Attention-Deficit/Hyperactivity Disorder Polygenic Risk Scores Predict Attention Problems in a Population-Based Sample of Children

Objective 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...

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Veröffentlicht in:Journal of the American Academy of Child and Adolescent Psychiatry 2014-10, Vol.53 (10), p.1123-1129.e6
Hauptverfasser: Groen-Blokhuis, Maria M., MD, PhD, Middeldorp, Christel M., MD, PhD, Kan, Kees-Jan, PhD, Abdellaoui, Abdel, MSc, van Beijsterveldt, Catharina E.M., PhD, Ehli, Erik A., PhD, Davies, Gareth E., PhD, Scheet, Paul A., PhD, Xiao, Xiangjun, MSc, Hudziak, James J., MD, Hottenga, Jouke-Jan, PhD, Neale, Ben M., PhD, Boomsma, Dorret I., PhD
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container_end_page 1129.e6
container_issue 10
container_start_page 1123
container_title Journal of the American Academy of Child and Adolescent Psychiatry
container_volume 53
creator Groen-Blokhuis, Maria M., MD, PhD
Middeldorp, Christel M., MD, PhD
Kan, Kees-Jan, PhD
Abdellaoui, Abdel, MSc
van Beijsterveldt, Catharina E.M., PhD
Ehli, Erik A., PhD
Davies, Gareth E., PhD
Scheet, Paul A., PhD
Xiao, Xiangjun, MSc
Hudziak, James J., MD
Hottenga, Jouke-Jan, PhD
Neale, Ben M., PhD
Boomsma, Dorret I., PhD
description Objective 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. Method 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. Results The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool- and school-aged children. Conclusion 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.
doi_str_mv 10.1016/j.jaac.2014.06.014
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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. Method 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. Results The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool- and school-aged children. Conclusion 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.</description><identifier>ISSN: 0890-8567</identifier><identifier>EISSN: 1527-5418</identifier><identifier>DOI: 10.1016/j.jaac.2014.06.014</identifier><identifier>PMID: 25245356</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>ADHD ; Attention Deficit Disorder with Hyperactivity - epidemiology ; Attention Deficit Disorder with Hyperactivity - genetics ; attention problems ; Child ; Child, Preschool ; dimensional models ; Female ; genetics ; Genome-Wide Association Study - statistics &amp; numerical data ; Humans ; Male ; Multifactorial Inheritance - genetics ; Netherlands - epidemiology ; Pediatrics ; polygenic scores ; Polymorphism, Single Nucleotide ; Psychiatry ; Registries - statistics &amp; numerical data ; Risk Assessment</subject><ispartof>Journal of the American Academy of Child and Adolescent Psychiatry, 2014-10, Vol.53 (10), p.1123-1129.e6</ispartof><rights>American Academy of Child and Adolescent Psychiatry</rights><rights>2014 American Academy of Child and Adolescent Psychiatry</rights><rights>Copyright © 2014 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c477t-45d489cedd3db9510ceed36ca35e37ab0c4a54d621bd0167952671f5ac569da63</citedby><cites>FETCH-LOGICAL-c477t-45d489cedd3db9510ceed36ca35e37ab0c4a54d621bd0167952671f5ac569da63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jaac.2014.06.014$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,777,781,3537,27905,27906,45976</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25245356$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Groen-Blokhuis, Maria M., MD, PhD</creatorcontrib><creatorcontrib>Middeldorp, Christel M., MD, PhD</creatorcontrib><creatorcontrib>Kan, Kees-Jan, PhD</creatorcontrib><creatorcontrib>Abdellaoui, Abdel, MSc</creatorcontrib><creatorcontrib>van Beijsterveldt, Catharina E.M., PhD</creatorcontrib><creatorcontrib>Ehli, Erik A., PhD</creatorcontrib><creatorcontrib>Davies, Gareth E., PhD</creatorcontrib><creatorcontrib>Scheet, Paul A., PhD</creatorcontrib><creatorcontrib>Xiao, Xiangjun, MSc</creatorcontrib><creatorcontrib>Hudziak, James J., MD</creatorcontrib><creatorcontrib>Hottenga, Jouke-Jan, PhD</creatorcontrib><creatorcontrib>Neale, Ben M., PhD</creatorcontrib><creatorcontrib>Boomsma, Dorret I., PhD</creatorcontrib><creatorcontrib>Psychiatric Genomics Consortium ADHD Working Group</creatorcontrib><title>Attention-Deficit/Hyperactivity Disorder Polygenic Risk Scores Predict Attention Problems in a Population-Based Sample of Children</title><title>Journal of the American Academy of Child and Adolescent Psychiatry</title><addtitle>J Am Acad Child Adolesc Psychiatry</addtitle><description>Objective 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. Method 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. Results The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool- and school-aged children. Conclusion 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. 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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. Method 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. Results The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool- and school-aged children. Conclusion 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.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>25245356</pmid><doi>10.1016/j.jaac.2014.06.014</doi></addata></record>
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subjects ADHD
Attention Deficit Disorder with Hyperactivity - epidemiology
Attention Deficit Disorder with Hyperactivity - genetics
attention problems
Child
Child, Preschool
dimensional models
Female
genetics
Genome-Wide Association Study - statistics & numerical data
Humans
Male
Multifactorial Inheritance - genetics
Netherlands - epidemiology
Pediatrics
polygenic scores
Polymorphism, Single Nucleotide
Psychiatry
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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