37 research outputs found

    Genetics of callous-unemotional behavior in children

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    Callous-unemotional behavior (CU) is currently under consideration as a subtyping index for conduct disorder diagnosis. Twin studies routinely estimate the heritability of CU as greater than 50%. It is now possible to estimate genetic influence using DNA alone from samples of unrelated individuals, not relying on the assumptions of the twin method. Here we use this new DNA method (implemented in a software package called Genome-wide Complex Trait Analysis, GCTA) for the first time to estimate genetic influence on CU. We also report the first genome-wide association (GWA) study of CU as a quantitative trait. We compare these DNA results to those from twin analyses using the same measure and the same community sample of 2,930 children rated by their teachers at ages 7, 9 and 12. GCTA estimates of heritability were near zero, even though twin analysis of CU in this sample confirmed the high heritability of CU reported in the literature, and even though GCTA estimates of heritability were substantial for cognitive and anthropological traits in this sample. No significant associations were found in GWA analysis, which, like GCTA, only detects additive effects of common DNA variants. The phrase ‘missing heritability’ was coined to refer to the gap between variance associated with DNA variants identified in GWA studies versus twin study heritability. However, GCTA heritability, not twin study heritability, is the ceiling for GWA studies because both GCTA and GWA are limited to the overall additive effects of common DNA variants, whereas twin studies are not. This GCTA ceiling is very low for CU in our study, despite its high twin study heritability estimate. The gap between GCTA and twin study heritabilities will make it challenging to identify genes responsible for the heritability of CU

    Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank.

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    BackgroundAutism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of biospecimens, phenotypes and genomic data for research on autism.MethodsGenome-wide single-nucleotide polymorphism genotypes were available for 2,477 individuals (after quality control) from 546 families (436 complete), including 886 participants aged 2 to 17 years with diagnosed (n = 871) or suspected (n = 15) ASD, 218 siblings without ASD, 1,256 parents, and 117 unrelated children without an ASD diagnosis. The genetic data were used to confirm familial relationships and assign ancestry, which was majority European (n = 1,964 European individuals). We generated polygenic scores (PGS) for ASD, IQ, chronotype and height in the subset of Europeans, and in 3,490 unrelated ancestry-matched participants from the UK Biobank. We tested for group differences for each PGS, and performed prediction analyses for related phenotypes in the AAB. We called copy-number variants (CNVs) in all participants, and intersected these with high-confidence ASD- and intellectual disability (ID)-associated CNVs and genes from the public domain.ResultsThe ASD (p = 6.1e-13), sibling (p = 4.9e-3) and unrelated (p = 3.0e-3) groups had significantly higher ASD PGS than UK Biobank controls, whereas this was not the case for height-a control trait. The IQ PGS was a significant predictor of measured IQ in undiagnosed children (r = 0.24, p = 2.1e-3) and parents (r = 0.17, p = 8.0e-7; 4.0% of variance), but not the ASD group. Chronotype PGS predicted sleep disturbances within the ASD group (r = 0.13, p = 1.9e-3; 1.3% of variance). In the CNV analysis, we identified 13 individuals with CNVs overlapping ASD/ID-associated CNVs, and 12 with CNVs overlapping ASD/ID/developmental delay-associated genes identified on the basis of de novo variants.LimitationsThis dataset is modest in size, and the publicly-available genome-wide-association-study (GWAS) summary statistics used to calculate PGS for ASD and other traits are relatively underpowered.ConclusionsWe report on common genetic variation and rare CNVs within the AAB. Prediction analyses using currently available GWAS summary statistics are largely consistent with expected relationships based on published studies. As the size of publicly-available GWAS summary statistics grows, the phenotypic depth of the AAB dataset will provide many opportunities for analyses of autism profiles and co-occurring conditions, including when integrated with other omics datasets generated from AAB biospecimens (blood, urine, stool, hair)

    Childhood behaviour problems show the greatest gap between DNA-based and twin heritability

