Longitudinal Assessment of Biomarkers for Predicting Alzheimer's Disease Progression: A Prospective Cohort Study in Thailand

Introduction: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory impairment. Early identification and prediction of disease progression are critical for timely intervention and management. This prospective cohort study aimed to investigate the longitudinal trajectories of various biomarkers and their predictive value for AD progression in a Thai population. Methods: A cohort of participants, including individuals with mild cognitive impairment (MCI) and cognitively normal older adults, were recruited from memory clinics and community settings in Thailand. Baseline assessments included clinical evaluations, neuropsychological tests, and biomarker measurements (cerebrospinal fluid (CSF) biomarkers, neuroimaging, and blood-based markers). Participants underwent follow-up assessments at regular intervals over several years to track disease progression. Results: The study identified longitudinal changes in various biomarkers associated with AD progression. CSF biomarkers, such as amyloid-beta (Aβ) and tau, showed significant alterations over time, with decreasing Aβ and increasing tau levels observed in individuals transitioning from MCI to AD. Neuroimaging markers, including hippocampal volume and cortical thickness, demonstrated progressive atrophy in AD patients. Blood-based markers, such as neurofilament light chain (NfL), showed promising potential as predictors of disease progression. Conclusion: This study provides valuable insights into the longitudinal trajectories of biomarkers and their predictive value for AD progression in the Thai population. The findings support the use of a multi-modal biomarker approach for early identification and monitoring of AD, paving the way for personalized interventions and improved patient management.

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Publication Details

Journal
Sriwijaya Journal of Neurology
Published
2024-08-21
DOI
https://doi.org/10.59345/sjn.v2i1.154
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

Longitudinal Assessment of Biomarkers for Predicting Alzheimer's Disease Progression: A Prospective Cohort Study in Thailand

Serene Hanphanitphan
Sriwijaya Journal of Neurology
Artificial Intelligence in Healthcare
article

Longitudinal Assessment of Biomarkers for Predicting Alzheimer's Disease Progression: A Prospective Cohort Study in Thailand

Serene Hanphanitphan
article en

Abstract

Introduction: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory impairment. Early identification and prediction of disease progression are critical for timely intervention and management. This prospective cohort study aimed to investigate the longitudinal trajectories of various biomarkers and their predictive value for AD progression in a Thai population. Methods: A cohort of participants, including individuals with mild cognitive impairment (MCI) and cognitively normal older adults, were recruited from memory clinics and community settings in Thailand. Baseline assessments included clinical evaluations, neuropsychological tests, and biomarker measurements (cerebrospinal fluid (CSF) biomarkers, neuroimaging, and blood-based markers). Participants underwent follow-up assessments at regular intervals over several years to track disease progression. Results: The study identified longitudinal changes in various biomarkers associated with AD progression. CSF biomarkers, such as amyloid-beta (Aβ) and tau, showed significant alterations over time, with decreasing Aβ and increasing tau levels observed in individuals transitioning from MCI to AD. Neuroimaging markers, including hippocampal volume and cortical thickness, demonstrated progressive atrophy in AD patients. Blood-based markers, such as neurofilament light chain (NfL), showed promising potential as predictors of disease progression. Conclusion: This study provides valuable insights into the longitudinal trajectories of biomarkers and their predictive value for AD progression in the Thai population. The findings support the use of a multi-modal biomarker approach for early identification and monitoring of AD, paving the way for personalized interventions and improved patient management.

Sriwijaya Journal of NeurologyVol. 2(1)
Good health and well-being
Openalex Percentile: Top 83%
Artificial Intelligence in Healthcare
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