Introduction: Proteomics and Dementia
Proteomics is the large-scale experimental study of proteins and their interactions, function, composition, and structure. Proteomics is used in medicine to identify and monitor biomarkers (a biological molecule that signifies normal or abnormal processes, or the presence of disease) by analyzing proteins in bodily fluids. Understanding biomarkers is key in dementia, where early detection is crucial for slowing the disease from progressing. According to the Alzheimer’s Association, dementia describes an interference with daily life, including loss of memory, language, problem-solving, and other thinking abilities. The three major types of dementia are all-cause dementia (ACD), Alzheimer’s disease (AD), and vascular dementia (VaD). ACD is an umbrella term used to describe a range of neurological conditions affecting the brain that worsen over time. AD occurs when abnormal deposits of proteins form amyloid plaques and tau tangles (both are abnormal clumps of protein fragments) throughout the brain, causing brain inflammation and damage. VaD is a specific type of dementia caused by reduced blood flow to the brain. According to the World Health Organization (WHO), there are almost 10 million new cases of dementia worldwide, making this disease the seventh leading cause of death. With no effective therapies available and costing global economies $1.3 trillion, detecting dementia in the early stages is crucial for the prompt implementation of interventions. In terms of the relation between proteomics and dementia, new studies have found that certain plasma proteins can be used to predict the onset of dementia.
Study: Plasma Proteomic Profiles Predict Future Dementia in Healthy Adults
Given the need for earlier and more accessible diagnostic tools, one major study used proteomics to identify proteins that signal dementia risk years before clinical symptoms arise. Researchers from Fudan University used proteomics to predict dementia onset through a longitudinal study of 52,645 adults without diagnosed dementia from the UK Biobank. From 1,463 plasma proteins, four proteins were found to be consistently associated with ACD, AD, and VaD: GFAP (Glial Fibrillary Acidic Protein), NEFL (Neurofilament Light Chain), GDF15 (Growth Differentiation Factor 15), and LTBP2 (Latent Transforming Growth Factor Beta Binding Protein 2). GFAP is an intermediate filament protein primarily expressed in astrocytes (cells that provide metabolic and structural support). Findings from this study strongly highlight that GFAP is an optimal biomarker for dementia, as individuals with higher GFAP levels were 2.32 times more likely to develop the disease. The protein also showed strong specificity, meaning it was able to predict dementia, but it did not predict other neurological or psychiatric diseases. The study additionally found that GFAP and NEFL levels started to diverge from healthy control levels more than 10 years before the diagnosis of dementia onset, suggesting that these plasma markers reflect early pre-symptomatic neurodegeneration. Thus, researchers suggest that blood tests can accurately identify individuals who are at high risk for dementia a decade before symptoms occur. GFAP could be used in screening, determining risk, and implementing interventions before dementia is fully expressed.
Study: Proteomic Advancements with Alzheimer’s Disease (AD)
AD is marked by amyloid-β plaques, tau tangles, brain cell damage, and inflammation. Research suggests that general health problems such as heart disease, high blood pressure, diabetes, kidney disease, and obesity are linked to cognitive decline and higher AD risk. A study by Jay M. Yarbro and Him K. Shrestha at St. Jude Research Hospital used blood-based proteomic markers to examine overall health and its link to AD-related biomarkers and brain changes. The scientists analyzed data from the Baltimore Longitudinal Study of Aging (BLSA) and the Atherosclerosis Risk in Communities (ARIC) study, where long-term dementia risk was assessed over 25 years. The study found 14 protein-based health indicators in plasma reflecting cardiovascular, kidney, and metabolic health. These plasma indicators reflect underlying systemic health, which suggests that impaired kidney and cardiovascular function may influence brain pathology by disrupting amyloid clearance and increasing neurodegeneration. Kidney disease risk, secondary cardiovascular disease risk, and heart failure prognosis showed strong and consistent associations with lower amyloid-β peptides (Aβ42/40), higher phosphorylated tau (pTau-181), greater neurofilament light chain (NfL; proteins released from neurons during disease or injury), and increased GFAP levels. The study found that kidney and cardiovascular health were strongly linked to higher plasma levels of AD-related proteins, even in participants without a diagnosed disease. These relationships held even after excluding participants with known kidney or cardiovascular disease, suggesting that non-detected disease still impacts AD biomarkers.
These findings suggest that dementia is not solely a disease of the brain, but a condition deeply connected to a person’s overall physical health. Poor kidney and cardiovascular function may create chronic inflammation or reduce the brain’s ability to clear harmful proteins, which can contribute to amyloid buildup, tau changes (increased addition of phosphate groups during phosphorylation can lead to neurotoxic tau tangles) , and neurodegeneration. These health problems often appear years before cognitive symptoms; therefore, combining proteomic biomarkers with routine health measures may allow doctors to identify risk at a much earlier stage.
