Shared and Anxiety-Specific Pediatric Psychopathology Dimensions Manifest Distributed Neural Correlates

Linke, Julia; Abend, Rany; Kircanski, Katharina; Clayton, Michal; Stavish, Caitlin; Benson, Brenda E.; Brotman, Melissa A.; Renaud, Olivier; Smith, Stephen M.; Nichols, Thomas E.; Leibenluft, Ellen; Winkler, Anderson M.; Pine, Daniel S.

doi:10.1016/j.biopsych.2020.10.018

Cited by 32 publications

(40 citation statements)

References 34 publications

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“…This is in line with comorbidity as a prevalent feature of mental illness 41 , as well as the pfactor framework that transdiagnostic symptom burden is more predictive of clinical life trajectories than any specific diagnosis 12,42 . Similarly, other studies have reported shared connectivity patterns across anxiety, irritability, and ADHD in other clinical samples of youth 9 . While substantial evidence now points towards cross-diagnostic brain deviations in psychopathology 43,44 , this does not rule out disorder-specific patterns, and a full account of the brain basis of mental illness require mapping of both 3,9 .…”

Section: Discussionsupporting

confidence: 58%

“…Similarly, other studies have reported shared connectivity patterns across anxiety, irritability, and ADHD in other clinical samples of youth 9 . While substantial evidence now points towards cross-diagnostic brain deviations in psychopathology 43,44 , this does not rule out disorder-specific patterns, and a full account of the brain basis of mental illness require mapping of both 3,9 . Mood disorders predicted mode 1 unlike the other diagnostic categories, likely because individuals with a mood disorder were older than the rest of the sample.…”

Section: Discussionsupporting

confidence: 58%

“…A pattern relating distributed brain connectivity to both shared and unique aspects of anxiety, irritability, and attention-deficit hyperactivity disorder (ADHD) was replicated across two independent clinical samples of youth 9 , alluding to both disorder-general and disorder-specific patterns in the youth brain. Another recent study identified four neuroimaging patterns related to phenotypic variation across children with and without an ADHD diagnosis 10 , one of which related higher ADHD symptom load with poorer academic performance, delayed pubertal development, and regional variability in cortical brain structure.…”

Section: Introductionmentioning

confidence: 98%

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Traces of impaired social communication and cognitive ability in the youth brain are shared across diagnostic boundaries

Voldsbekk¹,

Kjelkenes²,

Wolfers³

et al. 2022

Preprint

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Many mental disorders debut during adolescence, a period also characterised by substantial brain development. The interplay of preceding factors and how they relate to neurodevelopmental trajectories of mental illness is not well understood. Here, we used canonical correlation and independent component analysis to estimate modes of covariation between structural neuroimaging measures with cognitive, clinical, and environmental measures in a clinical youth sample. We then performed out-of-sample validation of the detected brain-patterns in an independent non-clinical sample of youth with a similar age range. The brain patterns were estimated using the Healthy Brain Network cohort, in participants aged 5-21 (n=1732, 64% male), with the majority meeting the criteria for at least one psychiatric disorder. These analyses identified two significant modes of brain-behaviour covariation: the first linked age, physical and cognitive maturation to brain features including lower cortical thickness and gyrification (r=.92, p=.005). The second mode linked lower language skills, lower academic performance, and social communication and psychological difficulties, with lower white matter surface area and gyrification (r=.92, p=.006). Diagnosed youth showed elevated mode 2 scores compared to undiagnosed peers. Out-of-sample validation of these brain patterns was performed in the Philadelphia Neurodevelopmental Cohort in largely undiagnosed youth aged 8-21 (n=1253, 54% female). We replicated the covariation pattern across brain features for both modes. Mode 1 correlated highly with age (r [95% CI]; .7 [.68-.71]) and age-related cognitive maturation (.36 [.33-.38]), while mode 2 correlated with deviations from normative cognitive development (-.24 [-.27 - -.21]). Together, our results identify both expected and novel brain-behaviour patterns, linking maturation and socio-cognitive difficulties to brain structure across diagnostic boundaries. Our results support the notion of aberrant cognitive development as a cross-diagnostic risk factor for mental illness, with a traceable pattern in the youth brain.

