Metabolomic Study of Patients with Wet Age-Related Macular Degeneration in Aqueous Humor

A recent study conducted at the Shanghai Jiao Tong University School of Medicine (Shanghai, China) ascertained metabolic biomarkers and investigated the metabolic alterations associated with aqueous humor (AH) in wet age-related macular degeneration (AMD). Analysis was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify and quantify metabolites. An article resulting from this analysis has been published in Clinical Interventions in Aging (1).

Metabolomics is a research field involving the identification and quantification of small molecules (metabolites) in biological samples and has been utilized to study metabolic alterations associated with various diseases, offering insights into their underlying mechanisms (2,3). Metabolomic analysis of aqueous humor (AH) has exhibited potential in revealing metabolic changes related to eye diseases (4,5). Studies have indicated that myopic patients have significantly different metabolic profiles in AH compared to healthy controls (6).

A common cause of irreversible vision loss in individuals over the age of 50 and constitutes a significant concern in global public health (7,8). AMD can be clinically classified into two forms: dry AMD and wet AMD. Wet AMD, accounting for 90% of blindness cases caused by AMD, is characterized by choroidal neovascularization (CNV) (9,10). Although the diagnosis of wet AMD is conclusive, there is still controversy surrounding the etiology and pathophysiological mechanisms of the condition (1).

The LC-MS/MS analytical procedure utilized an ultra-high-performance liquid chromatography (UPLC) platform equipped with a diode array detector. Chromatographic separation was achieved through a UPLC BEH Amide column (2.1×100mm, 1.7μm) interfaced with a mass spectrometer capability to acquire tandem mass spectrometry (MS/MS) data in a data-dependent acquisition mode, which enabled successive full-scan MS spectrum analysis. The electrospray ionization (ESI) source parameters were set as follows: sheath gas flow rate at 30 arbitrary units, auxiliary gas flow rate at 25 arbitrary units, capillary temperature at 350°C, mass resolution for full MS scan at 60,000, and a mass resolution for MS/MS scans at 7500, with collision-induced dissociation settings appropriately adjusted. The mobile phase was composed of a mixture containing 25 mmol/L ammonium acetate, 25 mmol/L ammonia solution at pH 9.75, and acetonitrile. The autosampler temperature was maintained at 4°C, with a set injection volume of 3 μL (1).

The authors indicated a complex and severe metabolic disruption occurring in the AH of these patients. Also, uncovered valuable metabolic biomarkers linked to wet AMD was observed. These findings may shed light on potential prognostic metabolic biomarkers and novel therapeutic strategies for the prevention or delay of wet AMD development. However, some limitations to this study were noted. The sample size was relatively small, and only specific metabolomics analysis was performed. Further research is warranted to expand the sample size and incorporate other analytical techniques such as genomics and proteomics to comprehensively and systematically elucidate the metabolic features associated with wet AMD. Additionally, the establishment of animal models and experimental validation are important directions for future studies to verify the reliability and corresponding functions of these potential biomarkers (1).

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References

1. Wei, Q.; Tu, X.; Qiu, Q.; Wang, L. Untargeted Metabolomic Study of Patients with Wet Age-Related Macular Degeneration in Aqueous Humor. Clin. Interv. Aging 2024, 19, 1571-1580. DOI: 10.2147/CIA.S475920

2. Lains, I.; Kelly, R.S.; Miller, JB, et al. Human Plasma Metabolomics Study Across All Stages of Age-Related Macular Degeneration Identifies Potential Lipid Biomarkers. Ophthalmology 2018, 125 (2), 245–254. DOI: 10.1016/j.ophtha.2017.08.008

3. Wishart, D. S. Metabolomics for Investigating Physiological and Pathophysiological Processes. Physiol. Rev. 2019, 99 (4),1819–1875. DOI: 10.1152/physrev.00035.2018

4. Li, S.; Ren, J.; Jiang, Z, et al. Metabolomics Identifies and Validates Serum Androstenedione as Novel Biomarker for Diagnosing Primary Angle Closure Glaucoma and Predicting the Visual Field Progression. Elife. 2024, 12, RP91407. DOI: 10.7554/eLife.91407

5. Deng, Y.; Liang, Y.; Lin, S. et al. Design and Baseline Data of a Population-Based Metabonomics Study of Eye Diseases in Eastern China: The Yueqing Ocular Diseases Investigation. Eye Vis. 2020, 7 (1), 8. DOI: 10.1186/s40662-019-0170-1

6. Cuadrado-Vilanova, M.; Liu, J.; Paco, S, et al. Identification of Immunosuppressive Factors in Retinoblastoma Cell Secretomes and Aqueous Humor from Patients. J. Pathol. 2022, 257 (3), 327–339. DOI: 10.1002/path.5893

7. Wong, W. L.; Su, X.; Li, X, et al. Global Prevalence of Age-Related Macular Degeneration and Disease Burden Projection for 2020 and 2040: A Systematic Review and Meta-Analysis. Lancet Glob. Health. 2014, 2 (2), e106–116. DOI: 10.1016/S2214-109X(13)70145-1

8. Guymer, R. H.; Campbell, T. G. Age-Related Macular Degeneration. Lancet2023, 401(10386), 1459–1472. DOI: 10.1016/S0140-6736(22)02609-5

9. Spraul, C. W.; Lang, G. E.; Grossniklaus, H. E.; Lang, G. K. Histologic and Morphometric Analysis of the Choroid, Bruch’s Membrane, and Retinal Pigment Epithelium in Postmortem Eyes with Age-Related Macular Degeneration and Histologic Examination of Surgically Excised Choroidal Neovascular Membranes. Surv. Ophthalmol. 1999, 44 (44 Suppl 1), S10–32. DOI: 10.1016/s0039-6257(99)00086-7

10. Stahl, A. The Diagnosis and Treatment of Age-Related Macular Degeneration. Dtsch. Arztebl. Int. 2020, 117 (29–30), 513–520. DOI: 10.3238/arztebl.2020.0513