The Serum Exosome Derived MicroRNA-135a, -193b, and -384 Were Potential Alzheimer's Disease Biomarkers

Ting Ting Yang1, Chen Geng Liu1, Shi Chao Gao1

  • 1Department of Clinical Laboratory, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.

Abstract

Insights

Serum exosomal microRNAs (miRs) show promise as early diagnostic biomarkers for Alzheimer's disease (AD). Specific miRs, particularly miR-384, can differentiate AD from other dementias, with combinations offering improved early detection.

Area of Science:

  • Biochemistry
  • Neuroscience
  • Molecular Biology

Background:

  • MicroRNAs (miRs) are emerging as potential blood-based biomarkers for neurodegenerative disorders.
  • Alzheimer's disease (AD) diagnosis often relies on clinical assessments and costly imaging, highlighting the need for accessible biomarkers.

Purpose of the Study:

  • To investigate the diagnostic value of exosomal microRNAs (miRs) in serum for Alzheimer's disease (AD).
  • To explore the potential of specific miRs (miR-135a, -193b, -384) as blood-based biomarkers for differentiating AD from other cognitive impairments.

Main Methods:

  • Serum samples from patients with mild cognitive impairment (MCI), dementia of Alzheimer-type (DAT), Parkinson's disease with dementia (PDD), and vascular dementia (VaD) were analyzed.
  • Exosomal microRNA expression levels were quantified using real-time quantitative reverse transcriptase PCR (qRT-PCR).

Main Results:

  • Serum exosomal miR-135a and miR-384 were upregulated, while miR-193b was downregulated in AD patients compared to controls.
  • Exosomal miR-384 demonstrated the strongest ability to discriminate between AD, VaD, and PDD.
  • A combination of miR-135a, -193b, and -384 showed superior performance for early AD diagnosis compared to individual miRs.

Conclusions:

  • Exosomal miRs in serum are potential biomarkers for early AD diagnosis.
  • These findings may offer new insights for disease screening and prevention strategies.
  • The study highlights the utility of cut-off values over reference intervals for interpreting diagnostic results.