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

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.

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

2018 ◽  
Vol 21 (2) ◽  
pp. 84-88 ◽  
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.

scholarly journals Estimating heritability and its enrichment in tissue-specific gene sets in admixed populations

2018 ◽  
Author(s):  
Yang Luo ◽  
Xinyi Li ◽  
Xin Wang ◽  
Steven Gazal ◽  
Josep Maria Mercader ◽  
...  
Keyword(s):  
African American ◽  
Complex Traits ◽  
Association Studies ◽  
Genetic Data ◽  
Age At Menarche ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Diverse Populations ◽  
Tissue Specific ◽  
Different Populations

AbstractThe increasing size and diversity of genome-wide association studies provide an exciting opportunity to study how the genetics of complex traits vary among diverse populations. Here, we introduce covariate-adjusted LD score regression (cov-LDSC), a method to accurately estimate genetic heritability and its enrichment in both homogenous and admixed populations with summary statistics and in-sample LD estimates. In-sample LD can be estimated from a subset of the GWAS samples, allowing our method to be applied efficiently to very large cohorts. In simulations, we show that unadjusted LDSC underestimates by 10% − 60% in admixed populations; in contrast, cov-LDSC is robust to all simulation parameters. We apply cov-LDSC to genotyping data from approximately 170,000 Latino, 47,000 African American and 135,000 European individuals. We estimate and detect heritability enrichment in three quantitative and five dichotomous phenotypes respectively, making this, to our knowledge, the most comprehensive heritability-based analysis of admixed individuals. Our results show that most traits have high concordance of and consistent tissue-specific heritability enrichment among different populations. However, for age at menarche, we observe population-specific heritability estimates of . We observe consistent patterns of tissue-specific heritability enrichment across populations; for example, in the limbic system for BMI, the per-standardized-annotation effect size τ* is 0.16 ± 0.04, 0.28 ± 0.11 and 0.18 ± 0.03 in Latino, African American and European populations respectively. Our results demonstrate that our approach is a powerful way to analyze genetic data for complex traits from underrepresented populations.Author summaryAdmixed populations such as African Americans and Hispanic Americans bear a disproportionately high burden of disease but remain underrepresented in current genetic studies. It is important to extend current methodological advancements for understanding the genetic basis of complex traits in homogeneous populations to individuals with admixed genetic backgrounds. Here, we develop a computationally efficient method to answer two specific questions. First, does genetic variation contribute to the same amount of phenotypic variation (heritability) across diverse populations? Second, are the genetic mechanisms shared among different populations? To answer these questions, we use our novel method to conduct the first comprehensive heritability-based analysis of a large number of admixed individuals. We show that there is a high degree of concordance in total heritability and tissue-specific enrichment between different ancestral groups. However, traits such as age at menarche show a noticeable differences among populations. Our work provides a powerful way to analyze genetic data in admixed populations and may contribute to the applicability of genomic medicine to admixed population groups.

scholarly journals Identification of 12 genetic loci associated with human healthspan

2018 ◽  
Author(s):  
Aleksandr Zenin ◽  
Yakov Tsepilov ◽  
Sodbo Sharapov ◽  
Evgeny Getmantsev ◽  
L. I. Menshikov ◽  
...  
Keyword(s):  
Association Studies ◽  
Statistical Significance ◽  
Genetic Correlations ◽  
Human Longevity ◽  
Age At First Birth ◽  
Genome Wide Association Studies ◽  
Psychological Traits ◽  
Regulatory Pathways ◽  
Age Related ◽  
A Genome

The mounting challenge of preserving the quality of life in an aging population directs the focus of longevity science to the regulatory pathways controlling healthspan. To understand the nature of the relationship between the healthspan and lifespan and uncover the genetic architecture of the two phenotypes, we studied the incidence of major age-related diseases in the UK Biobank (UKB) cohort. We observed that the incidence rates of major chronic diseases increase exponentially. The risk of disease acquisition doubled approximately every eight years, i.e., at a rate compatible with the doubling time of the Gompertz mortality law. Assuming that aging is the single underlying factor behind the morbidity rates dynamics, we built a proportional hazards model to predict the risks of the diseases and therefore the age corresponding to the end of healthspan of an individual depending on their age, gender, and the genetic background. We suggested a computationally efficient procedure for the determination of the effect size and statistical significance of individual gene variants associations with healthspan in a form suitable for a Genome-Wide Association Studies (GWAS). Using the UKB sub-population of 300,447 genetically Caucasian, British individuals as a discovery cohort, we identified 12 loci associated with healthspan and reaching the whole-genome level of significance. We observed strong (|ρg| > 0.3) genetic correlations between healthspan and the incidence of specific age-related disease present in our healthspan definition (with the notable exception of dementia). Other examples included all-cause mortality (as derived from parental survival, with ρg = −0.76), life-history traits (metrics of obesity, age at first birth), levels of different metabolites (lipids, amino acids, glycemic traits), and psychological traits (smoking behaviour, cognitive performance, depressive symptoms, insomnia). We conclude by noting that the healthspan phenotype, suggested and characterized here, offers a promising new way to investigate human longevity by exploiting the data from genetic and clinical data on living individuals.

