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A Machine Learning Approach to Identify a Circulating MicroRNA Signature for Alzheimer Disease.

Xuemei Zhao1, John Kang2, Vladimir Svetnik2

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The Journal of Applied Laboratory Medicine
|December 8, 2019
PubMed
Summary

A novel 12-microRNA (miRNA) signature in blood shows promise for diagnosing Alzheimer disease (AD). This blood test offers a less invasive and potentially more accessible method for AD identification compared to current diagnostics.

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Area of Science:

  • Biomarkers
  • Neuroscience
  • Genomics

Background:

  • Accurate Alzheimer disease (AD) diagnosis requires less invasive and cost-effective molecular methods.
  • Current diagnostic procedures for AD can be invasive and expensive.
  • A reliable blood-based biomarker for AD diagnosis remains an unmet clinical need.

Purpose of the Study:

  • To identify a serum microRNA (miRNA) signature for Alzheimer disease (AD) diagnosis.
  • To develop a less invasive diagnostic tool for AD compared to cerebrospinal fluid analysis.
  • To assess the potential of a miRNA signature for early AD detection.

Main Methods:

  • Serum samples from 96 participants (51 controls, 32 AD, 13 mild cognitive impairment) from the OPTIMA study were analyzed using multiplex miRNA quantitative PCR.
  • Machine learning, including random forest analysis, was employed to construct and validate a 12-miRNA signature for AD identification.
  • Clinical diagnoses were confirmed by postmortem (PM) examination in a subset of participants.

Main Results:

  • A 12-miRNA signature achieved 76.0% accuracy, 90.0% sensitivity, and 66.7% specificity for AD identification in an independent test cohort.
  • The signature did not identify participants with mild cognitive impairment (MCI).
  • A separate signature using PM-confirmed cases showed improved accuracy (85.7%) with high sensitivity (88.9%) and specificity (80.0%).

Conclusions:

  • The developed miRNA signature shows potential as a blood test for diagnosing Alzheimer disease.
  • Further validation in diverse cohorts is necessary to confirm the robustness of the miRNA signature.
  • This blood-based biomarker approach could offer a more accessible diagnostic option for AD.