UP TO 16 PRIZES, VALUED FROM $5,000-$10,000 PLUS MANUSCRIPT FEES
About the GNPC Data Challenge
We're backing accelerated biomarker discovery in Alzheimer's disease and related dementias.
The Global Neurodegeneration Proteomics Consortium (GNPC) is analyzing the largest disease-specific proteomics dataset ever assembled, consisting of over 300 million protein measurements.
Our goal is to use the GNPC v1 Harmonized Dataset to generate insights that could improve detection, prognosis, and treatment pathways. All data analysis is being conducted using AD Workbench.
Questions Being Researched
The GNPC Data Challenge aims to research the following questions:
- Protein dynamics over time: Do longitudinal protein changes track healthy aging and disease progression, including preclinical to post-diagnosis AD?
- Plasma markers & progression: Do plasma changes influence/reflect progression speed? Any promising therapeutic targets?
- Prognostic markers: Can we predict cognitive decline and neurodegeneration?
- Subtyping AD: Can biomarker patterns define meaningful clinical subtypes?
- Delaying onset: Can proteomics inform prevention?
- Early diagnosis: Can we leverage proteomics for earlier detection of disease?
- How do the cellular origins and biological pathways of plasma proteins reflect and influence Alzheimer’s disease processes, and what insights could this provide for developing diagnostic or therapeutic strategies?
GNPC Data Challenge Process
The submission process closed in January 2026.
Competitors from across the globe submitted research projects that analyze the GNPC v1 Harmonized Dataset and optionally leverage additional datasets available via AD Workbench.
Decisions will be announced in Spring 2026.
Partners
GAP Bio-Hermes
Cross-platform AD diagnostics (blood biomarkers, digital tests, cognitive assessments).

Emory Goizueta Alzheimer’s Disease Research Center (ADRC)

University of Kansas Alzheimer’s Disease Research Center (KU ADRC)

Mayo Clinic Study of Aging (MCSA)
Longitudinal biomarkers, cognitive outcomes, and select PET.


