ADNeuronNet is a large-scale map of protein interactions in human excitatory neurons, to explore how Alzheimer's risk genes work together in disease-relevant cells. The network captures more than 1,700 high-confidence interactions—many previously unknown—linking genetic risk to neuronal pathways and potential disease mechanisms. ADNeuronNet provides a resource for discovering candidate risk genes and guiding future therapeutic research.

Why this project matters

• Alzheimer's disease is marked by amyloid-beta plaques and Tau tangles, but the mechanisms linking genetic risk to neuronal dysfunction remain unclear.
• Proteins operate in interconnected networks, understanding Alzheimer's requires studying how risk-associated proteins interact in disease-relevant brain cells.
• Most existing protein-interaction maps were created in yeast or generic cell lines and may miss important neuron-specific biology.
• We developed ADNeuronNet to map these interactions directly in human excitatory neurons, revealing previously unknown proteins and pathways associated with Alzheimer's disease.
• This resource helps connect genetic discoveries to disease mechanisms and supports the search for new risk genes and therapeutic targets.

This project is lead by Yu Lab at Cornell University, with collaboration with Gan Lab at Weill Cornell Medicine and Cheng Lab at the Cleveland Clinic. The ADNeuronNet platform is designed to be a resource for the research community, enabling exploration of neuron-specific protein interactions and their relevance to Alzheimer's disease.