Cumulative Effects of Resting-state Connectivity Across All Brain Networks Significantly Correlate with ADHD Symptoms

Mooney, Michael A.; Hermosillo, Robert; Feczko, Eric; Miranda-Domínguez, Óscar; Moore, Lucille A; Perrone, Anders; Byington, Nora; Grimsrud, Gracie; Rueter, Amanda; Nousen, Elizabeth K.; Antovich, Dylan; Ewing, Sarah W. Feldstein; Nagel, Bonnie J.; Nigg, Joel T.; Fair, Damien A.

doi:10.1101/2021.11.16.21266121

Cited by 6 publications

(4 citation statements)

References 55 publications

(81 reference statements)

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“…61 Similarly, there was no convergence in the spatial patterns of functional brain connectivity associated with ADHD in the literature, 17 and ADHD traits have been reported to be more associated with brainwide connectivity than with local connectivity. 62 Thus, our findings support the distributed involvement of brain regions in intelligence and hyperactivity and impulsivity symptoms.…”

Section: Jama Network Open | Imagingsupporting

confidence: 78%

Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data

et al. 2023

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ImportanceNeurodevelopmental conditions, such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD), have highly heterogeneous and overlapping phenotypes and neurobiology. Data-driven approaches are beginning to identify homogeneous transdiagnostic subgroups of children; however, findings have yet to be replicated in independently collected data sets, a necessity for translation into clinical settings.ObjectiveTo identify subgroups of children with and without neurodevelopmental conditions with shared functional brain characteristics using data from 2 large, independent data sets.Design, Setting, and ParticipantsThis case-control study used data from the Province of Ontario Neurodevelopmental (POND) network (study recruitment began June 2012 and is ongoing; data were extracted April 2021) and the Healthy Brain Network (HBN; study recruitment began May 2015 and is ongoing; data were extracted November 2020). POND and HBN data are collected from institutions across Ontario and New York, respectively. Participants who had diagnoses of ASD, ADHD, and OCD or were typically developing (TD); were aged between 5 and 19 years; and successfully completed the resting-state and anatomical neuroimaging protocol were included in the current study.Main Outcomes and MeasuresThe analyses consisted of a data-driven clustering procedure on measures derived from each participant’s resting-state functional connectome, performed independently on each data set. Differences between each pair of leaves in the resulting clustering decision trees in the demographic and clinical characteristics were tested.ResultsOverall, 551 children and adolescents were included from each data set. POND included 164 participants with ADHD; 217 with ASD; 60 with OCD; and 110 with TD (median [IQR] age, 11.87 [9.51-14.76] years; 393 [71.2%] male participants; 20 [3.6%] Black, 28 [5.1%] Latino, and 299 [54.2%] White participants) and HBN included 374 participants with ADHD; 66 with ASD; 11 with OCD; and 100 with TD (median [IQR] age, 11.50 [9.22-14.20] years; 390 [70.8%] male participants; 82 [14.9%] Black, 57 [10.3%] Hispanic, and 257 [46.6%] White participants). In both data sets, subgroups with similar biology that differed significantly in intelligence as well as hyperactivity and impulsivity problems were identified, yet these groups showed no consistent alignment with current diagnostic categories. For example, there was a significant difference in Strengths and Weaknesses ADHD Symptoms and Normal Behavior Hyperactivity/Impulsivity subscale (SWAN-HI) between 2 subgroups in the POND data (C and D), with subgroup D having increased hyperactivity and impulsivity traits compared with subgroup C (median [IQR], 2.50 [0.00-7.00] vs 1.00 [0.00-5.00]; U = 1.19 × 104; P = .01; η2 = 0.02). A significant difference in SWAN-HI scores between subgroups g and d in the HBN data was also observed (median [IQR], 1.00 [0.00-4.00] vs 0.00 [0.00-2.00]; corrected P = .02). There were no differences in the proportion of each diagnosis between the subgroups in either data set.Conclusions and RelevanceThe findings of this study suggest that homogeneity in the neurobiology of neurodevelopmental conditions transcends diagnostic boundaries and is instead associated with behavioral characteristics. This work takes an important step toward translating neurobiological subgroups into clinical settings by being the first to replicate our findings in independently collected data sets.

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Section: Jama Network Open | Imagingsupporting

confidence: 78%

Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data

et al. 2023

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“…As mathematical description of these processes rapidly improves, targeted intervention should improve as well 8 . Further, clinical algorithms could utilize composite scores reflecting system-wide activity in brain, such as a polyvertex score (Zhao et al, 2019) or related score for functional networks (Mooney et al, 2021), or epigenetic or physiological summary scores (Stevenson et al, 2020). These would target regulatory process and could become indices of clinical change (the complexity of interpreting poly-scores notwithstanding).…”

Section: Part 2: Sketch Of the Theory And Hypothesesmentioning

confidence: 99%

Considerations toward an epigenetic and common pathways theory of mental disorder.

