Metabolomic profile of diabetic retinopathy: a GC-TOFMS-based approach using vitreous and aqueous humor
Metabolomic profile of diabetic retinopathy: a GC-TOFMS-based approach using vitreous and aqueous humor
复制标题
糖尿病视网膜病变的代谢组学特征：使用玻璃体和房水的基于 GC-TOFMS- 的方法
DOI：
10.1007/s00592-019-01363-0
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发表时间：
2020-01-01
影响因子：
3.8
通讯作者：
Liu, Kun
中科院分区：
文献类型：
--
作者：
Wang, Haiyan;Fang, Junwei;Liu, Kun
目的采用气相色谱-飞行时间质谱联用技术（GC-TOFMS）鉴定糖尿病视网膜病变（DR）的潜在代谢物标志物。方法对糖尿病患者和非糖尿病患者玻璃体和房水（AH）样品进行气相色谱- tofms谱分析。通过比较分析来阐明dr的不同代谢物。通过代谢途径来阐明dr的代谢重编程途径。通过逻辑回归和受体操作特征分析来选择和验证生物标志物代谢物，并建立治疗模型。结果对比分析显示，疾病组与对照组明显分离。8种AH分化代谢物和15种玻璃体分化代谢物。在这23种代谢物中，有11种是以前未检测到的新代谢物。途径分析发现9条通路（AH中3条，玻璃体中6条）是与dr相关的主要紊乱通路，其中糖异生异常、抗坏血酸-醛酸代谢异常、缬氨酸-亮氨酸-异亮氨酸生物合成异常、精氨酸-脯氨酸代谢异常可能在dr的发展中起最大作用。AH中d-2,3-二羟基丙酸、异柠檬酸、果糖6-磷酸和l-乳酸建立的logistic回归模型的AUC为0.965。玻璃体中焦谷氨酸和丙酮酸建立的AUC为0.951。结论这些发现扩大了我们对已鉴定代谢物的认识，并首次揭示了DR中一些新的代谢物，这些结果可能为探索DR的机制提供有用的信息，并可能最终允许开发用于预后的代谢生物标志物和新的治疗策略。
Aim To identify the potential metabolite markers in diabetic retinopathy (DR) by using gas chromatography coupled with time-of-flight mass spectrometry (GC-TOFMS). Methods GC-TOFMS spectra were acquired from vitreous and aqueous humor (AH) samples of patients with DR and non-diabetic participants. Comparative analysis was used to elucidate the distinct metabolites of DR. Metabolic pathway was employed to explicate the metabolic reprogramming pathways involved in DR. Logistic regression and receiver-operating characteristic analyses were carried out to select and validate the biomarker metabolites and establish a therapeutic model. Results Comparative analysis showed a clear separation between disease and control groups. Eight differentiating metabolites from AH and 15 differentiating metabolites from vitreous were highlighted. Out of these 23 metabolites, 11 novel metabolites have not been detected previously. Pathway analysis identified nine pathways (three in AH and six in vitreous) as the major disturbed pathways associated with DR. The abnormal of gluconeogenesis, ascorbate-aldarate metabolism, valine-leucine-isoleucine biosynthesis, and arginine-proline metabolism might weigh the most in the development of DR. The AUC of the logistic regression model established by d-2,3-Dihydroxypropanoic acid, isocitric acid, fructose 6-phosphate, and l-Lactic acid in AH was 0.965. The AUC established by pyroglutamic acid and pyruvic acid in vitreous was 0.951. Conclusions These findings have expanded our understanding of identified metabolites and revealed for the first time some novel metabolites in DR. These results may provide useful information to explore the mechanism and may eventually allow the development of metabolic biomarkers for prognosis and novel therapeutic strategies for the management of DR.