Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, the Netherlands.
Institute for Ophthalmic Research, Core Facility for Medical Bioanalytics, University of Tübingen, Tübingen, Germany.
PLoS One. 2019 Jun 20;14(6):e0218457. doi: 10.1371/journal.pone.0218457. eCollection 2019.
Age-related macular degeneration (AMD) is a common, progressive multifactorial vision-threatening disease and many genetic and environmental risk factors have been identified. The risk of AMD is influenced by lifestyle and diet, which may be reflected by an altered metabolic profile. Therefore, measurements of metabolites could identify biomarkers for AMD, and could aid in identifying high-risk individuals. Hypothesis-free technologies such as metabolomics have a great potential to uncover biomarkers or pathways that contribute to disease pathophysiology. To date, only a limited number of metabolomic studies have been performed in AMD. Here, we aim to contribute to the discovery of novel biomarkers and metabolic pathways for AMD using a targeted metabolomics approach of 188 metabolites. This study focuses on non-advanced AMD, since there is a need for biomarkers for the early stages of disease before severe visual loss has occurred. Targeted metabolomics was performed in 72 patients with early or intermediate AMD and 72 control individuals, and metabolites predictive for AMD were identified by a sparse partial least squares discriminant analysis. In our cohort, we identified four metabolite variables that were most predictive for early and intermediate stages of AMD. Increased glutamine and phosphatidylcholine diacyl C28:1 levels were detected in non-advanced AMD cases compared to controls, while the rate of glutaminolysis and the glutamine to glutamate ratio were reduced in non-advanced AMD. The association of glutamine with non-advanced AMD corroborates a recent report demonstrating an elevated glutamine level in early AMD using a different metabolomics technique. In conclusion, this study indicates that metabolomics is a suitable method for the discovery of biomarker candidates for AMD. In the future, larger metabolomics studies could add to the discovery of novel biomarkers in yet unknown AMD pathways and expand our insights in AMD pathophysiology.
年龄相关性黄斑变性（AMD）是一种常见的、进行性的多因素致盲性眼病，许多遗传和环境风险因素已被确定。AMD 的风险受生活方式和饮食的影响，这可能反映在代谢谱的改变上。因此，代谢物的测量可以确定 AMD 的生物标志物，并有助于识别高危个体。无假设的技术，如代谢组学，具有很大的潜力来发现与疾病病理生理学相关的生物标志物或途径。迄今为止，只有少数代谢组学研究在 AMD 中进行。在这里，我们旨在通过 188 种代谢物的靶向代谢组学方法，为 AMD 发现新的生物标志物和代谢途径做出贡献。本研究重点关注非晚期 AMD，因为在严重视力丧失发生之前，需要用于疾病早期阶段的生物标志物。在 72 例早期或中期 AMD 患者和 72 例对照个体中进行了靶向代谢组学检测，并通过稀疏偏最小二乘判别分析确定了预测 AMD 的代谢物。在我们的队列中，我们确定了四个对 AMD 的早期和中期阶段最具预测性的代谢物变量。与对照组相比，非晚期 AMD 病例中谷氨酰胺和磷脂酰胆碱二酰基 C28:1 水平升高，而非晚期 AMD 中谷氨酰胺分解代谢率和谷氨酰胺/谷氨酸比值降低。谷氨酰胺与非晚期 AMD 的关联证实了最近的一项报告，该报告使用不同的代谢组学技术证明了早期 AMD 中谷氨酰胺水平升高。总之，本研究表明代谢组学是发现 AMD 生物标志物候选物的合适方法。在未来，更大的代谢组学研究可能会在尚未确定的 AMD 途径中发现新的生物标志物，并扩展我们对 AMD 病理生理学的认识。
