ArticleInvestigative ophthalmology & visual science2025
Metabolomic Profiling of Ocular Fluid Identifies Host Response Factors for Risk Stratification in Bacterial Endophthalmitis.
Article in Investigative ophthalmology & visual science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Areas of uncertainty in endophthalmitis care.World journal of clinical cases · 2026Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study aimed to identify metabolite biomarkers in ocular fluid that can serve as indicators of infection severity, guide risk stratification, and monitor the host response to bacterial endophthalmitis. Methods: We performed untargeted metabolomics to profile ocular fluids from 26 patients diagnosed with bacterial endophthalmitis and 17 control samples. Multivariate data analysis and pathway enrichment of metabolites were performed using the MetaboAnalyst R package. Results: The volcano plot analysis revealed significantly altered m/z values (log fold change > 2; P < 0.05), with 1824 m/z values upregulated and 3854 m/z values downregulated species. Notably, the levels of methyl linolenate significantly decreased from grade 2 to grade 5, whereas no significant alterations were observed in grade 1 compared with controls. The peak intensities of palmitoleamide also showed a decrease from grade 2 to grade 5 compared with controls. Conversely, myristoleoyl carnitine exhibited significantly increased levels in both grade 2 and grade 5. Methyl linolenate (AUC, 0.885), palmitoleamide (AUC, 0.885), and myristoleoyl carnitine (AUC, 0.869) were identified as the three metabolites with the highest classification capacity for bacterial endophthalmitis in tear samples. Conclusions: This report is the first of a set of metabolite biomarkers in ocular fluid that correlate with the severity of bacterial endophthalmitis. These biomarkers have the potential to aid in risk stratification and personalized treatment approaches. The metabolomic profiles generated in this study provide insight into the host response mechanisms and the pathophysiology of the infection in human eyes.
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Registered trials
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