Proteomics Advances Offer New Hope for Early Detection and Treatment of Neurological Disorders
Recent advancements in proteomics, coupled with large-scale biobank initiatives like the UK Biobank-Pharma Proteomics Project (UKB-PPP), are revolutionizing our understanding of neurological diseases such as Alzheimer’s disease, Parkinson’s disease and multiple sclerosis. These developments are paving the way for earlier diagnosis, improved patient classification, and the identification of novel therapeutic targets.
The Power of the UK Biobank-Pharma Proteomics Project
The UKB-PPP represents a significant leap forward in neurological research. By combining large-scale proteome profiling – initially using the Olink® Explore 3072 platform and expanding to the Olink® Explore HT platform covering over 5,400 proteins – with genetic and clinical data from over 50,000 (eventually 500,000) UK Biobank participants, researchers have gained access to an unprecedented dataset. This resource is accelerating discoveries at the intersection of genomics and proteomics, offering insights into complex disease mechanisms and enabling more personalized medical interventions.
Neurological Disorders Represented in the UKB-PPP
The UKB-PPP encompasses a wide range of neurological conditions. As of recent data, the project includes cases of:
- Depression (5,446 cases)
- Pain (3,477 cases)
- Sleep disorders (1,872 cases)
- Stroke (893 cases)
- Epilepsy (807 cases)
- Alzheimer’s disease & related dementias (690 cases)
- Parkinson’s disease (342 cases)
- Motor neuronal disease (232 cases)
- Multiple sclerosis (217 cases)
- Schizophrenia (130 cases)
- Total: ~15,000 cases
Predicting Dementia with Plasma Biomarkers
Research utilizing UKB-PPP data has demonstrated the potential to predict dementia up to 10 years before clinical diagnosis. A study by Guo et al. (2024)1 identified 4-11 significant predictive analytes for all-cause dementia (ACD), Alzheimer’s disease (AD), and vascular dementia (VaD). Combining glial fibrillary acidic protein (GFAP) or growth differentiation factor 15 (GDF15) with demographic factors yielded reliable predictions. Notably, GFAP levels, along with neurofilament light chain (NEFL), began to change considerably at least 10 years before incident dementia was identified.
Unraveling Parkinson’s Disease Pathology
Another study leveraged Mendelian randomization and UKB data to uncover proteins associated with Parkinson’s disease (PD). The research identified 38 proteins linked to PD incidence over a 14.5-year follow-up period.2 Six of the top ten most significant proteins were validated in the Parkinson’s Progression Markers Initiative (PPMI) cohort, including integrin alpha V (ITGAV), histidine ammonia-lyase (HNMT), and integrin alpha M (ITGAM). These findings contribute to a better understanding of the early-stage pathology of sporadic PD and aid in biomarker and therapy development.
Multiple Sclerosis: A Large-Scale Proteomic Screen
A recent study assessed markers of multiple sclerosis (MS) risk and disease severity in 407 prevalent MS cases from the UKB.3 Seventy-two proteins were linked to MS, including the novel identification of granzyme A (GZMA) as an MS biomarker. Pathway analysis revealed enrichment of cytokines, cytokine receptors, and lysosomal processing proteins, along with a decrease in proteins involved in leukocyte migration and cell adhesion. The findings demonstrate the value of biobank-scale datasets for discovering alterations in the plasma proteome in MS, potentially leading to new drug targets and improved prognosis.
The Future of Proteomics in Neurology
The UKB-PPP and similar initiatives are poised to continue driving transformative research in neurological science. The expanded dataset, profiling 500,000 UK Biobank members with the Olink® Explore HT platform, promises to reveal even more intricate relationships between proteins and disease, ultimately leading to tailored medicines and more effective diagnostic tools.
References:
- Guo, Y., et al. (2024). Plasma proteomic profiles predict future dementia in healthy adults. Nature Aging. DOI: 10.1038/s43587-023-00565-0.
- Gan, Y.-H., et al. (2025). Large-scale proteomic analyses of incident Parkinson’s disease reveal new pathophysiological insights and potential biomarkers. Nature Aging. DOI: 10.1038/s43587-025-00818-0.
- Jacobs, B.M., et al. (2024). Plasma proteomic profiles of UK Biobank participants with multiple sclerosis. Annals of Clinical and Translational Neurology, 11(3), pp.698–709. DOI: 10.1002/acn3.51990.