Plasma proteomic profiles may predict onset of dementia
A recent study published in the Nature Aging journal unveiled the promising use of proteomics in predicting the onset of dementia which offers hope for early detection and intervention.
The study analyzed data from the UK Biobank which included a total of 52,645 adults without dementia and tracked 1,417 incident cases over a span of 14.1 years. The focus of the research was on examining plasma proteins; out of 1,463 proteins studied, GFAP, NEFL, GDF15 and LTBP2 was found to be associated with incident all-cause dementia (ACD), Alzheimer’s disease (AD) and vascular dementia (VaD).
These proteins significantly ranked high in importance ordering and expressed promise in predicting dementia onset when combined with demographic factors. For instance, combining GFAP (or GDF15) with demographics produced highly accurate predictions for ACD (AUC = 0.891) and AD (AUC = 0.872) (or VaD (AUC = 0.912)), even over a 10-year period.
The participants with elevated levels of GFAP were found to be 2.32 times more risk to develop dementia by underlining its potential as a major biomarker for early detection. Also, GFAP and LTBP2 demonstrated high specificity for dementia prediction. Changes in GFAP and NEFL were observed at least a decade before dementia diagnosis which highlights the possibility of identifying high-risk individuals well in advance.
The findings of this study highlight the intricate mechanisms underlying dementia but also offer a hope for proactive screening and intervention strategies. Leveraging proteomics and understanding the predictive power of specific proteins could enable the healthcare professionals to identify individuals at risk of dementia long before symptoms manifest by improving the targeted interventions and outcomes.
Reference:
Guo, Y., You, J., Zhang, Y., Liu, W.-S., Huang, Y.-Y., Zhang, Y.-R., Zhang, W., Dong, Q., Feng, J.-F., Cheng, W., & Yu, J.-T. (2024). Plasma proteomic profiles predict future dementia in healthy adults. In Nature Aging. Springer Science and Business Media LLC. https://doi.org/10.1038/s43587-023-00565-0
