Publication: Metabolomic profile associated with obstructive sleep apnoea severity in obese pregnant women with gestational diabetes mellitus: A pilot study
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Issued Date
2021-10-01
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ISSN
13652869
09621105
09621105
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2-s2.0-85103924071
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Mahidol University
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SCOPUS
Bibliographic Citation
Journal of Sleep Research. Vol.30, No.5 (2021)
Suggested Citation
Sirimon Reutrakul, Hui Chen, Naricha Chirakalwasan, Suranut Charoensri, Ekasitt Wanitcharoenkul, Somvang Amnakkittikul, Sunee Saetung, Brian T. Layden, George E. Chlipala Metabolomic profile associated with obstructive sleep apnoea severity in obese pregnant women with gestational diabetes mellitus: A pilot study. Journal of Sleep Research. Vol.30, No.5 (2021). doi:10.1111/jsr.13327 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/78896
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Title
Metabolomic profile associated with obstructive sleep apnoea severity in obese pregnant women with gestational diabetes mellitus: A pilot study
Abstract
Obstructive sleep apnoea (OSA) is prevalent in obese women with gestational diabetes mellitus (GDM). The present pilot study explored associations between OSA severity and metabolites in women with GDM. A total of 81 obese women with diet-controlled GDM had OSA assessment (median gestational age [GA] 29 weeks). The metabolic profile was assayed from fasting serum samples via liquid chromatography–mass spectrometry (LC-MS) using an untargeted approach. Metabolites were extracted and subjected to an Agilent 1,290 UPLC coupled to an Agilent 6,545 quadrupole time-of-flight (Q-TOF) MS. Data were acquired using electrospray ionisation in positive and negative ion modes. The raw LC-MS data were processed using the OpenMS toolkit to detect and quantify features, and these features were annotated using the Human Metabolite Database. The feature data were compared with OSA status, apnea–hypopnea index (AHI), body mass index (BMI) and GA using “limma” in R. Correlation analyses of the continuous covariates were performed using Kendall’s Tau test. The p values were adjusted for multiple testing using the Benjamini–Hochberg false discovery rate correction. A total of 42 women (51.8%) had OSA, with a median AHI of 9.1 events/hr. There were no significant differences in metabolomics profiles between those with and without OSA. However, differential analyses modelling in GA and BMI found 12 features that significantly associated with the AHI. These features could be annotated to oestradiols, lysophospholipids, and fatty acids, with higher levels related to higher AHI. Metabolites including oestradiols and phospholipids may be involved in pathogenesis of OSA in pregnant women with GDM. A targeted approach may help elucidate our understanding of their role in OSA in this population.