scholarly journals Genetic association study of childhood aggression across raters, instruments, and age

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hill F. Ip ◽  
Camiel M. van der Laan ◽  
Eva M. L. Krapohl ◽  
Isabell Brikell ◽  
Cristina Sánchez-Mora ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Genetic Correlations ◽  
Teacher Assessment ◽  
Childhood Aggression ◽  
Age At First Birth ◽  
Psychological Traits ◽  
Compulsive Disorder ◽  
Genome Wide ◽  
A Genome ◽  
Variance Explained

AbstractChildhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E–06), PCDH7 (P = 2.0E–06), and IPO13 (P = 2.5E–06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg = 0.46 between self- and teacher-assessment to rg = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range $$\left| {r_g} \right|$$ r g : 0.19–1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg = ~−0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range $$\left| {r_g} \right|$$ r g : 0.46–0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.

scholarly journals Genetic Association Study of Childhood Aggression across raters, instruments and age

2019 ◽  
Author(s):  
Hill F. Ip ◽  
Camiel M. van der Laan ◽  
Eva M. L. Krapohl ◽  
Isabell Brikell ◽  
Cristina Sánchez-Mora ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Genetic Correlations ◽  
Childhood Aggression ◽  
Age At First Birth ◽  
Nucleotide Polymorphisms ◽  
Obsessive Compulsive ◽  
Psychological Traits ◽  
Compulsive Disorder ◽  
Genome Wide ◽  
Polygenic Scores

AbstractBackgroundHuman aggressive behavior (AGG) has a substantial genetic component. Here we present a large genome-wide association meta-analysis (GWAMA) of childhood AGG.MethodsWe analyzed assessments of AGG for a total of 328,935 observations from 87,485 children (aged 1.5 – 18 years), from multiple assessors, instruments, and ages, while accounting for sample overlap. We performed an overall analysis and meta-analyzed subsets of the data within rater, instrument, and age.ResultsHeritability based on the overall meta-analysis (AGGall) that could be attributed to Single Nucleotide Polymorphisms (SNPs) was 3.31% (SE=0.0038). No single SNP reached genome-wide significance, but gene-based analysis returned three significant genes: ST3GAL3 (P=1.6E-06), PCDH7 (P=2.0E-06) and IPO13 (P=2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children and in retrospectively assessed childhood aggression. We obtained moderate-to-strong genetic correlations (rg‘s) with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range |rg|: 0.19 –.1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg =∼-0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range |rg|: 0.46 – 0.60). Genetic correlations between AGG and psychiatric disorders were strongest for mother- and self-reported AGG.ConclusionsThe current GWAMA of childhood aggression provides a powerful tool to interrogate the genetic etiology of AGG by creating individual polygenic scores and genetic correlations with psychiatric traits.

scholarly journals Genome-wide association meta-analysis of childhood and adolescent internalising symptoms

2020 ◽  
Author(s):  
Eshim S Jami ◽  
Anke R Hammerschlag ◽  
Hill F Ip ◽  
Andrea G Allegrini ◽  
Beben Benyamin ◽  
...  
Keyword(s):  
Confidence Intervals ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Genetic Effects ◽  
Childhood Aggression ◽  
Genome Wide Association ◽  
Childhood And Adolescence ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Genome Wide

Internalising symptoms in childhood and adolescence are as heritable as adult depression and anxiety, yet little is known of their molecular basis. This genome-wide association meta-analysis of internalising symptoms included repeated observations from 64,641 individuals, aged between 3 and 18. The N-weighted meta-analysis of overall internalising symptoms (INToverall) detected no genome-wide significant hits and showed low SNP heritability (1.66%, 95% confidence intervals 0.84-2.48%, Neffective=132,260). Stratified analyses showed rater-based heterogeneity in genetic effects, with self-reported internalising symptoms showing the highest heritability (5.63%, 95% confidence intervals 3.08-8.18%). Additive genetic effects on internalising symptoms appeared stable over age, with overlapping estimates of SNP heritability from early-childhood to adolescence. Gene-based analyses showed significant associations with three genes: WNT3 (p=1.13×10-06), CCL26 (p=1.88×10-06), and CENPO (p=2.54×10-06). Of these, WNT3 was previously associated with neuroticism, with which INToverall also shared a strong genetic correlation (rg=0.76). Genetic correlations were also observed with adult anxiety, depression, and the wellbeing spectrum (|rg|> 0.70), as well as with insomnia, loneliness, attention-deficit hyperactivity disorder, autism, and childhood aggression (range |rg|=0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Overall, childhood and adolescent internalising symptoms share substantial genetic vulnerabilities with adult internalising disorders and other childhood psychiatric traits, which could explain both the persistence of internalising symptoms over time, and the high comorbidity amongst childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

