DATA-DRIVEN PSYCHOMETRIC ARCHETYPES REVEAL BIOLOGICAL SIGNATURES OF VULNERABILITY, RESILIENCE, AND FUTURE MENTAL HEALTH IN YOUNG ADULTS

Mental health comprises emotional, psychological, and social dimensions and extends beyond the mere absence of illness. Shaped by a complex interplay of hereditary and experiential factors, mental health can deteriorate into clinical conditions. However, blurred boundaries within and between mental health states underscore the need for dimensional approaches to risk detection and stratification. Here, we analyzed multimodal data from 258 young adults, integrating psychometric measures with genomic, neuroimaging, and plasma metabolomic data. Using a psychometry-based soft-clustering approach (archetyping), we identified latent psychological profiles based on cognitive, emotional, and behavioral traits and examined their associations with biological features and mental health outcomes cross-sectionally and at five-year follow-up. We identified five psychometric archetypes spanning a continuum from vulnerability to resilience. Archetypes at the vulnerable end, marked by emotional dysregulation and high neuroticism, were associated with elevated psychiatric polygenic risk, regionally specific cortical alterations, and metabolomic profiles previously linked to psychopathology. In contrast, the resilient archetype showed opposing biological patterns alongside emotional stability and adaptive functioning. Archetype scores were prospectively associated with symptom burden, and biological features prioritized through archetype associations tended to improve prediction of clinical outcomes compared with agnostic feature selection. Together, these findings show that psychometric archetyping provides a dimensional framework for identifying biologically grounded, transdiagnostic features associated with mental health risk in young adulthood.