Altered metabolic profile in early and late onset preeclampsia: An FTIR spectroscopic study

Pregnancy Hypertens. 2014 Jan;4(1):70-80. doi: 10.1016/j.preghy.2013.11.005. Epub 2013 Nov 19.

Abstract

Objective: Metabolic anomalies, if any, between early and late onset preeclampsia [PE] were explored using Fourier transform infrared [FTIR] spectroscopy.

Setting: Department of Gynecology and Obstetrics, SSKM Hospital, IPGMER, Kolkata and Midnapur Medical College Hospital, Midnapur, India.

Sample: 80 pregnant women attending routine antenatal care units; (i) early onset PE [gestational age; GA<34weeks] (ii) late onset PE [GA>34weeks] (iii) early onset control [GA 24-34weeks] and (iv) late onset control [GA>34weeks].

Methods: 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.

Main outcome measure(s): Clinical characteristics and metabolic profile.

Results: 13 spectral peaks corresponding to the carbohydrate, protein and lipid region were significantly altered in early onset PE [P<0.001; 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.

Conclusion: Our study reveals differences in metabolomic profiles of early and late onset preeclamptic cases.

Keywords: Discriminant analysis; Fourier transformed infra-red spectroscopy; Hierarchial cluster analysis; Metabolite profiling; Nuclear magnetic resonance spectroscopy; Preeclampsia; Principal component analysis.