Erratum to: Heritability and genome-wide analyses of problematic peer relationships during childhood and adolescence.
Ontology highlight
ABSTRACT:
SUBMITTER: Pourcain BS
PROVIDER: S-EPMC6828428 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Peer behaviour plays an important role in the development of social adjustment, though little is known about its genetic architecture. We conducted a twin study combined with a genome-wide complex trait analysis (GCTA) and a genome-wide screen to characterise genetic influences on problematic peer behaviour during childhood and adolescence. This included a series of longitudinal measures (parent-reported Strengths-and-Difficulties Questionnaire) from a UK population-based birth-cohort (ALSPAC, 4-17 years), and a UK twin sample (TEDS, 4-11 years). Longitudinal twin analysis (TEDS; N ≤ 7,366 twin pairs) showed that peer problems in childhood are heritable (4-11 years, 0.60 < twin-h(2) ≤ 0.71) but genetically heterogeneous from age to age (4-11 years, twin-r(g) = 0.30). GCTA (ALSPAC: N ≤ 5,608, TEDS: N ≤ 2,691) provided furthermore little support for the contribution of measured common genetic variants during childhood (4-12 years, 0.02 < GCTA-h(2)(Meta) ≤ 0.11) though these influences become stronger in adolescence (13-17 years, 0.14 < GCTA-h (2)(ALSPAC) ≤ 0.27). A subsequent cross-sectional genome-wide screen in ALSPAC (N ≤ 6,000) focussed on peer problems with the highest GCTA-heritability (10, 13 and 17 years, 0.0002 < GCTA-P ≤ 0.03). Single variant signals (P ≤ 10(-5)) were followed up in TEDS (N ≤ 2835, 9 and 11 years) and, in search for autism quantitative trait loci, explored within two autism samples (AGRE: N Pedigrees = 793; ACC: N Cases = 1,453/N Controls = 7,070). There was, however, no evidence for association in TEDS and little evidence for an overlap with the autistic continuum. In summary, our findings suggest that problematic peer relationships are heritable but genetically complex and heterogeneous from age to age, with an increase in common measurable genetic variation during adolescence.
| S-EPMC4424375 | biostudies-literature
Project description:STUDY OBJECTIVES:Low or excessive sleep duration has been associated with multiple outcomes, but the biology behind these associations remains elusive. Specifically, genetic studies in children are scarce. In this study, we aimed to: (1) estimate the proportion of genetic variance of sleep duration in children attributed to common single nucleotide polymorphisms (SNPs), (2) identify novel SNPs associated with sleep duration in children, and (3) investigate the genetic overlap of sleep duration in children and related metabolic and psychiatric traits. METHODS:We performed a population-based molecular genetic study, using data form the EArly Genetics and Life course Epidemiology (EAGLE) Consortium. 10,554 children of European ancestry were included in the discovery, and 1,250 children in the replication phase. RESULTS:We found evidence of significant but modest SNP heritability of sleep duration in children (SNP h2 0.14, 95% CI [0.05, 0.23]) using the LD score regression method. A novel region at chromosome 11q13.4 (top SNP: rs74506765, P = 2.27e-08) was associated with sleep duration in children, but this was not replicated in independent studies. Nominally significant genetic overlap was only found (rG = 0.23, P = 0.05) between sleep duration in children and type 2 diabetes in adults, supporting the hypothesis of a common pathogenic mechanism. CONCLUSIONS:The significant SNP heritability of sleep duration in children and the suggestive genetic overlap with type 2 diabetes support the search for genetic mechanisms linking sleep duration in children to multiple outcomes in health and disease.
| S-EPMC5020368 | biostudies-literature
Project description:BackgroundCurrently, diabetes has become one of the leading causes of death worldwide. Fasting plasma glucose (FPG) levels that are higher than optimal, even if below the diagnostic threshold of diabetes, can also lead to increased morbidity and mortality. Here we intend to study the magnitude of the genetic influence on FPG variation by conducting structural equation modelling analysis and to further identify specific genetic variants potentially related to FPG levels by performing a genome-wide association study (GWAS) in Chinese twins.ResultsThe final sample included 382 twin pairs: 139 dizygotic (DZ) pairs and 243 monozygotic (MZ) pairs. The DZ twin correlation for the FPG level (rDZ = 0.20, 95% CI: 0.04-0.36) was much lower than half that of the MZ twin correlation (rMZ = 0.68, 95% CI: 0.62-0.74). For the variation in FPG level, the AE model was the better fitting model, with additive genetic parameters (A) accounting for 67.66% (95% CI: 60.50-73.62%) and unique environmental or residual parameters (E) accounting for 32.34% (95% CI: 26.38-39.55%), respectively. In the GWAS, although no genetic variants reached the genome-wide significance level (P < 5 × 10- 8), 28 SNPs exceeded the level of a suggestive association (P < 1 × 10- 5). One promising genetic region (2q33.1) around rs10931893 (P = 1.53 × 10- 7) was found. After imputing untyped SNPs, we found that rs60106404 (P = 2.38 × 10- 8) located at SPATS2L reached the genome-wide significance level, and 216 SNPs exceeded the level of a suggestive association. We found 1007 genes nominally associated with the FPG level (P < 0.05), including SPATS2L, KCNK5, ADCY5, PCSK1, PTPRA, and SLC26A11. Moreover, C1orf74 (P = 0.014) and SLC26A11 (P = 0.021) were differentially expressed between patients with impaired fasting glucose and healthy controls. Some important enriched biological pathways, such as β-alanine metabolism, regulation of insulin secretion, glucagon signaling in metabolic regulation, IL-1 receptor pathway, signaling by platelet derived growth factor, cysteine and methionine metabolism pathway, were identified.ConclusionsThe FPG level is highly heritable in the Chinese population, and genetic variants are significantly involved in regulatory domains, functional genes and biological pathways that mediate FPG levels. This study provides important clues for further elucidating the molecular mechanism of glucose homeostasis and discovering new diagnostic biomarkers and therapeutic targets for diabetes.
