Polygenic profiles define aspects of clinical heterogeneity in ADHD

Attention deficit hyperactivity disorder (ADHD) is a complex disorder with heterogeneous clinical presentations that manifest variability in long-term outcomes. The genetic contributions to this clinical heterogeneity, however, are not well understood. Here, we study 14 084 individuals diagnosed with ADHD to identify several genetic factors underlying clinical heterogeneity. One genome-wide significant locus was specifically associated with an autism spectrum disorder (ASD) diagnosis among individuals diagnosed with ADHD and it was not previously associated with ASD nor ADHD, individually. We used a novel approach to compare profiles of polygenic scores for groups of individuals diagnosed with ADHD and uncovered robust evidence that biology is an important factor in on-going clinical debates. Specifically, individuals diagnosed with ASD and ADHD, substance use disorder (SUD) and ADHD, or first diagnosed with ADHD in adulthood had different profiles of polygenic scores for ADHD and multiple other psychiatric, cognitive, and socio-behavioral traits. A polygene overlap between an ASD diagnosis in ADHD and cognitive performance was replicated in an independent, typically developing cohort. Our unique approach uncovered evidence of genetic heterogeneity in a widely studied complex disorder, allowing for timely contributions to the understanding of ADHD etiology and providing a model for similar studies of other disorders.

[1]  P. Visscher,et al.  From Basic Science to Clinical Application of Polygenic Risk Scores: A Primer. , 2020, JAMA psychiatry.

[2]  N. Zaitlen,et al.  Genetic Influences on Disease Subtypes. , 2020, Annual review of genomics and human genetics.

[3]  K. D. Jakobsen,et al.  Copy Number Variants and Polygenic Risk Scores Predict Need of Care in Autism and/or ADHD Families , 2020, Journal of Autism and Developmental Disorders.

[4]  P. Bolton,et al.  Guidance for identification and treatment of individuals with attention deficit/hyperactivity disorder and autism spectrum disorder based upon expert consensus , 2020, BMC Medicine.

[5]  E. Vassos,et al.  Polygenic risk scores: from research tools to clinical instruments , 2020, Genome Medicine.

[6]  J. Potash,et al.  Minimal phenotyping yields genome-wide association signals of low specificity for major depression , 2020, Nature Genetics.

[7]  N. Wray,et al.  Association of Mental Disorder in Childhood and Adolescence With Subsequent Educational Achievement. , 2020, JAMA psychiatry.

[8]  K. Kendler,et al.  The impact on estimations of genetic correlations by the use of super‐normal, unscreened, and family‐history screened controls in genome wide case–control studies , 2020, Genetic epidemiology.

[9]  T. Werge,et al.  Genetic liability to ADHD and substance use disorders in individuals with ADHD. , 2019, Addiction.

[10]  N. Wray,et al.  Genetic correlations of polygenic disease traits: from theory to practice , 2019, Nature Reviews Genetics.

[11]  Jakob Grove,et al.  Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have a similar burden of rare protein-truncating variants , 2019, Nature Neuroscience.

[12]  C. Hartl,et al.  Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms , 2019, Cell.

[13]  T. Stafford,et al.  Co-Occurrence of ASD and ADHD Traits in an Adult Population , 2019, Journal of attention disorders.

[14]  D. Posthuma,et al.  Psychiatric Polygenic Risk Scores as Predictor for Attention Deficit/Hyperactivity Disorder and Autism Spectrum Disorder in a Clinical Child and Adolescent Sample , 2019, Behavior Genetics.

[15]  A. Dale,et al.  Gene-experience correlation during cognitive development: Evidence from the Adolescent Brain Cognitive Development (ABCD) StudySM , 2019, bioRxiv.

[16]  M. S. Artigas,et al.  Shared genetic background between children and adults with attention deficit/hyperactivity disorder , 2019, bioRxiv.

