Attention-deficit/hyperactivity disorder polygenic risk scores predict attention problems in a population-based sample of children

Clinically, attention-deficit/hyperactivity disorder (ADHD) is characterized by hyperactivity, impulsivity, and inattention and is among the most common childhood disorders. These same traits that define ADHD are variable in the general population, and the clinical diagnosis may represent the extrem...

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Vydáno v:Journal of the American Academy of Child and Adolescent Psychiatry Ročník 53; číslo 10; s. 1123
Hlavní autoři: Groen-Blokhuis, Maria M, Middeldorp, Christel M, Kan, Kees-Jan, Abdellaoui, Abdel, van Beijsterveldt, Catharina E M, Ehli, Erik A, Davies, Gareth E, Scheet, Paul A, Xiao, Xiangjun, Hudziak, James J, Hottenga, Jouke-Jan, Neale, Ben M, Boomsma, Dorret I
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States 01.10.2014
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ISSN:1527-5418, 1527-5418
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Abstract Clinically, attention-deficit/hyperactivity disorder (ADHD) is characterized by hyperactivity, impulsivity, and inattention and is among the most common childhood disorders. These same traits that define ADHD are variable in the general population, and the clinical diagnosis may represent the extreme end of a continuous distribution of inattentive and hyperactive behaviors. This hypothesis can be tested by assessing the predictive value of polygenic risk scores derived from a discovery sample of ADHD patients in a target sample from the general population with continuous scores of inattention and hyperactivity. In addition, the genetic overlap between ADHD and continuous ADHD scores can be tested across rater and age. The Psychiatric Genomics Consortium has performed the largest genome-wide analysis (GWA) study of ADHD so far, including 5,621 clinical patients and 13,589 controls. The effects sizes of single nucleotide polymorphisms (SNPs) estimated in this meta-analysis were used to obtain individual polygenic risk scores in an independent population-based cohort of 2,437 children from the Netherlands Twin Register. The variance explained in Attention Problems (AP) scale scores by the polygenic risk scores was estimated by linear mixed modeling. The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool- and school-aged children. These results indicate genetic overlap between a diagnosis of ADHD and AP scale scores across raters and age groups and provides evidence for a dimensional model of ADHD. Future GWA studies on ADHD can likely benefit from the inclusion of population-based cohorts and the analysis of continuous scores.
AbstractList Clinically, attention-deficit/hyperactivity disorder (ADHD) is characterized by hyperactivity, impulsivity, and inattention and is among the most common childhood disorders. These same traits that define ADHD are variable in the general population, and the clinical diagnosis may represent the extreme end of a continuous distribution of inattentive and hyperactive behaviors. This hypothesis can be tested by assessing the predictive value of polygenic risk scores derived from a discovery sample of ADHD patients in a target sample from the general population with continuous scores of inattention and hyperactivity. In addition, the genetic overlap between ADHD and continuous ADHD scores can be tested across rater and age. The Psychiatric Genomics Consortium has performed the largest genome-wide analysis (GWA) study of ADHD so far, including 5,621 clinical patients and 13,589 controls. The effects sizes of single nucleotide polymorphisms (SNPs) estimated in this meta-analysis were used to obtain individual polygenic risk scores in an independent population-based cohort of 2,437 children from the Netherlands Twin Register. The variance explained in Attention Problems (AP) scale scores by the polygenic risk scores was estimated by linear mixed modeling. The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool- and school-aged children. These results indicate genetic overlap between a diagnosis of ADHD and AP scale scores across raters and age groups and provides evidence for a dimensional model of ADHD. Future GWA studies on ADHD can likely benefit from the inclusion of population-based cohorts and the analysis of continuous scores.
