Alamar Biosciences, Inc. has partnered with leading research universities to launch a national-scale proteomics initiative aimed at accelerating biomarker discovery and validation for Alzheimer’s disease and related neurodegenerative conditions. The project will utilize Alamar’s NULISAseq Neuro 220 panel to generate large-scale plasma proteomic data from approximately 21,000 samples collected from 10,000 Alzheimer’s Disease Research Center (ADRC) participants across the United States. This initiative seeks to provide the research community with a deeply multiplexed, clinically anchored proteomic dataset to support discovery and translational research.

The project is co-led by professors Sarah Biber, PhD, at Washington University in St. Louis; Sterling Johnson, PhD, at the University of Wisconsin; and Tatiana Foroud, PhD, director of the National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD) at Indiana University. Samples are stored at NCRAD, which provides centralized national infrastructure for coordinated access and biomarker generation at scale. The initiative is part of the CLARiTI portfolio and leverages its infrastructure to support harmonized data workflows.

Profiling will employ Alamar’s NULISAseq Neuro 220 panel, enhanced with a newly added eMTBR-Tau assay. This assay enables simultaneous blood-based representation of tau tangle burden alongside a broad panel of neurodegeneration and neuroinflammation biomarkers. The panel offers the largest number of brain-derived Tau targets along with assays relevant to alpha-synuclein biology and other protein aggregation markers, facilitating the study of multiple neurodegenerative disease pathways within the same cohort.

A central goal of the project is the creation of an open, publicly accessible proteomic dataset linked to National Alzheimer’s Coordinating Center (NACC) IDs. This linkage allows researchers to connect new proteomic profiles with rich longitudinal data available through the ADRC Program, including clinical, cognitive, neuroimaging, genetic, genomic, fluid biomarker, and neuropathology data. AI and computational teams will apply multimodal approaches for disease classification, biomarker discovery, and prediction of disease progression.

The effort has been advanced through partnerships with the Alzheimer’s Association, the Robertson Foundation, an anonymous foundation, and the Alzheimer’s Disease Data Initiative. All data generated through the initiative will be made freely available to the global research community. The next phase of the project will include a national data challenge inviting the broader research community to develop and test new analytical methods using this resource.