用拉曼尿化学分析分析肾功能不全,特别参考covid - 19、狼疮性肾炎和糖尿病肾病

John Robertson, Amr Issa, Mariana Gomez, Kathleen Sullivan, Ryan Senger
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摘要

背景:许多全身和泌尿系统疾病改变肾脏的结构和功能,包括改变尿液的成分。虽然常规尿液分析(物理性质、沉积物评价、尿液化学分析)对筛查有用,但它在区分疾病过程、结构变化和功能异常方面存在局限性。同样,虽然许多个体“生物标志物”已被用于筛查疾病,但它们尚未得到广泛的临床应用。最近的covid - 19大流行和对急性后后遗症SARS-CoV-2感染(PASC)的认识突出表明,需要快速、可扩展、经济和准确的筛查工具来管理疾病。目的:验证一种基于拉曼光谱的尿液分析筛选技术,该技术可用于识别和量化急性和PASC covid - 19疾病的全身和肾脏影响。方法:通过RT-PCR和/或与经RT-PCR确诊的covid - 19疾病有近距离(家庭)接触的自愿诊断为covid - 19疾病的成年人采集110份尿液标本。样本使用拉曼化学尿液分析进行分析,该技术可以检测尿液中的数百种离散化学物质,并应用计算比较机器学习来检测与covid - 19相关的分子模式(“指纹”)。结果:与健康个体和已知改变肾脏结构和功能的全身性疾病(糖尿病、狼疮)患者的尿液多分子“指纹”相比,急性和PASC covid - 19患者具有独特的指示肾功能改变的“指纹”(即感染改变了尿液成分)。尿中不同的“指纹”反映了疾病严重程度(轻度到重度)的差异。大约20%的住院患者出现了一定程度的肾功能障碍(eGFR下降),这与尿指纹的明显变化相关。结论:尿拉曼化学分析可能是新冠肺炎患者管理的有效工具,特别是在发现肾功能不全的患者时,应注意用药和肾脏健康的恢复/保存。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Profiling renal dysfunction using Raman chemometric urinalysis, with special reference to COVID19, lupus nephritis, and diabetic nephropathy
Background: Many systemic and urinary tract diseases alter renal structure and function, including changing the composition of urine. While routine urinalysis (physical properties, sediment evaluation, urine chemistry analytes) is useful in screening, it has limitations on separating disease processes, structural changes, and functional abnormalities. Likewise, while many individual ‘biomarkers’ have been used to screen for disease, they have not met with widespread clinical adoption. The recent COVID19 Pandemic and the recognition of post-acute sequelae SARS-CoV-2 infection (PASC) have highlighted the need for rapid, scalable, economical, and accurate screening tools for managing disease. Aims: Validate a Raman spectroscopy-based screening technology for urine analysis that could be used for recognition and quantification of systemic and renal effects of acute and PASC COVID19 disease. Methods: One hundred ten (110) urine specimens were obtained from consented adults diagnosed with COVID19 disease by RT-PCR and/or proximate (household) contact With RT-PCR-confirmed COVID19 disease. Samples were analyzed using Raman chemometric urinalysis, a technology that detects hundreds of discrete chemicals in urine and applies computational comparison-machine learning to detect COVID19-associated molecular patterns (‘fingerprints’). Results: When compared with the urine multimolecular ‘fingerprints’ of healthy individuals and patients with known systemic diseases (diabetes mellitus, lupus) that alter renal structure and function, patients with acute and PASC COVID19 had unique ‘fingerprints’ indicative of alterations in renal function (i.e. – infection altered urine composition). Differences in disease severity (mild to severe) were reflected by different ‘fingerprints’ in urine. Roughly 20% of hospitalized patients developed a degree of renal dysfunction (decrements in eGFR) that were correlated with distinct changes in urine fingerprints. Conclusion: Raman chemometric urinalysis may be a useful tool in management of patients with COVID19 disease, particularly in detecting patients with evolving renal dysfunction for whom there should be attention to medication use and renal health restoration/preservation.
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