Familial resemblance in mental health symptoms, social and cognitive vulnerability, and personality: A study of patients with depressive and anxiety disorders and their siblings

Background: Investigating siblings of probands with affective disorders enables the identification of psychopathology-related risk features. Leveraging data from an older adult sample, as compared to most previous sibling studies, enabled us to study more definitive clinical profiling across the lifespan. We examined prevalence of depressive/anxiety disorders in siblings, proband-sibling resemblance in psychopathology-related features, and whether unaffected siblings showed higher levels of these features than healthy controls. Methods: The sample (N=929; M_age=50.6) consisted of 256 probands with lifetime depressive and/or anxiety disorders, their 380 siblings, and 293 healthy controls without affected relatives. Fifteen psychopathology-related features were investigated across four domains: mental health symptoms, social vulnerabilities, cognitive vulnerabilities, and personality. Results: Lifetime disorders were present in 50.3% of siblings. Prevalence was 2-3 times higher than Dutch population frequencies. We found small to medium probandsibling resemblance across psychopathology-related features (ρ=0.10-0.32). Unaffected siblings reported poorer interpersonal functioning and more negative life events, childhood trauma, and rumination than healthy controls. Limitations: Due to the cross-sectional study design, the directionality of effects cannot be determined. No inferences can be made about potential differences in familial resemblance in psychopathology-related features between high- and low-risk families. Conclusions: Siblings of probands with affective disorders are at higher risk for depressive/anxiety disorders. Even when unaffected, still show higher psychosocial vulnerability than healthy controls. Nevertheless, the only modest proband-sibling resemblance across psychopathology-related features suggests that individual mechanisms differentiate clinical trajectories across the lifespan. Identification of these mechanisms is crucial to improve resilience in subjects with familial risk.