Resting state functional connectivity in patients with remitted psychotic depression: A multi-centre STOP-PD study

Abstract

BackgroundThere is paucity of neurobiological knowledge about major depressive disorder with psychotic features (“psychotic depression”). This study addresses this knowledge gap by using resting state functional magnetic resonance imaging (R-fMRI) to compare functional connectivity in patients with psychotic depression and healthy controls.MethodsWe scanned patients who participated in a randomized controlled trial as well as healthy controls. All patients achieved remission from depressive and psychotic symptoms with sertraline and olanzapine. We employed Independent Component Analysis in independent samples to isolate the default mode network (DMN) and compared patients and controls.FindingsThe Toronto sample included 28 patients (mean [SD], age 56·2 [13·7]) and 39 controls (age 55·1 [13·5]). The Replication sample included 29 patients (age 56·1 [17·7]) and 36 controls (age 48·3 [17·9]). Patients in the Toronto sample demonstrated decreased between-network functional connectivity between the DMN and bilateral insular, somatosensory/motor, and auditory cortices with peak activity in the right planum polare (t = 4·831; p = 0·001, Family Wise Error (FWE) corrected). A similar pattern of between-network functional connectivity was present in our Replication sample with peak activity in the right precentral gyrus (t = 4·144; p = 0·003, FWE corrected).InterpretationRemission from psychotic depression is consistently associated with an absence of increased DMN-related functional connectivity and presence of decreased between-network functional connectivity. Future research will evaluate this abnormal DMN-related functional connectivity as a potential biomarker for treatment trajectories.FundingNational Institute of Mental Health.

Iranian Brain Imaging Database: A Neuropsychiatric Database of Healthy Brain

“…Neuroimaging data are also primarily used for disease diagnosis research: as a few examples, fMRI is used for the diagnosis of depression (Neufeld et al, 2018), bipolar disorder (Li, Liu, Andari, Zhang, & Zhang, 2018), Alzheimer disease (Oghabian, Batouli, Norouzian, Ziaei, & Sikaroodi, 2010), aging (Batouli et al, 2009), autism (He et al, 2018), epilepsy (Klugah-Brown et al, 2018), and coma (Tomaiuolo et al, 2016). The analyses for functional connectivity between brain areas are also helpful in diagnosing mild cognitive impairment (Lin, Xing, & Han, 2018), lateral sclerosis (Clark et al, 2018), addiction (Zare Sadeghi et al, 2017), and many other conditions (Du, Fu, & Calhoun, 2018).…”

Indexing the neurobiology of psychotic depression with resting state connectivity: Insights from the STOP-PD study

“…Notably, the replication sample of patients with remitted psychotic depression had a similar pattern of functional connectivity. This suggests that the lack of increased DMN associated functional connectivity and attenuated between-network connectivity may be neurobiological correlates of remitted psychotic depression ([ 8 ] (In Press)).…”

“…Further, DMN, hyperactivity and hyperconnectivity may be associated with psychotic symptoms and a reflection of decreased gamma-Aminobutyric acid neurotransmission [ 9 ]. Given that the present study by Voineskos and colleagues is the first of its kind and cross-sectional, it is unclear if the demonstrated pattern of a lack of DMN hyperconnectivity to other brain regions is a trait biomarker of psychotic depression or a reflection of dynamic brain changes associated with remission from psychotic depression ([ 8 ] (In Press)). Regardless, this important work establishes a benchmark for future longitudinal studies of psychotic depression.…”

“…Clinical diagnoses such as MDD with psychotic features have substantial heterogeneity that contributes to poor outcomes and uncertainty in treatment approaches. Resting state functional connectivity studies such as the effort by Voineskos and colleagues hold promise for understanding the neurobiology of psychiatric disorders and honing treatment approaches ([ 8 ] (In Press)). However, one current challenge and unfortunate irony is the widespread heterogeneity of reported findings in neuroimaging literature.…”

“…Multimodal work assimilating neuroimaging findings with risk genes, epigenetic markers, refined clinical characterization, and measures of environment will likely be key factors to unlock the mysteries of psychiatric heterogeneity. The study by Voineskos and colleagues is an important step in this process and has provided exciting new insights regarding the neurobiology of psychotic depression([ 8 ] (In Press)).…”