1,477
Views
93
CrossRef citations to date
0
Altmetric
Original Article

Metabolomics and first-trimester prediction of early-onset preeclampsia

, , , , , , & show all
Pages 1840-1847 | Received 17 Apr 2012, Accepted 17 Apr 2012, Published online: 28 Apr 2012

References

  • Villar J, Say L, Gulmezoghe AM, Merialdi M, Lindheimer M, Beltran AP, et al. Eclampsia and preeclampsia: a worldwide health problem for 2000 years. In: Critchley H, MacLean A, Poston L, Walker J, editors. Preeclampsia. London, UK: RCOG; 2003.
  • Maternal Mortality in 2005. Estimates developed by WHO, UNICEF, UNFPA and the World Bank. Geneva, Switzerland: World Health Organization 2007.
  • Bellamy L, Casas JP, Hingorani AD, Williams DJ. Pre-eclampsia and risk of cardiovascular disease and cancer in later life: systematic review and meta-analysis. BMJ 2007;335:974.
  • Yu CK, Khouri O, Onwudiwe N, Spiliopoulos Y, Nicolaides KH; Fetal Medicine Foundation Second-Trimester Screening Group. Prediction of pre-eclampsia by uterine artery Doppler imaging: relationship to gestational age at delivery and small-for-gestational age. Ultrasound Obstet Gynecol 2008;31:310–313.
  • Witlin AG, Saade GR, Mattar F, Sibai BM. Predictors of neonatal outcome in women with severe preeclampsia or eclampsia between 24 and 33 weeks’ gestation. Am J Obstet Gynecol 2000;182:607–611.
  • Irgens HU, Reisaeter L, Irgens LM, Lie RT. Long term mortality of mothers and fathers after pre-eclampsia: population based cohort study. BMJ 2001;323:1213–1217.
  • von Dadelszen P, Magee LA, Roberts JM. Subclassification of preeclampsia. Hypertens Pregnancy 2003;22:143–148.
  • Brosens I, Pijnenborg R, Vercruysse L, Romero R. The “Great Obstetrical Syndromes” are associated with disorders of deep placentation. Am J Obstet Gynecol 2011;204:193–201.
  • Wikström AK, Larsson A, Eriksson UJ, Nash P, Nordén-Lindeberg S, Olovsson M. Placental growth factor and soluble FMS-like tyrosine kinase-1 in early-onset and late-onset preeclampsia. Obstet Gynecol 2007;109:1368–1374.
  • Wishart DS, Knox C, Guo AC, Eisner R, Young N, Gautam B, Hau DD, et al. HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res 2009;37:D603–D610.
  • Villas-Bôas SG, Mas S, Akesson M, Smedsgaard J, Nielsen J. Mass spectrometry in metabolome analysis. Mass Spectrom Rev 2005;24:613–646.
  • Wishart DS. Advances in metabolite identification. Bioanalysis 2011;3:1769–1782.
  • Gowda GA, Zhang S, Gu H, Asiago V, Shanaiah N, Raftery D. Metabolomics-based methods for early disease diagnostics. Expert Rev Mol Diagn 2008;8:617–633.
  • Robinson HP, Fleming JE. A critical evaluation of sonar “crown-rump length” measurements. Br J Obstet Gynaecol 1975;82:702–710.
  • Syngelaki A, Chelemen T, Dagklis T, Allan L, Nicolaides KH. Challenges in the diagnosis of fetal non-chromosomal abnormalities at 11-13 weeks. Prenat Diagn 2011;31:90–102.
  • Plasencia W, Maiz N, Bonino S, Kaihura C, Nicolaides KH. Uterine artery Doppler at 11 + 0 to 13 + 6 weeks in the prediction of pre-eclampsia. Ultrasound Obstet Gynecol 2007;30:742–749.
  • Brown MA, Lindheimer MD, de Swiet M, Van Assche A, Moutquin JM. The classification and diagnosis of the hypertensive disorders of pregnancy: statement from the International Society for the Study of Hypertension in Pregnancy (ISSHP). Hypertens Pregnancy 2001;20:IX–XIV.