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 Genome-wide analyses in 1,987,836 participants identify 39 genetic loci associated with sleep apnoea

2020 ◽  
Author(s):  
Adrian I Campos ◽  
Nathan Ingold ◽  
Yunru Huang ◽  
Pik Fang Kho ◽  
Xikun Han ◽  
...  
Keyword(s):  
Complex Traits ◽  
Statistical Power ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Sleep Apnoea ◽  
Risk Scores ◽  
Genetic Associations ◽  
Genome Wide ◽  
A Genome

Rationale: Sleep apnoea is a complex disorder characterised by periods of halted breathing during sleep. Despite its association with serious health conditions such as cardiovascular disease, the aetiology of sleep apnoea remains understudied, and previous genetic studies have failed to identify replicable genetic risk factors. Objective: To advance our understanding of factors that increase susceptibility to sleep apnoea by identifying novel genetic associations. Methods: We conducted a genome-wide association study (GWAS) meta-analysis of sleep apnoea across five cohorts, and a previously published GWAS of apnoea-hypopnea index (N Total =510,484). Further, we used multi-trait analysis of GWAS (MTAG) to boost statistical power, leveraging the high genetic correlations between apnoea, snoring and body mass index. Replication was performed in an independent sample from 23andMe, Inc (N Total =1,477,352; N cases =175,522). Results: Our results revealed 39 independent genomic loci robustly associated with sleep apnoea risk, and significant genetic correlations with multisite chronic pain, sleep disorders, diabetes, high blood pressure, osteoarthritis, asthma and BMI-related traits. We also derived polygenic risk scores for sleep apnoea in a leave-one-out independent cohort and predicted probable sleep apnoea in participants (OR=1.15 to 1.22; variance explained = 0.4 to 0.9%). Conclusions: We report novel genetic markers robustly associated with sleep apnoea risk and substantial molecular overlap with other complex traits, thus advancing our understanding of the underlying biological mechanisms of susceptibility to sleep apnoea.

scholarly journals A genome-wide association study finds novel genetic associations with broadly-defined headache in UK Biobank (N = 223,773)

2017 ◽  
Author(s):  
Weihua Meng ◽  
Mark J Adams ◽  
Harry L Hebert ◽  
Ian J Deary ◽  
Andrew M McIntosh ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Uk Biobank ◽  
Genetic Associations ◽  
Psychological Traits ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

AbstractHeadache is the most common neurological symptom and a leading cause of years lived with disability. We sought to identify the genetic variants associated with a broadly-defined headache phenotype in 223,773 subjects from the UK Biobank cohort. We defined headache based on a specific question answered by the UK Biobank participants. We performed a genome-wide association study of headache as a single entity, using 74,461 cases and 149,312 controls. We identified 3,343 SNPs which reached the genome-wide significance level of P < 5 × 10−8. The SNPs were located in 28 loci, with the top SNP of rs11172113 in the LRP1 gene having a P value of 4.92 × 10−47. Of the 28 loci, 14 have previously been associated with migraine. Among 14 new loci, rs77804065 with a P value of 5.87 × 10−15 in the LINC02210-CRHR1 gene was the top SNP.Positive relationships (P < 0.001) between multiple brain tissues and genetic associations were identified through tissue expression analysis, whereas no vascular related tissues showed significant relationships. We identified several significant positive genetic correlations between headache and other psychological traits including neuroticism, depressive symptoms, insomnia, and major depressive disorder.Our results suggest that brain function is closely related to broadly-defined headache. In addition, we also found that many psychological traits have genetic correlations with headache.

scholarly journals Genetic meta-analysis of obsessive-compulsive disorder and self-report compulsive symptoms

