New “omic” technologies are revealing shared and distinct biological pathways within and across neurodegenerative diseases (NDDs), allowing a better understanding of endophenotypes that exceeds the boundaries of the current diagnostic criteria. Moreover, a diagnostic framework is needed that can accommodate the co-pathology and the clinical overlap and heterogeneity of NDDs. Apart from dissecting the reasons for a revolution in how we conceive NDD, this article aims to prompt a change in how we diagnose and classify NDD, drafting a general scheme for a new nosology. As identifying a cause is the key to using the term “disease” properly, we propose using a tridimensional classification based on three axes: (1) etiology or pathogenic mechanism, (2) pathology markers and molecular biomarkers, (3) anatomic–clinical; and three hierarchical levels of etiology: (1) genetic/sporadic (2) cellular pathways and processes, and function of fluidic brain systems, and (3) risk factors.
We propose a tridimensional diagnostic framework that enhances diagnostic accuracy and personalized medicine by incorporating three key axes:
- Etiology: Genetic and environmental factors.
- Molecular Markers: Biomarkers such as amyloid, tau, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP).
- Neuroanatomical-Clinical Correlation: Linking biomarker findings to affected brain regions and clinical symptoms.
By leveraging omics technologies, neuroimaging, and AI-driven probabilistic modeling, this framework allows for more precise patient stratification, improved disease monitoring, and targeted treatment strategies.
Key Contributions
- Addresses Clinical Heterogeneity: Overcomes limitations of traditional disease classifications like Alzheimer's and Parkinson’s, which often fail to account for mixed proteinopathies.
- Enhances Precision Medicine: Facilitates personalized treatment plans based on molecular and anatomical insights.
- Integrates AI and Biomarkers: Uses artificial intelligence to synthesize incomplete datasets, predict disease progression, and refine diagnostic criteria.
- Includes a Timestamped Annotation System: Enables longitudinal tracking of disease progression and response to treatments.
AI Integration: neurodiagnoses.com
To support the implementation of this system, we are actively developing neurodiagnoses.com, an AI-powered platform designed to assist in integrating computational modeling, neuroimaging, biomarker analysis, and clinical data into a unified diagnostic system. This computational science-based tool will enhance diagnostic precision, automate data synthesis, and facilitate real-time patient monitoring, ensuring a scalable and adaptable solution for both clinical practice and research applications.
Discussion & Future Directions
- The framework bridges the gap between molecular findings and clinical practice, allowing for more adaptive and individualized treatment strategies.
- Neurodiagnoses.com will play a crucial role in AI-based data processing, annotation standardization, and probabilistic modeling to refine diagnosis and treatment pathways.
- It supports precision medicine initiatives by improving patient stratification in clinical trials.
Conclusion
This tridimensional diagnostic system provides a scalable, integrative, and clinically relevant tool for diagnosing and managing neurodegenerative diseases. The integration of AI-driven computing science through neurodiagnoses.com represents a paradigm shift towards holistic and precision-based approaches, offering a new nosology that moves beyond classical disease definitions.
References:
. Toward a new nosology of neurodegenerative diseases. Alzheimer's Dement. 2023; 1- 7. https://doi.org/10.1002/alz.13041
2. Menendez-Gonzalez M. Implementing a tridimensional diagnostic framework for personalized medicine in neurodegenerative diseases. Alzheimers Dement. 2025 Feb;21(2):e14591. doi: 10.1002/alz.14591. PMID: 39976261; PMCID: PMC11840702.
