Implementing a tridimensional diagnostic framework for personalized medicine in neurodegenerative diseases

Neurodegenerative diseases (NDDs) pose a significant challenge in modern medicine due to their clinical heterogeneity, multifactorial etiologies, and frequent co-pathologies. Traditional diagnostic systems, based on clinical symptoms and post mortem findings, are limited in capturing the complex interactions among genetic, molecular, and neuroanatomical factors. This manuscript introduces a novel tridimensional diagnostic framework that integrates these factors across three key axes: etiology (genetic and environmental influences), molecular markers (primary and secondary biomarkers), and neuroanatomoclinical correlations. Through case studies, we demonstrate the framework's ability to synthesize incomplete datasets, stratify patients, and guide precision medicine. By incorporating omics technologies, neuroimaging, and AI-driven probabilistic modeling, the framework enhances diagnostic accuracy and clinical relevance. This approach may contribute to overcoming the limitations of traditional nosologies, offering a scalable and adaptable tool for both clinical practice and research and advancing the field of precision medicine in NDD management. HIGHLIGHTS: Tridimensional diagnostic system: We propose a new framework that incorporates three axes - etiology, molecular markers, and neuroanatomical-clinical correlations - to enhance diagnostic accuracy for NDDs. Personalized medicine: The tridimensional system enables the integration of genetic, molecular, and clinical data, allowing for highly personalized treatment strategies tailored to individual patients. Proteinopathies as key biomarkers: This diagnostic system emphasizes the use of primary proteinopathies (amyloid, tau, synuclein) and secondary biomarkers (eg, NfL, GFAP) to monitor disease progression and treatment efficacy. Addressing clinical heterogeneity: The framework accommodates the complexity and heterogeneity of NDDs, offering an adaptable diagnostic approach for classical conditions like Alzheimer's disease, Parkinson's disease, frontotemporal dementia, and ALS. Case studies and real-world application: Practical case studies illustrate how this system can be implemented in clinical practice, enabling the combination of DMTs with symptomatic treatments.