7 research outputs found

    Hepatitis E virus: Western Cape, South Africa

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    AIM To conduct a prospective assessment of anti-hepatitis E virus (HEV) IgG seroprevalence in the Western Cape Province of South Africa in conjunction with evaluating risk factors for exposure. METHODS Consenting participants attending clinics and wards of Groote Schuur, Red Cross Children's Hospital and their affiliated teaching hospitals in Cape Town, South Africa, were sampled. Healthy adults attending blood donor clinics were also recruited. Patients with known liver disease were excluded and all major ethnic/race groups were included to broadly represent local demographics. Relevant demographic data was captured at the time of sampling using an interviewer-administered confidential questionnaire. Human immunodeficiency virus (HIV) status was self-disclosed. HEV IgG testing was performed using the Wantai assay. RESULTS HEV is endemic in the region with a seroprevalence of 27.9% (n = 324/1161) 95%CI: 25.3%-30.5% (21.9% when age-adjusted) with no significant differences between ethnic groups or HIV status. Seroprevalence in children is low but rapidly increases in early adulthood. With univariate analysis, age ? 30 years old, pork and bacon/ham consumption suggested risk. In the multivariate analysis, the highest risk factor for HEV IgG seropositivity (OR = 7.679, 95%CI: 5.38-10.96, p < 0.001) was being 30 years or older followed by pork consumption (OR = 2.052, 95%CI: 1.39-3.03, p < 0.001). A recent clinical case demonstrates that HEV genotype 3 may be currently circulating in the Western Cape. CONCLUSION Hepatitis E seroprevalence was considerably higher than previously thought suggesting that hepatitis E warrants consideration in any patient pre

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

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    Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association metaanalysis (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 |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). 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.</p

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

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    Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association metaanalysis (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 AGG(overall). 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 r(g)= 0.46 between self- and teacher-assessment to r(g)d= 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 r(g): 0.19-1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (r(g)=-0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range |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.Peer reviewe

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

    No full text
    Childhood 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 ∣ 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). 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

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

    No full text
    Childhood 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 (AGG) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGG. 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 (r ) among rater-specific assessment of AGG ranged from r = 0.46 between self- and teacher-assessment to r = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong r 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 : 0.19-1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (r = ~−0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range : 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
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