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Label-free atherosclerosis diagnosis through a blood drop of apolipoprotein E knockout mouse model using
Sanghwa Lee1, Miyeon Jue1, Minju Cho1
1Biomedical Engineering Research Center Asan Medical Center Seoul Republic of Korea.
Bioengineering & Translational Medicine
|July 21, 2023
Summary
This study introduces a novel method for early atherosclerosis detection using a single blood drop and surface-enhanced Raman spectroscopy (SERS). The technique accurately diagnoses and classifies disease severity, paving the way for improved preventative care.
Area of Science:
- Biomedical Engineering
- Nanotechnology
- Spectroscopy
Background:
- Early detection of atherosclerosis, particularly flow-induced types, is crucial for effective treatment and prevention.
- Current diagnostic methods often lack the sensitivity for early-stage detection, necessitating advanced approaches.
Purpose of the Study:
- To develop and validate a method for diagnosing and classifying atherosclerosis severity using nanometer biomarker measurements from single blood drops.
- To leverage surface-enhanced Raman spectroscopy (SERS) and machine learning for non-invasive, early-stage vascular disease detection.
Main Methods:
- Apolipoprotein E knockout mice were used to induce atherosclerosis via high-fat diet and carotid ligation.
- Single blood drops were analyzed using SERS on gold-coated ZnO nanorod chips.
- Principal Component Analysis (PCA) and PCA-PLS-DA machine learning algorithms were employed for spectral analysis and classification.
Main Results:
- The PCA-based method achieved 94.5% accuracy in classifying atherosclerosis severity (control, mild, severe).
- The PCA-PLS-DA algorithm demonstrated even higher accuracy at 97.5%.
- The study successfully correlated bloodborne nanometer biomarkers and vascular factors with early atherosclerosis development.
Conclusions:
- Diagnosing and grading atherosclerosis severity is feasible with a single blood drop, SERS, and machine learning.
- This approach offers a promising avenue for non-invasive, early detection of atherosclerosis.
- The findings highlight the potential for identifying blood biomarkers indicative of early vascular disease stages.
