Abstract
Context
Undiagnosed gestational diabetes mellitus (GDM) is a major preventable cause of stillbirth. In the United Kingdom, women are selected for diagnostic testing for GDM based on risk factors, including body mass index (BMI) > 30 kg/m2.
Objective
To improve the prediction of GDM using metabolomics.
Methods
We performed metabolomics on maternal serum from the Pregnancy Outcome Prediction (POP) study at 12 and 20 weeks of gestational age (wkGA; 185 GDM cases and 314 noncases). Predictive metabolites were internally validated using the 28 wkGA POP study serum sample and externally validated using 24- to 28-wkGA fasting plasma from the Born in Bradford (BiB) cohort (349 GDM cases and 2347 noncases). The predictive ability of a model including the metabolites was compared with BMI > 30 kg/m2 in the POP study.
Results
Forty-seven predictive metabolites were identified using the 12- and 20-wkGA samples. At 28 wkGA, 4 of these [mannose, 4-hydroxyglutamate, 1,5-anhydroglucitol, and lactosyl-N-palmitoyl-sphingosine (d18:1/16:0)] independently increased the bootstrapped area under the receiver operating characteristic curve (AUC) by >0.01. All 4 were externally validated in the BiB samples (P = 2.6 × 10−12, 2.2 × 10−13, 6.9 × 10−28, and 2.6 × 10−17, respectively). In the POP study, BMI > 30 kg/m2 had a sensitivity of 28.7% (95% CI 22.3-36.0%) and a specificity of 85.4% whereas at the same level of specificity, a predictive model using age, BMI, and the 4 metabolites had a sensitivity of 60.2% (95% CI 52.6-67.4%) and an AUC of 0.82 (95% CI 0.78-0.86).
Conclusions
We identified 4 strongly and independently predictive metabolites for GDM that could have clinical utility in screening for GDM.
Undiagnosed gestational diabetes mellitus (GDM) is a major preventable cause of stillbirth. In the United Kingdom, women are selected for diagnostic testing for GDM based on risk factors, including body mass index (BMI) > 30 kg/m2.
Objective
To improve the prediction of GDM using metabolomics.
Methods
We performed metabolomics on maternal serum from the Pregnancy Outcome Prediction (POP) study at 12 and 20 weeks of gestational age (wkGA; 185 GDM cases and 314 noncases). Predictive metabolites were internally validated using the 28 wkGA POP study serum sample and externally validated using 24- to 28-wkGA fasting plasma from the Born in Bradford (BiB) cohort (349 GDM cases and 2347 noncases). The predictive ability of a model including the metabolites was compared with BMI > 30 kg/m2 in the POP study.
Results
Forty-seven predictive metabolites were identified using the 12- and 20-wkGA samples. At 28 wkGA, 4 of these [mannose, 4-hydroxyglutamate, 1,5-anhydroglucitol, and lactosyl-N-palmitoyl-sphingosine (d18:1/16:0)] independently increased the bootstrapped area under the receiver operating characteristic curve (AUC) by >0.01. All 4 were externally validated in the BiB samples (P = 2.6 × 10−12, 2.2 × 10−13, 6.9 × 10−28, and 2.6 × 10−17, respectively). In the POP study, BMI > 30 kg/m2 had a sensitivity of 28.7% (95% CI 22.3-36.0%) and a specificity of 85.4% whereas at the same level of specificity, a predictive model using age, BMI, and the 4 metabolites had a sensitivity of 60.2% (95% CI 52.6-67.4%) and an AUC of 0.82 (95% CI 0.78-0.86).
Conclusions
We identified 4 strongly and independently predictive metabolites for GDM that could have clinical utility in screening for GDM.
| Original language | English |
|---|---|
| Pages (from-to) | E3479-E3486 |
| Number of pages | 8 |
| Journal | Journal of Clinical Endocrinology and Metabolism |
| Volume | 107 |
| Issue number | 8 |
| Early online date | 18 Apr 2022 |
| DOIs | |
| Publication status | Published - 1 Aug 2022 |
Bibliographical note
Funding Information:This work was supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (Women’s Health theme), the Medical Research Council (United Kingdom; 1100221 to G.C.S.S. and D.S.C-J), and the NIHR Cambridge Clinical Research Facility. D.A.L.’s contribution to this study is supported by the University of Bristol and UK Medical Research Council (MM_UU_00011/3), US National Institutes of Health (R01 DK10324), European Research Council via Advanced Grant 669545, the British Heart Foundation (AA/18/7/34219 and CH/F/20/90003), the NIHR Bristol Biomedical Research Centre, and the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 733206 (LifeCycle). The European Union’s Horizon 2020 research and innovation programme under grant agreement no. 733206 (LifeCycle) funds G.L.C.’s salary. BiB receives core funding from the Wellcome Trust (WT101597MA), a joint grant from the UK Medical and Economic and Social Science Research Councils (MR/N024397/1), the British Heart Foundation (CS/16/4/32482), and the National Institute for Health Research under its Applied Research Collaboration for Yorkshire and Humber and Clinical Research Network research delivery support. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. The funders of the study had no role in the choice of the study design, in the collection, analysis or interpretation of the data, in the writing of the manuscript, or in the decision to submit the paper for publication.
Publisher Copyright:
© 2022 Endocrine Society. All rights reserved.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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