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Yinan Zhang

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Jul 2026

Metabolomic and Lipidomic Profiling Reveals Dysregulated Glycerophospholipid Metabolism in New-Onset Acute Vogt-Koyanagi-Harada Disease.

PURPOSE Vogt-Koyanagi-Harada (VKH) disease is a sight-threatening autoimmune disorder whose early systemic metabolic alterations remain poorly defined. We aimed to characterize plasma metabolomic and lipidomic signatures in new-onset acute VKH disease and to explore their clinical relevance. DESIGN Retrospective case-control study. PARTICIPANTS Twenty-six patients with new-onset acute VKH disease and 39 healthy controls were included. METHODS Untargeted metabolomics and quantitative lipidomics were performed in plasma from treatment-naïve VKH patients and healthy controls. An elastic net model was applied to identify a discriminative glycerophospholipid signature. MAIN OUTCOME MEASURES Differential metabolites and lipids and their correlations with cerebrospinal fluid (CSF) white blood cell (WBC) count and subfoveal choroidal thickness (SFCT) were analyzed. RESULTS Metabolomics identified 74 significantly altered metabolites, with lipids as the predominate class and glycerophospholipid metabolism as a core perturbed pathway. Lipidomics further revealed 262 significantly altered lipids, with 254 downregulated in the VKH group. Glycerophospholipids predominated among the altered lipids (67.2%), representing a marked enrichment compared with their proportion in the overall lipidome (43.9%, p < 0.0001). Nine glycerophospholipids correlated negatively with CSF WBC count (all p < 0.05), with PE(16:0_22:4) showing the strongest association (r = -0.59, p = 0.003). Three phosphatidylcholine species correlated negatively with SFCT (all p < 0.05). An elastic net model identified a 25-glycerophospholipid signature that achieved an area under the curve of 0.953 in discriminating VKH patients from healthy controls. CONCLUSIONS These findings highlight dysregulated glycerophospholipid metabolism as a key metabolic feature of new-onset acute VKH disease and provide additional insights into disease pathogenesis.

Yang Deng, Ziqian Huang, Xiaoran Jiang et al. · 0 citations

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