  • Psychogios N, Hau DD, Peng J, Guo AC, Mandal R, Bouatra S, Sinelnikov I, et al. The human serum metabolome. PLoS ONE 2011;6:e16957.
  • Saude EJ, Slupksy CM, Sykes BD. Optimization of NMR analysis of biological fluids for quantitative accuracy. Metabolom ICD 2006;2: 113–123.
  • Wishart DS. Computational approaches to metabolomics. Methods Mol Biol 2010;593:283–313.
  • Xia J, Psychogios N, Young N, Wishart DS. MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucleic Acids Res 2009;37:W652–W660.
  • Bijlsma S, Bobeldijk I, Verheij ER, Ramaker R, Kochhar S, Macdonald IA, van Ommen B, Smilde AK. Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation. Anal Chem 2006;78:567–574.
  • Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982;143:29–36.
  • Kell D. Genetic computing: defence against the flood: a solution to the data mining and predictive modeling challenges of today. Bioinforma World 2002;1:16–18.
  • Kell DB. Metabolomics and machine learning: explanatory analysis of complex metabolome data using genetic programming to produce simple, robust rules. Mol Biol Rep 2002;29:237–241.
  • Dunn WB, Broadhurst DI, Atherton HJ, Goodacre R, Griffin JL. Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy. Chem Soc Rev 2011;40:387–426.
  • Bijlsma S, Bodelijk I, Verheij E, Ramaker R, Kochhar S, MacDonald IA, et al. Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation. Anal Chem 2006;78: 567–574.
  • Demircio O, Tugriel AS, Dolgun N, Sozen H, Eren S. Serum lipid levels assessed in early pregnancy and the risk of pre-eclampsia. J Obstet Gyencol Res 2011 doi: 10.1111/j.1447-0756.2011.01562
  • Acilmis YG, Dikensoy E, Kutlar AI, Balat O, Cebesoy FB, Ozturk E, Cicek H, Pence S. Homocysteine, folic acid and vitamin B12 levels in maternal and umbilical cord plasma and homocysteine levels in placenta in pregnant women with pre-eclampsia. J Obstet Gynaecol Res 2011;37:45–50.
  • Peña-Reyes CA, Sipper M. Evolutionary computation in medicine: an overview. Artif Intell Med 2000;19:1–23.
  • Whitley D. An overview of evolutionary algorithms: practical issues and common pitfalls. Info Software Tech 2001;43:87–31.
  • Goodcare R. Making sense of the metabolome using evolutionary computing: seeing the wood with the trees. J Exp Bot 2005;56:245–254.
  • Miranda V, Srinivasan D, Proenca LM. Evolutionary computation in power systems. Elec Power Energ Sys 1998;20:89–98.
  • Akolekar R, Syngelaki A, Sarquis R, Zvanca M, Nicolaides KH. Prediction of early, intermediate and late pre-eclampsia from maternal factors, biophysical and biochemical markers at 11-13 weeks. Prenat Diagn 2011;31:66–74.
  • Poon LC, Kametas NA, Maiz N, Akolekar R, Nicolaides KH. First-trimester prediction of hypertensive disorders in pregnancy. Hypertension 2009;53:812–818.
  • Bahado-Singh RO, Jodicke C. Uterine artery Doppler in first-trimester pregnancy screening. Clin Obstet Gynecol 2010;53:879–887.
  • Kenny LC, Broadhurst DI, Dunn W, Brown M, North RA, McCowan L, Roberts C, et al.; Screening for Pregnancy Endpoints Consortium. Robust early pregnancy prediction of later preeclampsia using metabolomic biomarkers. Hypertension 2010;56:741–749.
  • Odibo AO, Goetzinger KR, Odibo L, Cahill AG, Macones GA, Nelson DM, Dietzen DJ. First-trimester prediction of preeclampsia using metabolomic biomarkers: a discovery phase study. Prenat Diagn 2011;31:990–994.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.