| Download | - View final version: Prediction of gestational age using urinary metabolites in term and preterm pregnancies (PDF, 7.7 MiB)
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| DOI | Resolve DOI: https://doi.org/10.1038/s41598-022-11866-6 |
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| Author | Search for: Contrepois, Kévin; Search for: Chen, Songjie; Search for: Ghaemi, Mohammad S.1; Search for: Wong, Ronald J.; Search for: Jehan, Fyezah; Search for: Sazawal, Sunil; Search for: Baqui, Abdullah H.; Search for: Nisar, Muhammad I.; Search for: Dhingra, Usha; Search for: Khanam, Rasheda; Search for: Ilyas, Muhammad; Search for: Dutta, Arup; Search for: Mehmood, Usma; Search for: Deb, Saikat; Search for: Hotwani, Aneeta; Search for: Ali, Said M.; Search for: Rahman, Sayedur; Search for: Nizar, Ambreen; Search for: Ame, Shaali M.; Search for: Muhammad, Sajid; Search for: Chauhan, Aishwarya; Search for: Khan, Waqasuddin; Search for: Raqib, Rubhana; Search for: Das, Sayan; Search for: Ahmed, Salahuddin; Search for: Hasan, Tarik; Search for: Khalid, Javairia; Search for: Juma, Mohammed H.; Search for: Chowdhury, Nabidul H.; Search for: Kabir, Furqan; Search for: Aftab, Fahad; Search for: Quaiyum, Md Abdul; Search for: Manu, Alexander; Search for: Yoshida, Sachiyo; Search for: Bahl, Rajiv; Search for: Rahman, Anisur; Search for: Pervin, Jesmin; Search for: Price, Joan T.; Search for: Rahman, Monjur; Search for: Kasaro, Margaret P.; Search for: Litch, James A.; Search for: Musonda, Patrick; Search for: Vwalika, Bellington; Search for: Stringer, Jeffrey S. A.; Search for: Shaw, Gary; Search for: Stevenson, David K.; Search for: Aghaeepour, Nima; Search for: Snyder, Michael P. |
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| Affiliation | - National Research Council of Canada. Digital Technologies
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| Funder | Search for: Bill and Melinda Gates Foundation; Search for: National Institutes of Health; Search for: National Institute of Allergy and Infectious Diseases |
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| Format | Text, Article |
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| Abstract | Assessment of gestational age (GA) is key to provide optimal care during pregnancy. However, its accurate determination remains challenging in low- and middle-income countries, where access to obstetric ultrasound is limited. Hence, there is an urgent need to develop clinical approaches that allow accurate and inexpensive estimations of GA. We investigated the ability of urinary metabolites to predict GA at time of collection in a diverse multi-site cohort of healthy and pathological pregnancies (n = 99) using a broad-spectrum liquid chromatography coupled with mass spectrometry (LC–MS) platform. Our approach detected a myriad of steroid hormones and their derivatives including estrogens, progesterones, corticosteroids, and androgens which were associated with pregnancy progression. We developed a restricted model that predicted GA with high accuracy using three metabolites (rho = 0.87, RMSE = 1.58 weeks) that was validated in an independent cohort (n = 20). The predictions were more robust in pregnancies that went to term in comparison to pregnancies that ended prematurely. Overall, we demonstrated the feasibility of implementing urine metabolomics analysis in large-scale multi-site studies and report a predictive model of GA with a potential clinical value. |
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| Publication date | 2022-05-16 |
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| Publisher | Springer Science and Business Media LLC |
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| Licence | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 52c2b4e3-bf14-441c-b0c3-308f432671df |
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| Record created | 2022-05-31 |
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| Record modified | 2022-05-31 |
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