Dataset Information

Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders.

ABSTRACT:

Background

Current diagnostic systems for neurodevelopmental disorders do not have clear links to underlying neurobiology, limiting their utility in identifying targeted treatments for individuals. Here, we aimed to investigate differences in functional brain network integrity between traditional diagnostic categories (autism spectrum disorder [ASD], attention-deficit/hyperactivity disorder [ADHD], typically developing [TD]) and carefully consider the impact of comorbid ASD and ADHD on functional brain network integrity in a sample adequately powered to detect large effects. We also assess the neurobiological separability of a novel, potential alternative categorical scheme based on behavioral measures of executive function.

Method

Five-minute resting-state fMRI data were obtained from 168 children (128 boys, 40 girls) with ASD, ADHD, comorbid ASD and ADHD, and TD children. Independent component analysis and dual regression were used to compute within- and between-network functional connectivity metrics at the individual level.

Results

No significant group differences in within- or between-network functional connectivity were observed between traditional diagnostic categories (ASD, ADHD, TD) even when stratified by comorbidity (ASD + ADHD, ASD, ADHD, TD). Similarly, subgroups classified by executive functioning levels showed no group differences.

Conclusions

Using clinical diagnosis and behavioral measures of executive function, no differences in functional connectivity were observed among the categories examined. Despite our limited ability to detect small- to medium-sized differences between groups, this work contributes to a growing literature suggesting that traditional diagnostic categories do not define neurobiologically separable groups. Future work is necessary to ascertain the validity of the executive function-based nosology, but current results suggest that nosologies reliant on behavioral data alone may not lead to discovery of neurobiologically distinct categories.

SUBMITTER: Dajani DR

PROVIDER: S-EPMC6356009 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportanceCognitive impairment occurs across the psychosis spectrum and is associated with functional outcome. However, it is unknown whether these shared manifestations of cognitive dysfunction across diagnostic categories also reflect shared neurobiological mechanisms or whether the source of impairment differs.ObjectiveTo examine whether the general cognitive deficit observed across psychotic disorders is similarly associated with functional integrity of 2 brain networks widely implicated in supporting many cognitive domains.Design, setting, and participantsA total of 201 healthy control participants and 375 patients with psychotic disorders from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium were studied from September 29, 2007, to May 31, 2011. The B-SNIP recruited healthy controls and stable outpatients from 6 sites: Baltimore, Maryland; Boston, Massachusetts; Chicago, Illinois; Dallas, Texas; Detroit, Michigan; and Hartford, Connecticut. All participants underwent cognitive testing and resting-state functional magnetic resonance imaging. Data analysis was performed from April 28, 2015, to February 21, 2017.Main outcomes and measuresThe Brief Assessment of Cognition in Schizophrenia was used to measure cognitive ability. A principal axis factor analysis on the Brief Assessment of Cognition in Schizophrenia battery yielded a single factor (54% variance explained) that served as the measure of general cognitive ability. Functional network integrity measures included global and local efficiency of the whole brain, cingulo-opercular network (CON), frontoparietal network, and auditory network and exploratory analyses of all networks from the Power atlas. Group differences in network measures, associations between cognition and network measures, and mediation models were tested.ResultsThe final sample for the current study included 201 healthy controls, 143 patients with schizophrenia, 103 patients with schizoaffective disorder, and 129 patients with psychotic bipolar disorder (mean [SD] age, 35.1 [12.0] years; 281 male [48.8%] and 295 female [51.2%]; 181 white [31.4%], 348 black [60.4%], and 47 other [8.2%]). Patients with schizophrenia (Cohen d = 0.36, P < .001) and psychotic bipolar disorder (Cohen d = 0.33, P = .002) had significantly reduced CON global efficiency compared with healthy controls. All patients with psychotic disorders had significantly reduced CON local efficiency, but the clinical groups did not differ from one another. The CON global efficiency was significantly associated with general cognitive ability across all groups (β = 0.099, P = .009) and significantly mediated the association between psychotic disorder status and general cognition (β = -0.037; 95% CI, -0.076 to -0.014). Subcortical network global efficiency was also significantly reduced in psychotic disorders (F3,587 = 4.01, P = .008) and positively predicted cognitive ability (β = 0.094, P = .009).Conclusions and relevanceThese findings provide evidence that reduced CON and subcortical network efficiency play a role in the general cognitive deficit observed across the psychosis spectrum. They provide new support for the dimensional hypothesis that a shared neurobiological mechanism underlies cognitive impairment in psychotic disorders.