A mass spectrometry-based strategy allows signature metabolite identification in tear fluid from people with diabetic cataracts.

Metabolic biomarker discovery in trace body fluids remains a significant challenge, toward molecular diagnosis and pathology studies in many diseases. Especially for eye-related diseases, such an approach based on non-invasive tear fluids remains an unsatisfied urgent need in ophthalmology. Here we construct a metabolic biomarker panel from 10 nL of tear fluids in seconds using nanoparticle-enhanced laser desorption/ionization -mass spectrometry (MS), which achieves an area under the curve of 0.923 for discriminating diabetic cataracts from alone age-related cataracts. Importantly, we integrate liquid chromatography -MS into the above analysis process to construct an integrated strategy, allowing reliable metabolite annotation by nanoliter sample volume without compromising high throughput. Further, using matched aqueous humors, we identify 1,5-anhydroglucitol as a biomarker of diabetic cataracts, revealing its protective effect against high glucose-induced lens oxidative stress and opacification, as a demonstration of the metabolic reprogramming. Our approach can be universally applied to uncover biomarkers using trace body fluid, promising next-generation metabolic reprogramming identification.