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

Abstract

Background: Imaging research has not yet delivered reliable psychiatric biomarkers. One challenge, particularly among youth, is high comorbidity. This challenge might be met through canonical correlation analysis designed to model mutual dependencies between symptom dimensions and neural measures. We mapped the multivariate associations that intrinsic functional connectivity manifests with pediatric symptoms of anxiety, irritability, and attention-deficit/hyperactivity disorder (ADHD) as common, impactful, co-occurring problems. We evaluate the replicability of such latent dimensions in an independent sample.

Methods: We obtained ratings of anxiety, irritability, and ADHD, and 10 minutes of resting-state functional magnetic resonance imaging data, from two independent cohorts. Both cohorts (discovery: n = 182; replication: n = 326) included treatment-seeking youth with anxiety disorders, with disruptive mood dysregulation disorder, with ADHD, or without psychopathology. Functional connectivity was modeled as partial correlations among 216 brain areas. Using canonical correlation analysis and independent component analysis jointly we sought maximally correlated, maximally interpretable latent dimensions of brain connectivity and clinical symptoms.

Results: We identified seven canonical variates in the discovery and five in the replication cohort. Of these canonical variates, three exhibited similarities across datasets: two variates consistently captured shared aspects of irritability, ADHD, and anxiety, while the third was specific to anxiety. Across cohorts, canonical variates did not relate to specific resting-state networks but comprised edges interconnecting established networks within and across both hemispheres.

Conclusions: Findings revealed two replicable types of clinical variates, one related to multiple symptom dimensions and a second relatively specific to anxiety. Both types involved a multitude of broadly distributed, weak brain connections as opposed to strong connections encompassing known resting-state networks.

Trial registration: ClinicalTrials.gov NCT02531893 NCT00025935 NCT00018057.

Keywords: Anxiety; Disruptive behavior; Intrinsic brain connectivity; Irritability; Joint canonical correlation and independent component analysis; Youth.

Conflict of interest statement

Competing interests

The authors report no biomedical financial interests or potential conflicts of interest.

Published by Elsevier Inc.

Figures

Figure 1.

Demographics and clinical characteristics of the discovery and replication samples.

Figure 2.. Clinical loadings in the discovery dataset.

Associations between the latent dimensions and symptoms in the domains of anxiety, irritability, and behavioral problems. Each of the seven concentric circles shows the positive (solid fill) and negative correlations (transparent fill) between the canonical variate and the original symptom ratings as bars. The length of the bars indicates the strength of the association. Exact numbers of the loadings are provided in the Supplementary Table S3. Note that CCA results are characterized by sign indeterminacy meaning that it is valid to flip the sign for an entire latent dimension, which will affect the directions of the correlations.

Figure 3.. Replicable, transdimensional latent variable (CV3∣D, CV5∣R).

Scatter plots on panel A show canonical variate 3 from the discovery dataset and 5 from the replication dataset, which represent linear combinations of brain connectivity scores obtained during rsfMRI in the horizontal axis, and linear combinations of clinical scores derived from symptom ratings in the vertical axis. Panel B shows clinical loadings ∣r∣ > 0.2 in for both datasets, showing the same symptoms but an informant effect. Dark red indicates symptoms associated with the latent dimension in both datasets. Panel C depicts edges in red that load strongly positively on u3∣D and u5∣R. Edges that load strongly negatively on u3∣D and u5∣R are depicted in blue. Given baseline differences in the strength of the connectivity patterns, connectivity maps were thresholded at ∣r∣ > 0.2 for the discovery sample and at ∣r∣ > 0.15 for the replication sample. Next only edges that loaded highly positively or negatively in both datasets were retained for this figure.

Figure 4.. Replicable, shared aspects of disruptive behavior and irritability (CV4∣D, CV4∣R).

Scatter plots on panel A show canonical variate 4 from the discovery dataset and 4 from the replication dataset, which represent linear combinations of brain connectivity scores obtained during rsfMRI in the horizontal axis, and linear combinations of clinical scores derived from symptom ratings in the vertical axis. Panel B shows clinical loadings ∣r∣ > 0.2 in for both datasets. Dark red indicates symptoms associated with the latent dimension in both datasets. Panel C depicts edges in red that load strongly positively on u4∣D and u4∣R. Edges that load strongly negatively on u4∣D and u4∣R are depicted in blue. Given baseline differences in the strength of the connectivity patterns, connectivity maps were thresholded at ∣r∣ > 0.2 for the discovery sample and at ∣r∣ > 0.15 for the replication sample. Next only edges that loaded highly positively or negatively in both datasets were retained for this figure.

Figure 5.. Replicable, anxiety-specific latent variable (CV7∣D, CV3∣R).

Scatter plots on panel A show canonical variate 7 from the discovery dataset and 3 from the replication dataset, which represent linear combinations of brain connectivity scores obtained during rsfMRI in the horizontal axis, and linear combinations of clinical scores derived from symptom ratings in the vertical axis. Panel B shows clinical loadings ∣r∣ > 0.2 in for both datasets. Dark red indicates symptoms associated with the latent dimension in both datasets. Panel C depicts edges in red that load strongly positively on u7∣D and u3∣R. Edges that load strongly negatively on u7∣D and u3∣R are depicted in blue. Given baseline differences in the strength of the connectivity patterns, connectivity maps were thresholded at ∣r∣ > 0.2 for the discovery sample and at ∣r∣ > 0.15 for the replication sample. Next only edges that loaded highly positively or negatively in both datasets were retained for this figure.