Repurposing schirmer strips for tear biomarker profiling using infrared spectroscopy

Area of Science:

• Ophthalmology
• Analytical Chemistry
• Biomedical Engineering

Background:

• Dry eye disease (DED) is a prevalent ocular condition with various subtypes.
• Accurate diagnosis and subtyping of DED are crucial for effective treatment.
• Current diagnostic methods may have limitations in comprehensively profiling tear biomarkers.

Purpose of the Study:

• To develop and validate a label-free analytical platform using ATR-FTIR spectroscopy on Schirmer strips.
• To profile tear biomarkers for DED diagnosis.
• To assess the platform's utility in differentiating aqueous-deficient DED subtypes.

Main Methods:

• Tear samples collected on Schirmer strips from DED patients and healthy individuals.
• ATR-FTIR spectroscopy analysis of wetted Schirmer strip regions.
• Statistical modeling (stepwise linear regression, sPLS-DA) for spectral analysis and classification.

Main Results:

• ATR-FTIR spectroscopy revealed distinct spectral features in tear samples.
• Spectral Euclidean distance correlated well with biomarker concentrations and clinical parameters.
• Sparse partial least squares discriminant analysis (sPLS-DA) achieved high accuracy (AUC=0.963) in classifying DED subtypes.

Conclusions:

• The developed ATR-FTIR platform on Schirmer strips offers a cost-effective method for tear biomarker profiling.
• This technology enables accurate differentiation of DED subtypes by capturing molecular fingerprints.
• The platform supports the integration of tear-based precision medicine into clinical practice.