Platform to identify causal proteins in Alzheimer's for drug discovery
This technology is a computational platform that integrates Mendelian randomization with AlphaFold3 to identify the causal protein biomarkers in Alzheimer’s Disease and guide drug target discovery.
Unmet Need: Quantitative assay to identify disease-related phenotypes
Current methods for identifying causal biomarkers in Alzheimer’s disease are limited by their inability to connect genetic risk and functional protein changes. While Mendelian randomization offers ways to infer causality, it often captures unrelated signals and lacks insight into how mutations impact structure or function. This gap makes it incredibly challenging to prioritize biologically relevant targets in drug development. Addressing these shortcomings is essential to advancing more precise diagnostics and effective therapies for Alzheimer’s and other neurodegenerative diseases.
The Technology: Integrated genetic-structural pipeline identifying causal Alzheimer’s biomarkers
This technology combines a genetic analysis method with AlphaFold3-based protein structure prediction to identify proteins that are causally linked to Alzheimer’s disease. By analyzing large-scale genetic datasets, it identifies mutations associated with disease risk and models how these mutations may alter protein structure. This approach helps bridge the gap between genetic associations and functional protein changes, which will enable researchers to better prioritize therapeutic targets.
Initial analyses using Alzheimer’s Disease datasets identified seven target proteins with potential roles in the disease, along with structural models showing how specific mutations may impact their function.
Applications:
- Diagnostic assays for Alzheimer’s and other neurodegenerative diseases
- Target identification for drug development
- Screening tool for clinicians to predict disease risk
- Tool to assess and evaluate Alzheimer’s progression
- Research tool for understanding neurodegenerative diseases
Advantages:
- Enables automated, high-throughput disease detection
- Can integrate with standard microscopy platforms
- Capable of analyzing hundreds of proteins to identify causal relationships with Alzheimer’s
- Automated, unbiased, objective, and consistent computational platform
Lead Inventor:
Related Publications:
Tech Ventures Reference:
IR CU25371
Licensing Contact: Joan Martinez