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Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with onset or first recognition during pregnancy and it affects 18% of pregnant women worldwide. GDM is considered a high-risk state which may lead to type II diabetes which is associated with an increase in a number of interrelated adverse perinatal outcomes. Given the fact that the progress of a successful pregnancy is dependent on the intricate communication between several biological molecules, identification of the proteomic profile perturbations in women with GDM is expected to help in understanding the disease pathogenesis and also discovery of clinical biomarker(s). In recent years, both gel-free and gel-based proteomics have been extensively investigated for improving maternal and child health. Although there are several reports integrating various aspects of proteomics in pregnancy related diseases such as preeclampsia, extensive Pubmed search shows no review so far on the application of proteomics in gestational diabetes. In this review, we focus on various high-throughput proteomic technologies for the identification of unique biosignatures and biomarkers responsible for the early prediction of GDM. Further, different analytical strategies and biological samples involved in proteomic analysis of this pregnancy-related disease are discussed.This article is part of a Special Issue entitled: Proteomics in India.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Metabolic anomalies, if any, between early and late onset preeclampsia [PE] were explored using Fourier transform infrared [FTIR] spectroscopy.Department of Gynecology and Obstetrics, SSKM Hospital, IPGMER, Kolkata and Midnapur Medical College Hospital, Midnapur, India.80 pregnant women attending routine antenatal care units; (i) early onset PE [gestational age; GA34weeks] (ii) late onset PE [GA34weeks] (iii) early onset control [GA 24-34weeks] and (iv) late onset control [GA34weeks].Serum FTIR spectra were obtained in the wave-number range of 600-4000cm(-1) at 4cm(-1) resolution. (1)H NMR and estimation of atherosclerotic index (AI) were performed to validate the FTIR findings.Clinical characteristics and metabolic profile.13 spectral peaks corresponding to the carbohydrate, protein and lipid region were significantly altered in early onset PE [P0.001; at 95% confidence interval]. Discriminant analysis identified five highly significant wave-numbers (1078, 1088, 1122, 1169 and 1171cm(-1)) having ⩾80% overall accuracy. Hierarchical cluster analysis of the obtained spectra at these 5 wave-numbers provided excellent segregation of early and late onset PE with respect to their controls. Principal component analysis revealed that these 5 wave-numbers significantly separated the two sub-groups of PE (97.95% of the total variance). (1)H NMR results showed that serum levels of glutamate, choline, alanine and lactate were significantly higher while ariginine and citrate were significantly decreased in early onset PE as compared to late onset cases.Our study reveals differences in metabolomic profiles of early and late onset preeclamptic cases.