In a new study that stands as the largest of its kind, scientists have taken a significant step forward in the early detection of dementia, potentially up to 15 years before clinical diagnosis.
This research, conducted by teams from The University of Warwick and Fudan University, Shanghai, has highlighted the power of protein “biomarkers” in the blood to predict the onset of dementia with remarkable accuracy.
Biomarkers are molecules present in blood, body fluids, or tissues that signal normal or abnormal processes, conditions, or diseases.
The study focused on analyzing the profiles of proteins in the blood of 52,645 healthy participants from the UK Biobank, a large-scale population-based study cohort.
These blood samples were collected between 2006 and 2010, frozen, and later analyzed by the researchers between April 2021 and February 2022.
By March 2023, 1,417 of these participants had developed dementia, and their blood samples exhibited dysregulation in certain protein biomarkers.
Through the use of machine learning, the research team identified a panel of 11 proteins that, when combined, showed a high level of accuracy in predicting future dementia.
The inclusion of traditional risk factors—such as age, sex, educational level, and genetics—into the model further enhanced its predictive accuracy, surpassing 90%.
This marks a significant advancement in the potential for community-based dementia screening programs.
Previous studies have identified potential biomarkers for dementia, such as the Glial Fibrillary Acidic Protein (GFAP), but this study’s scale and longitudinal approach provide a more robust analysis.
By tracking participants over 15 years, the researchers could distinguish the trajectories of those who developed dementia from those who did not.
Early diagnosis of dementia is crucial for effective treatment. Recent advancements in drug technology, such as lecanemab, offer the potential to slow or even reverse Alzheimer’s disease progression, but early detection is key.
The lead author, Professor Jianfeng Feng, expressed hope that future drugs could interact with the proteins identified in this study.
The integration of artificial intelligence with protein analysis represents a promising direction for precision medicine, especially for screening individuals at high risk of dementia.
Professor Feng suggested that this model could be integrated into healthcare systems like the NHS and used by general practitioners as a screening tool.
Professor Wei Cheng from Fudan University highlighted the breakthrough nature of this protein-based model compared to previous dementia prediction models developed by the team.
Additionally, Professor Jintai Yu, a neuro-vegetative disease specialist at Fudan University, emphasized the advantages of proteomic biomarkers for large-scale population screening due to their non-invasive nature and ease of access.
This research overcomes the limitations of previous models that relied on invasive and costly procedures, such as lumbar punctures or complex imaging methods, making widespread screening challenging.
Published in Nature Aging, the study’s findings offer a new horizon in the fight against dementia, promising earlier detection and, consequently, more effective intervention.
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The research findings can be found in Circulation.
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