Anticevic, Alan

Decades of research on biomarker identification and integration in Alzheimer’s disease (AD) have helped to advance biologically driven disease models, disease subtypes, and disease-modifying treatments. Key lessons learned from AD biomarker development include the need for integration of new biological insights, investment in large cross-sectional and longitudinal studies, a multicomponent biomarker approach, and recruitment of clinical trial cohorts and biosamples that are representative of the target population. We describe how these lessons are being applied in Parkinson’s disease, Huntington’s disease, multiple sclerosis, and psychotic disorders as use cases to inform biomarker-based approaches across central nervous system disorders.