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Research Articles, Behavioral/Cognitive

Cumulative Effects of Resting-State Connectivity Across All Brain Networks Significantly Correlate with Attention-Deficit Hyperactivity Disorder Symptoms

Michael A. Mooney, Robert J. M. Hermosillo, Eric Feczko, Oscar Miranda-Dominguez, Lucille A. Moore, Anders Perrone, Nora Byington, Gracie Grimsrud, Amanda Rueter, Elizabeth Nousen, Dylan Antovich, Sarah W. Feldstein Ewing, Bonnie J. Nagel, Joel T. Nigg and Damien A. Fair
Journal of Neuroscience 6 March 2024, 44 (10) e1202232023; https://doi.org/10.1523/JNEUROSCI.1202-23.2023
Michael A. Mooney
1Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon 97239
2Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon 97239
3Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
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  • ORCID record for Michael A. Mooney
Robert J. M. Hermosillo
4Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
5Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
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Eric Feczko
4Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
5Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
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Oscar Miranda-Dominguez
4Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
5Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
6Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455
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Lucille A. Moore
7Department of Neurology, Oregon Health & Science University, Portland, Oregon 97239
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Anders Perrone
5Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
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Nora Byington
5Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
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Gracie Grimsrud
5Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
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Amanda Rueter
5Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
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Elizabeth Nousen
3Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
8Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
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Dylan Antovich
8Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
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Sarah W. Feldstein Ewing
9Department of Psychology, University of Rhode Island, Kingston, Rhode Island 02881
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Bonnie J. Nagel
3Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
8Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
10Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon 97239
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Joel T. Nigg
3Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
8Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
10Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon 97239
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Damien A. Fair
4Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
5Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
11Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, Minnesota 55455
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  • Figure 1.
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    Figure 1.

    Polyneuro risk score (PNRS) discovery and validation workflow. Note the thresholding done to select connections used in the PNRS is based on significance determined in the discovery cohort.

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    Figure 2.

    Distribution of ADHD symptom scores in (A) both ARMS of ABCD (Mann–Whitney U test p-value = 0.916) and (B) the Oregon-ADHD-1000 case–control cohort. The ADHD composite symptom scores are the average of multiple standardized (mean = 0, SD = 1) symptom scales (see Materials and Methods).

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    Figure 3.

    Brain-wide connectivity associated with ADHD symptoms in the ABCD Study cohort. A, The matrix of standardized regression coefficients showing the strength of association between all connections (organized by brain network) and ADHD symptoms. B, Gordon parcellation showing the relative contribution of each brain network to the ADHD PNRS. Only the top 10% most significant connections (representing the most predictive PNRS) are considered. The fill color represents the sum of the absolute value of β weights for all connections in which a parcel participates; the outline color represents network assignment. Aud, auditory; CiO, cingulo-opercular; CiP, cingulo-parietal; Def, default mode; DoA, dorsal attention; FrP, frontoparietal; Sal, salience; SMm, somatomotor medial; SMl, somatomotor lateral; Sub, subcortical; VeA, ventral attention; Vis, visual; ReT, retrosplenial temporal; NA, not assigned.

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    Figure 4.

    The matrix of standardized regression coefficients showing the strength of association between the top 10% most significant connections (organized by brain network) and ADHD symptoms. The cumulative effect of these connections comprised the most predictive PNRS, demonstrating the brain-wide, distributed nature of the ADHD PNRS. Aud, auditory; CiO, cingulo-opercular; CiP, cingulo-parietal; Def, default mode; DoA, dorsal attention; FrP, frontoparietal; Sal, salience; SMm, somatomotor medial; SMl, somatomotor lateral; Sub, subcortical; VeA, ventral attention; Vis, visual; ReT, retrosplenial temporal; NA, not assigned.

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    Figure 5.

    ADHD polyneuro score associated with ADHD symptoms. Polyneuro scores and residualized ADHD symptom scores, after adjusting for relevant covariates (see Materials and Methods), for all subjects in the (A) ABCD ARMS-2 (N = 2,796) and (B) Oregon-ADHD-1000 cohort, using each subject’s earliest scan (N = 494). C, The proportion of ADHD symptom score variance explained in the Oregon cohort, by the single most significantly associated connection (Min-p); polyneuro scores comprised of the top 1%, 10%, and 50% most significant connections; and all connections (bootstrapped standard errors are shown). D, Subjects in the Oregon-ADHD-1000 cohort with persistent ADHD showed higher ADHD PNRS than controls (p = 0.00142), though this difference decreases with age. PNRS_U, unadjusted polyneuro score; PNRS_B, Bayesian-adjusted polyneuro score.

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    Figure 6.