| S-EPMC7368793 | biostudies-literature
Project description:Human gait is a complex neurological and musculoskeletal function, of which the genetic basis remains largely unknown. To determine the influence of common genetic variants on gait parameters, we studied 2,946 participants of the Rotterdam Study, a population-based cohort of unrelated elderly individuals. We assessed 30 gait parameters using an electronic walkway, which yielded seven independent gait domains after principal component analysis. Genotypes of participants were imputed to the 1,000 Genomes reference panel for generating genetic relationship matrices to estimate heritability of gait parameters, and for subsequent genome-wide association scans (GWASs) to identify specific variants. Gait domains with the highest age- and sex-adjusted heritability were Variability (h (2) = 61%), Rhythm (37%), and Tandem (32%). For other gait domains, heritability estimates attenuated after adjustment for height and weight. Genome-wide association scans identified a variant on 1p22.3 that was significantly associated with single support time, a variable from the Rhythm domain (rs72953990; N = 2,946; β [SE] = 0.0069 (0.0012), p = 2.30×10(-8)). This variant did not replicate in an independent sample (N = 362; p = .78). In conclusion, human gait has highly heritable components that are explained by common genetic variation, which are partly attributed to height and weight. Collaborative efforts are needed to identify robust single variant associations for the heritable parameters.
| S-EPMC4888380 | biostudies-literature
Project description:Estimation of narrow-sense heritability, h(2), from genome-wide SNPs genotyped in unrelated individuals has recently attracted interest and offers several advantages over traditional pedigree-based methods. With the use of this approach, it has been estimated that over half the heritability of human height can be attributed to the ~300,000 SNPs on a genome-wide genotyping array. In comparison, only 5%-10% can be explained by SNPs reaching genome-wide significance. We investigated via simulation the validity of several key assumptions underpinning the mixed-model analysis used in SNP-based h(2) estimation. Although we found that the method is reasonably robust to violations of four key assumptions, it can be highly sensitive to uneven linkage disequilibrium (LD) between SNPs: contributions to h(2) are overestimated from causal variants in regions of high LD and are underestimated in regions of low LD. The overall direction of the bias can be up or down depending on the genetic architecture of the trait, but it can be substantial in realistic scenarios. We propose a modified kinship matrix in which SNPs are weighted according to local LD. We show that this correction greatly reduces the bias and increases the precision of h(2) estimates. We demonstrate the impact of our method on the first seven diseases studied by the Wellcome Trust Case Control Consortium. Our LD adjustment revises downward the h(2) estimate for immune-related diseases, as expected because of high LD in the major-histocompatibility region, but increases it for some nonimmune diseases. To calculate our revised kinship matrix, we developed LDAK, software for computing LD-adjusted kinships.
| S-EPMC3516604 | biostudies-literature
Project description:The discovery and prioritization of heritable phenotypes is a computational challenge in a variety of settings, including neuroimaging genetics and analyses of the vast phenotypic repositories in electronic health record systems and population-based biobanks. Classical estimates of heritability require twin or pedigree data, which can be costly and difficult to acquire. Genome-wide complex trait analysis is an alternative tool to compute heritability estimates from unrelated individuals, using genome-wide data that are increasingly ubiquitous, but is computationally demanding and becomes difficult to apply in evaluating very large numbers of phenotypes. Here we present a fast and accurate statistical method for high-dimensional heritability analysis using genome-wide SNP data from unrelated individuals, termed massively expedited genome-wide heritability analysis (MEGHA) and accompanying nonparametric sampling techniques that enable flexible inferences for arbitrary statistics of interest. MEGHA produces estimates and significance measures of heritability with several orders of magnitude less computational time than existing methods, making heritability-based prioritization of millions of phenotypes based on data from unrelated individuals tractable for the first time to our knowledge. As a demonstration of application, we conducted heritability analyses on global and local morphometric measurements derived from brain structural MRI scans, using genome-wide SNP data from 1,320 unrelated young healthy adults of non-Hispanic European ancestry. We also computed surface maps of heritability for cortical thickness measures and empirically localized cortical regions where thickness measures were significantly heritable. Our analyses demonstrate the unique capability of MEGHA for large-scale heritability-based screening and high-dimensional heritability profile construction.
