Showing papers by "Andrew C. Heath published in 2019"
University of California, San Diego1, McGill University2, Oregon Health & Science University3, Florida International University4, Yale University5, Washington University in St. Louis6, Virginia Commonwealth University7, University of Vermont8, University of Michigan9, Medical University of South Carolina10, National Institutes of Health11, SRI International12, University of Southern California13, McGovern Institute for Brain Research14, Harvard University15, Medical College of Wisconsin16, University of California, Irvine17, University of California, Los Angeles18, University of California, San Francisco19, University of Colorado Boulder20, University of Florida21, University of Maryland, Baltimore22, University of Massachusetts Boston23, University of Minnesota24, University of Pittsburgh25, University of Rochester26, University of Tennessee27, University of Utah28, University of Wisconsin–Milwaukee29, United States Department of Veterans Affairs30, Boston University31
TL;DR: The baseline neuroimaging processing and subject-level analysis methods used by the Adolescent Brain Cognitive Development Study are described to be a resource of unprecedented scale and depth for studying typical and atypical development.
431 citations
Wellcome Trust Centre for Human Genetics1, University of Liverpool2, University of Virginia3, Washington University in St. Louis4, University of Manchester5, University Medical Center Groningen6, University of Bristol7, University of California, San Diego8, Icahn School of Medicine at Mount Sinai9, Mexican Social Security Institute10, University of Miami11, UCLA Medical Center12, Fred Hutchinson Cancer Research Center13, University of Washington14, QIMR Berghofer Medical Research Institute15, Karolinska Institutet16, Dalarna University17, University of Southern California18, Federation University Australia19, University of Leicester20, University of Melbourne21, Fu Jen Catholic University22, Erasmus University Medical Center23, Columbia University24, Uppsala University25, University of California, Los Angeles26, Loyola University Medical Center27, Broad Institute28, University of Queensland29, University of California, Irvine30, Jackson Memorial Hospital31, University of Düsseldorf32, Kaiser Permanente33, Stanford University34, University of North Carolina at Chapel Hill35, Osaka University36, University of Tokyo37, York University38
TL;DR: Trans-ethnic genome-wide meta-analyses for eGFR in 312,468 individuals are performed and novel loci and downstream putative causal genes are identified, offering insight into clinical outcomes and routes to CKD treatment development.
Abstract: Chronic kidney disease (CKD) affects ~10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assemble genome-wide association studies of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals of diverse ancestry. We identify 127 distinct association signals with homogeneous effects on eGFR across ancestries and enrichment in genomic annotations including kidney-specific histone modifications. Fine-mapping reveals 40 high-confidence variants driving eGFR associations and highlights putative causal genes with cell-type specific expression in glomerulus, and in proximal and distal nephron. Mendelian randomisation supports causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure and hypertension. These results define novel molecular mechanisms and putative causal genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.
111 citations
TL;DR: Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior, including nonsynonymous/loss-of-function coding variants.
60 citations
Radboud University Nijmegen1, University of Amsterdam2, QIMR Berghofer Medical Research Institute3, VU University Amsterdam4, University of California, San Diego5, University of Bristol6, University of Cambridge7, University of Chicago8, Vanderbilt University9, St. Joseph's Healthcare Hamilton10, University of Illinois at Urbana–Champaign11, Utrecht University12, University Medical Center Groningen13, Washington University in St. Louis14, University of Tartu15, University of Queensland16, Hospital for Sick Children17, University of Toronto18, Carlos III Health Institute19, Autonomous University of Barcelona20, University of Helsinki21, King's College London22, Yale University23, Virginia Commonwealth University24
TL;DR: Several occurrences of the word "schizophrenia" have been re-worded as "liability to schizophrenia" or "Schizophrenia risk", including in the title, which should have been "GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability" as mentioned in this paper.
Abstract: Several occurrences of the word 'schizophrenia' have been re-worded as 'liability to schizophrenia' or 'schizophrenia risk', including in the title, which should have been "GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability," as well as in Supplementary Figures 1-10 and Supplementary Tables 7-10, to more accurately reflect the findings of the work.
17 citations
TL;DR: The current genome-wide association meta-analysis (GWAMA) of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.
Abstract: Background Human aggressive behavior (AGG) has a substantial genetic component. Here we present a large genome-wide association meta-analysis (GWAMA) of childhood AGG. Methods We 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. Results Heritability 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. Conclusions The 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.
14 citations
Melissa A. Munn-Chernoff1, Emma C. Johnson2, Yi-Ling Chou2, Jonathan R. I. Coleman3 +406 more•Institutions (135)
TL;DR: The genetic correlation between AUD and AN was no longer significant after co-varying for MDD loci, and the patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and Substance-specific relationships between these behaviors.
Abstract: Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa (BN) and problem alcohol use (genetic correlation [rg], twin-based=0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge-eating, AN without binge-eating, and a BN factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder (MDD). Total sample sizes per phenotype ranged from ~2,400 to ~537,000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg=0.18; false discovery rate q=0.0006), cannabis initiation and AN (rg=0.23; q<0.0001), and cannabis initiation and AN with binge-eating (rg=0.27; q=0.0016). Conversely, significant negative genetic correlations were observed between three non-diagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge-eating (rgs=-0.19 to -0.23; qs<0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for MDD loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships between these behaviors.
14 citations