Trace Aqueous Humor Proteome via Macroporous MOF Platform Reveals High‐Resolution Molecular Phenotypes of Diabetic Macular Edema

Abstract

ABSTRACT Diabetic macular edema (DME) is a leading cause of vision impairment worldwide. While aqueous humor (AH) proteomics holds promise for uncovering disease mechanisms and biomarkers, its proteome coverage has been constrained by limited sample volume and low protein concentration. Here, we present quaternary lanthanide‐based macroporous metal–organic frameworks to enrich AH proteins and a corresponding streamline for ultrasensitive trace aqueous humor proteome (TAHP). TAHP permits end‐to‐end sample‐to‐result analysis in <4 h and quantifies >3300 proteins from merely just 1 µL AH. Applied to cataract ( n = 31) and DME ( n = 52) clinical cohorts, TAHP delineated DME molecular landscape and uncovered proteomic signatures of pathological angiogenesis, amplified inflammatory signaling, and compromised antioxidant defenses. By integrating machine learning, we prioritized PAFAH2 as a high‐performance single biomarker for DME stratification (AUC = 0.98 ± 0.02). TAHP enables rapid, robust and deep AH proteomics, offering a broadly accessible platform to decipher proteome atlas across fundus diseases not limited to DME.