Refinement by integration: aggregated effects of multimodal imaging markers on adult ADHD

Refinement by integration: aggregated effects of multimodal imaging markers on adult ADHD

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J Psychiatry Neurosci 2017;42(6):386-394

Thomas Wolfers, MSc*; Alberto Llera Arenas, PhD*; A. Marten H. Onnink, PhD; Janneke Dammers, MSc; Martine Hoogman, PhD; Marcel P. Zwiers, PhD; Jan K. Buitelaar, MD, PhD†; Barbara Franke, PhD†; Andre F. Marquand, PhD†; Christian F. Beckmann, PhD†

Abstract

Background: Attention-deficit/hyperactivity disorder (ADHD) is biologically heterogeneous, with different biological predispositions — mediated through developmental processes — converging upon a common clinical phenotype. Brain imaging studies have variably shown altered brain structure, activity and connectivity in children and adults with ADHD. Recent methodological developments allow for the integration of information across imaging modalities, potentially yielding a more coherent view regarding the biology underlying the disorder.

Methods: We analyzed a sample of adults with persistent ADHD and healthy controls using an advanced multimodal linked independent component analysis approach. Diffusion and structural MRI data were fused to form imaging markers reflecting independent components that explain variation across modalities. We included these markers as predictors into logistic regression models on adult ADHD and put those into context with predictions of estimated intelligence, age and sex.

Results: We included 87 adults with ADHD and 93 controls in our analysis. Participants’ courses associated with all imaging markers explained 27.86% of the variance in adult ADHD. No single imaging modality dominated this result. Instead, it was explained by aggregation of relatively small effects across several modalities and markers. One of the top markers for adult ADHD was multimodal and linked to morphological and microstructural effects within anterior temporal brain regions; another was linked to cortical thickness. Several markers were also influenced by estimated intelligence, age and/or sex.

Limitations: Although complex analytical approaches, such as the one applied here, provide insight into otherwise hidden mechanisms, they also increase the complexity of interpretations.

Conclusion: No dominant imaging modality or marker characterizes structural brain phenotypes in adults with ADHD, but we can refine our characterization of the disorder by the integration of small effects across modalities.


Submitted Dec. 16, 2016; Revised Apr. 13, 2017; Accepted May 10, 2017; Early-released Aug. 23, 2017

These authors share *first authorship or †senior authorship.

Acknowledgements: The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 602450 (IMAGEMEND). In addition, the study was supported by grants from the Netherlands Organization for Scientific Research (NWO), a Vici grant to B. Franke (grant no. 016-130-669), Brain & Cognition grants no. 433-09-242 and no. 056-13-015 to J. Buitelaar, and the Gravitation Programme Language in Interaction (grant 024.001.006). The research of B. Franke and J. Buitelaar also receives funding from the FP7 Programme under grant agreements no. 602805 (AGGRESSOTYPE), no. 603016 (MATRICS) and no. 278948 (TACTICS), from the European Community’s Horizon 2020 Programme (H2020/2014–2020) under grant agreements no. 643051 (MiND) and no. 642996 (BRAINVIEW), and from a grant for the ENIGMA Center for Worldwide Medicine Imaging and Genomics from the National Institute of Health’s BD2K Initiative (grant no.U54 EB020403). A. Marquand acknowledges support from the Language in Interaction consortium, funded by the NWO under the Gravitation Programme.

Affiliations: From the Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands (Wolfers, Onnink, Dammers, Hoogman, Franke); the Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands (Wolfers, Arenas, Hoogman, Zwiers, Franke, Marquand, Beckman); the Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands (Buitelaar, Marquand, Beckmann); the Centre for Functional MRI of the Brain (FMRIB), Oxford University, Oxford, UK (Beckmann); the Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands (Franke); the Karakter Child and Adolescent Psychiatry University Centre, Radboud University Medical Centre, Nijmegen, the Netherlands (Buitelaar); and the Department of Neuroimaging, Institute of Psychiatry, King’s College London, London, UK (Marquand).

Competing interests: J. Buitelaar has been a consultant, member of the advisory board and/or speaker for Janssen Cilag BV, Eli Lilly, Shire, Lundbeck, Roche and Servier. B. Franke has received speaker fees from Merz. None of these companies or any of the funding agencies had any influence on the content of this paper. No other competing interests declared.

Contributors: T. Wolfers, A. Arenas, B. Franke, A. Marquand and C. Beckmann designed the study. T. Wolders, M. Onnink, J. Dammers, M. Hoogman, M. Zwiers, J. Buitelaar and B. Franke acquired the data, which T. Wolfers, A. Arenas, M. Zwiers, J. Buitelaar, B. Franke, A. Marquand and C. Beckmann analyzed. T. Wolfers, A. Arenas and A. Marquand wrote the article, which all authors reviewed and approved for publication.

DOI: 10.1503/jpn.160240

Correspondence to: T. Wolfers, Donders Centre for Cognitive Neuroimaging, Radboud University, PO Box 9101, 6500 HB Nijmegen, the Netherlands; t.wolfers@donders.ru.nl