Utility of metabolic profiling of serum in the diagnosis of pregnancy complications

Katie L Powell, Anthony Carrozzi, Alexandre S Stephens, Vitomir Tasevski, Jonathan M Morris, Anthony W Ashton, Anthony C Dona

Research output: Contribution to journalArticleResearchpeer-review

2 Citations (Scopus)

Abstract

INTRODUCTION: Currently there are no clinical screening tests available to identify pregnancies at risk of developing preeclampsia (PET) and/or intrauterine growth restriction (IUGR), both of which are associated with abnormal placentation. Metabolic profiling is now a stable analytical platform used in many laboratories and has successfully been used to identify biomarkers associated with various pathological states.

METHODS: We used nuclear magnetic resonance spectroscopy (NMR) to metabolically profile serum samples collected from 143 pregnant women at 26-41 weeks gestation with pregnancy outcomes of PET, IUGR, PET IUGR or small for gestational age (SGA) that were age-matched to normal pre/term pregnancies.

RESULTS: Spectral analysis found no difference in the measured metabolites from normal term, pre-term and SGA samples, and of 25 identified metabolites, only glutamate was marginally different between groups. Of the identified metabolites, 3-methylhistidine, creatinine, acetyl groups and acetate, were determined to be independent predictors of PET and produced area under the curves (AUC) = 0.938 and 0.936 for the discovery and validation sets. Only 3-hydroxybutyrate was determined to be an independent predictor of IUGR, however the model had low predictive power (AUC = 0.623 and 0.581 for the discovery and validation sets).

CONCLUSIONS: A sub-panel of metabolites had strong predictive power for identifying PET samples in a validation dataset, however prediction of IUGR was more difficult using the identified metabolites. NMR based metabolomics can identify metabolites strongly associated with disease and has the potential to be useful in developing early clinical screening tests for at risk pregnancies.

Original languageEnglish
Pages (from-to)65-73
Number of pages9
JournalPlacenta
Volume66
Early online date10 Apr 2018
DOIs
Publication statusPublished - Jun 2018
Externally publishedYes

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Pregnancy Complications
Growth
Pregnancy
Serum
Gestational Age
Area Under Curve
Magnetic Resonance Spectroscopy
Placentation
Metabolomics
3-Hydroxybutyric Acid
Pregnancy Outcome
Pre-Eclampsia
Pregnant Women
Glutamic Acid
Creatinine
Acetates
Biomarkers

Cite this

Powell, K. L., Carrozzi, A., Stephens, A. S., Tasevski, V., Morris, J. M., Ashton, A. W., & Dona, A. C. (2018). Utility of metabolic profiling of serum in the diagnosis of pregnancy complications. Placenta, 66, 65-73. https://doi.org/10.1016/j.placenta.2018.04.005
Powell, Katie L ; Carrozzi, Anthony ; Stephens, Alexandre S ; Tasevski, Vitomir ; Morris, Jonathan M ; Ashton, Anthony W ; Dona, Anthony C. / Utility of metabolic profiling of serum in the diagnosis of pregnancy complications. In: Placenta. 2018 ; Vol. 66. pp. 65-73.
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abstract = "INTRODUCTION: Currently there are no clinical screening tests available to identify pregnancies at risk of developing preeclampsia (PET) and/or intrauterine growth restriction (IUGR), both of which are associated with abnormal placentation. Metabolic profiling is now a stable analytical platform used in many laboratories and has successfully been used to identify biomarkers associated with various pathological states.METHODS: We used nuclear magnetic resonance spectroscopy (NMR) to metabolically profile serum samples collected from 143 pregnant women at 26-41 weeks gestation with pregnancy outcomes of PET, IUGR, PET IUGR or small for gestational age (SGA) that were age-matched to normal pre/term pregnancies.RESULTS: Spectral analysis found no difference in the measured metabolites from normal term, pre-term and SGA samples, and of 25 identified metabolites, only glutamate was marginally different between groups. Of the identified metabolites, 3-methylhistidine, creatinine, acetyl groups and acetate, were determined to be independent predictors of PET and produced area under the curves (AUC) = 0.938 and 0.936 for the discovery and validation sets. Only 3-hydroxybutyrate was determined to be an independent predictor of IUGR, however the model had low predictive power (AUC = 0.623 and 0.581 for the discovery and validation sets).CONCLUSIONS: A sub-panel of metabolites had strong predictive power for identifying PET samples in a validation dataset, however prediction of IUGR was more difficult using the identified metabolites. NMR based metabolomics can identify metabolites strongly associated with disease and has the potential to be useful in developing early clinical screening tests for at risk pregnancies.",
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Powell, KL, Carrozzi, A, Stephens, AS, Tasevski, V, Morris, JM, Ashton, AW & Dona, AC 2018, 'Utility of metabolic profiling of serum in the diagnosis of pregnancy complications' Placenta, vol. 66, pp. 65-73. https://doi.org/10.1016/j.placenta.2018.04.005

