores ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Inverse Association ◽  
Genetic Risk Scores ◽  
Genome Wide

RationaleGenome-wide association studies (GWASs) have identified numerous loci associated with lower pulmonary function. Pulmonary function is strongly related to smoking and has also been associated with asthma and dust endotoxin. At the individual SNP level, genome-wide analyses of pulmonary function have not identified appreciable evidence for gene by environment interactions. Genetic Risk Scores (GRSs) may enhance power to identify gene–environment interactions, but studies are few.MethodsWe analysed 2844 individuals of European ancestry with 1000 Genomes imputed GWAS data from a case–control study of adult asthma nested within a US agricultural cohort. Pulmonary function traits were FEV1, FVC and FEV1/FVC. Using data from a recent large meta-analysis of GWAS, we constructed a weighted GRS for each trait by combining the top (p value<5×10−9) genetic variants, after clumping based on distance (±250 kb) and linkage disequilibrium (r2=0.5). We used linear regression, adjusting for relevant covariates, to estimate associations of each trait with its GRS and to assess interactions.ResultsEach trait was highly significantly associated with its GRS (all three p values<8.9×10−8). The inverse association of the GRS with FEV1/FVC was stronger for current smokers (pinteraction=0.017) or former smokers (pinteraction=0.064) when compared with never smokers and among asthmatics compared with non-asthmatics (pinteraction=0.053). No significant interactions were observed between any GRS and house dust endotoxin.ConclusionsEvaluation of interactions using GRSs supports a greater impact of increased genetic susceptibility on reduced pulmonary function in the presence of smoking or asthma.

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 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 Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Guy Hindley ◽  
Shahram Bahrami ◽  
Nils Eiel Steen ◽  
Kevin S. O’Connell ◽  
Oleksandr Frei ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Psychiatric Disorders ◽  
Risk Taking ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Increased Risk ◽  
Risky Behaviours ◽  
Shared Risk ◽  
Shared Genetic

AbstractIncreased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315–466,751). Genomic loci were functionally annotated using FUMA. Of 8.6–8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2–10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.

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