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Patterns, Influences and Genetic Underpinnings of the Development of ADHD

Liu, Chaoyu K.; (2021) Patterns, Influences and Genetic Underpinnings of the Development of ADHD. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

Background Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterised by age-inappropriate, disruptive and pervasive manifestations of inattention and/or hyperactivity/impulsivity. ADHD symptoms typically emerge in childhood and persist into later stages of life. ADHD also frequently co-occurs with a number of psychiatric disorders and medical conditions, thereby bringing a tremendous burden to affected individuals as well as society. In addition to symptom severity and chronicity, the development of ADHD also plays a determinant role in disease outcomes. However, few studies have systematically investigated different predictive factors and underlying aetiologies associated with the development of ADHD. Aims This thesis aims to examine patterns, influences and genetic underpinnings of the development of ADHD from childhood to adolescence. The first study investigates childhood factors that differentiate late-onset ADHD from childhood-onset ADHD and differences in adolescent outcomes. The second study examines genetic and environmental contributions underlying the effects of the development of inattention on academic performance. The third and the fourth studies investigate the developmental relationships between ADHD and BMI through triangulation of evidence from longitudinal statistical analyses and genetically informed causal inference approaches. Methods All of the studies adopt a development-sensitive design using data from the “Twin Early Development Study” (TEDS), a longitudinal cohort in the UK. A pluralistic statistical approach is employed for different study objectives. To strengthen causal inference, this thesis compares and contrasts findings from longitudinal statistical approaches and different genetically informed methods under a triangulation framework. Results Findings of this thesis suggest that 1) late-onset ADHD is more likely to be found in males and children who exhibit increased conduct problems and experience more childhood family adversity. Moreover, low socioeconomic status specifically predicts de novo late-onset ADHD, while additional factors predict subthreshold late-onset ADHD; 2) both the baseline level and the developmental course of inattention influence academic performance. Genetic contributions to the development of inattention also affect academic performance; 3) longitudinal statistical analyses identify unidirectional effects from ADHD symptoms to subsequent BMI, while genetic methods suggest a bidirectional causal relationship. Triangulation of evidence shows that multiple sources of confounding are involved in the relationships between ADHD and BMI, including unmeasured confounding and dynastic effects. Conclusions This thesis identifies specific childhood risk factors and genetic underpinnings associated with different developmental patterns of ADHD. Influences of the developmental course of ADHD on psychological and functional outcomes can be attributable to direct causal relationships, genetic and environmental confounding, or a combination of both. Altogether, these findings contribute to a more complete and systematic understanding of different developmental aspects of ADHD. To disentangle aetiological pathways between the development of ADHD and associated conditions, a pluralistic statistical approach to triangulate evidence regarding causal mechanisms is necessary.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Patterns, Influences and Genetic Underpinnings of the Development of ADHD
Event: University College London
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2021. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10123912
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