Utility of metabolic profiling of serum in the diagnosis of pregnancy complications. / Powell, Katie L; Carrozzi, Anthony; Stephens, Alexandre S; Tasevski, Vitomir; Morris, Jonathan M; Ashton, Anthony W; Dona, Anthony C.

In: Placenta, Vol. 66, 06.2018, p. 65-73.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Utility of metabolic profiling of serum in the diagnosis of pregnancy complications

AU - Powell, Katie L

AU - Carrozzi, Anthony

AU - Stephens, Alexandre S

AU - Tasevski, Vitomir

AU - Morris, Jonathan M

AU - Ashton, Anthony W

AU - Dona, Anthony C

N1 - Copyright © 2018 Elsevier Ltd. All rights reserved.

PY - 2018/6

Y1 - 2018/6

N2 - INTRODUCTION: Currently there are no clinical screening tests available to identify pregnancies at risk of developing preeclampsia (PET) and/or intrauterine growth restriction (IUGR), both of which are associated with abnormal placentation. Metabolic profiling is now a stable analytical platform used in many laboratories and has successfully been used to identify biomarkers associated with various pathological states.METHODS: We used nuclear magnetic resonance spectroscopy (NMR) to metabolically profile serum samples collected from 143 pregnant women at 26-41 weeks gestation with pregnancy outcomes of PET, IUGR, PET IUGR or small for gestational age (SGA) that were age-matched to normal pre/term pregnancies.RESULTS: Spectral analysis found no difference in the measured metabolites from normal term, pre-term and SGA samples, and of 25 identified metabolites, only glutamate was marginally different between groups. Of the identified metabolites, 3-methylhistidine, creatinine, acetyl groups and acetate, were determined to be independent predictors of PET and produced area under the curves (AUC) = 0.938 and 0.936 for the discovery and validation sets. Only 3-hydroxybutyrate was determined to be an independent predictor of IUGR, however the model had low predictive power (AUC = 0.623 and 0.581 for the discovery and validation sets).CONCLUSIONS: A sub-panel of metabolites had strong predictive power for identifying PET samples in a validation dataset, however prediction of IUGR was more difficult using the identified metabolites. NMR based metabolomics can identify metabolites strongly associated with disease and has the potential to be useful in developing early clinical screening tests for at risk pregnancies.

AB - INTRODUCTION: Currently there are no clinical screening tests available to identify pregnancies at risk of developing preeclampsia (PET) and/or intrauterine growth restriction (IUGR), both of which are associated with abnormal placentation. Metabolic profiling is now a stable analytical platform used in many laboratories and has successfully been used to identify biomarkers associated with various pathological states.METHODS: We used nuclear magnetic resonance spectroscopy (NMR) to metabolically profile serum samples collected from 143 pregnant women at 26-41 weeks gestation with pregnancy outcomes of PET, IUGR, PET IUGR or small for gestational age (SGA) that were age-matched to normal pre/term pregnancies.RESULTS: Spectral analysis found no difference in the measured metabolites from normal term, pre-term and SGA samples, and of 25 identified metabolites, only glutamate was marginally different between groups. Of the identified metabolites, 3-methylhistidine, creatinine, acetyl groups and acetate, were determined to be independent predictors of PET and produced area under the curves (AUC) = 0.938 and 0.936 for the discovery and validation sets. Only 3-hydroxybutyrate was determined to be an independent predictor of IUGR, however the model had low predictive power (AUC = 0.623 and 0.581 for the discovery and validation sets).CONCLUSIONS: A sub-panel of metabolites had strong predictive power for identifying PET samples in a validation dataset, however prediction of IUGR was more difficult using the identified metabolites. NMR based metabolomics can identify metabolites strongly associated with disease and has the potential to be useful in developing early clinical screening tests for at risk pregnancies.

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U2 - 10.1016/j.placenta.2018.04.005

DO - 10.1016/j.placenta.2018.04.005

M3 - Article

VL - 66

SP - 65

EP - 73

JO - Placenta

JF - Placenta

SN - 0143-4004

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