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    For most complex traits, DNA-based heritability (‘SNP heritability’) is roughly half that of twin-based heritability. A previous report from the Twins Early Development Study suggested that this heritability gap is much greater for childhood behaviour problems than for other domains. If true, this finding is important because SNP heritability, not twin heritability, is the ceiling for genome-wide association studies. With twice the sample size as the previous report, we estimated SNP heritabilities (N up to 4653 unrelated individuals) and compared them with twin heritabilities from the same sample (N up to 4724 twin pairs) for diverse domains of childhood behaviour problems as rated by parents, teachers, and children themselves at ages 12 and 16. For 37 behaviour problem measures, the average twin heritability was 0.52, whereas the average SNP heritability was just 0.06. In contrast, results for cognitive and anthropometric traits were more typical (average twin and SNP heritabilities were 0.58 and 0.28, respectively). Future research should continue to investigate the reasons why SNP heritabilities for childhood behaviour problems are so low compared with twin estimates, and find ways to maximise SNP heritability for genome-wide association studies

    Genetic and Environmental Causes of Variation in Trait Resilience in Young People

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    The aim of this multi-informant twin study was to determine the relative role of genetic and environmental factors in explaining variation in trait resilience in adolescents. Participants were consenting families (N = 2,638 twins in 1,394 families), from seven national cohorts (age 12–18 years, both sexes) of monozygotic and dizygotic twins reared together. Questionnaire data on the adolescents’ Ego-resilience (ER89) was collected from mothers, fathers and twins, and analysed by means of multivariate genetic modelling. Variance in trait resilience was best represented in an ADE common pathways model with sex limitation. Variance in the latent psychometric resilience factor was largely explained by additive genetic factors (77% in boys, 70% in girls), with the remaining variance (23 and 30%) attributable to non-shared environmental factors. Additive genetic sources explained more than 50% of the informant specific variation in mothers and fathers scores. In twins, additive and non-additive genetic factors together explained 40% and non-shared environmental factor the remaining 60% of variation. In the mothers’ scores, the additive genetic effect was larger for boys than for girls. The non-additive genetic factor found in the twins’ self ratings was larger in boys than in girls. The remaining sex differences in the specific factors were small. Trait resilience is largely genetically determined. Estimates based on several informants rather than single informants approaches are recommended

    Corrigendum to Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci

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    Neuroticism is a personality trait of fundamental importance for psychological well-being and public health. It is strongly associated with major depressive disorder (MDD) and several other psychiatric conditions. Although neuroticism is heritable, attempts to identify the alleles involved in previous studies have been limited by relatively small sample sizes. Here we report a combined meta-analysis of genome-wide association study (GWAS) of neuroticism that includes 91 370 participants from the UK Biobank cohort, 6659 participants from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and 8687 participants from a QIMR (Queensland Institute of Medical Research) Berghofer Medical Research Institute (QIMR) cohort. All participants were assessed using the same neuroticism instrument, the Eysenck Personality Questionnaire-Revised (EPQ-R-S) Short Form’s Neuroticism scale. We found a single-nucleotide polymorphism-based heritability estimate for neuroticism of ~15% (s.e.=0.7%). Meta-analysis identified nine novel loci associated with neuroticism. The strongest evidence for association was at a locus on chromosome 8 (P=1.5 × 10−15) spanning 4 Mb and containing at least 36 genes. Other associated loci included interesting candidate genes on chromosome 1 (GRIK3 (glutamate receptor ionotropic kainate 3)), chromosome 4 (KLHL2 (Kelch-like protein 2)), chromosome 17 (CRHR1 (corticotropin-releasing hormone receptor 1) and MAPT (microtubule-associated protein Tau)) and on chromosome 18 (CELF4 (CUGBP elav-like family member 4)). We found no evidence for genetic differences in the common allelic architecture of neuroticism by sex. By comparing our findings with those of the Psychiatric Genetics Consortia, we identified a strong genetic correlation between neuroticism and MDD and a less strong but significant genetic correlation with schizophrenia, although not with bipolar disorder. Polygenic risk scores derived from the primary UK Biobank sample captured ~1% of the variance in neuroticism in the GS:SFHS and QIMR samples, although most of the genome-wide significant alleles identified within a UK Biobank-only GWAS of neuroticism were not independently replicated within these cohorts. The identification of nine novel neuroticism-associated loci will drive forward future work on the neurobiology of neuroticism and related phenotypes

