Recent advances in understanding of attention deficit hyperactivity disorder (ADHD): how genetics are shaping our conceptualization of this disorder

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Abstract

Attention deficit hyperactivity disorder (ADHD) is a clinically defined disorder, and inattention and hyperactivity/impulsivity are its main symptom domains. The presentation, lifelong continuation and treatment response of ADHD symptoms, however, is highly heterogeneous. To better define, diagnose, treat and prevent ADHD, it is essential that we understand the biological processes underlying all of these elements. In this review, given the high heritability of ADHD, we discuss how and why genetics can foster such progress. We examine what genetics have taught us so far with regard to ADHD definition, classification, clinical presentation, diagnosis and treatment. Finally, we offer a prospect of what genetic studies on ADHD may bring in the future.

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Most cited references 21

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The nature of nurture: Effects of parental genotypes

Augustine Kong, Gudmar Thorleifsson, Michael L. Frigge … (2018)

Sequence variants in the parental genomes that are not transmitted to a child (the proband) are often ignored in genetic studies. Here we show that nontransmitted alleles can affect a child through their impacts on the parents and other relatives, a phenomenon we call "genetic nurture." Using results from a meta-analysis of educational attainment, we find that the polygenic score computed for the nontransmitted alleles of 21,637 probands with at least one parent genotyped has an estimated effect on the educational attainment of the proband that is 29.9% (P = 1.6 × 10-14) of that of the transmitted polygenic score. Genetic nurturing effects of this polygenic score extend to other traits. Paternal and maternal polygenic scores have similar effects on educational attainment, but mothers contribute more than fathers to nutrition- and heath-related traits.

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Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults

Michael Inouye, Gad Abraham, Christopher P. Nelson … (2018)

Background Coronary artery disease (CAD) has substantial heritability and a polygenic architecture. However, the potential of genomic risk scores to help predict CAD outcomes has not been evaluated comprehensively, because available studies have involved limited genomic scope and limited sample sizes. Objectives This study sought to construct a genomic risk score for CAD and to estimate its potential as a screening tool for primary prevention. Methods Using a meta-analytic approach to combine large-scale, genome-wide, and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS) consisting of 1.7 million genetic variants. We externally tested metaGRS, both by itself and in combination with available data on conventional risk factors, in 22,242 CAD cases and 460,387 noncases from the UK Biobank. Results The hazard ratio (HR) for CAD was 1.71 (95% confidence interval [CI]: 1.68 to 1.73) per SD increase in metaGRS, an association larger than any other externally tested genetic risk score previously published. The metaGRS stratified individuals into significantly different life course trajectories of CAD risk, with those in the top 20% of metaGRS distribution having an HR of 4.17 (95% CI: 3.97 to 4.38) compared with those in the bottom 20%. The corresponding HR was 2.83 (95% CI: 2.61 to 3.07) among individuals on lipid-lowering or antihypertensive medications. The metaGRS had a higher C-index (C = 0.623; 95% CI: 0.615 to 0.631) for incident CAD than any of 6 conventional factors (smoking, diabetes, hypertension, body mass index, self-reported high cholesterol, and family history). For men in the top 20% of metaGRS with >2 conventional factors, 10% cumulative risk of CAD was reached by 48 years of age. Conclusions The genomic score developed and evaluated here substantially advances the concept of using genomic information to stratify individuals with different trajectories of CAD risk and highlights the potential for genomic screening in early life to complement conventional risk prediction.

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3-year follow-up of the NIMH MTA study.

Peter S Jensen, L Eugene Arnold, James M. Swanson … (2007)

In the intent-to-treat analysis of the Multimodal Treatment Study of Children With ADHD (MTA), the effects of medication management (MedMgt), behavior therapy (Beh), their combination (Comb), and usual community care (CC) differed at 14 and 24 months due to superiority of treatments that used the MTA medication algorithm (Comb+MedMgt) over those that did not (Beh+CC). This report examines 36-month outcomes, 2 years after treatment by the study ended. For primary outcome measures (attention-deficit/hyperactivity disorder [ADHD] and oppositional defiant disorder [ODD] symptoms, social skills, reading scores, impairment, and diagnostic status), mixed-effects regression models and orthogonal contrasts examined 36-month outcomes. At 3 years, 485 of the original 579 subjects (83.8%) participated in the follow-up, now at ages 10 to 13 years, (mean 11.9 years). In contrast to the significant advantage of MedMgt+Comb over Beh+CC for ADHD symptoms at 14 and 24 months, treatment groups did not differ significantly on any measure at 36 months. The percentage of children taking medication >50% of the time changed between 14 and 36 months across the initial treatment groups: Beh significantly increased (14% to 45%), MedMed+Comb significantly decreased (91% to 71%), and CC remained constant (60%-62%). Regardless of their treatment use changes, all of the groups showed symptom improvement over baseline. Notably, initial symptom severity, sex (male), comorbidity, public assistance, and parental psychopathology (ADHD) did not moderate children's 36-month treatment responses, but these factors predicted worse outcomes over 36 months, regardless of original treatment assignment. By 36 months, the earlier advantage of having had 14 months of the medication algorithm was no longer apparent, possibly due to age-related decline in ADHD symptoms, changes in medication management intensity, starting or stopping medications altogether, or other factors not yet evaluated.

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Author and article information

Contributors

Tetyana Zayats: Role: ConceptualizationRole: Writing – Original Draft Preparation

Benjamin M Neale: Role: ConceptualizationRole: Writing – Review & Editing

ORCID: https://orcid.org/0000-0003-1513-6077

Journal

Journal ID (nlm-ta): F1000Res

Journal ID (iso-abbrev): F1000Res

Journal ID (pmc): F1000Research

Title: F1000Research

Publisher: F1000 Research Limited (London, UK )

ISSN (Electronic): 2046-1402

Publication date (Electronic): 5 December 2019

Publication date Collection: 2019

Volume: 8

Electronic Location Identifier: F1000 Faculty Rev-2060

Affiliations

[1 ]Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA

[2 ]Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA

Author notes

[a ] tzayats@ 123456broadinstitute.org

Competing interests: BMN is a member of the scientific advisory board at Deep Genomics and a paid consultant with Camp4 Therapeutics Corporation, Merck & Co., Takeda Pharmaceutical, and Biogen. TZ declares that she has no competing interests.

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Benjamin M Neale https://orcid.org/0000-0003-1513-6077

Article

DOI: 10.12688/f1000research.18959.1

PMC ID: 6896240

SO-VID: a33b0d78-3a33-45fe-8f4f-46b822e83829

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This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date accepted : 27 November 2019

Funding

Funded by: Gerstner Family Foundation

Funded by: National Institute of Mental Health

Award ID: 1R01MH094469

Award ID: 5U01MH109539

The authors are supported by the Gerstner Family Foundation (NIMH 1R01MH094469- Quantifying the impact of rare mutations on attention deficit hyperactivity disorder [ADHD]) and by the Psychiatric Genomics Consortium: Finding Actionable Variation (NIMH 5U01MH109539-03-2/7).

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Recent advances in understanding of attention deficit hyperactivity disorder (ADHD): how genetics are shaping our conceptualization of this disorder

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G3: Genes|Genomes|Genetics

Most cited references 21

The nature of nurture: Effects of parental genotypes

Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults

3-year follow-up of the NIMH MTA study.

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