scholarly journals Genetic analysis identifies molecular systems and biological pathways associated with household income

2019 ◽  
Author(s):  
W. David Hill ◽  
Neil M. Davies ◽  
Stuart J. Ritchie ◽  
Nathan G. Skene ◽  
Julien Bryois ◽  
...  
Keyword(s):  
Cognitive Ability ◽  
Genetic Variants ◽  
Household Income ◽  
Association Studies ◽  
Genetic Correlations ◽  
Functional Enrichment ◽  
Genome Wide Association Studies ◽  
Income Differences ◽  
Genome Wide ◽  
Common Genetic Variants

AbstractSocio-economic position (SEP) is a multi-dimensional construct reflecting (and influencing) multiple socio-cultural, physical, and environmental factors. Previous genome-wide association studies (GWAS) using household income as a marker of SEP have shown that common genetic variants account for 11% of its variation. Here, in a sample of 286,301 participants from UK Biobank, we identified 30 independent genome-wide significant loci, 29 novel, that are associated with household income. Using a recently-developed method to meta-analyze data that leverages power from genetically-correlated traits, we identified an additional 120 income-associated loci. These loci showed clear evidence of functional enrichment, with transcriptional differences identified across multiple cortical tissues, in addition to links with GABAergic and serotonergic neurotransmission. We identified neurogenesis and the components of the synapse as candidate biological systems that are linked with income. By combining our GWAS on income with data from eQTL studies and chromatin interactions, 24 genes were prioritized for follow up, 18 of which were previously associated with cognitive ability. Using Mendelian Randomization, we identified cognitive ability as one of the causal, partly-heritable phenotypes that bridges the gap between molecular genetic inheritance and phenotypic consequence in terms of income differences. Significant differences between genetic correlations indicated that, the genetic variants associated with income are related to better mental health than those linked to educational attainment (another commonly-used marker of SEP). Finally, we were able to predict 2.5% of income differences using genetic data alone in an independent sample. These results are important for understanding the observed socioeconomic inequalities in Great Britain today.

Genetic correlations between subcortical brain volumes and psychiatric disorders

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.

Genetic contributions to anxiety disorders: where we are and where we are heading

2021 ◽  
pp. 1-16
Author(s):  
Helga Ask ◽  
Rosa Cheesman ◽  
Eshim S. Jami ◽  
Daniel F. Levey ◽  
Kirstin L. Purves ◽  
...  
Keyword(s):  
Anxiety Disorders ◽  
Psychiatric Disorders ◽  
Large Scale ◽  
Current Knowledge ◽  
Association Studies ◽  
Twin Studies ◽  
Future Research ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Genome Wide

Abstract Anxiety disorders are among the most common psychiatric disorders worldwide. They often onset early in life, with symptoms and consequences that can persist for decades. This makes anxiety disorders some of the most debilitating and costly disorders of our time. Although much is known about the synaptic and circuit mechanisms of fear and anxiety, research on the underlying genetics has lagged behind that of other psychiatric disorders. However, alongside the formation of the Psychiatric Genomic Consortium Anxiety workgroup, progress is rapidly advancing, offering opportunities for future research. Here we review current knowledge about the genetics of anxiety across the lifespan from genetically informative designs (i.e. twin studies and molecular genetics). We include studies of specific anxiety disorders (e.g. panic disorder, generalised anxiety disorder) as well as those using dimensional measures of trait anxiety. We particularly address findings from large-scale genome-wide association studies and show how such discoveries may provide opportunities for translation into improved or new therapeutics for affected individuals. Finally, we describe how discoveries in anxiety genetics open the door to numerous new research possibilities, such as the investigation of specific gene–environment interactions and the disentangling of causal associations with related traits and disorders. We discuss how the field of anxiety genetics is expected to move forward. In addition to the obvious need for larger sample sizes in genome-wide studies, we highlight the need for studies among young people, focusing on specific underlying dimensional traits or components of anxiety.

scholarly journals Tissue-specific 5-hydroxymethylcytosine landscape of the human genome

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bo He ◽  
Chao Zhang ◽  
Xiaoxue Zhang ◽  
Yu Fan ◽  
Hu Zeng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Genome ◽  
Association Studies ◽  
Specific Gene ◽  
Epigenetic Mark ◽  
Genome Wide Association Studies ◽  
Human Tissues ◽  
Tissue Specific ◽  
Tissue Specific Gene ◽  
Specific Gene Expression