2019 ◽  
Author(s):  
Dirk J.A. Smit ◽  
Danielle Cath ◽  
Nuno R. Zilhão ◽  
Hill F. Ip ◽  
Damiaan Denys ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Genetic Correlations ◽  
Significant Snps ◽  
Population Based ◽  
Case Control ◽  
Reward Processing ◽  
Self Report ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Genome Wide

AbstractWe investigated whether obsessive compulsive (OC) symptoms from a population-based sample could be analyzed to detect genetic variants influencing OCD. We performed a GWAS on the obsession (rumination and impulsions) and compulsion (checking, washing, and ordering/precision) subscales of an abbreviated version of the Padua Inventory (N=8267 with genome-wide genotyping and phenotyping). The compulsion subscale showed a substantial and significant positive genetic correlation with an OCD case-control GWAS (rG=0.61, p=0.017) previously published by the Psychiatric Genomics Consortium (PGC-OCD). The obsession subscale and the total Padua score showed no significant genetic correlations (rG=–0.02 and rG=0.42, respectively). A meta-analysis of the compulsive symptoms GWAS with the PGC-OCD revealed no genome-wide significant SNPs (combined N=17992, indicating that the power is still low for individual SNP effects). A gene-based association analysis, however, yielded two novel genes (WDR7 and ADCK1). The top 250 genes in the gene-based test also showed significant increase in enrichment for psychiatric and brain-expressed genes. S-Predixcan testing showed that for genes expressed in hippocampus, amygdala, and caudate nucleus significance increased in the meta-analysis with compulsive symptoms compared to the original PGC-OCD GWAS. Thus, inclusion of dimensional symptom data in genome-wide association on clinical case-control GWAS of OCD may be useful to find genes for OCD if the data are based on quantitative indices of compulsive behavior. SNP-level power increases were limited, but aggregate, gene-level analyses showed increased enrichment for brain-expressed genes related to psychiatric disorders, and increased association with gene-expression in brain tissues with known emotional, reward processing, memory, and fear-formation functions.

Abstract 16003: Genetic Variation Associated With Favorable Exercise Response in Patients With Systolic Heart Failure: A Hf-action Trial Substudy

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Sara Coles ◽  
Stephanie Giamberardino ◽  
Carol Haynes ◽  
Ruicong She ◽  
Hongsheng Gui ◽  
...  
Keyword(s):  
Heart Failure ◽  
Clinical Trial ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Systolic Heart Failure ◽  
Genome Wide Association ◽  
Supervised Exercise ◽  
Genome Wide ◽  
A Genome ◽  
Response To Exercise

Background: Exercise has shown benefit in patients with systolic heart failure, including in the clinical trial Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION). There is heterogeneity in who derives benefit from exercise, and the biologic mechanisms of favorable response to exercise in systolic heart failure are not well understood. Hypothesis: Genetic variation is an underlying factor influencing heterogeneity in response to exercise in patients with systolic heart failure. Methods: The HF-ACTION trial randomized individuals with systolic heart failure (left ventricular ejection fraction <35%) to supervised exercise versus usual care. In this study, we performed a genome wide association study (GWAS) in the HF-ACTION biorepository using the Axiom Biobank1 genotyping array (13,403,591 single nucleotide polymorphisms [SNPs] after quality control on directly genotyped and 1000 genomes imputed data), in N=377 study subjects who completed the supervised exercise arm. Using change in peak VO2 as our outcome, we ran within-ancestry GWASes, modeling SNP effects as both additive and dominant, and conducted across-ancestry meta-analysis within each genetic model. Results: Five loci met genome-wide significance in the European ancestry analyses, 5 loci in the African ancestry, and 8 in the meta-analyses. The two most significantly associated loci across both additive and dominant meta-analysis models were rs111577308 located in the histone acetylation for transcription elongator complex 3 gene ( ELP3, p=1.212x10 -9 ) and rs75444785 located in the phosphodiesterase 4D gene ( PDE4D , p=1.565x10 -9 ). ELP3 is responsible for histone modifications related to DNA transcription factor complexes, and PDE4D is involved in cyclic AMP cell signaling. In silico analysis of these loci showed that they are in linkage with regions associated with skeletal muscle and peripheral vascular disease phenotypes. Conclusions: Using a genome-wide association study in a well-phenotyped clinical trial of exercise in systolic heart failure, we found common genetic variants in genes involved in DNA transcription histone modification and cyclic AMP cell signaling that are associated with a more favorable response to exercise.