[17]  P. Asherson,et al.  Annual Research Review: Does late-onset attention-deficit/hyperactivity disorder exist? , 2019, Journal of child psychology and psychiatry, and allied disciplines.

[18]  D. Geschwind,et al.  Defining the Genetic, Genomic, Cellular, and Diagnostic Architectures of Psychiatric Disorders , 2019, Cell.

[19]  Brian K. Lee,et al.  Exploring Comorbidity Within Mental Disorders Among a Danish National Population , 2019, JAMA psychiatry.

[20]  John P. Rice,et al.  Identification of common genetic risk variants for autism spectrum disorder , 2019, Nature Genetics.

[21]  J. Halperin,et al.  A Review of Heterogeneity in Attention Deficit/Hyperactivity Disorder (ADHD) , 2019, Front. Hum. Neurosci..

[22]  N. Wray,et al.  A genome-wide association study of shared risk across psychiatric disorders implicates gene regulation during fetal neurodevelopment , 2019, Nature Neuroscience.

[23]  Hunna J. Watson,et al.  Genome wide meta-analysis identifies genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders , 2019, bioRxiv.

[24]  Dajiang J. Liu,et al.  Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci , 2019, Molecular Psychiatry.

[25]  O. Andreassen,et al.  A global overview of pleiotropy and genetic architecture in complex traits , 2019, Nature Genetics.

[26]  Prashant S. Emani,et al.  Comprehensive functional genomic resource and integrative model for the human brain , 2018, Science.

[27]  Alicia R. Martin,et al.  Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder , 2018, Nature Genetics.

[28]  B. Franke,et al.  Live fast, die young? A review on the developmental trajectories of ADHD across the lifespan , 2018, European Neuropsychopharmacology.

[29]  Annie W Shieh,et al.  Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia , 2018, Nature Communications.

[30]  M. Daly,et al.  Prevalence of rearrangements in the 22q11.2 region and population-based risk of neuropsychiatric and developmental disorders in a Danish population: a case-cohort study. , 2018, The lancet. Psychiatry.

[31]  R. Marioni,et al.  Misestimation of heritability and prediction accuracy of male-pattern baldness , 2018, Nature Communications.

[32]  S. Faraone,et al.  Genetics of attention deficit hyperactivity disorder , 2018, Molecular Psychiatry.

[33]  K. D. Jakobsen,et al.  Brief Report: Clusters and Trajectories Across the Autism and/or ADHD Spectrum , 2018, Journal of autism and developmental disorders.

[34]  D. Geschwind,et al.  The Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis , 2018, Cell.

[35]  D. Posthuma,et al.  Functional mapping and annotation of genetic associations with FUMA , 2017, Nature Communications.

[36]  Terry L. Jernigan,et al.  Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description , 2017, Developmental Cognitive Neuroscience.

[37]  Michael P. Milham,et al.  Association of White Matter Structure With Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder , 2017, JAMA psychiatry.

[38]  Jonathan Sidi,et al.  heatmaply: an R package for creating interactive cluster heatmaps for online publishing , 2017, Bioinform..

[39]  N. Volkow,et al.  The conception of the ABCD study: From substance use to a broad NIH collaboration , 2017, Developmental Cognitive Neuroscience.

[40]  John P. Rice,et al.  Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes , 2017, Cell.

[41]  Alicia R. Martin,et al.  A Genetic Investigation of Sex Bias in the Prevalence of Attention-Deficit/Hyperactivity Disorder , 2017, Biological Psychiatry.

[42]  M. Daly,et al.  The iPSYCH2012 case–cohort sample: new directions for unravelling genetic and environmental architectures of severe mental disorders , 2017, Molecular Psychiatry.

[43]  Robert Plomin,et al.  Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence , 2017, Nature Genetics.

[44]  B. Franke,et al.  The familial co-aggregation of ASD and ADHD: a register-based cohort study , 2017, Molecular Psychiatry.

[45]  Evan Z. Macosko,et al.  Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types , 2017, Nature Genetics.

