Global protein study reveals new biomarkers for Alzheimer’s disease
A landmark international collaboration has created one of the world’s largest protein datasets, analysing 250 million protein measurements from over 35,000 biofluid samples to identify novel biomarkers for Alzheimer’s disease, Parkinson’s disease, and other neurodegenerative conditions that affect 57 million people globally.
Bill Gates
The Global Neurodegeneration Proteomics Consortium (GNPC) has published groundbreaking research in Nature Medicine revealing new insights into the biological mechanisms underlying major neurodegenerative diseases. The studies, published on 15 July 2025, represent an unprecedented collaborative effort involving 23 research communities worldwide.
Massive dataset enables breakthrough discoveries
The GNPC dataset includes approximately 250 million unique protein measurements from more than 35,000 biofluid samples, including blood plasma, serum, and cerebrospinal fluid. These samples were contributed by 23 partners globally, spanning participants with Alzheimer’s disease, Parkinson’s disease, frontotemporal dementia, and amyotrophic lateral sclerosis, as well as cognitively unimpaired individuals.
“Fortunately, big breakthroughs such as blood-based diagnostic tests and approved antibody treatments are finally turning the tide. We are closer than ever to the day when a diagnosis of Alzheimer’s disease stops being a death sentence,” writes Bill Gates, co-founder and chair of Gates Ventures, in a corresponding commentary. “The Global Neurodegeneration Proteomics Consortium (GNPC) is a perfect example of what is possible when scientists around the world work together.”
Disease-specific protein signatures identified
The research team identified specific proteins associated with each neurodegenerative condition. In Alzheimer’s disease, 27 proteins were significantly elevated compared to controls across multiple study cohorts, including ACHE, SPC25, LRRN1, and CTF1. Conversely, 130 proteins showed consistently lower levels, including VAT1, GPD1, ARPC2, and PA2G4.
For Parkinson’s disease, 40 proteins were elevated across multiple cohorts, including SUMF1, PRR15, AARDC3, and RDH16, while 15 proteins showed decreased levels. The study also revealed distinct protein changes in frontotemporal dementia and amyotrophic lateral sclerosis, with ALS showing a particularly strong signature related to skeletal muscle pathology.
APOE genetic variant reveals immune connections
One of the most significant discoveries concerned the APOE ε4 genetic variant, the strongest known genetic risk factor for Alzheimer’s disease. The researchers identified blood protein signatures that could predict APOE ε4 carrier status with 99% confidence, using just five proteins: SPC25, NEFL, S100A13, TBCA, and LRRN1.
“GNPC researchers identified certain blood signatures that tell us with 99% confidence whether someone has copies of the high-risk APOE4 gene. They also help us understand the role the gene has in inflammation and infection response – two biological mechanisms that may contribute to the disease,” Gates explained.
Accelerated ageing patterns across diseases
The study revealed disease-specific patterns of accelerated biological ageing across different organ systems. Using established organ-specific ageing models, the researchers found that Alzheimer’s disease was associated with accelerated ageing in brain, artery, liver, and intestine tissues, while Parkinson’s disease showed unique links to muscle ageing.
The authors noted that these findings “extend previous work by demonstrating shared and distinct patterns of blood-detectable accelerated organ aging across AD, FTD and PD, underscoring connections between systemic health and neurodegenerative disease that may be related as a cause, correlate or consequence.”
Clinical severity prediction capabilities
The research team developed a 256-protein clinical impairment signature that could predict Clinical Dementia Rating scores with remarkable accuracy. This signature correlated strongly with cognitive decline across Alzheimer’s disease, Parkinson’s disease, and frontotemporal dementia, suggesting potential applications for monitoring disease progression and treatment response.
Implications for drug discovery
The massive dataset offers significant potential for therapeutic target identification. The authors suggest that “very large protein datasets have potential to add value to drug discovery,” noting that genetic targets with support are more likely to progress through drug development pipelines.
“These data, as well as these vignette analyses and those in the accompanying papers, suggest that very large protein datasets have potential to add value to drug discovery,” the authors write. “The proteomic profiles identified include strong support for synaptic dysfunction with proteins identified that are already clearly part of a mechanism targeted for neurodegeneration drug discovery.”
Future directions and accessibility
The GNPC dataset is accessible to consortium members via the Alzheimer’s Disease Data Initiative’s AD Workbench and became publicly available on 15 July 2025. The collaboration plans to expand the dataset with additional cohorts, samples, and analytical platforms in future versions.
The authors emphasise that “only then will we be able to maximize disease insights from GNPC V1 and its combination with other datasets to accelerate translation of insights into the next generation of diagnostics and therapeutics for neurodegenerative diseases.”
This unprecedented collaboration demonstrates the power of international data sharing in advancing our understanding of neurodegenerative diseases and developing new approaches to diagnosis and treatment.
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The collection of papers is available here:
Global Neurodegeneration Proteomics Consortium
