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

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.

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

10.1101/467910 ◽

2018 ◽

Cited By ~ 1

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.

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Comment on ‘Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets’ by Lam et al.

Twin Research and Human Genetics ◽

10.1017/thg.2018.12 ◽

2018 ◽

Vol 21 (2) ◽

pp. 84-88 ◽

Cited By ~ 6

Author(s):

W. David Hill

Keyword(s):

Genetic Information ◽

Drug Targets ◽

Large Scale ◽

Association Studies ◽

Meta Analysis ◽

Genetic Correlations ◽

Data Sets ◽

Genome Wide Association Studies ◽

Nootropic Drug ◽

Genome Wide

Intelligence and educational attainment are strongly genetically correlated. This relationship can be exploited by Multi-Trait Analysis of GWAS (MTAG) to add power to Genome-wide Association Studies (GWAS) of intelligence. MTAG allows the user to meta-analyze GWASs of different phenotypes, based on their genetic correlations, to identify association's specific to the trait of choice. An MTAG analysis using GWAS data sets on intelligence and education was conducted by Lam et al. (2017). Lam et al. (2017) reported 70 loci that they described as ‘trait specific’ to intelligence. This article examines whether the analysis conducted by Lam et al. (2017) has resulted in genetic information about a phenotype that is more similar to education than intelligence.

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

Neurology ◽

10.1212/wnl.0000000000005415 ◽

2018 ◽

Vol 90 (18) ◽

pp. e1605-e1612 ◽

Cited By ~ 24

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.

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Human demographic history impacts genetic risk prediction across diverse populations

10.1101/070797 ◽

2016 ◽

Cited By ~ 7

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.

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

10.1101/2020.05.02.053983 ◽

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.

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Large-scale cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets

10.1101/176842 ◽

2017 ◽

Author(s):

Max Lam ◽

Joey W. Trampush ◽

Jin Yu ◽

Emma Knowles ◽

Gail Davies ◽

...

Keyword(s):

Cognitive Ability ◽

Large Scale ◽

Association Studies ◽

Genetic Correlations ◽

Adult Brain ◽

Specific Gene ◽

Age At First Birth ◽

Genome Wide Association Studies ◽

Tissue Specific ◽

Brain Expression

AbstractNeurocognitive ability is a fundamental readout of brain function, and cognitive deficits are a critical component of neuropsychiatric disorders, yet neurocognition is poorly understood at the molecular level. In the present report, we present the largest genome-wide association studies (GWAS) of cognitive ability to date (N=107,207), and further enhance signal by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with cognitive ability, 34 of which were novel. A total of 350 genes were implicated, and this list showed significant enrichment for genes associated with Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis of gene results implicated the biological process of neurogenesis, as well as the gene targets of two pharmacologic agents: cinnarizine, a T-type calcium channel blocker; and LY97241, a potassium channel inhibitor. Transcriptome-wide analysis revealed that the implicated genes were strongly expressed in neurons, but not astrocytes or oligodendrocytes, and were more strongly associated with fetal brain expression than adult brain expression. Several tissue-specific gene expression relationships to cognitive ability were observed (for example, DAG1 levels in the hippocampus). Finally, we report novel genetic correlations between cognitive ability and disparate phenotypes such as maternal age at first birth and number of children, as well as several autoimmune disorders.

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Genetic correlations between subcortical brain volumes and psychiatric disorders

The British Journal of Psychiatry ◽

10.1192/bjp.2019.277 ◽

2020 ◽

Vol 216 (5) ◽

pp. 280-283

Author(s):

Kazutaka Ohi ◽

Takamitsu Shimada ◽

Yuzuru Kataoka ◽

Toshiki Yasuyama ◽

Yasuhiro Kawasaki ◽

...

Keyword(s):

Psychiatric Disorders ◽

Genetic Variants ◽

Large Scale ◽

Association Studies ◽

Genetic Correlations ◽

Intracranial Volume ◽

Genome Wide Association Studies ◽

Brain Volumes ◽

Subcortical Brain ◽

Genome Wide

SummaryPsychiatric disorders as well as subcortical brain volumes are highly heritable. Large-scale genome-wide association studies (GWASs) for these traits have been performed. We investigated the genetic correlations between five psychiatric disorders and the seven subcortical brain volumes and the intracranial volume from large-scale GWASs by linkage disequilibrium score regression. We revealed weak overlaps between the genetic variants associated with psychiatric disorders and subcortical brain and intracranial volumes, such as in schizophrenia and the hippocampus and bipolar disorder and the accumbens. We confirmed shared aetiology and polygenic architecture across the psychiatric disorders and the specific subcortical brain and intracranial volume.

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

PLoS ONE ◽

10.1371/journal.pone.0243104 ◽

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.

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Improving Polygenic Prediction in Ancestrally Diverse Populations

10.21203/rs.3.rs-133290/v1 ◽

2021 ◽

Author(s):

Hailiang Huang ◽

Yunfeng Ruan ◽

Yen-Chen Anne Feng ◽

Chia-Yen Chen ◽

Max Lam ◽

...

Keyword(s):

Association Studies ◽

Genetic Correlations ◽

Genomic Research ◽

Alternative Methods ◽

Risk Scores ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Size Estimation ◽

Wide Range ◽

European Populations

Abstract Polygenic risk scores (PRS) have attenuated cross-population predictive performance. As existing genome-wide association studies (GWAS) were predominantly conducted in individuals of European descent, the limited transferability of PRS reduces its clinical value in non-European populations and may exacerbate healthcare disparities. Recent efforts to level ancestry imbalance in genomic research have expanded the scale of non-European GWAS, although they remain under-powered. Here we present a novel PRS construction method, PRS-CSx, which improves cross-population polygenic prediction by integrating GWAS summary statistics from multiple populations. PRS-CSx couples genetic effects across populations via a shared continuous shrinkage prior, enabling more accurate effect size estimation by sharing information between summary statistics and leveraging linkage disequilibrium (LD) diversity across discovery samples, while inheriting computational efficiency and robustness from PRS-CS. We show that PRS-CSx outperforms alternative methods across traits with a wide range of genetic architectures and cross-population genetic correlations in simulations, and substantially improves the prediction of quantitative traits and schizophrenia risk in non-European populations.

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

10.1101/2020.11.30.403188 ◽

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.

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