[Differential analysis of aqueous humor metabolomics between presenile cataract and senile cataract].

Objective: To explore the differences in metabolites and metabolic pathways in the aqueous humor between patients with presenile cataracts and senile cataracts. Methods: This metabolomic study was conducted at Tianjin Medical University Eye Hospital from August 2020 to September 2022. Eight patients with presenile cataracts (8 eyes) and 8 patients with senile cataracts (9 eyes) were included. Data were collected, including age, gender, preoperative uncorrected visual acuity, intraocular pressure, lens dysfunction index, and axial length. Aqueous humor and anterior capsule tissue samples were obtained during cataract surgery. Metabolites in the aqueous humor were detected using Liquid Chromatography-Mass Spectrometry in a non-targeted approach. The principal component analysis, differential analysis, clustering analysis, and correlation analysis were performed to identify differentially expressed metabolites. These metabolites were ranked based on the fold change (FC). The receiver operating characteristic (ROC) curve analysis and metabolic enrichment analysis were used to identify differential pathways and potential biomarkers for presenile cataracts. Immunohistochemistry was conducted on anterior capsule tissues, and pyruvate levels were measured by colorimetry to validate metabolomic results. Results: Patients with presenile cataracts included 7 males and 1 female, with a mean age of (37.50±4.90) years. Patients with senile cataracts were 7 males and 1 female, with a mean age of (73.44±5.22) years. Except for age, there were no significant differences in baseline data ( P >0.05). A total of 347 differential metabolites were identified, 10 of which were potential biomarkers for presenile cataract according to the ROC curve analysis (all P <0.05), including propoxycaine (log ₂ FC=7.26), 2-methyl-2, 3, 4, 5-tetrahydro-1, 5-benzodiazepine-4-ketone (log ₂ FC=6.35), l -pyroglutamic acid (log ₂ FC=-1.72), leanly-proline (log ₂ FC=-0.77), and choline (log ₂ FC=-0.56) in the positive ion mode, and N-phenylacetyl glutamine (log ₂ FC=-1.84), pyruvate (log ₂ FC=1.07), ascorbic acid (log ₂ FC=0.92), pseudouracil nucleoside (log ₂ FC=-0.68), and palmitic acid (log ₂ FC=-0.51) in the negative ion mode. The metabolic enrichment analysis identified 72 differential pathways (32 cationic and 40 anionic), with significant differences in glutathione metabolism, cysteine and methionine metabolism, glycolysis or gluconeogenesis, pyruvate metabolism, and the citric acid cycle ( P <0.05). The experimental validation showed reduced lactate dehydrogenase and increased pyruvate levels in patients with presenile cataracts ( P <0.05). Conclusions: Pyruvate and nine other metabolites may serve as potential biomarkers for presenile cataracts. Pathways involving glutathione metabolism, cysteine and methionine metabolism, glycolysis or gluconeogenesis, pyruvate metabolism, and the citric acid cycle are notably dysregulated in patients with presenile cataracts.