Journal
FRONTIERS IN AGING NEUROSCIENCE
Volume 14, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fnagi.2022.849443
Keywords
late onset Alzheimer's disease; polygenic risk score; biomarker; prediction; brain
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Funding
- National Natural Science Foundation of China [81801687]
- Science & Technology Development Fund of Tianjin Education Commission for Higher Education [2019KJ195]
- Open Research Project of The Beijing Key Laboratory of High Dynamic Navigation Technology [HDN2020102]
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Late-onset Alzheimer's disease is a common neurodegenerative disease with heterogeneous genetic characteristics. Studying multiple biomarkers, such as neuroimaging, cerebrospinal fluid, and plasma, can help predict the probability of developing late-onset Alzheimer's disease and improve the effectiveness of accurate treatment.
Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD.
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