abstract
Metabolic biomarkers of pre- and postdiagnosis gestational diabetes mellitus (GDM) were sought, using nuclear magnetic resonance (NMR) metabolomics of maternal plasma and corresponding lipid extracts. Metabolite differences between controls and disease were identified through multivariate analysis of variable selected H-1 NMR spectra. For postdiagnosis GDM, partial least squares regression identified metabolites with higher dependence on normal gestational age evolution. Variable selection of NMR spectra produced good classification Models for both pre- and postdiagnostic GDM. Prediagnosis GDM was accompanied by cholesterol increase and minor increases in lipoproteins (plasma), fatty acids, and triglycerides. (extracts). Small metabolite changes comprised variations in glucose (up regulated), amino acids, betaine, urea, creatine, and metabolites related to gut microflora. Most changes were enhanced upon GDM diagnosis, in addition to newly observed changes in low-M-w compounds. GDM prediction seems possible exploiting multivariate profile changes rather than a,set of univariate changes. Postdiagnosis GDM is successfully classified using a 26-resonance plasma biomarker. Plasma and extracts display comparable classification performance, the former enabling direct and more rapid analysis. Results and putative biochemical hypotheses require further,confirmation in larger cohorts of distinct ethnicities.
keywords
PRENATAL DISORDERS; PREGNANCY OUTCOMES; MELLITUS; PLASMA; HYPERGLYCEMIA; BIOMARKER; METABONOMICS; DIAGNOSIS; MOTHERS; PROFILE
subject category
Biochemistry & Molecular Biology
authors
Pinto, J; Almeida, LM; Martins, AS; Duarte, D; Barros, AS; Gahano, E; Pita, C; Almeida, MD; Carreira, IM; Gil, AM
our authors
Ana Maria Pissarra Coelho Gil
Associate Professor with Aggregation
Ana Sofia da Costa Martins
PhD Student
António de Sousa Barros
Post-doc Fellowship
Daniela Duarte
PhD Student
Joana Isabel Monteiro Pinto
Post-doc Fellowshipacknowledgements
This work was developed within the scope of the project CICECO-Aveiro Institute of Materials (FCT UID/CTM/50011/2013), financed by national funds through the FCT/MEC, and cofinanced by FEDER under the PT2020 Partnership Agreement and QOPNA FCT-Funding: PEst-C/QUI/UI0062/2013. J.P. thanks FCT for the SFRH/BD/73343/2010 grant and D.D. acknowledges funds from the Observatoire Hommes-Milieux International (OHM.I)