Nigg¹

2023

Journal of Psychopathology and Clinical Science

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Psychopathology emerges from the dynamic interplay of physiological and mental processes and ecological context. It can be seen as a failure of recursive, homeostatic processes to achieve adaptive reequilibrium. This general statement can be actualized with consideration of polygenic liability, early exposures, and multiunit (multi-"level") analysis of the psychological action and the associated physiological and neural operations, all in the context of the developmental exposome. This article begins by identifying key principles and clarifying key terms necessary to mental disorder theory. It then ventures a sketch of a model that highlights epigenetic dynamics and proposes a common pathways hypothesis toward psychopathology. An epigenetic perspective elevates the importance of developmental context and adaptive systems, particularly in early life, while opening the door to new mechanistic discovery. The key proposal is that a finite number of homeostatic biological and psychological mechanisms are shared across most risky environments (and possibly many genetic liabilities) for psychopathology. Perturbation of these mediating mechanisms leads to development of psychopathology. A focus on dynamic changes in these homeostatic mechanisms across multiple units of analysis and time points can render the problem of explaining psychopathology tractable. Key questions include the mapping of recursive processes over time, at adequate density, as mental disorders unfold across development. General Scientific SummaryMental disorders develop in the midst of complex processes. A focus on causal mechanism can benefit from a focus on regulatory processes and on common pathways of effect across multiple risks and conditions.

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“…Furthermore, following the polygenic scores in the field of genetics, recently, the use of polyneuro scores has been proposed (Mooney et al, 2021). Polyneuro scores are summary scores of the cumulative effect of brainwide measures that capture effects across widely distributed brain systems and regions that are involved in different human traits (Mooney et al, 2021). Applied to ADHD, Mooney et al (2021) showed that such summary scores of functional connectivity across the brain have increased predictive power for ADHD symptoms.…”

Section: Brain-wide Association Studiesmentioning

confidence: 99%

“…Polyneuro scores are summary scores of the cumulative effect of brainwide measures that capture effects across widely distributed brain systems and regions that are involved in different human traits (Mooney et al, 2021). Applied to ADHD, Mooney et al (2021) showed that such summary scores of functional connectivity across the brain have increased predictive power for ADHD symptoms. The scores explained around 8 times more variation than the variation explained by the most significant connection in the brain.…”

Section: Brain-wide Association Studiesmentioning

confidence: 99%

Differences in well-being

Vries¹

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Well-being is a complex, and multifaceted construct that includes feeling good and functioning well. There is a growing global recognition of well-being as an important research topic and public policy goal. Well-being is related to less behavioral and emotional problems, and is associated with many positive aspects of daily life, including longevity, higher educational achievement, happier marriage, and more productivity at work. People differ in their levels of well-being, i.e., some people are in general happier or more satisfied with their lives than others. These individual differences in well-being can arise from many different factors, including biological (genetic) influences and environmental influences. To enhance the development of future mental health prevention and intervention strategies to increase well-being, more knowledge about these determinants and factors underlying well-being is needed. In this dissertation, I aimed to increase the understanding of the etiology in a series of studies using different methods, including systematic reviews, meta-analyses, twin designs, and molecular genetic designs. In part I, we brought together all published studies on the neural and physiological factors underlying well-being. This overview allowed us to critically investigate the claims made about the biology involved in well-being. The number of studies on the neural and physiological factors underlying well-being is increasing and the results point towards potential correlates of well-being. However, samples are often still small, and studies focus mostly on a single biomarker. Therefore, more well-powered, data-driven, and integrative studies across biological categories are needed to better understand the neural and physiological pathways that play a role in well-being. In part II, we investigated the overlap between well-being and a range of other phenotypes to learn more about the etiology of well-being. We report a large overlap with phenotypes including optimism, resilience, and depressive symptoms. Furthermore, when removing the genetic overlap between well-being and depressive symptoms, we showed that well-being has unique genetic associations with a range of phenotypes, independently from depressive symptoms. These results can be helpful in designing more effective interventions to increase well-being, taking into account the overlap and possible causality with other phenotypes. In part III, we used the extreme environmental change during the COVID-19 pandemic to investigate individual differences in the effects of such environmental changes on well-being. On average, we found a negative effect of the pandemic on different aspects of well-being, especially further into the pandemic. Whereas most previous studies only looked at this average negative effect of the pandemic on well-being, we focused on the individual differences as well. We reported large individual differences in the effects of the pandemic on well-being in both chapters. This indicates that one-size-fits-all preventions or interventions to maintain or increase well-being during the pandemic or lockdowns will not be successful for the whole population. Further research is needed for the identification of protective factors and resilience mechanisms to prevent further inequality during extreme environmental situations. In part IV, we looked at the real-time assessment of well-being, investigating the feasibility and results of previous studies. The real-time assessment of well-being, related variables, and the environment can lead to new insights about well-being, i.e., results that we cannot capture with traditional survey research. The real-time assessment of well-being is therefore a promising area for future research to unravel the dynamic nature of well-being fluctuations and the interaction with the environment in daily life. Integrating all results in this dissertation confirmed that well-being is a complex human trait that is influenced by many interrelated and interacting factors. Future directions to understand individual differences in well-being will be a data-driven approach to investigate the complex interplay of neural, physiological, genetic, and environmental factors in well-being.

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Cumulative Effects of Resting-state Connectivity Across All Brain Networks Significantly Correlate with ADHD Symptoms

Cited by 6 publications

References 55 publications

Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data

Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data

Considerations toward an epigenetic and common pathways theory of mental disorder.

Differences in well-being

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