[46]  N. Craddock,et al.  Evidence for genetic heterogeneity between clinical subtypes of bipolar disorder , 2017, Translational Psychiatry.

[47]  J. Todd,et al.  A method for identifying genetic heterogeneity within phenotypically-defined disease subgroups , 2016, Nature Genetics.

[48]  N. Eriksson,et al.  Genome-wide analysis identifies 12 loci influencing human reproductive behavior , 2016 .

[49]  Alexander Gusev,et al.  Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights , 2016, Nature Genetics.

[50]  S. Faraone,et al.  Can Attention-Deficit/Hyperactivity Disorder Onset Occur in Adulthood? , 2016, JAMA psychiatry.

[51]  L. Wain,et al.  Haplotype estimation for biobank scale datasets , 2016, Nature Genetics.

[52]  Tom R. Gaunt,et al.  LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis , 2016, bioRxiv.

[53]  Jonathan P. Beauchamp,et al.  Genome-wide association study identifies 74 loci associated with educational attainment , 2016, Nature.

[54]  Luigi Ferrucci,et al.  Human longevity is influenced by many genetic variants: evidence from 75,000 UK Biobank participants , 2016, bioRxiv.

[55]  Jonathan P. Beauchamp,et al.  Genetic Associations with Subjective Well-Being Also Implicate Depression and Neuroticism , 2015, bioRxiv.

[56]  Mitchell J. Machiela,et al.  LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants , 2015, Bioinform..

[57]  P. Visscher,et al.  Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores , 2015, bioRxiv.

[58]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[59]  Andrew D. Johnson,et al.  Nature Genetics Advance Online Publication Large-scale Genomic Analyses Link Reproductive Aging to Hypothalamic Signaling, Breast Cancer Susceptibility and Brca1-mediated Dna Repair , 2022 .

[60]  T. Südhof,et al.  RIM-BPs Mediate Tight Coupling of Action Potentials to Ca2+-Triggered Neurotransmitter Release , 2015, Neuron.

[61]  T. Lehtimäki,et al.  Integrative approaches for large-scale transcriptome-wide association studies , 2015, Nature Genetics.

[62]  D. Daley,et al.  Costing Adult Attention Deficit Hyperactivity Disorder: Impact on the Individual and Society , 2015 .

[63]  F. Rijsdijk,et al.  The Genetic Overlap of Attention-Deficit/Hyperactivity Disorder and Autistic-like Traits: an Investigation of Individual Symptom Scales and Cognitive markers , 2015, Journal of abnormal child psychology.

[64]  S. Dalsgaard,et al.  Mortality in children, adolescents, and adults with attention deficit hyperactivity disorder: a nationwide cohort study , 2015, The Lancet.

[65]  Jack Euesden,et al.  PRSice: Polygenic Risk Score software , 2014, Bioinform..

[66]  C. Spencer,et al.  Biological Insights From 108 Schizophrenia-Associated Genetic Loci , 2014, Nature.

[67]  S. Scherer,et al.  Biological Overlap of Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder: Evidence From Copy Number Variants , 2014, Journal of the American Academy of Child and Adolescent Psychiatry.

[68]  M. Stephens,et al.  fastSTRUCTURE: Variational Inference of Population Structure in Large SNP Data Sets , 2014, Genetics.

[69]  M. Daly,et al.  LD Score regression distinguishes confounding from polygenicity in genome-wide association studies , 2014, Nature Genetics.

[70]  P. Visscher,et al.  Childhood intelligence is heritable, highly polygenic and associated with FNBP1L , 2014, Molecular Psychiatry.

[71]  Jonathan P. Beauchamp,et al.  GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment , 2013, Science.

[72]  Ceri H. Davies,et al.  Neurodevelopmental disorders , 2013, Neuropharmacology.

[73]  Ellen T. Gelfand,et al.  The Genotype-Tissue Expression (GTEx) project , 2013, Nature Genetics.

