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This study investigated changes in the volatile organic compound (VOC) pattern induced by pregnancy, focusing on urine samples. Pregnancy leads to significant alterations in maternal anatomy and physiology to meet metabolic demands and support fetal development. Understanding these changes is crucial for distinguishing between normal and pathological conditions. Metabolic variations in the body result in modifications to VOC patterns in biological fluids. Urine VOCs from 30 pregnant women (at the end of the first trimester) and 21 non-pregnant women were analyzed using a porphyrinoids QMB-based gas sensor array and gas chromatography coupled with ion mobility spectrometry (GC-IMS) to characterize the volatilome of pregnancy under physiological conditions. Kruskal-Wallis rank test on GC-IMS data identified 27 compounds that differentiated pregnant from non-pregnant women (p < 0.05). Considering those data, Linear Discriminant Analysis (LDA) achieved an accuracy of over 80% in testing. The gas sensor array had an accuracy of 71% in the LDA model test, a slightly lower compared to the analytical method.

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Evaluation of Pregnacy-Induced Modification of Urinary Volatilome by a Gas Sensor Array

  • 会议论文

  • 发表日期：

    2025年

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  • Rosamaria Capuano,
  • Eleonora Nicolai,
  • Alexandro Catini,
  • Roberto Paolesse,
  • Sergio Bernardini,
  • Giuseppe Rizzo,
  • Corrado Di Natale

摘要

This study investigated changes in the volatile organic compound (VOC) pattern induced by pregnancy, focusing on urine samples. Pregnancy leads to significant alterations in maternal anatomy and physiology to meet metabolic demands and support fetal development. Understanding these changes is crucial for distinguishing between normal and pathological conditions. Metabolic variations in the body result in modifications to VOC patterns in biological fluids. Urine VOCs from 30 pregnant women (at the end of the first trimester) and 21 non-pregnant women were analyzed using a porphyrinoids QMB-based gas sensor array and gas chromatography coupled with ion mobility spectrometry (GC-IMS) to characterize the volatilome of pregnancy under physiological conditions. Kruskal-Wallis rank test on GC-IMS data identified 27 compounds that differentiated pregnant from non-pregnant women (p < 0.05). Considering those data, Linear Discriminant Analysis (LDA) achieved an accuracy of over 80% in testing. The gas sensor array had an accuracy of 71% in the LDA model test, a slightly lower compared to the analytical method.