Multi-biomarker combination detection system for diagnosis and classification of dry eye disease by imaging of a multi-channel metasurface

Abstract

Dry eye disease (DED) is one of the most common ocular surface diseases, characterized by unstable tear film and ocular inflammation, affecting hundreds of millions of people worldwide. Currently, the clinical diagnosis of DED mainly relies on physical methods such as optical microscopy and ocular surface interferometric imaging, but classifying DED is still difficult. Here, we propose a compact and portable immune detection system based on the direct imaging of a nanophotonic metasurface with gradient geometry, for fast and ultra-sensitive detection of multiple biomarkers (i.e. Matrix metalloproteinase-9 (MMP-9), Lipocalin-1 (LCN-1), Lactoferrin (LTF)) in tears for the diagnosis and classification of DED. This centimeter-scale concentric nanophotonic metasurface, which consists of millions of unique metallic nanostructures, was fabricated through a cost-effective nanoimprint lithography (NIL) process. The immune detection system based on the antibody-modified metasurface shows favorable detection selectivity, an ultra-high sensitivity (3350 pixels/Refractive Index Unit (RIU)) and low limit of detection (LOD) (0.3 ng/mL for MMP-9, 1 ng/mL for LTF, and 0.5 ng/mL for LCN-1). Further clinical sampling and detection results demonstrated that this multi-biomarker detection system enabled accurate determination and symptom classification of DED, manifesting high correlation and consistency with clinical diagnosis results. The advantages such as low sample consumption, one-step detection, simple operation, and simultaneous detection of multiple biomarkers make the platform promising for screening and detecting a broader range of biomarker combinations in clinical practice.

Keywords: Biomarker in tears; Dry eye disease; Imaging-based sensing; Metasurface; Multi-biomarker combination.