Predicting the course of ADHD symptoms through the integration of childhood genomic, neural, and cognitive features

0
7

  • 1.

    Sibley MH, Mitchell JT, Becker SP. Method of adult diagnosis influences estimated persistence of childhood ADHD: a systematic review of longitudinal studies. Lancet Psychiatry. 2016;3:1157–65.

    Article 

    Google Scholar
     

  • 2.

    Faraone SV, Biederman J, Mick E. The age-dependent decline of attention deficit hyperactivity disorder: a meta-analysis of follow-up studies. Psychol Med. 2006;36:159–65.

    Article 

    Google Scholar
     

  • 3.

    Caye A, Spadini AV, Karam RG, Grevet EH, Rovaris DL, Bau CH, et al. Predictors of persistence of ADHD into adulthood: a systematic review of the literature and meta-analysis. Eur Child Adolesc Psychiatry. 2016;25:1151–9.

    Article 

    Google Scholar
     

  • 4.

    Demontis D, Walters RK, Martin J, Mattheisen M, Als TD, Agerbo E, et al. Discovery of the first genome-wide significant risk loci for ADHD. bioRxiv. 2017. https://doi.org/10.1101/145581.

  • 5.

    Wray NR, Goddard ME, Visscher PM. Prediction of individual genetic risk to disease from genome-wide. Genome Res. 2007;17:1520–8.

    CAS 
    Article 

    Google Scholar
     

  • 6.

    Pingault JB, Viding E, Galera C, Greven C, Zheng YRP, et al. Genetic and environmental influences on the developmental course of attention-deficit/hyperactivity disorder symptoms from childhood to adolescence. JAMA Psychiatry. 2015. https://doi.org/10.1001/jamapsychiatry.2015.0469T.

  • 7.

    Riglin L, Collishaw S, Thapar AK, Dalsgaard S, Langley K, Smith GD, et al. Association of genetic risk variants with attention-deficit/hyperactivity disorder trajectories in the general population. JAMA Psychiatry. 2016;73:1285–92.

    Article 

    Google Scholar
     

  • 8.

    Mackie S, Shaw P, Lenroot R, Pierson R, Greenstein DK, Nugent TF 3rd, et al. Cerebellar development and clinical outcome in attention deficit hyperactivity disorder. Am J Psychiatry. 2007;164:647–55.

    Article 

    Google Scholar
     

  • 9.

    Shaw P, Lerch J, Greenstein D, Sharp W, Clasen L, Evans A, et al. Longitudinal mapping of cortical thickness and clinical outcome in children and adolescents with attention deficit/hyperactivity disorder. Arch Gen Psychiatry. 2006;63:540–9.

    Article 

    Google Scholar
     

  • 10.

    Clarke AR, Barry RJ, Dupuy FE, McCarthy R, Selikowitz M, Heaven PC. Childhood EEG as a predictor of adult attention-deficit/hyperactivity disorder. Clin Neurophysiol. 2011;122:73–80.

    Article 

    Google Scholar
     

  • 11.

    Whitfield-Gabrieli S, Wendelken C, Nieto-Castañón A, Bailey SK, Anteraper SA, Lee YJ, et al. Association of intrinsic brain architecture with changes in attentional and mood symptoms during development. JAMA Psychiatry. 2020;77:378–86. https://doi.org/10.1001/jamapsychiatry.2019.4208.

    Article 
    PubMed 

    Google Scholar
     

  • 12.

    Martinussen R, Hayden J, Hogg-Johnson S, Tannock R. A meta-analysis of working memory impairments in children with attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2005;44:377–84.

    Article 

    Google Scholar
     

  • 13.

    Willcutt EG, Doyle AE, Nigg JT, Faraone SV, Pennington BF. Validity of the executive function theory of attention-deficit/hyperactivity disorder: a meta-analytic review. Biol Psychiatry. 2005;57:1336–46.

    Article 

    Google Scholar
     

  • 14.

    Cook NE, Braaten EB, Surman CB. Clinical and functional correlates of processing speed in pediatric attention-deficit/hyperactivity disorder: a systematic review and meta-analysis. Child Neuropsychol. 2018;24:598–616.

    Article 

    Google Scholar
     

  • 15.

    Reich W, Welner Z, Herkanic B. Diagnostic interview for children and adolescents (DICA-IV). North Tonawanda, NY: Multi-Health Systems; 1997.

  • 16.

    Euesden J, Lewis CM, O’Reilly PF. PRSice: polygenic risk score software. Bioinformatics. 2014;31:1466–8.

