Prediction of gestational diabetes mellitus based on an analysis of amniotic fluid by capillary electrophoresis.
OBJECTIVE
To detect gestational diabetes mellitus biomarkers in human amniotic fluid collected for age-related genetic testing using capillary electrophoresis and a sophisticated data analysis methodology.


METHODS
Amniotic fluid samples were separated by capillary electrophoresis. Samples were classified using a genetic algorithm with Bayesian benefit function. The best model maximized the sensitivity and specificity and employed a leave-one-out cross-validation strategy.


RESULTS
Gestational diabetes mellitus (GDM; n = 14) was distinguished from non-GDM (n = 95) with 86% sensitivity and 99% specificity using two wavelets. These wavelets were located in the unresolved protein region and on the edge of the maternally derived albumin peak.


CONCLUSIONS
GDM is a maternal pathology; however, it was shown that it alters the biochemical profile of amniotic fluid. Testing for GDM is normally carried out at 24-28 weeks, but changes can be detected at 15 weeks gestation, suggesting that GDM onset occurs early in gestation.
Department of Chemistry & Biochemistry, Concordia University, Montreal, QC, H4B 1R6, Canada.
Michel R
MR
Boisvert
Kristine G
KG
Koski
David H
DH
Burns
Cameron D
CD
Skinner
D000328:Adult; D000653:Amniotic Fluid / Q000737:chemistry*; D001499:Bayes Theorem; D015415:Biomarkers / Q000032:analysis; D016640:Diabetes, Gestational / Q000175:diagnosis* / Q000503:physiopathology; D019075:Electrophoresis, Capillary / Q000379:methods*; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D011247:Pregnancy; D011262:Pregnancy Trimester, Second; D058067:Wavelet Analysis
D015415:Biomarkers