Towards early diagnosis of Alzheimer's disease: Advances in
immune-related blood biomarkers and computational modeling approaches
- URL: http://arxiv.org/abs/2312.02248v2
- Date: Wed, 6 Dec 2023 10:05:42 GMT
- Title: Towards early diagnosis of Alzheimer's disease: Advances in
immune-related blood biomarkers and computational modeling approaches
- Authors: Sophia Krix, Ella Wilczynski, Neus Falg\`as, Raquel S\'anchez-Valle,
Eti Yoles, Uri Nevo, Kuti Baruch, Holger Fr\"ohlich
- Abstract summary: Alzheimer's disease is usually diagnosed late, which contrasts with the currently available treatment options.
We give a background on advances in research on brain-immune system cross-talk in Alzheimer's disease.
We review recent machine learning and mechanistic modeling approaches which leverage modern omics technologies for blood-based immune system-related biomarker discovery.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Alzheimer's disease has an increasing prevalence in the population
world-wide, yet current diagnostic methods based on recommended biomarkers are
only available in specialized clinics. Due to these circumstances, Alzheimer's
disease is usually diagnosed late, which contrasts with the currently available
treatment options that are only effective for patients at an early stage.
Blood-based biomarkers could fill in the gap of easily accessible and low-cost
methods for early diagnosis of the disease. In particular, immune-based
blood-biomarkers might be a promising option, given the recently discovered
cross-talk of immune cells of the central nervous system with those in the
peripheral immune system. With the help of machine learning algorithms and
mechanistic modeling approaches, such as agent-based modeling, an in-depth
analysis of the simulation of cell dynamics is possible as well as of
high-dimensional omics resources indicative of pathway signaling changes. Here,
we give a background on advances in research on brain-immune system cross-talk
in Alzheimer's disease and review recent machine learning and mechanistic
modeling approaches which leverage modern omics technologies for blood-based
immune system-related biomarker discovery.
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