    Article 

    Google Scholar
     

  • 17.

    Demontis D, Walters RK, Martin J, Mattheisen M, Als TD, Agerbo E, et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat Genet. 2019;51:63–75. https://doi.org/10.1038/s41588-018-0269-7.

    CAS 
    Article 

    Google Scholar
     

  • 18.

    Fischl B. FreeSurfer. Neuroimage. 2012;62:774–81.

    Article 

    Google Scholar
     

  • 19.

    Shaw P, Ishii-Takahashi A, Park MT, Devenyi GA, Zibman C, Kasparek S, et al. A multicohort, longitudinal study of cerebellar development in attention deficit hyperactivity disorder. J Child Psychol Psychiatry. 2018;59:1114–23. https://doi.org/10.1111/jcpp.12920.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • 20.

    Hoogman M, Muetzel R, Guimaraes JP, Shumskaya E, Mennes M, Zwiers MP, et al. Brain imaging of the cortex in ADHD: a coordinated analysis of large-scale clinical and population-based samples. Am J Psychiatry. 2019;176:531–42.

    Article 

    Google Scholar
     

  • 21.

    Hoogman M, Buitelaar JK, Faraone SV, Shaw P, Franke B. Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults—authors’ reply. Lancet Psychiatry. 2017;4:440–1.

    Article 

    Google Scholar
     

  • 22.

    Rubia K. Cognitive neuroscience of attention deficit hyperactivity disorder (ADHD) and Its clinical translation. Front Hum Neurosci. 2018;12:100.

    Article 

    Google Scholar
     

  • 23.

    Hua K, Zhang J, Wakana S, Jiang H, Li X, Reich DS, et al. Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification. Neuroimage. 2008;39:336–47.

    Article 

    Google Scholar
     

  • 24.

    Wechsler, D. Wechsler abbreviated scale of intelligence, Second Edition (WASI-II). San Antonio, TX. NCS Pearson; 2011.

  • 25.

    Wechsler D. Wechsler preschool and primary scale of intelligence, Fourth edition. San Antonio, TX: Psychological Corporation; 2012.

  • 26.

    Wechsler, D. Wechsler Intelligence Scale for Children—Fourth Edition. San Antonio, TX. Psychological Corporation; 2003.

  • 27.

    Beery KE. Beery VMI: the Beery-Buktenica developmental test of visual-motor integration. Minneapolis, MN: Pearson; 2004.

  • 28.

    Woodcock RW, McGrew KS, Mather N. Woodcock-Johnson III: tests of achievement. Itasca, IL. Riverside Publishing Company; 2001.

  • 29.

    Hollingshead A. Four factor index of social status. New Haven: Yale University Department of Sociology; 1975.

  • 30.

    Rosnow RL, Rosenthal R. Computing contrasts, effect sizes, and counternulls on other people’s published data: General procedures for research consumers. Psychol Methods. 1996;1:331.

    Article 

    Google Scholar
     

  • 31.

    Hothorn T, Hornik K, Zeileis A. Unbiased recursive partitioning: a conditional inference framework. J Comput Graph Stat. 2006;15:651–74.

    Article 

    Google Scholar
     

  • 32.

    Vuijk PJ, Martin J, Braaten EB, Genovese G, Capawana MR, O’Keefe SM, et al. Translating Discoveries in Attention-Deficit/Hyperactivity Disorder Genomics to an Outpatient Child and Adolescent Psychiatric Cohort. J Am Acad Child Adolesc Psychiatry. 2020;59:964–77. https://doi.org/10.1016/j.jaac.2019.08.004.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • 33.

    Nigg JT, Gustafsson HC, Karalunas SL, Ryabinin P, McWeeney SK, Faraone SV, et al. Working memory and vigilance as multivariate endophenotypes related to common genetic risk for attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2018;57:175–82.

    Article 

    Google Scholar
     

  • 34.

    Sudre G, Frederick J, Sharp W, Ishii-Takahashi A, Mangalmurti A, Choudhury S, et al. Mapping associations between polygenic risks for childhood neuropsychiatric disorders, symptoms of attention deficit hyperactivity disorder, cognition, and the brain. Mol Psychiatry. 2020;25:2482–92. https://doi.org/10.1038/s41380-019-0350-3.

    Article 
    PubMed 

    Google Scholar
     

  • 35.

    Martin J, Hamshere ML, Stergiakouli E, O’Donovan MC, Thapar A. Genetic risk for attention-deficit/hyperactivity disorder contributes to neurodevelopmental traits in the general population. Biol Psychiatry. 2014;76:664–71.

