Mass spectrometry for metabolomics analysis: Applications in neonatal and cancer screening

代谢组学 代谢组 计算生物学 生物标志物发现 仪表(计算机编程) 蛋白质组 串联质谱法 代谢物 生物信息学 化学 蛋白质组学 质谱法 计算机科学 生物 色谱法 生物化学 基因 操作系统
作者
Alexander J. Grooms,Benjamin J. Burris,Abraham K. Badu‐Tawiah
出处
期刊:Mass Spectrometry Reviews [Wiley]
卷期号:43 (4): 683-712 被引量:12
标识
DOI:10.1002/mas.21826
摘要

Abstract Chemical analysis by analytical instrumentation has played a major role in disease diagnosis, which is a necessary step for disease treatment. While the treatment process often targets specific organs or compounds, the diagnostic step can occur through various means, including physical or chemical examination. Chemically, the genome may be evaluated to give information about potential genetic outcomes, the transcriptome to provide information about expression actively occurring, the proteome to offer insight on functions causing metabolite expression, or the metabolome to provide a picture of both past and ongoing physiological function in the body. Mass spectrometry (MS) has been elevated among other analytical instrumentation because it can be used to evaluate all four biological machineries of the body. In addition, MS provides enhanced sensitivity, selectivity, versatility, and speed for rapid turnaround time, qualities that are important for instance in clinical procedures involving the diagnosis of a pediatric patient in intensive care or a cancer patient undergoing surgery. In this review, we provide a summary of the use of MS to evaluate biomarkers for newborn screening and cancer diagnosis. As many reviews have recently appeared focusing on MS methods and instrumentation for metabolite analysis, we sought to describe the biological basis for many metabolomic and additional omics biomarkers used in newborn screening and how tandem MS methods have recently been applied, in comparison to traditional methods. Similar comparison is done for cancer screening, with emphasis on emerging MS approaches that allow biological fluids, tissues, and breath to be analyzed for the presence of diagnostic metabolites yielding insight for treatment options based on the understanding of prior and current physiological functions of the body.

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