Study: Using Proteomics to Link Infections to Dementia Risk
Researchers from the Laboratory of Behavioral Neuroscience in Baltimore, Maryland, found that several types of infections, such as influenza, viral infections, respiratory infections, and skin infections, are linked with a higher long-term risk of developing Alzheimer’s disease and related dementias. Six of the fifteen infections examined were associated with specific patterns of brain atrophy (brain tissue loss), specifically in the gray and white matter regions in the temporal lobe (a region important for memory) and occipital lobe (responsible for vision). For example, influenza was linked to gray matter loss in both the temporal and occipital lobes, while herpes viruses primarily affected white matter in the temporal lobe. Additionally, upper and lower respiratory infections and skin infections were related to volume loss in specific brain regions. The volume loss is clinically important because brain atrophy in these areas is strongly associated with cognitive decline and increased dementia risk. By studying blood samples, the team identified 260 immune-related proteins that changed in people with a history of infection. 35 of the immune-related proteins were directly related to shrinkage in brain areas vulnerable to infections. Some of these proteins, such as PIK3CG, PACSIN2, and PRKCB, were also tied to cognitive decline and common dementia biomarkers like Aβ42/40, GFAP, NfL, and pTau-181. The study further showed that certain genetic variants affecting immune-related proteins (including ITGB6 and TLR5) predicted brain volume loss.
The findings suggest that infections may increase dementia risk by triggering immune-driven molecular changes that contribute to neurodegeneration. Moreover, infection-related proteins were associated with changes in cognitive performance over time, with protective proteins generally decreasing and pathogenic proteins increasing after infection. For example, ten protective proteins that decrease after infection were associated with having preserved verbal memory performance over time, with their reduction linked to subsequent cognitive decline. Furthermore, pathway analyses revealed that many of the candidate proteins mentioned above are involved in pathogen-related signaling cascades (how the body responds to infections). Certain medications, such as monoclonal antibodies (proteins that stimulate the immune system), may be able to target these proteins, suggesting prevention or treatment in people who are at a higher risk of dementia due to a history of past infections.
Moving Forward: Using Proteomic Discoveries for Dementia Drug Discoveries
Proteomics offers a powerful opportunity to improve dementia diagnosis and treatment. Current diagnostic tools, such as CSF amyloid and tau tests or MRI, are expensive, invasive, and often inaccessible to older adults who are most affected by dementia. The article notes how existing Alzheimer’s treatments provide limited benefits and require intensive monitoring, making them impractical for many patients. On the other hand, proteomics studies have discovered several protein changes in the brain that are linked to dementia. However, as proteomics produces large data sets, understanding which proteins are the most important to focus on is difficult. The study proposes a solution through a ranking system that can help scientists decide which proteins are the best targets for new tests or treatments. This system looks at variables such as how strongly a protein is linked to a disease, if its location is mostly found in the brain, how safe it would be to target, and whether it could be reached by drugs. By using the ranking system on tau-related proteins, researchers show how large proteomics datasets can be used to speed up the development of more effective and accessible tools to diagnose and treat dementia.
Conclusion
Proteomics offers a powerful new approach for understanding and predicting dementia long before symptoms become apparent. Across both large-scale population studies and focused aging cohorts, specific plasma proteins such as GFAP and NEFL have emerged as strong indicators of early neurodegeneration. These biomarkers can reflect subtle brain changes more than a decade before diagnosis, showing their potential for early intervention and prevention. The connection between cardiovascular and metabolic health with AD-related proteins further highlights the importance of whole-body health in protecting brain function. By integrating proteomics into healthcare, humanity moves closer to a future where dementia can be detected earlier and managed more effectively.
References
Al-Amrani, S. et al (2021, September 27). Proteomics: Concepts and applications in human medicine. World Journal of Biological Chemistry, 12(5), 57-69. https://pmc.ncbi.nlm.nih.gov/articles/PMC8473418/
Alzheimer’s Association. (n.d.). What is Dementia? Symptoms, Causes & Treatment | alz.org. Alzheimer’s Association. Retrieved November 18, 2025, from https://www.alz.org/alzheimers-dementia/what-is-dementia
Duggan, M.R., Peng, Z., Sipilä, P.N. et al. Proteomics identifies potential immunological drivers of postinfection brain atrophy and cognitive decline. Nat Aging 4, 1263–1278 (2024). https://doi.org/10.1038/s43587-024-00682-4
Guo, Y., You, J., & Zhang, Y. (2024, February 12). Plasma proteomic profiles predict future dementia in healthy adults. Nat Aging, 4, 247-260. https://doi.org/10.1038/s43587-023-00565-0
World Health Organization. (2025, March 31). Dementia. World Health Organization (WHO). Retrieved November 18, 2025, from https://www.who.int/news-room/fact-sheets/detail/dementia
Yarbro, J.M., Shrestha, H.K., Wang, Z. et al. Proteomic landscape of Alzheimer’s disease: emerging technologies, advances and insights (2021 – 2025). Mol Neurodegeneration 20, 83 (2025). https://doi.org/10.1186/s13024-025-00874-5