Alzheimer’s disease (AD) remains one of the greatest medical challenges of our time, affecting millions of individuals worldwide with no reliable method for pre-symptomatic detection or accurate prognosis. Current approaches often rely on amyloid and tau biomarkers, which capture only part of the disease process. Our proposal introduces a transformative strategy: integrating cell-free RNA (cfRNA) with proteomic data to create a comprehensive, blood-based diagnostic platform for AD, powered by artificial intelligence (AI).

cf-mRNA reflects the real-time activity of genes across multiple organs, including the brain, and has been shown to reveal both known and novel pathways implicated in AD, such as inflammation, mitochondrial dysfunction, and synaptic signaling. Proteomic data complements this by measuring the protein-level outcomes of these transcriptional changes, capturing the functional impact on cellular systems. Together, these modalities offer a holistic view of disease biology that no single measurement can provide.

A unique value of this integrated dataset lies in its ability to train next-generation AI models. By combining the features from cf-mRNA (differential gene expression, splice variant detection, mutation information) and protein abundance profiles - we can develop multimodal classifiers that achieve higher accuracy and interpretability than single-modality models. Importantly, AI models trained on large, well-annotated datasets—such as the ~6,000 plasma samples Superfluid has already collected from 21 US Alzheimer’s Disease Research Centers—can identify subtle molecular patterns that correlate with early disease, predict progression from mild cognitive impairment, and uncover pathways of resilience in patients who remain cognitively intact despite amyloid positivity.

This proposal will deliver not only a powerful diagnostic tool for AD but also a scalable framework for multi-omic AI-driven precision medicine. By leveraging the synergy of cfRNA, proteomics, and AI, we aim to fundamentally change how neurodegenerative diseases are detected, understood, and treated.