2017/03/19 by Rose Ann Huynh, Chandra Mohan · 1 citation
Medicine · Biochemistry, Genetics and Molecular Biology · Neuroscience · #Alzheimer's disease research and treatments #Dementia and Cognitive Impairment Research #Bioinformatics and Genomic Networks #Disease #Cerebrospinal fluid #Senile plaques #Omics #Biomarker #Neuroscience #Medicine #Neuroimaging #Cognitive decline #Proteomics #Alzheimer's disease #Bioinformatics #Pathology #Biology #Dementia #Gene
paper · pdf · doi:10.3389/fneur.2017.00102
openalex publication_date 2017/03/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that slowly destroys memory and thinking skills, resulting in behavioral changes. It is estimated that nearly 36 million are affected globally with numbers reaching 115 million by 2050. AD can only be definitively diagnosed at autopsy since its manifestations of senile plaques and neurofibrillary tangles throughout the brain cannot yet be fully captured with current imaging technologies. Current AD therapeutics have also been suboptimal. Besides identifying markers that distinguish AD from controls, there has been a recent drive to identify better biomarkers that can predict the rates of cognitive decline and neocortical amyloid burden in those who exhibit preclinical, prodromal, or clinical AD. This review covers biomarkers of three main types: genes, cerebrospinal fluid-derived, and blood-derived biomarkers. Looking ahead, cutting-edge OMICs technologies, including proteomics and metabolomics, ought to be fully tapped in order to mine even better biomarkers for AD that are more predictive.