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Section: Discussionsupporting

confidence: 58%

Section: Discussionsupporting

confidence: 58%

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

Traces of impaired social communication and cognitive ability in the youth brain are shared across diagnostic boundaries

Voldsbekk¹,

Kjelkenes²,

Wolfers³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…In addition to anxiety, impulsivity -the tendency to act inappropriately and prematurely despite adverse outcomes also represents a major dimension of psychopathology (Cosi et al 2011;Cummings et al 2014;Whiteside and Lynam 2001). Whereas both dimensions have been increasingly associated with robust neurobiological dysregulations across diagnoses (Xu et al 2020;Linke et al 2021; . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.…”

Section: Introductionmentioning

confidence: 99%

Anxiety-impulsivity subtypes in adolescent internalizing disorder are characterized by distinguishable neurodevelopmental, neurocognitive and clinical trajectory signatures

Fan

Kuang

et al. 2021

Preprint

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Background Anxiety and impulsivity represent transdiagnostic pathology dimensions yet their interaction and contribution to emotional disorders in adolescence and to disease development remain controversial, and previous studies indicate heterogeneity within the broad category of internalizing disorders. Methods A combination of hierarchical and non-hierarchical clustering strategies was employed to determine impulsivity-related subtypes (based on the facets of negative urgency, lack of planning, lack of perseverance, sensation seeking and positive urgency in UPPS-P scales) in a large cohort of adolescents with internalizing disorders (n=2437) from Adolescent Brain Cognitive Development (ABCD) Study. Linear mixed-effect models were employed to determine cortical thickness alterations of the subtypes. Results Data-driven clustering identified two distinct subtypes of internalizing patients (subtype 1/subtype 2) with comparable levels of increased anxiety yet distinguishable levels of impulsivity, i.e., enhanced (subtype 1) or decreased (subtype 2) compared to healthy controls. Subtype 1 was further characterized by thicker prefrontal and temporal cortical regions involved in regulatory control and fear processing, while subtype 2 did not demonstrate significant thickness alterations. The differential neuroanatomical profiles remained stable over the two-year follow-up, while the two subtypes had different neurodevelopmental trajectories. Subtype 1 additionally reported more psychopathology and dysfunctionality including higher suicidal ideation, depressive symptoms and transition rates to externalizing disorders during follow-up as well as impaired neurocognitive and educational performance compared to subtype 2. Moreover, for subtype 1, anxiety at baseline (9-10 years) was significantly positively associated with impulsivity (lack of perseverance) at 2-year follow-up, while in subtype 2, baseline anxiety was significantly negatively associated with impulsivity (sensation seeking) at 2-year follow-up. Conclusions Our results demonstrate an impulsivity-dependent heterogeneity in adolescent internalizing disorders, with high-impulsivity patients being characterized by neurodevelopmental delay at the neural and cognitive levels. Individuals with elevated impulsivity are at a greater risk to develop behavioral dysregulation over the following two years and may thus require specific early interventions.

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“…Before submitting the brain features into the CCA, two preprocessing steps were performed at the group level. First, Tier-1 covariates were regressed out from the connectome and behavior dataset separately, and the residuals were transformed into a lower dimensional basis where data are exchangeable (70, 71). Second, a procedure of Principal Component Analysis (PCA) was applied on both datasets of functional connectome and the multi-domain behaviors, respectively.…”

Section: Methodsmentioning

confidence: 99%

Brain Functional Connectome Defines a Transdiagnostic Dimension Shared by Cognitive Dysfunction and Psychopathology in Preadolescents

Xiao

Hammond

Salmeron

et al. 2021

Preprint

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The search for psychiatric biomarkers has remained elusive, in part, due to high comorbidity, low specificity, and poor concordance between neurobiological abnormalities and existing diagnostic categories. Developmental shifts in symptom expression and brain function across the lifespan further complicate biomarker identification. Recent studies suggest that focusing on cognition may be a pathway forward: Cognitive dysfunction is a common feature across psychiatric disorders. Individual differences in cognition may reflect variability in the connectivity of underlying neurocognitive brain networks, and predict psychopathology at different developmental periods. In the present study we identified brain-based dimensions of general cognitive capacity and psychopathology using sparse canonical correlation analysis (sCCA) in a sample of 7,383 preadolescents from the Adolescent Brian Cognitive Development (ABCD) study. This analysis revealed correlated patterns of functional connectivity with cognitive control capacity and psychopathology. Specifically, the results identified a single connectome-based latent brain variate that was positively correlated with performance on cognitive measures across domains and negatively correlated with parent-reported psychopathology across diagnoses and domains. Functional connectivity loadings for the brain variate were across distributed cortical and subcortical brain networks and a dose-dependent relationship with psychopathology based upon the cumulative number of psychiatric diagnoses was observed. These findings provide preliminary evidence for a connectome-based biomarker that indexes individual differences in cognitive control and predicts transdiagnostic psychopathology in a dose-dependent fashion.

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Shared and Anxiety-Specific Pediatric Psychopathology Dimensions Manifest Distributed Neural Correlates

Cited by 32 publications

References 34 publications

Traces of impaired social communication and cognitive ability in the youth brain are shared across diagnostic boundaries

Traces of impaired social communication and cognitive ability in the youth brain are shared across diagnostic boundaries

Anxiety-impulsivity subtypes in adolescent internalizing disorder are characterized by distinguishable neurodevelopmental, neurocognitive and clinical trajectory signatures

Brain Functional Connectome Defines a Transdiagnostic Dimension Shared by Cognitive Dysfunction and Psychopathology in Preadolescents

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