    Genome-wide analysis of over 106  000 individuals identifies 9 neuroticism-associated loci

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    Neuroticism is a personality trait of fundamental importance for psychological well-being and public health. It is strongly associated with major depressive disorder (MDD) and several other psychiatric conditions. Although neuroticism is heritable, attempts to identify the alleles involved in previous studies have been limited by relatively small sample sizes. Here we report a combined meta-analysis of genome-wide association study (GWAS) of neuroticism that includes 91 370 participants from the UK Biobank cohort, 6659 participants from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and 8687 participants from a QIMR (Queensland Institute of Medical Research) Berghofer Medical Research Institute (QIMR) cohort. All participants were assessed using the same neuroticism instrument, the Eysenck Personality Questionnaire-Revised (EPQ-R-S) Short Form’s Neuroticism scale. We found a single-nucleotide polymorphism-based heritability estimate for neuroticism of ~15% (s.e.=0.7%). Meta-analysis identified nine novel loci associated with neuroticism. The strongest evidence for association was at a locus on chromosome 8 (P=1.5 × 10−15) spanning 4 Mb and containing at least 36 genes. Other associated loci included interesting candidate genes on chromosome 1 (GRIK3 (glutamate receptor ionotropic kainate 3)), chromosome 4 (KLHL2 (Kelch-like protein 2)), chromosome 17 (CRHR1 (corticotropin-releasing hormone receptor 1) and MAPT (microtubule-associated protein Tau)) and on chromosome 18 (CELF4 (CUGBP elav-like family member 4)). We found no evidence for genetic differences in the common allelic architecture of neuroticism by sex. By comparing our findings with those of the Psychiatric Genetics Consortia, we identified a strong genetic correlation between neuroticism and MDD and a less strong but significant genetic correlation with schizophrenia, although not with bipolar disorder. Polygenic risk scores derived from the primary UK Biobank sample captured ~1% of the variance in neuroticism in the GS:SFHS and QIMR samples, although most of the genome-wide significant alleles identified within a UK Biobank-only GWAS of neuroticism were not independently replicated within these cohorts. The identification of nine novel neuroticism-associated loci will drive forward future work on the neurobiology of neuroticism and related phenotypes

    Attentional switching forms a genetic link between attention problems and autistic traits in adults

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    Background. Attention deficit hyperactivity disorder (ADHD) symptoms and autistic traits often occur together. The pattern and etiology of co-occurrence are largely unknown, particularly in adults. This study investigated the co-occurrence between both traits in detail, and subsequently examined the etiology of the co-occurrence, using two independent adult population samples. Method. Data on ADHD traits (Inattention and Hyperactivity/Impulsivity) were collected in a population sample (S1, n = 559) of unrelated individuals. Data on Attention Problems (AP) were collected in a population-based family sample of twins and siblings (S2, n = 560). In both samples five dimensions of autistic traits were assessed (social skills, routine, attentional switching, imagination, patterns). Results. Hyperactive traits (S1) did not correlate substantially with the autistic trait dimensions. For Inattention (S1) and AP (S2), the correlations with the autistic trait dimensions were low, apart from a prominent correlation with the attentional switching scale (0.47 and 0.32 respectively). Analyses in the genetically informative S2 revealed that this association could be explained by a shared genetic factor. Conclusions. Our findings suggest that the co-occurrence of ADHD traits and autistic traits in adults is not determined by problems with hyperactivity, social skills, imagination or routine preferences. Instead, the association between those traits is due primarily to shared attention-related problems (inattention and attentional switching capacity). As the etiology of this association is purely genetic, biological pathways involving attentional control could be a promising focus of future stud
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