Suppr超能文献

早期代谢、血管和肾脏健康下降阶段中蛋白质糖基化、氧化和硝化的尿代谢组学标志物。

Urinary Metabolomic Markers of Protein Glycation, Oxidation, and Nitration in Early-Stage Decline in Metabolic, Vascular, and Renal Health.

机构信息

Warwick Medical School, Clinical Sciences Research Laboratories, University of Warwick, University Hospital, Coventry CV2 2DX, UK.

Clinical Division of Nephrology, Department of Internal Medicine, Medical University of Graz, 8036 Graz, Austria.

出版信息

Oxid Med Cell Longev. 2019 Nov 19;2019:4851323. doi: 10.1155/2019/4851323. eCollection 2019.

Abstract

Glycation, oxidation, nitration, and crosslinking of proteins are implicated in the pathogenic mechanisms of type 2 diabetes, cardiovascular disease, and chronic kidney disease. Related modified amino acids formed by proteolysis are excreted in urine. We quantified urinary levels of these metabolites and branched-chain amino acids (BCAAs) in healthy subjects and assessed changes in early-stage decline in metabolic, vascular, and renal health and explored their diagnostic utility for a noninvasive health screen. We recruited 200 human subjects with early-stage health decline and healthy controls. Urinary amino acid metabolites were determined by stable isotopic dilution analysis liquid chromatography-tandem mass spectrometry. Machine learning was applied to optimise and validate algorithms to discriminate between study groups for potential diagnostic utility. Urinary analyte changes were as follows: impaired metabolic health-increased N -carboxymethyl-lysine, glucosepane, glutamic semialdehyde, and pyrraline; impaired vascular health-increased glucosepane; and impaired renal health-increased BCAAs and decreased N -(-glutamyl)lysine. Algorithms combining subject age, BMI, and BCAAs discriminated between healthy controls and impaired metabolic, vascular, and renal health study groups with accuracy of 84%, 72%, and 90%, respectively. In 2-step analysis, algorithms combining subject age, BMI, and urinary N -fructosyl-lysine and valine discriminated between healthy controls and impaired health (any type), accuracy of 78%, and then between types of health impairment with accuracy of 69%-78% ( random selection 33%). From likelihood ratios, this provided small, moderate, and conclusive evidence of early-stage cardiovascular, metabolic, and renal disease with diagnostic odds ratios of 6 - 7, 26 - 28, and 34 - 79, respectively. We conclude that measurement of urinary glycated, oxidized, crosslinked, and branched-chain amino acids provides the basis for a noninvasive health screen for early-stage health decline in metabolic, vascular, and renal health.

摘要

糖基化、氧化、硝化和蛋白质交联与 2 型糖尿病、心血管疾病和慢性肾病的发病机制有关。蛋白酶解形成的相关修饰氨基酸从尿液中排出。我们在健康受试者中定量检测了这些代谢物和支链氨基酸(BCAA)的尿液水平,评估了代谢、血管和肾脏健康早期下降的变化,并探索了它们在非侵入性健康筛查中的诊断效用。我们招募了 200 名早期健康状况下降的人类受试者和健康对照组。通过稳定同位素稀释分析液相色谱-串联质谱法测定尿液氨基酸代谢物。应用机器学习来优化和验证算法,以区分研究组之间的潜在诊断效用。尿液分析物的变化如下:代谢健康受损-增加 N-羧甲基赖氨酸、葡糖基赖氨酸、谷氨酸半醛和吡咯啉;血管健康受损-增加葡糖基赖氨酸;肾脏健康受损-增加 BCAA 和减少 N-(-谷氨酰)赖氨酸。结合受试者年龄、BMI 和 BCAA 的算法可分别准确区分健康对照组和代谢、血管和肾脏健康受损的研究组,准确率分别为 84%、72%和 90%。在 2 步分析中,结合受试者年龄、BMI 和尿 N-果糖基赖氨酸和缬氨酸的算法可将健康对照组与健康受损组(任何类型)区分开来,准确率为 78%,然后将健康受损类型区分开来,准确率为 69%-78%(随机选择 33%)。从似然比来看,这为心血管、代谢和肾脏疾病的早期阶段提供了小、中、大的诊断证据,诊断比值比分别为 6-7、26-28 和 34-79。我们得出的结论是,测量尿糖基化、氧化、交联和支链氨基酸为代谢、血管和肾脏健康的早期健康下降提供了非侵入性健康筛查的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a835/6885816/f30bb68917da/OMCL2019-4851323.001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验