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Duan K, Chen J, Calhoun VD, Jiang W, Rootes-Murdy K, Schoenmacker G, Silva RF, Franke B, Buitelaar JK, Hoogman M, Oosterlaan J, Hoekstra PJ, Heslenfeld D, Hartman CA, Sprooten E, Arias-Vasquez A, Turner JA, Liu J. Genomic patterns linked to gray matter alterations underlying working memory deficits in adults and adolescents with attention-deficit/hyperactivity disorder. Transl Psychiatry 2023; 13:50. [PMID: 36774336 PMCID: PMC9922257 DOI: 10.1038/s41398-023-02349-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 01/26/2023] [Accepted: 01/31/2023] [Indexed: 02/13/2023] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder, with onset in childhood and a considerable likelihood to persist into adulthood. Our previous work has identified that across adults and adolescents with ADHD, gray matter volume (GMV) alteration in the frontal cortex was consistently associated with working memory underperformance, and GMV alteration in the cerebellum was associated with inattention. Recent knowledge regarding ADHD genetic risk loci makes it feasible to investigate genomic factors underlying these persistent GMV alterations, potentially illuminating the pathology of ADHD persistence. Based on this, we applied a sparsity-constrained multivariate data fusion approach, sparse parallel independent component analysis, to GMV variations in the frontal and cerebellum regions and candidate risk single nucleotide polymorphisms (SNPs) data from 341 unrelated adult participants, including 167 individuals with ADHD, 47 unaffected siblings, and 127 healthy controls. We identified one SNP component significantly associated with one GMV component in superior/middle frontal regions and replicated this association in 317 adolescents from ADHD families. The association was stronger in individuals with ADHD than in controls, and stronger in adults and older adolescents than in younger ones. The SNP component highlights 93 SNPs in long non-coding RNAs mainly in chromosome 5 and 21 protein-coding genes that are significantly enriched in human neuron cells. Eighteen identified SNPs have regulation effects on gene expression, transcript expression, isoform percentage, or methylation level in frontal regions. Identified genes highlight MEF2C, CADM2, and CADPS2, which are relevant for modulating neuronal substrates underlying high-level cognition in ADHD, and their causality effects on ADHD persistence await further investigations. Overall, through a multivariate analysis, we have revealed a genomic pattern underpinning the frontal gray matter variation related to working memory deficit in ADHD.
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Affiliation(s)
- Kuaikuai Duan
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - Jiayu Chen
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Vince D Calhoun
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Wenhao Jiang
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | | | - Gido Schoenmacker
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Rogers F Silva
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Martine Hoogman
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jaap Oosterlaan
- Department of Clinical Neuropsychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Pieter J Hoekstra
- Department of Child and Adolescent Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Dirk Heslenfeld
- Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, University of Groningen, Groningen, The Netherlands
| | - Emma Sprooten
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Alejandro Arias-Vasquez
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jessica A Turner
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Jingyu Liu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA.
- Department of Computer Science, Georgia State University, Atlanta, GA, USA.
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Green A, Baroud E, DiSalvo M, Faraone SV, Biederman J. Examining the impact of ADHD polygenic risk scores on ADHD and associated outcomes: A systematic review and meta-analysis. J Psychiatr Res 2022; 155:49-67. [PMID: 35988304 DOI: 10.1016/j.jpsychires.2022.07.032] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 07/12/2022] [Accepted: 07/18/2022] [Indexed: 11/29/2022]
Abstract
Early identification of attention-deficit/hyperactivity disorder (ADHD) is critical for mitigating the many negative functional outcomes associated with its diagnosis. Because of the strong genetic basis of ADHD, the use of polygenic risk scores (PRS) could potentially aid in the early identification of ADHD and associated outcomes. Therefore, a systematic search of the literature on the association between ADHD and PRS in pediatric populations was conducted. All articles were screened for a priori inclusion and exclusion criteria, and, after careful review, 33 studies were included in our systematic review and 16 studies with extractable data were included in our meta-analysis. The results of the review were categorized into three common themes: the associations between ADHD-PRS with 1) the diagnosis of ADHD and ADHD symptoms 2) comorbid psychopathology and 3) cognitive and educational outcomes. Higher ADHD-PRS were associated with increased odds of having a diagnosis (OR = 1.37; p<0.001) and more symptoms of ADHD (β = 0.06; p<0.001). While ADHD-PRS were associated with a persistent diagnostic trajectory over time in the systematic review, the meta-analysis did not confirm these findings (OR = 1.09; p = 0.62). Findings showed that ADHD-PRS were associated with increased odds for comorbid psychopathology such as anxiety/depression (OR = 1.16; p<0.001) and irritability/emotional dysregulation (OR = 1.14; p<0.001). Finally, while the systematic review showed that ADHD-PRS were associated with a variety of negative cognitive outcomes, the meta-analysis showed no significant association (β = 0.08; p = 0.07). Our review of the available literature suggests that ADHD-PRS, together with risk factors, may contribute to the early identification of children with suspected ADHD and associated disorders.
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Affiliation(s)
- Allison Green
- Clinical and Research Programs in Pediatric Psychopharmacology and Adult ADHD, Massachusetts General Hospital, Boston, MA, USA; Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Evelyne Baroud
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Massachusetts General Hospital and McLean Hospital, Harvard Medical School, Boston, MA, United States
| | - Maura DiSalvo
- Clinical and Research Programs in Pediatric Psychopharmacology and Adult ADHD, Massachusetts General Hospital, Boston, MA, USA
| | | | - Joseph Biederman
- Clinical and Research Programs in Pediatric Psychopharmacology and Adult ADHD, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
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