    Article 

    Google Scholar
     

  • 36.

    Carr LA, Nigg JT, Henderson JM. Attentional versus motor inhibition in adults with attention-deficit/hyperactivity disorder. Neuropsychology. 2006;20:430–41. https://doi.org/10.1037/0894-4105.20.4.430.

    Article 
    PubMed 

    Google Scholar
     

  • 37.

    van Lieshout M, Luman M, Twisk JWR, Faraone SV, Heslenfeld DJ, Hartman CA, et al. Neurocognitive predictors of ADHD outcome: a 6-year follow-up study. J Abnorm Child Psychol. 2017;45:261–72.

    Article 

    Google Scholar
     

  • 38.

    Sjöwall D, Bohlin G, Rydell A-M, Thorell LB. Neuropsychological deficits in preschool as predictors of ADHD symptoms and academic achievement in late adolescence. Child Neuropsychol. 2017;23:111–28.

    Article 

    Google Scholar
     

  • 39.

    Karalunas SL, Gustafsson HC, Dieckmann NF, Tipsord J, Mitchell SH, Nigg JT. Heterogeneity in development of aspects of working memory predicts longitudinal attention deficit hyperactivity disorder symptom change. J Abnorm Psychol. 2017;126:774.

    Article 

    Google Scholar
     

  • 40.

    Makris N, Buka SL, Biederman J, Papadimitriou GM, Hodge SM, Valera EM, et al. Attention and executive systems abnormalities in adults with childhood ADHD: A DT-MRI study of connections. Cereb Cortex. 2008;18:1210–20.

    Article 

    Google Scholar
     

  • 41.

    Chiang H-L, Chen Y-J, Lo Y-C, Tseng W-YI, Gau SS-F. Altered white matter tract property related to impaired focused attention, sustained attention, cognitive impulsivity and vigilance in attention-deficit/hyperactivity disorder. J Psychiatry Neurosci. 2015;40:325.

    Article 

    Google Scholar
     

  • 42.

    Lebel C, Gee M, Camicioli R, Wieler M, Martin W, Beaulieu C. Diffusion tensor imaging of white matter tract evolution over the lifespan. Neuroimage. 2012;60:340–52.

    CAS 
    Article 

    Google Scholar
     

  • 43.

    Kuriyan AB, Pelham WE Jr, Molina BS, Waschbusch DA, Sibley MH, Gnagy EM. Concordance between parent and physician medication histories for children and adolescents with attention-deficit/hyperactivity disorder. J Child Adolesc Psychopharmacol. 2014;24:269–74.

    Article 

    Google Scholar
     

  • 44.

    Owens EB, Cardoos SL, Hinshaw SP. Developmental progression and gender differences among individuals with ADHD. In: Barkley RA, editor. Attention-deficit hyperactivity disorder: a handbook for diagnosis and treatment. New York, NY. The Guilford Press; 2015.

  • 45.

    Dalsgaard S, Mortensen PB, Frydenberg M, Thomsen PH. Conduct problems, gender and adult psychiatric outcome of children with attention-deficit hyperactivity disorder. Br J Psychiatry. 2002;181:416–21.

    Article 

    Google Scholar
     

  • 46.

    Wolfers T, Buitelaar JK, Beckmann CF, Franke B, Marquand AF. From estimating activation locality to predicting disorder: a review of pattern recognition for neuroimaging-based psychiatric diagnostics. Neurosci Biobehav Rev. 2015;57:328–49.

    Article 

    Google Scholar
     

  • 47.

    Kim JW, Sharma V, Ryan ND. Predicting Methylphenidate Response in ADHD Using Machine Learning Approaches. Int J Neuropsychopharmacol. 2015;18:pyv052.

    Article 

    Google Scholar
     

  • 48.

    Luo Y, Alvarez TL, Halperin JM, Li X. Multimodal neuroimaging-based prediction of adult outcomes in childhood-onset ADHD using ensemble learning techniques. NeuroImage: Clin. 2020;26:102238. https://doi.org/10.1016/j.nicl.2020.102238.

    Article 

    Google Scholar
     

  • 49.

    Caye A, Agnew-Blais J, Arseneault L, Gonçalves H, Kieling C, Langley K, et al. A risk calculator to predict adult attention-deficit/hyperactivity disorder: generation and external validation in three birth cohorts and one clinical sample. Epidemiol Psychiatr Sci. 2019;29:e37. https://doi.org/10.1017/S2045796019000283.

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