The Global Neurodegeneration Proteomics Consortium: biomarker and drug target discovery for common neurodegenerative diseases and aging

Abstract

More than 57 million people globally suffer from neurodegenerative diseases, a figure expected to double every 20 years. Despite this growing burden, there are currently no cures, and treatment options remain limited due to disease heterogeneity, prolonged preclinical and prodromal phases, poor understanding of disease mechanisms, and diagnostic challenges. Identifying novel biomarkers is crucial for improving early detection, prognosis, staging and subtyping of these conditions. High-dimensional molecular studies in biofluids ('omics') offer promise for scalable biomarker discovery, but challenges in assembling large, diverse datasets hinder progress. To address this, the Global Neurodegeneration Proteomics Consortium (GNPC)-a public-private partnership-established one of the world's largest harmonized proteomic datasets. It includes approximately 250 million unique protein measurements from multiple platforms from more than 35,000 biofluid samples (plasma, serum and cerebrospinal fluid) contributed by 23 partners, alongside associated clinical data spanning Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). This dataset is accessible to GNPC members via the Alzheimer's Disease Data Initiative's AD Workbench, a secure cloud-based environment, and will be available to the wider research community on 15 July 2025. Here we present summary analyses of the plasma proteome revealing disease-specific differential protein abundance and transdiagnostic proteomic signatures of clinical severity. Furthermore, we describe a robust plasma proteomic signature of APOE ε4 carriership, reproducible across AD, PD, FTD and ALS, as well as distinct patterns of organ aging across these conditions. This work demonstrates the power of international collaboration, data sharing and open science to accelerate discovery in neurodegeneration research.

Fig. 1. Circulating blood proteome specifies neurodegenerative disease type, mechanism and clinical severity.

a–d, Meta-analytic differential abundance analysis showing changes in relative protein expression of AD (a), PD (b), FTD (c) and ALS (d) compared to Controls. Each dot represents a protein. The x axis shows the direction and effect size of protein changes relative to Controls, from linear regression models including age and sex as covariates; the y axis shows the –log₁₀ FDR-adjusted P value. P values from two-sided tests and after adjustment from FDR are reported. The parallel line at the bottom of each plot shows which proteins are significant after FDR correction for multiple comparisons. The line above shows proteins further surviving Bonferroni correction. Dots are colored based on the number of cohorts where the protein was found to be independently significant after (within-cohort) FDR correction and changed in the same direction relative to Controls (that is, increased or decreased compared to Controls). e–h, Significant proteins from the differential abundance analyses were fed into Reactome enrichment analysis for AD (e), PD (f), FTD (g) and ALS (h), using unique SomaScan 7K proteins as background. Enriched Reactome pathway terms for each condition are visualized as dot plots, with dot size corresponding to the number of differentially abundant proteins assigned to a given pathway (one-sided Fisherʼs test with FDR adjustments). Full Reactome enrichment summary statistics are reported in Supplementary Table 6. HIV, human immunodeficiency virus; FGF, fibroblast growth factor; TBC/RABGAPs, Tre2–Bub2–Cdc16 (TBC) domain-containing RAB-specific GTPase-activating proteins. i, Violin plots displaying LASSO-derived clinical severity protein signatures across CDR global level in training and test sets. j, Violin plots displaying LASSO-derived clinical severity protein signatures across CDR global level (0.5 and higher) in AD, FTD and PD, using the combined training and test sets. k, LASSO coefficients for the top 12 protein aptamers selected in the clinical severity protein signature. avg, average; pFDR, FDR-corrected P value.

Fig. 2. Organ age patterns characterize distinct neurodegenerative disease types.

a, Scatterplots of chronological age versus predicted age for each organ aging clock in clinically normal individuals. Black dashed line indicates the LOWESS regression estimate of the population mean. Pearsonʼs correlation coefficient r is reported for each clock. b, Body plots showing associations of standardized organ age gaps with neurodegenerative disease based on binary logistic regression models. P values are from two-sided tests. Red dots indicate positive associations (higher age gap with disease); blue dots indicate negative associations (lower age gap with disease). Bold labels highlight organ ages associated with organ age gap with P < 0.05 after FDR correction. The body plots were created in BioRender: Oh, H. (2025): https://BioRender.com/afoqtwz.

Fig. 3. Disease-dependent and disease-independent of APOE ε4 on the human proteome.

a, Volcano plot shows the protein association profile of APOE ε4 after adjusting for AD dementia diagnosis, with red representing significant associations (after FDR correction). At the y axis, the −log₁₀(FDR-adjusted P values) > 300 were set to 300 for better visualization. This was done for S100A13, TBCA, NEFL, LRRN1 and SPC25. b,c, Box plots show plasma protein level changes of the proteins with the strongest APOE ε4 associations (b) and for APOE ε4-associated proteins strongly tied to AD dementia diagnosis (c). For b and c, the y axis represents residual protein levels after adjusting for age, sex, mean protein level and contribution site. The center line of each box indicates the median, with lower and upper edges representing the 25th and 75th percentiles. Whiskers extend to the most extreme values within 1.5 times the interquartile range; data points beyond this range were excluded as outliers. The x axis represents AD diagnosis. The color indicates APOE ε4 carrier status; ‘−/−’ indicates APOE ε4 non-carriers; ‘±’ indicates ε3/ε4; and ‘+/+’ indicates ε4/ε4. Welch’s t-test was used to compare residual protein levels between groups. Two-sided P values are reported. ****P < 0.0001 and *P < 0.05. P values were not adjusted for multiple comparisons, as only prespecified group contrasts are shown. Results marked with **** remain significant (pFDR < 0.0001) even after adjustment for multiple comparisons with the Benjamini–Hochberg method, whereas those marked with * do not. d, Receiver operating characteristic area under the curve (ROC-AUC) showing the performance of a machine learning model using only five proteins to predict APOE ε4 status across different diagnostic groups, in a held-out sample. e, Protein interaction network including four of those five proteins (red). f, Neural cell type expression of RNA transcripts encoding the five APOE ε4-predictive proteins. Plot shows mix-max scaling of protein-coding transcripts per million for each identified APOE ε4 protein. g, Correlation of effect sizes for proteins associated with APOE ε4 in cognitively unimpaired samples (x axis) and AD associated with AD diagnosis in APOE ε3/ε3 homozygotes. Limma t-statistic is shown for both contrasts; only proteins associated with both APOE ε4 and AD (adjusted P < 0.05 for both analyses) with the same direction of effect are visualized. For visibility purposes, t-statistic values higher than 10 were capped. PDD, Parkinsonʼs disease dementia; pFDR, FDR-corrected P value.