Abstract5-Hydroxymethylcytosine (5hmC) is an important epigenetic mark that regulates gene expression. Charting the landscape of 5hmC in human tissues is fundamental to understanding its regulatory functions. Here, we systematically profiled the whole-genome 5hmC landscape at single-base resolution for 19 types of human tissues. We found that 5hmC preferentially decorates gene bodies and outperforms gene body 5mC in reflecting gene expression. Approximately one-third of 5hmC peaks are tissue-specific differentially-hydroxymethylated regions (tsDhMRs), which are deposited in regions that potentially regulate the expression of nearby tissue-specific functional genes. In addition, tsDhMRs are enriched with tissue-specific transcription factors and may rewire tissue-specific gene expression networks. Moreover, tsDhMRs are associated with single-nucleotide polymorphisms identified by genome-wide association studies and are linked to tissue-specific phenotypes and diseases. Collectively, our results show the tissue-specific 5hmC landscape of the human genome and demonstrate that 5hmC serves as a fundamental regulatory element affecting tissue-specific gene expression programs and functions.

scholarly journals nMAGMA: a network enhanced method for inferring risk genes from GWAS summary statistics and its application to schizophrenia

2020 ◽  
Author(s):  
Anyi Yang ◽  
Jingqi Chen ◽  
Xing-Ming Zhao
Keyword(s):  
Gene Networks ◽  
Association Studies ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Nucleotide Polymorphisms ◽  
Risk Genes ◽  
Tissue Specific ◽  
Genomic Annotation ◽  
Genome Wide

AbstractMotivationAnnotating genetic variants from summary statistics of genome-wide association studies (GWAS) is crucial for predicting risk genes of various disorders. The multi-marker analysis of genomic annotation (MAGMA) is one of the most popular tools for this purpose, where MAGMA aggregates signals of single nucleotide polymorphisms (SNPs) to their nearby genes. However, SNPs may also affect genes in a distance, thus missed by MAGMA. Although different upgrades of MAGMA have been proposed to extend gene-wise variant annotations with more information (e.g. Hi-C or eQTL), the regulatory relationships among genes and the tissue-specificity of signals have not been taken into account.ResultsWe propose a new approach, namely network-enhanced MAGMA (nMAGMA), for gene-wise annotation of variants from GWAS summary statistics. Compared with MAGMA and H-MAGMA, nMAGMA significantly extends the lists of genes that can be annotated to SNPs by integrating local signals, long-range regulation signals, and tissue-specific gene networks. When applied to schizophrenia, nMAGMA is able to detect more risk genes (217% more than MAGMA and 57% more than H-MAGMA) that are reasonably involved in schizophrenia compared to MAGMA and H-MAGMA. Some disease-related functions (e.g. the ATPase pathway in Cortex) tissues are also uncovered in nMAGMA but not in MAGMA or H-MAGMA. Moreover, nMAGMA provides tissue-specific risk signals, which are useful for understanding disorders with multi-tissue origins.

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 Heritability of pubertal timing: detailed evaluation of specific milestones in healthy boys and girls

2020 ◽  
Vol 183 (1) ◽  
pp. 13-20
Author(s):  
Alexander S Busch ◽  
Casper P Hagen ◽  
Anders Juul
Keyword(s):  
Genetic Heterogeneity ◽  
Large Scale ◽  
Pubertal Timing ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genetic Data ◽  
Genome Wide Association Studies ◽  
Facial Hair ◽  
Timing Of Menarche ◽  
Relative Category

Objective Pubertal timing is highly heritable. Observational studies were inconclusive concerning a potential sex-specific difference in the parental contribution, while genome-wide association studies highlighted a heterogeneity in the genetic architecture of pubertal timing between sexes. Our objectives were to evaluate the association of timing of pubertal milestones in offspring with parental pubertal timing and to identify the genetic basis of the heterogeneity. Design (1.) Population-based mixed cross-sectional/longitudinal cohort (2006–2014, COPENHAGEN Puberty Study) comprising 1381 healthy Danish children including their parents. (2.) UK Biobank-based summary statistics of genetic data on timing of menarche (n = 188 644), voice-break (n = 154 459) and facial hair (n = 161 470). Methods (1.) Participants underwent clinical examination(s) including blood sampling. Parental pubertal timing was obtained by questionnaire. Timing of milestones were analyzed using SAS-lifereg. (2.) Genetic correlations between pubertal outcomes were estimated using LD Score regression. Genetic heterogeneity was analyzed using METAL. Results We observed significant associations of relative parental pubertal timing with timing of pubertal milestones in offspring of concordant sex, that is, fathers/sons (e.g. testicular enlargement: P = 0.004, β = 0.34 years per relative category) and mothers/daughters (e.g. thelarche: P < 0.001, β = 0.45 years per relative category). Fewer milestones were associated with relative parental pubertal timing in offspring of discordant sex compared to concordant sex. Large-scale genetic data highlight both moderate to strong genetic correlations between timing of menarche, voice-break and facial hair. Out of 434 lead single-nucleotide polymorphisms significantly associated with at least one outcome, 39 exhibited a significant genetic heterogeneity between sexes (P < 1.15 × 10−4). Conclusion Our results highlight a distinct genetic heterogeneity of pubertal timing between sexes.

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