Untargeted metabolomics for lifestyle biomarker discovery in human hair

Ana M. F. Pego, Edward J. Knaven, Anke P. C. van de Plas,Jos F. Brouwers,Eva Cuypers,Bryn Flinders,Ron M. A. Heeren,Arian C. van Asten, Ben M. de Rooij

FORENSIC SCIENCE INTERNATIONAL(2024)

引用 0|浏览4
暂无评分
摘要
There is a risk of crimes remaining unsolved when no matching DNA profiles or fingermarks are found. If this is the case, forensic investigations are faced with a significant shortage of evidence and information regarding the unknown perpetrator and/or victim as well as any missing persons. However, a rather commonly found biological trace encountered at crime scenes is human hair. As hair acts as a biochemical reservoir, it may contain valuable information regarding one's characteristics and habits. This study aimed to build an analytical method capable of determining a marker set of relevant metabolites in hair, eventually building up a profile of its donor. To find potential markers, an untargeted metabolomics approach was developed to select and identify statistically significant features. For that purpose, a total of 68 hair samples were collected at several hairdresser shops in varying neighbourhoods. Compound extraction was achieved via methanolic incubation overnight and analysis performed using a high -resolution mass spectrometry (HRMS) Orbitrap Q Exactive Focus. The acquired data was uploaded and statistically evaluated using two free online software/libraries, where a total of eight compounds have given a match on both tools. Their presumptive identity was confirmed using reference standards and consequently added to a dynamic target donor profiling list. These results show the potential of using untargeted metabolomics for the search for lifestyle biomarkers capable of differentiating individuals. Such tools are of paramount importance in a forensic setting with little or no evidence available and no clear tactical leads.
更多
查看译文
关键词
Untargeted screening,Metabolomics,Hair,Forensic science,Donor profiling,Lifestyle markers
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要