[74]  N. Wray,et al.  A mega-analysis of genome-wide association studies for major depressive disorder , 2013, Molecular Psychiatry.

[75]  Preben Bo Mortensen,et al.  Long-term criminal outcome of children with attention deficit hyperactivity disorder. , 2013, Criminal behaviour and mental health : CBMH.

[76]  D. Altshuler,et al.  Informed Conditioning on Clinical Covariates Increases Power in Case-Control Association Studies , 2012, PLoS genetics.

[77]  N. Wray,et al.  Impact of diagnostic misclassification on estimation of genetic correlations using genome-wide genotypes , 2012, European Journal of Human Genetics.

[78]  O. Mors,et al.  The Danish Psychiatric Central Research Register , 2011, Scandinavian journal of public health.

[79]  J. Hallas,et al.  The Danish National Prescription Registry , 2011, Scandinavian journal of public health.

[80]  C. Pedersen,et al.  The Danish Civil Registration System , 2011, Scandinavian journal of public health.

[81]  Elsebeth Lynge,et al.  The Danish National Patient Register , 2011, Scandinavian journal of public health.

[82]  V. Savalei What to Do About Zero Frequency Cells When Estimating Polychoric Correlations , 2011 .

[83]  P. Visscher,et al.  GCTA: a tool for genome-wide complex trait analysis. , 2011, American journal of human genetics.

[84]  Josyf Mychaleckyj,et al.  Robust relationship inference in genome-wide association studies , 2010, Bioinform..

[85]  H. Stefánsson,et al.  Supplementary webappendix , 2018 .

[86]  Susanne Walitza,et al.  Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder. , 2010, Journal of the American Academy of Child and Adolescent Psychiatry.

[87]  H. Hakonarson,et al.  ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data , 2010, Nucleic acids research.

[88]  M. King,et al.  Genetic Heterogeneity in Human Disease , 2010, Cell.

[89]  Jan K. Buitelaar,et al.  Shared heritability of attention-deficit/hyperactivity disorder and autism spectrum disorder , 2010, European Child & Adolescent Psychiatry.

[90]  M. McCarthy,et al.  A Powerful Approach to Sub-Phenotype Analysis in Population-Based Genetic Association Studies , 2009, Genetic epidemiology.

[91]  Esben Agerbo,et al.  Bipolar disorder, schizoaffective disorder, and schizophrenia overlap: a new comorbidity index. , 2009, The Journal of clinical psychiatry.

[92]  John A. Sweeney,et al.  Genome-Wide Analyses of Exonic Copy Number Variants in a Family-Based Study Point to Novel Autism Susceptibility Genes , 2009, PLoS genetics.

[93]  P. Donnelly,et al.  A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies , 2009, PLoS genetics.

[94]  S. Schoch,et al.  Structure and evolution of RIM-BP genes: identification of a novel family member. , 2007, Gene.

[95]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[96]  D. Hougaard,et al.  Storage policies and use of the Danish Newborn Screening Biobank , 2007, Journal of Inherited Metabolic Disease.

[97]  D. Reich,et al.  Population Structure and Eigenanalysis , 2006, PLoS genetics.

[98]  A. Fanous,et al.  Genetic heterogeneity, modifier genes, and quantitative phenotypes in psychiatric illness: searching for a framework , 2006, Molecular Psychiatry.

[99]  A. Hudspeth,et al.  RIM Binding Proteins (RBPs) Couple Rab3-Interacting Molecules (RIMs) to Voltage-Gated Ca2+ Channels , 2002, Neuron.

[100]  Joseph H. Nadeau,et al.  Modifier genes in mice and humans , 2001, Nature Reviews Genetics.

[101]  Gerome Breen,et al.  Psychiatric Genomics: An Update and an Agenda , 2017, bioRxiv.

[102]  Christopher S. Poultney,et al.  Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia , 2017, Molecular Autism.