Functional connectomics of affective and psychotic pathology

Abstract

Converging evidence indicates that groups of patients with nominally distinct psychiatric diagnoses are not separated by sharp or discontinuous neurobiological boundaries. In healthy populations, individual differences in behavior are reflected in variability across the collective set of functional brain connections (functional connectome). These data suggest that the spectra of transdiagnostic symptom profiles observed in psychiatric patients may map onto detectable patterns of network function. To examine the manner through which neurobiological variation might underlie clinical presentation, we obtained fMRI data from over 1,000 individuals, including 210 diagnosed with a primary psychotic disorder or affective psychosis (bipolar disorder with psychosis and schizophrenia or schizoaffective disorder), 192 presenting with a primary affective disorder without psychosis (unipolar depression, bipolar disorder without psychosis), and 608 demographically matched healthy comparison participants recruited through a large-scale study of brain imaging and genetics. Here, we examine variation in functional connectomes across psychiatric diagnoses, finding striking evidence for disease connectomic “fingerprints” that are commonly disrupted across distinct forms of pathology and appear to scale as a function of illness severity. The presence of affective and psychotic illnesses was associated with graded disruptions in frontoparietal network connectivity (encompassing aspects of dorsolateral prefrontal, dorsomedial prefrontal, lateral parietal, and posterior temporal cortices). Conversely, other properties of network connectivity, including default network integrity, were preferentially disrupted in patients with psychotic illness, but not patients without psychotic symptoms. This work allows us to establish key biological and clinical features of the functional connectomes of severe mental disease.

Shared and unique brain network features predict cognition, personality and mental health in childhood

“…Similarly, in the case of mental health measures, while diagnostically distinct psychiatric disorders are likely the result of differentially disrupted brain systems, there is significant comorbidity among disorders and overlap in clinical symptoms (Kessler et al 2011, Tamminga et al 2013, Russo et al 2014 . Certain brain circuits have also been disproportionately reported to be transdiagnostically aberrant across multiple psychiatric and neurological disorders (Menon 2011, Whitfield-Gabrieli and Ford 2012, Goodkind et al 2015, Baker et al 2019, Kebets et al 2019 . For instance, there is evidence for the core role of frontoparietal network disruptions across psychiatric diagnosis (Cole, Repovš, et al 2014) .…”

Whole-brain estimates of directed connectivity for human connectomics

“…Connectomics is not only crucial for studying organizational principles in the healthy human brain, but also in disease. Aberrant functional integration has been observed in most psychiatric and neurological disorders [15][16][17][18] However, to render connectomics useful for understanding large-scale brain networks and alterations thereof, individual connection estimates have to be neurobiologically interpretable.…”

Convergent molecular, cellular, and neural signatures of major depressive disorder

“…For instance, our whole-cortex analyses revealed a surprising pattern of slightly increased visual cortex thickness in patients relative to controls (Figure 1), an effect that may be missed by small samples or hypothesis driven examinations of select brain areas. Of interest, this anatomical effect may, at least in part, explain patterns of increased functional connectivity in occipital cortex, reported both here through other collection efforts 73 . We also find that MDD and trait negative affect were associated with distributed functional changes that dissociate unimodal versus heteromodal cortex ( Supplementary Figure 2).…”