Volatilomics as an emerging strategy to determine potential biomarkers of female infertility: a pilot study

Due to its high prevalence, infertility has become a prominent public health issue, posing a significant challenge to modern reproductive medicine. Some clinical conditions that lead to female infertility include polycystic ovary syndrome (PCOS), endometriosis, and premature ovarian failure (POF). Follicular fluid (FF) is the biological matrix that has the most contact with the oocyte and can, therefore, be used as a predictor of its quality. Volatilomics has emerged as a non-invasive, straightforward, affordable, and simple method for characterizing various diseases and determining the effectiveness of their current therapies. In order to find potential biomarkers of infertility, this study set out to determine the volatomic pattern of the follicular fluid from patients with PCOS, endometriosis, and POF. The chromatographic data integration was performed through solid-phase microextraction (SPME), followed by gas chromatography–mass spectrometry (GC-MS). The findings pointed to specific metabolite patterns as potential biomarkers for the studied diseases. These open the door for further research into the relevant metabolomic pathways to enhance infertility knowledge and diagnostic tools. An extended investigation may, however, produce a new mechanistic understanding of the pathophysiology of the diseases.This work is part of the project Centro-01-0145- FEDER-000019—C4—Centro de Competências em Cloud Computing supported by the European Regional Development Fund through the “Programa Operacional Regional do Centro (Centro 2020)—Sistema de Apoio à Investigação Científica e Tecnológica—Programas Integrados de IC&DT (Covilhã)”. The authors acknowledge the Laboratório de Fármaco-Toxicologia for the funding support. This work was developed within the scope of the CICS-UBI projects UIDB/00709/2020 and UIDP/00709/2020 and the CEF project UIDB/00239/2020, and financed by national funds through the Portuguese Foundation for Science and Technology (FCT)/MCTES. It was also supported by the Applied Molecular Biosciences Unit UCIBIO (UIDB/04378/2020 and UIDP/04378/2020) and the Associate Laboratory Institute for Health and Bioeconomy—i4HB (project LA/P/0140/2020), which are financed by national funds from FCT/MCTES.