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Review
. 2020 Dec;61(12):1282-1298.
doi: 10.1111/jcpp.13250. Epub 2020 May 26.

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

Affiliations
Review

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

Rajpreet Chahal et al. J Child Psychol Psychiatry. 2020 Dec.

Abstract

Background: Adolescence is a period of high risk for the onset of depression, characterized by variability in symptoms, severity, and course. During adolescence, the neurocircuitry implicated in depression continues to mature, suggesting that it is an important period for intervention. Reflecting the recent emergence of 'precision mental health' - a person-centered approach to identifying, preventing, and treating psychopathology - researchers have begun to document associations between heterogeneity in features of depression and individual differences in brain circuitry, most frequently in resting-state functional connectivity (RSFC).

Methods: In this review, we present emerging work examining pre- and post-treatment measures of network connectivity in depressed adolescents; these studies reveal potential intervention-specific neural markers of treatment efficacy. We also review findings from studies examining associations between network connectivity and both types of depressive symptoms and response to treatment in adults, and indicate how this work can be extended to depressed adolescents. Finally, we offer recommendations for research that we believe will advance the science of precision mental health of adolescence.

Results: Nascent studies suggest that linking RSFC-based pathophysiological variation with effects of different types of treatment and changes in mood following specific interventions will strengthen predictions of prognosis and treatment response. Studies with larger sample sizes and direct comparisons of treatments are required to determine whether RSFC patterns are reliable neuromarkers of treatment response for depressed adolescents. Although we are not yet at the point of using RSFC to guide clinical decision-making, findings from research examining the stability and reliability of RSFC point to a favorable future for network-based clinical phenotyping.

Conclusions: Delineating the correspondence between specific clinical characteristics of depression (e.g., symptoms, severity, and treatment response) and patterns of network-based connectivity will facilitate the development of more tailored and effective approaches to the assessment, prevention, and treatment of depression in adolescents.

Keywords: Depression; adolescence; brain networks; connectivity; heterogeneity; precision mental health.

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Conflict of interest statement

Conflict of interest statement: No conflicts declared.

Figures

Figure 1.
Figure 1.
A schematic of precision mental health of adolescence The goal of precision mental health of adolescence is to identify the optimal intervention(s) for depressed youth by associating treatment response with neurophenotypes – for example, based on brain network heterogeneity. Resting-state fMRI data may help us attain this goal. Initial findings suggest that patterns of resting-state functional connectivity (RSFC) cross traditional diagnostic boundaries and may elucidate brain-symptom phenotypes that could inform tailored treatments. In this figure, we convey how depressed adolescents may differ in patterns of RSFC, and how those neural signatures may elucidate individual differences in response to various treatments (e.g., antidepressant medication, psychotherapy, electroconvulsive therapy, transcranial magnetic stimulation, and other forms of treatment).

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