生物标志物发现
生物标志物
气体分析呼吸
荟萃分析
计算生物学
线性判别分析
代谢组学
生物信息学
计算机科学
化学
人工智能
生物
医学
蛋白质组学
病理
色谱法
生物化学
基因
作者
Theo Issitt,Wiggins L,Martin Veysey,Sean T. Sweeney,William J. Brackenbury,K. R. Redeker
出处
期刊:Journal of Breath Research
[IOP Publishing]
日期:2022-02-04
卷期号:16 (2): 024001-024001
被引量:10
标识
DOI:10.1088/1752-7163/ac5230
摘要
Volatile compounds contained in human breath reflect the inner workings of the body. A large number of studies have been published that link individual components of breath to disease, but diagnostic applications remain limited, in part due to inconsistent and conflicting identification of breath biomarkers. New approaches are therefore required to identify effective biomarker targets. Here, volatile organic compounds have been identified in the literature from four metabolically and physiologically distinct diseases and grouped into chemical functional groups (e.g. methylated hydrocarbons or aldehydes; based on known metabolic and enzymatic pathways) to support biomarker discovery and provide new insight on existing data. Using this functional grouping approach, principal component analysis doubled explanatory capacity from 19.1% to 38% relative to single individual compound approaches. Random forest and linear discriminant analysis reveal 93% classification accuracy for cancer. This review and meta-analysis provides insight for future research design by identifying volatile functional groups associated with disease. By incorporating our understanding of the complexities of the human body, along with accounting for variability in methodological and analytical approaches, this work demonstrates that a suite of targeted, functional volatile biomarkers, rather than individual biomarker compounds, will improve accuracy and success in diagnostic research and application.
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