Clinical ophthalmology (Auckland, N.Z.) · 2025
Untargeted Metabolomic Study of Patients with Macular Edema Secondary to Retinal Vein Occlusion in Aqueous Humor.
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Wei Qingquan, Luo Liying, Min Yingjun, Gong Yingying, Wang Li
Аннотация
PURPOSE: The aim of this study was to identify metabolic biomarkers and investigate the metabolic changes associated with aqueous humor in retinal vein occlusion macular edema (RVO-ME).
METHODS: Aqueous humor (AH) samples were collected from patients, including those diagnosed with central retinal vein occlusion macular edema (CRVO-ME), branch retinal vein occlusion macular edema (BRVO-ME), and a control group undergoing cataract surgery. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was utilized to analyze the metabolomic profiles in aqueous humor.
RESULTS: A total of 28 metabolites were identified as potential biomarkers capable of distinguishing RVO-ME patients from the control group. Of these, 26 metabolites were specific for distinguishing CRVO-ME patients from controls, and 24 metabolites were specific for differentiating BRVO-ME patients from controls. Additionally, 9 metabolites were identified that could differentiate CRVO-ME patients from BRVO-ME patients.
CONCLUSION: This study successfully identified significant metabolic biomarkers that enhance our understanding of the pathogenesis of RVO-ME. These findings may offer new avenues for the treatment of RVO-ME and aid in differentiating between CRVO-ME and BRVO-ME patients.
METHODS: Aqueous humor (AH) samples were collected from patients, including those diagnosed with central retinal vein occlusion macular edema (CRVO-ME), branch retinal vein occlusion macular edema (BRVO-ME), and a control group undergoing cataract surgery. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was utilized to analyze the metabolomic profiles in aqueous humor.
RESULTS: A total of 28 metabolites were identified as potential biomarkers capable of distinguishing RVO-ME patients from the control group. Of these, 26 metabolites were specific for distinguishing CRVO-ME patients from controls, and 24 metabolites were specific for differentiating BRVO-ME patients from controls. Additionally, 9 metabolites were identified that could differentiate CRVO-ME patients from BRVO-ME patients.
CONCLUSION: This study successfully identified significant metabolic biomarkers that enhance our understanding of the pathogenesis of RVO-ME. These findings may offer new avenues for the treatment of RVO-ME and aid in differentiating between CRVO-ME and BRVO-ME patients.