Research Review: Brain network connectivity and the heterogeneity of depression in adolescence – a precision mental health perspective

Background Early pubertal maturation has been posited to be a biopsychosocial risk factor for the onset of internalizing psychopathology in adolescence; further, early-maturing youth exhibit heightened reactivity to stressful events. School closures and enforced social distancing, as well as health and financial uncertainties, during the COVID-19 pandemic are expected to adversely affect mental health in youth, particularly adolescents who are already at risk for experiencing emotional difficulties. The executive control network (ECN) supports cognitive processes required to successfully navigate novel challenges and regulate emotions in stressful contexts. Methods : We examined whether functional coherence of the ECN, measured using resting-state fMRI five years before the pandemic (at T1), is a neurobiological marker of resilience to increases in the severity of internalizing symptoms during COVID-19 in adolescents who were in more advanced stages of puberty at T1 relative to their same-age peers (N=85; 49 F). Results On average, participants reported an increase in symptoms from the three months prior to pandemic to the two most recent weeks during the pandemic. We found that early-maturing youth exhibited greater increases in internalizing symptoms during the pandemic if their ECN coherence was low; in contrast, relative pubertal stage was not associated with changes in internalizing symptoms in adolescents with higher ECN coherence at T1. Conclusions These findings highlight the role of the functional architecture of the brain that supports executive functioning in protecting against risk factors that may exacerbate symptoms of internalizing psychopathology during periods of stress and uncertainty.

Background Major depressive disorder (MDD) is a clinically and biologically heterogeneous syndrome. Identifying discrete subtypes of illness with distinguishing neurobiological substrates and clinical features is a promising strategy for guiding personalised therapeutics. Aims This study aimed to identify depression subtypes with correlated patterns of functional network connectivity and clinical symptoms by clustering patients according to a weighted linear combination of both features in a relatively large, medication-naïve depression sample. Method We recruited 115 medication-naïve adults with MDD and 129 matched healthy controls, and evaluated all participants with magnetic resonance imaging. We used regularised canonical correlation analysis to identify component mapping relationships between functional network connectivity and symptom profiles, and K-means clustering was used to define distinct subtypes of patients. Results Two subtypes of MDD were identified: insomnia-dominated subtype 1 and anhedonia-dominated subtype 2. Subtype 1 was characterised by abnormal hyperconnectivity within the ventral attention network and sleep maintenance insomnia. Subtype 2 was characterised by abnormal hypoconnectivity in the subcortical and dorsal attention networks, and prominent anhedonia symptoms. Conclusions Our study identified two distinct subtypes of patients with specific neurobiological and clinical symptom profiles. These findings advance understanding of the biological and clinical heterogeneity of MDD, offering a pathway for defining categorical subtypes of illness via consideration of both biological and clinical features.

Background Neurophysiological patterns may distinguish which youth are at risk for the well-documented increase in internalizing symptoms during adolescence. Adolescents with internalizing problems exhibit altered resting-state functional connectivity (RSFC) of brain regions involved in socio-affective processing. Whether connectivity-based biotypes differentiate adolescents’ levels of internalizing problems remains unknown. Method Sixty-eight adolescents (37 females) reported on their internalizing problems at ages 14, 16, and 18 years. A resting-state functional neuroimaging scan was collected at age 16. Time-series data of 15 internalizing-relevant brain regions were entered into the Subgroup-Group Iterative Multi-Model Estimation program to identify subgroups based on RSFC maps. Associations between internalizing problems and connectivity-based biotypes were tested with regression analyses. Results Two connectivity-based biotypes were found: a Diffusely-connected biotype (N = 46), with long-range fronto-parietal paths, and a Hyper-connected biotype (N = 22), with paths between subcortical and medial frontal areas (e.g. affective and default-mode network regions). Higher levels of past (age 14) internalizing problems predicted a greater likelihood of belonging to the Hyper-connected biotype at age 16. The Hyper-connected biotype showed higher levels of concurrent problems (age 16) and future (age 18) internalizing problems. Conclusions Differential patterns of RSFC among socio-affective brain regions were predicted by earlier internalizing problems and predicted future internalizing problems in adolescence. Measuring connectivity-based biotypes in adolescence may offer insight into which youth face an elevated risk for internalizing disorders during this critical developmental period.