Connectome-wide network analysis of youth with Psychosis-Spectrum symptoms

Abstract

Adults with psychotic disorders have dysconnectivity in critical brain networks including the default mode (DM) and the cingulo-opercular (CO) networks. However, it is unknown whether such deficits are present in youths with less severe symptoms. We conducted a multivariate connectome-wide association study (CWAS) examining dysconnectivity with resting state functional MRI in a population-based cohort of 188 youths ages 8–22 with psychosis-spectrum (PS) symptoms and 204 typically developing (TD) comparators. We found evidence for multi-focal dysconnectivity in PS youths, implicating the bilateral anterior cingulate, frontal pole, medial temporal lobe, opercular cortex, and right orbitofrontal cortex. Follow-up seed-based and network-level analyses demonstrated that these results were driven by hyper-connectivity among DM regions and diminished connectivity among CO regions, as well as diminished coupling between frontal regions and DM regions. Collectively, these results provide novel evidence for functional dysconnectivity in PS youths, which show marked correspondence to abnormalities reported in adults with established psychotic disorders.

Aberrant Temporal Connectivity in Persons at Clinical High Risk for Psychosis

“…The cluster-defining threshold was Z>1.96, which is equivalent to a one-tailed p of 0.025; the corrected cluster-level threshold was p<0.05. Given the exploratory nature of MDMR, previous reports(35) in clinical samples had used more liberal criteria (for instance cluster defining threshold of Z>1.64 and a smaller number of permutations). Here, we chose a higher height threshold in order to be more conservative and improve the interpretability of the results.…”

“…These ROI-based approaches offer several statistical advantages, though they may present problems of interpretability, especially when investigating distributed relationships among brain regions, such as those captured by measures of functional connectivity. Other studies of both schizophrenia (32), the CHR phase (33) (34) and similar cohorts with psychosis spectrum symptoms (35) have applied data-driven approaches to the analysis of structural and functional imaging data. These data-driven methods can complement and extend hypothesis-driven methods because of their potential to assess whole-brain measures of functional connectivity in an unbiased manner, and to allow for data-driven selection of ROIs that can be subsequently investigated with more traditional seed-based analyses.…”

“…We employed a multivariate approach (multivariate distance matrix regression or MDMR) to evaluate simultaneously the contribution of all the possible functional connections of a given brain region to risk-status and symptoms severity in CHR individuals. This multivariate approach, already successfully applied to the study of psychosis (35), has the advantage of providing a comprehensive and unbiased characterization of the totality of functional connections in the brain, without requiring the high number of statistical tests inherent in the frequently used massive univariate approaches.…”

Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature

“…Complex, distributed disruptions in resting-state networks are consistently implicated in Schizophrenia (Baker et al, 2014; Khadka et al, 2013; Satterthwaite et al, 2015), ADHD (Castellanos and Aoki, 2016; Fair et al, 2012b), and Autism (Kessler et al, 2016; Moseley et al, 2015; Supekar et al, 2013) - though a thorough examination of this literature is beyond the scope of this review. Rather, we turn our attention here to two crucial challenges that are likely to dominate future research efforts into these conditions.…”

A neurogenetic model for the study of schizophrenia spectrum disorders: the International 22q11.2 Deletion Syndrome Brain Behavior Consortium

“…40,41 Neurocognitive measures and neuroimaging parameters show abnormalities in at-risk individuals, suggesting the presence of neurobiological aberrations early in the psychosis process. 42–44 With a known high-risk for schizophrenia, 22q11DS provides the opportunity to systematically investigate early abnormalities in development as well as the emergence of psychotic illness in cross-sectional and prospective studies of individuals who share the same genetic abnormality. 45–47 Investigations applying standard procedures to assess subthreshold psychotic symptoms in 22q11DS have reported their presence across samples.…”