Neural markers of depression risk predict the onset of depression

•Research highlights neural correlates of MDD, however it is unclear whether these correlates reflect the state of depression or a pre-existing risk factor.•We found that resting-state functional connectivity abnormalities in the default mode and cognitive control network that differentiated high-risk from low-risk youth predicted the onset of MDD during adolescence.•Increased functional activation to both happy and fearful faces was also associated with greater decreases in self-reported symptoms of depression.•This preliminary evidence could be used to identify youth at-risk for depression and inform future early intervention strategies to reduce the development of depression. Although research highlights neural correlates of Major Depressive Disorder (MDD), it is unclear whether these correlates reflect the state of depression or a pre-existing risk factor. The current study examined whether baseline differences in brain activations, resting-state connectivity, and brain structural differences between non-symptomatic children at high- and low-risk for MDD based on familial depression prospectively predict the onset of a depressive episode or increases in depressive symptomatology. We re-assessed 44 participants (28 high-risk; 16 low-risk) who had undergone neuroimaging in a previous study 3–4 years earlier (Mean age at follow-up = 14.3 years, SD = 1.9 years; 45% females; 70% Caucasian). We investigated whether baseline brain imaging data (including an emotional face match task fMRI, resting-state fMRI and structural MRI) that differentiated the risk groups also predicted the onset of depression. Resting-state functional connectivity abnormalities in the default mode and cognitive control network that differentiated high-risk from low-risk youth at baseline predicted the onset of MDD during adolescence, after taking risk status into account. Increased functional activation to both happy and fearful faces was associated with greater decreases in self-reported depression symptoms at follow-up. This preliminary evidence could be used to identify youth at-risk for depression and inform early intervention strategies.