Resilience beyond diagnosis: prospective neural correlates of better-than-expected outcomes in depression.

Resilience, the ability to adapt positively in the face of adversity, is shaped by combined influences of risk and protective factors. Previous neuroimaging studies on resilience have predominantly focused on single factors, often operationalizing resilience dichotomously as the absence of psychiatric disorders despite adversity. In this prospective magnetic resonance imaging study, we defined resilience as "better-than-expected" depressive symptom severity (Hamilton Depression Rating Scale) relative to cumulative risk across 22 risk and protective variables. Using ridge-regularized regression in N = 1804 participants (955 healthy, 849 depressed) from the Marburg-Münster Affective Disorders Cohort Study, we predicted symptom severity and derived residuals as measures of resilience. Residuals were then used to predict gray matter volume (GMV) and cortical thickness at baseline (T1) and two-year follow-up (T2; N = 808). This approach was complemented by extreme-group comparisons of resilient (better-than-expected outcome) and vulnerable (worse-than-expected outcome) individuals. Cumulative risk explained 49.6% of variance in depressive symptoms at T1 and 40.1% at T2. Residual scores showed moderate temporal stability (r = 0.32, p < 0.001). Region-of-interest and whole-brain analyses revealed no morphometric associations with resilience at T1. In contrast, higher resilience at T1 predicted lower GMV in the left inferior orbitofrontal gyrus (IOFG) and temporal pole at T2 (ROI, pFWE(peak)<0.001, rpartial = 0.18), with no changes in cortical thickness. Taken together, resilience to cumulative risk, defined as better-than-expected depressive symptom severity, was not associated with immediate brain structural differences. However, prospective analyses revealed smaller GMV in the IOFG and temporal pole over time, potentially reflecting greater neural efficiency or delayed biological costs.