scholarly journals Genome-wide association study of treatment-resistance in depression and meta-analysis of three independent samples

2018 ◽  
Vol 214 (1) ◽  
pp. 36-41 ◽  
Author(s):  
Chiara Fabbri ◽  
Siegfried Kasper ◽  
Alexander Kautzky ◽  
Lucie Bartova ◽  
Markus Dold ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Adenosine Monophosphate ◽  
Research Support ◽  
Antidepressant Treatments ◽  
Advisory Boards ◽  
Gene Sets ◽  
Genome Wide ◽  
A Genome ◽  
Resistant Depression

BackgroundTreatment-resistant depression (TRD) is the most problematic outcome of depression in terms of functional impairment, suicidal thoughts and decline in physical health.AimsTo investigate the genetic predictors of TRD using a genome-wide approach to contribute to the development of precision medicine.MethodA sample recruited by the European Group for the Study of Resistant Depression (GSRD) including 1148 patients with major depressive disorder (MDD) was characterised for the occurrence of TRD (lack of response to at least two adequate antidepressant treatments) and genotyped using the Infinium PsychArray. Three clinically relevant patient groups were considered: TRD, responders and non-responders to the first antidepressant trial, thus outcomes were based on comparisons of these groups. Genetic analyses were performed at the variant, gene and gene-set (i.e. functionally related genes) level. Additive regression models of the outcomes and relevant covariates were used in the GSRD participants and in a fixed-effect meta-analysis performed between GSRD, STAR*D (n = 1316) and GENDEP (n = 761) participants.ResultsNo individual polymorphism or gene was associated with TRD, although some suggestive signals showed enrichment in cytoskeleton regulation, transcription modulation and calcium signalling. Two gene sets (GO:0043949 and GO:0000183) were associated with TRD versus response and TRD versus response and non-response to the first treatment in the GSRD participants and in the meta-analysis, respectively (corrected P = 0.030 and P = 0.027).ConclusionsThe identified gene sets are involved in cyclic adenosine monophosphate mediated signal and chromatin silencing, two processes previously implicated in antidepressant action. They represent possible biomarkers to implement personalised antidepressant treatments and targets for new antidepressants.Declaration of interestD.S. has received grant/research support from GlaxoSmithKline and Lundbeck; has served as a consultant or on advisory boards for AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen and Lundbeck. S.M. has been a consultant or served on advisory boards for: AstraZeneca, Bristol-Myers Squibb, Forest, Johnson & Johnson, Leo, Lundbeck, Medelink, Neurim, Pierre Fabre, Richter. S.K. has received grant/research support from Eli Lilly, Lundbeck, Bristol-Myers Squibb, GlaxoSmithKline, Organon, Sepracor and Servier; has served as a consultant or on advisory boards for AstraZeneca, Bristol-Myers Squibb, GlaxoSmithKline, Eli Lilly, Lundbeck, Pfizer, Organon, Schwabe, Sepracor, Servier, Janssen and Novartis; and has served on speakers' bureaus for AstraZeneca, Eli Lily, Lundbeck, Schwabe, Sepracor, Servier, Pierre Fabre, Janssen and Neuraxpharm. J.Z. has received grant/research support from Lundbeck, Servier, Brainsway and Pfizer, has served as a consultant or on advisory boards for Servier, Pfizer, Abbott, Lilly, Actelion, AstraZeneca and Roche and has served on speakers' bureaus for Lundbeck, Roch, Lilly, Servier, Pfizer and Abbott. J.M. is a member of the Board of the Lundbeck International Neuroscience Foundation and of Advisory Board of Servier. A.S. is or has been consultant/speaker for: Abbott, AbbVie, Angelini, Astra Zeneca, Clinical Data, Boehringer, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, Innovapharma, Italfarmaco, Janssen, Lundbeck, Naurex, Pfizer, Polifarma, Sanofi and Servier. C.M.L. receives research support from RGA UK Services Limited.

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