| S-EPMC4345618 | biostudies-literature
Project description:IntroductionWhile whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma-related phenotypes.MethodsWe applied several WGP methods to a well-phenotyped cohort of 832 children with mild-to-moderate asthma from CAMP. We assessed narrow-sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre- and post-bronchodilator forced expiratory volume in 1 sec (FEV1), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort.ResultsWe found that longitudinal lung function phenotypes demonstrated significant narrow-sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4-8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts.ConclusionsLongitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP-prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma-related heritable traits.
| S-EPMC5134727 | biostudies-literature
Project description:Serum uric acid (SUA), as the end product of purine metabolism, has proven emerging roles in human disorders. Here based on a sample of 379 middle and old-aged Chinese twin pairs, we aimed to explore the magnitude of genetic impact on SUA variation by performing sex-limitation twin modeling analyses and further detect specific genetic variants related to SUA by conducting a genome-wide association study. Monozygotic (MZ) twin correlation for SUA level (rMZ?=?0.56) was larger than for dizygotic (DZ) twin correlation (rDZ?=?0.39). The common effects sex-limitation model provided the best fit with additive genetic parameter (A) accounting for 46.3%, common or shared environmental parameter (C) accounting for 26.3% and unique/nonshared environmental parameter (E) accounting for 27.5% for females and 29.9, 33.1, and 37.0% for males, respectively. Although no SUA-related genetic variants reached genome-wide significance level, 25 SNPs were suggestive of association (P?<?1?×?10-5). Most of the SNPs were located in an intronic region and detected to have regulatory effects on gene transcription. The cell-type specific enhancer of skeletal muscle was detected which has been reported to implicate SUA. Two promising genetic regions on chromosome 17 around rs2253277 and chromosome 14 around rs11621523 were found. Gene-based analysis found 167 genes nominally associated with SUA level (P?<?0.05), including PTGR2, ENTPD5, well-known SLC2A9, etc. Enrichment analysis identified one pathway of transmembrane transport of small molecules and 20 GO gene sets involving in ion transport, transmembrane transporter activity, hydrolase activity acting on acid anhydrides, etc. In conclusion, SUA shows moderate heritability in women and low heritability in men in the Chinese population and genetic variations are significantly involved in functional genes and regulatory domains that mediate SUA level. Our findings provide clues to further elucidate molecular physiology of SUA homeostasis and identify new diagnostic biomarkers and therapeutic targets for hyperuricemia and gout.
| S-EPMC5845532 | biostudies-literature
Project description:Asthma heritability has only been partially explained by genetic variants and is known to be sensitive to environmental factors, implicating epigenetic modifications such as DNA methylation in its pathogenesis.Using data collected in the Avon Longitudinal Study of Parents and Children (ALSPAC), we assessed associations of asthma and wheeze with DNA methylation at 7.5 and 16.5 years, at over 450,000 CpG sites in DNA from the peripheral blood of approx. 1000 participants. We used Mendelian randomization (MR), a method of causal inference that uses genetic variants as instrumental variables, to infer the direction of association between DNA methylation and asthma.We identified 302 CpGs associated with current asthma status (FDR-adjusted P value <?0.05) and 445 with current wheeze status at 7.5 years, with substantial overlap between the two. Genes annotated to the 302 associated CpGs were enriched for pathways related to movement of cellular/subcellular components, locomotion, interleukin-4 production and eosinophil migration. All associations attenuated when adjusted for eosinophil and neutrophil cell count estimates. At 16.5 years, two sites were associated with current asthma after adjustment for cell counts. The CpGs mapped to the AP2A2 and IL5RA genes, with a -?2.32 [95% CI -?1.47, -?3.18] and -?2.49 [95% CI -?1.56, -?3.43] difference in percentage methylation in asthma cases respectively. Two-sample bi-directional MR indicated a causal effect of asthma on DNA methylation at several CpG sites at 7.5 years. However, associations did not persist after adjustment for multiple testing. There was no evidence of a causal effect of asthma on DNA methylation at either of the two CpG sites at 16.5 years.The majority of observed associations are driven by higher eosinophil cell counts in asthma cases, acting as an intermediate phenotype, with important implications for future studies of DNA methylation in atopic diseases.
| S-EPMC5640901 | biostudies-other
Project description:Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits.
| S-EPMC7485556 | biostudies-literature