    ADHD polyneuro scores were robust to the motion threshold. The proportion of ADHD symptom score variance explained is nearly identical when analyzing the same set of subjects (N = 2,863) using a more stringent motion threshold (FD threshold of 0.1 mm vs 0.2 mm). Bootstrapped standard errors are shown. PNRS_U, unadjusted polyneuro score; PNRS_B, Bayesian-adjusted polyneuro score.

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    Figure 7.

    The matrix of standardized, motion-adjusted regression coefficients showing the strength of association between the top 10% most significant connections (organized by brain network) and ADHD symptoms. The regression coefficients shown here are from a BWAS that included mean FD as a covariate. Aud, auditory; CiO, cingulo-opercular; CiP, cingulo-parietal; Def, default mode; DoA, dorsal attention; FrP, frontoparietal; Sal, salience; SMm, somatomotor medial; SMl, somatomotor lateral; Sub, subcortical; VeA, ventral attention; Vis, visual; ReT, retrosplenial temporal; NA, not assigned.

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    Figure 8.

    The proportion of ADHD symptom score variance explained in the Oregon cohort, by the single most significantly associated connection (Min-p); polyneuro scores comprised of the top 1%, 10%, and 50% most significant connections; and all connections. The results are shown for PNRS based on the BWAS that adjusted for mean FD. Bootstrapped standard errors are shown.

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    Figure 9.

    ADHD polyneuro scores measured in the same subject were significantly correlated when measured (A) approximately 2 years apart and (B) approximately 3 years apart.

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    Figure 10.

    The proportion of ADHD symptom score variance explained by both the PNRS and the PLSR model in the Oregon baseline cohort (without adjusting for covariates). Due to the computational complexity of the PLSR, that model was fit with a maximum of 25% of the most significant functional connections. Nevertheless, the two methods provide comparable predictive power across various connection inclusion thresholds, suggesting there is no meaningful benefit from the more complex PLSR model. Bootstrapped standard errors are shown.

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    Table 1.

    Description of cohorts

    ABCD ARMS-1ABCD ARMS-2Oregon-ADHD-1000
    Sample size2,7472,796553
    Mean age (SD)9.97 (0.63)9.98 (0.62)10.25 (1.56)a
    % Female52.950.237.4
    % Caucasian65.065.579.7
    % ADHD Dx3.34.157.1a
    Inattention symptoms‡53.4 (5.7)53.3 (5.7)63.9 (16.8)a
    • ↵a At earliest scan.

    • ↵‡ Inattention symptoms (T-scores) measured by parent-reported Child Behavior Checklist in ABCD and parent-reported Conners 3 in the Oregon-ADHD-1000.

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    Table 2.

    Correlation of brain-wide effect estimates across ABCD ARMS

    T-stat quantilePearson’s correlationp-value
    All0.4600
    Top 50%0.5710
    Top 10%0.7170
    Top 1%0.7920
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The Journal of Neuroscience: 44 (10)
Journal of Neuroscience
Vol. 44, Issue 10
6 Mar 2024
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Cumulative Effects of Resting-State Connectivity Across All Brain Networks Significantly Correlate with Attention-Deficit Hyperactivity Disorder Symptoms
Michael A. Mooney, Robert J. M. Hermosillo, Eric Feczko, Oscar Miranda-Dominguez, Lucille A. Moore, Anders Perrone, Nora Byington, Gracie Grimsrud, Amanda Rueter, Elizabeth Nousen, Dylan Antovich, Sarah W. Feldstein Ewing, Bonnie J. Nagel, Joel T. Nigg, Damien A. Fair
Journal of Neuroscience 6 March 2024, 44 (10) e1202232023; DOI: 10.1523/JNEUROSCI.1202-23.2023

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Cumulative Effects of Resting-State Connectivity Across All Brain Networks Significantly Correlate with Attention-Deficit Hyperactivity Disorder Symptoms
Michael A. Mooney, Robert J. M. Hermosillo, Eric Feczko, Oscar Miranda-Dominguez, Lucille A. Moore, Anders Perrone, Nora Byington, Gracie Grimsrud, Amanda Rueter, Elizabeth Nousen, Dylan Antovich, Sarah W. Feldstein Ewing, Bonnie J. Nagel, Joel T. Nigg, Damien A. Fair
Journal of Neuroscience 6 March 2024, 44 (10) e1202232023; DOI: 10.1523/JNEUROSCI.1202-23.2023
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Keywords

  • attention-deficit hyperactivity disorder
  • brain-wide association study
  • MRI
  • polyneuro score
  • polygenic score
  • resting-state functional connectivity

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