Barbosa João Marcos G, David Lurian Caetano, Gabriela de Oliveira Camilla, Elcana de Oliveira Anselmo, Antoniosi Filho Nelson R
Laboratório de Métodos de Extração e Separação (LAMES), Instituto de Química (IQ), Universidade Federal de Goiás (UFG), Campus II - Samambaia, 74690-900, Goiânia, GO, Brazil.
Laboratório de Química Teórica e Computacional (LQTC), Instituto de Química (IQ), Universidade Federal de Goiás (UFG), Campus II - Samambaia, 74690-970, Goiânia, GO, Brazil.
Mol Omics. 2024 Dec 2;20(10):666-677. doi: 10.1039/d4mo00071d.
Human cerumen analysis is an innovative and non-invasive trend in diagnosing diseases. Recently, new cerumen volatile-based methods using binary (volatile presence/absence) and semiquantitative (volatile intensity) data approaches have shown great potential in detecting biomarkers for cancer, chronic and rare diseases, and xenobiotic exposures. However, to date, the impacts of demographic factors such as body mass index (BMI), sex, age, and ethnicity/race in cerumen data have not been widely described, which can hamper interpretation in biomarker discovery investigations. This study examined the effects of such factors in cerumen, defining the baseline volatile organic metabolites (VOMs) across different physiological groups. Cerumen samples from seventy volunteers were analyzed using headspace/gas chromatography-mass spectrometry (HS/GC-MS) and multivariate statistical analysis using binary and semiquantitative data approaches. In the binary data approach, several VOMs exhibited patterns of high occurrence in some specific demographic groups. However, no pattern of discrimination that could be attributed to demographic factors was observed. In the semiquantitative approach, the relative abundance of cerumen VOMs was more impacted by sex and BMI than age and ethnicity/race. In summary, we describe how cerumen VOM occurrence and abundance are affected by patient phenotype, which can pave the way for more personalized medicine in future cerumen volatile-based methods.
人体耳垢分析是疾病诊断领域一种创新的非侵入性方法。最近，基于耳垢挥发性成分的新方法，采用二元（挥发性成分存在与否）和半定量（挥发性成分强度）数据方法，在检测癌症、慢性和罕见疾病以及外源性物质暴露的生物标志物方面显示出巨大潜力。然而，迄今为止，体重指数（BMI）、性别、年龄和种族等人口统计学因素对耳垢数据的影响尚未得到广泛描述，这可能会妨碍生物标志物发现研究中的解释。本研究考察了这些因素对耳垢的影响，确定了不同生理组的基线挥发性有机代谢物（VOMs）。使用顶空/气相色谱 - 质谱联用仪（HS/GC-MS）对70名志愿者的耳垢样本进行分析，并采用二元和半定量数据方法进行多元统计分析。在二元数据方法中，几种VOMs在某些特定人口统计学组中呈现出高出现率的模式。然而，未观察到可归因于人口统计学因素的区分模式。在半定量方法中，耳垢VOMs的相对丰度受性别和BMI的影响大于年龄和种族。总之，我们描述了耳垢VOMs的出现和丰度如何受患者表型影响，这可为未来基于耳垢挥发性成分的方法实现更个性化的医学铺平道路。
