Biomarkers for Alzheimer’s Disease in the Current State: A Narrative Review

Serafettin Gunes, Yumi Aizawa, Takuma Sugashi, Masahiro Sugimoto, Pedro Pereira Rodrigues

Research output: Contribution to journalReview articlepeer-review

Abstract

Alzheimer’s disease (AD) has become a problem, owing to its high prevalence in an aging society with no treatment available after onset. However, early diagnosis is essential for preventive intervention to delay disease onset due to its slow progression. The current AD diagnostic methods are typically invasive and expensive, limiting their potential for widespread use. Thus, the development of biomarkers in available biofluids, such as blood, urine, and saliva, which enables low or non-invasive, reasonable, and objective evaluation of AD status, is an urgent task. Here, we reviewed studies that examined biomarker candidates for the early detection of AD. Some of the candidates showed potential biomarkers, but further validation studies are needed. We also reviewed studies for non-invasive biomarkers of AD. Given the complexity of the AD continuum, multiple biomarkers with machine-learning-classification methods have been recently used to enhance diagnostic accuracy and characterize individual AD phenotypes. Artificial intelligence and new body fluid-based biomarkers, in combination with other risk factors, will provide a novel solution that may revolutionize the early diagnosis of AD.

Original languageEnglish
Article number4962
JournalInternational journal of molecular sciences
Volume23
Issue number9
DOIs
Publication statusPublished - 2022 May 1
Externally publishedYes

Keywords

  • Alzheimer’s disease (AD)
  • biomarkers
  • low or non-invasively
  • machine-learning classification

ASJC Scopus subject areas

  • Catalysis
  • Molecular Biology
  • Spectroscopy
  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Organic Chemistry
  • Inorganic Chemistry

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