Clinically, attention-deficit/hyperactivity disorder (ADHD) is characterized by hyperactivity, impulsivity, and inattention and is among the most common childhood disorders. These same traits that define ADHD are variable in the general population, and the clinical diagnosis may represent the extreme end of a continuous distribution of inattentive and hyperactive behaviors. This hypothesis can be tested by assessing the predictive value of polygenic risk scores derived from a discovery sample of ADHD patients in a target sample from the general population with continuous scores of inattention and hyperactivity. In addition, the genetic overlap between ADHD and continuous ADHD scores can be tested across rater and age.OBJECTIVEClinically, attention-deficit/hyperactivity disorder (ADHD) is characterized by hyperactivity, impulsivity, and inattention and is among the most common childhood disorders. These same traits that define ADHD are variable in the general population, and the clinical diagnosis may represent the extreme end of a continuous distribution of inattentive and hyperactive behaviors. This hypothesis can be tested by assessing the predictive value of polygenic risk scores derived from a discovery sample of ADHD patients in a target sample from the general population with continuous scores of inattention and hyperactivity. In addition, the genetic overlap between ADHD and continuous ADHD scores can be tested across rater and age.The Psychiatric Genomics Consortium has performed the largest genome-wide analysis (GWA) study of ADHD so far, including 5,621 clinical patients and 13,589 controls. The effects sizes of single nucleotide polymorphisms (SNPs) estimated in this meta-analysis were used to obtain individual polygenic risk scores in an independent population-based cohort of 2,437 children from the Netherlands Twin Register. The variance explained in Attention Problems (AP) scale scores by the polygenic risk scores was estimated by linear mixed modeling.METHODThe Psychiatric Genomics Consortium has performed the largest genome-wide analysis (GWA) study of ADHD so far, including 5,621 clinical patients and 13,589 controls. The effects sizes of single nucleotide polymorphisms (SNPs) estimated in this meta-analysis were used to obtain individual polygenic risk scores in an independent population-based cohort of 2,437 children from the Netherlands Twin Register. The variance explained in Attention Problems (AP) scale scores by the polygenic risk scores was estimated by linear mixed modeling.The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool- and school-aged children.RESULTSThe ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool- and school-aged children.These results indicate genetic overlap between a diagnosis of ADHD and AP scale scores across raters and age groups and provides evidence for a dimensional model of ADHD. Future GWA studies on ADHD can likely benefit from the inclusion of population-based cohorts and the analysis of continuous scores.CONCLUSIONThese results indicate genetic overlap between a diagnosis of ADHD and AP scale scores across raters and age groups and provides evidence for a dimensional model of ADHD. Future GWA studies on ADHD can likely benefit from the inclusion of population-based cohorts and the analysis of continuous scores.
Author Davies, Gareth E
Middeldorp, Christel M
Boomsma, Dorret I
Neale, Ben M
van Beijsterveldt, Catharina E M
Hottenga, Jouke-Jan
Abdellaoui, Abdel
Kan, Kees-Jan
Ehli, Erik A
Hudziak, James J
Groen-Blokhuis, Maria M
Xiao, Xiangjun
Scheet, Paul A
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  organization: VU University Amsterdam, the Netherlands
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  organization: VU University Amsterdam, the Netherlands; Neuroscience Campus Amsterdam, VU University Amsterdam
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  organization: Avera Institute for Human Genetics, Sioux Falls, SD
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  organization: University of Texas M. D. Anderson Cancer Center, Houston
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  surname: Xiao
  fullname: Xiao, Xiangjun
  organization: Dartmouth Medical School, Hanover, NH
– sequence: 10
  givenname: James J
  surname: Hudziak
  fullname: Hudziak, James J
  organization: Vermont Center for Children, Youth, and Families and University of Vermont College of Medicine, Burlington, VT
– sequence: 11
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  surname: Neale
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  organization: Massachusetts General Hospital and Harvard Medical School, Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
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  givenname: Dorret I
  surname: Boomsma
  fullname: Boomsma, Dorret I
  email: dorret@psy.vu.nl
  organization: EMGO+ Institute for Health and Care Research, VU University Medical Center, Amsterdam; Neuroscience Campus Amsterdam, VU University Amsterdam. Electronic address: dorret@psy.vu.nl
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Keywords ADHD
genetics
dimensional models
attention problems
polygenic scores
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SubjectTerms Attention Deficit Disorder with Hyperactivity - epidemiology
Attention Deficit Disorder with Hyperactivity - genetics
Child
Child, Preschool
Female
Genome-Wide Association Study - statistics & numerical data
Humans
Male
Multifactorial Inheritance - genetics
Netherlands - epidemiology
Polymorphism, Single Nucleotide
Registries - statistics & numerical data
Risk Assessment
Title Attention-deficit/hyperactivity disorder polygenic risk scores predict attention problems in a population-based sample of children
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