Leeman L, Fontaine P: Hypertensive disorders of pregnancy. Am Fam Physician. 2008, 78 (1): 93-100.
PubMed
Google Scholar
National Collaborating Centre for Women’s and Children’s Health: Hypertension in pregnancy. The management of hypertensive disorders during pregnancy. 2010, London (UK): National Institute for Health and Clinical Excellence (NICE); 46. Clinical guideline; no. 107
Google Scholar
Jeffcoate TN: Pre-eclampsia and eclampsia: the disease of theories. Proc R Soc Med. 1966, 59 (5): 397-404.
CAS
PubMed
PubMed Central
Google Scholar
Sheppard SJ, Khalil RA: Risk factors and mediators of the vascular dysfunction associated with hypertension in pregnancy. Cardiovasc Hematol Disord Drug Targets. 2010, 10 (1): 33-52. 10.2174/187152910790780096.
Article
CAS
PubMed
PubMed Central
Google Scholar
Nishizawa H, Pryor-Koishi K, Kato T, Kowa H, Kurahashi H, Udagawa Y: Microarray analysis of differentially expressed fetal genes in placental tissue derived from early and late onset severe pre-eclampsia. Placenta. 2007, 28 (5–6): 487-497.
Article
CAS
PubMed
Google Scholar
Founds SA, Conley YP, Lyons-Weiler JF, Jeyabalan A, Hogge WA, Conrad KP: Altered global gene expression in first trimester placentas of women destined to develop Preeclampsia. Placenta. 2009, 30 (1): 15-24. 10.1016/j.placenta.2008.09.015.
Article
CAS
PubMed
Google Scholar
Sitras V, Paulssen RH, Grønaas H, Leirvik J, Hanssen TA, Vårtun A, Acharya G: Differential placental gene expression in severe preeclampsia. Placenta. 2009, 30 (5): 424-433. 10.1016/j.placenta.2009.01.012.
Article
CAS
PubMed
Google Scholar
Tejera E, Bernardes J, Rebelo I: Preeclampsia: a bioinformatics approach through protein-protein interaction networks analysis. BMC Syst Biol. 2012, 6: 97-10.1186/1752-0509-6-97.
Article
CAS
PubMed
PubMed Central
Google Scholar
Barrett T, Troup DB, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Muertter RN, Holko M, Ayanbule O, Yefanov A, Soboleva A: NCBI GEO: archive for functional genomics data sets-10 years on. Nucleic Acids Res. 2011, 39: D1005-D1010. 10.1093/nar/gkq1184.
Article
CAS
PubMed
Google Scholar
Parkinson H, Sarkans U, Kolesnikov N, Abeygunawardena N, Burdett T, Dylag M, Emam I, Farne A, Hastings E, Holloway E, Kurbatova N, Lukk M, Malone J, Mani R, Pilicheva E, Rustici G, Sharma A, Williams E, Adamusiak T, Brandizi M, Sklyar N, Brazma A: ArrayExpress update–an archive of microarray and high-throughput sequencing-based functional genomics experiments. Nucleic Acids Res. 2011, 39: D1002-D1004. 10.1093/nar/gkq1040.
Article
CAS
PubMed
Google Scholar
Roten LT, Johnson MP, Løset M, Mundal SV, Forsmo S, Skorpen F, Fenstad MH, Dyer TD, Blangero J, Moses EK, Austgulen E: Evaluation of COMT as a maternal preeclampsia candidate susceptibility gene; assessed by genotyping of the Val158Met polymorphism and by transcriptinal profiling of decidual tissue. Array Express Database. 2011, Ref:E-TABM-682. Last update, June 2011
Google Scholar
Eide IP, Isaksen CV, Salvesen KA, Langaas M, Schønberg SA, Austgulen R: Decidual expression and maternal serum levels of heme oxygenase 1 are increased in pre-eclampsia. Acta Obstet Gynecol Scand. 2008, 87 (3): 272-279. 10.1080/00016340701763015.
Article
CAS
PubMed
Google Scholar
Tsai S, Hardison NE, James AH, Motsinger-Reif AA, Bischoff SR, Thames BH, Piedrahita JA: Transcriptional profiling of human placentas from pregnancies complicated by preeclampsia reveals disregulation of sialic acid acetylesterase and immune signalling pathways. Placenta. 2011, 32 (2): 175-182. 10.1016/j.placenta.2010.11.014.
Article
CAS
PubMed
Google Scholar
Winn VD, Gormley M, Paquet AC, Kjaer-Sorensen K, Kramer A, Rumer KK, Haimov-Kochman R, Yeh RF, Overgaard MT, Varki A, Oxvig C, Fisher SJ: Severe preeclampsia-related changes in gene expression at the maternal-fetal interface include sialic acid-binding immunoglobulin-like lectin-6 and pappalysin-2. Endocrinology. 2009, 150 (1): 452-462.
Article
CAS
PubMed
Google Scholar
Gautier L, Cope L, Bolstad BM, Irizarry RA: affy–-analysis of Affymetrix GeneChip data at the probe level. Bioinformatics. 2004, 20 (3): 307-315. 10.1093/bioinformatics/btg405.
Article
CAS
PubMed
Google Scholar
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J: Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004, 5 (10): R80-10.1186/gb-2004-5-10-r80.
Article
PubMed
PubMed Central
Google Scholar
Du P, Kibbe WA, Lin SM: lumi: a pipeline for processing Illumina microarray. Bioinformatics. 2008, 24 (13): 1547-1548. 10.1093/bioinformatics/btn224.
Article
CAS
PubMed
Google Scholar
Davis S, Meltzer PS: GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics. 2007, 23 (14): 1846-1847. 10.1093/bioinformatics/btm254.
Article
PubMed
Google Scholar
Fan X, Shao L, Fang H, Tong W, Cheng Y: Cross-platform comparison of microarray-based multiple-class prediction. PLoS One. 2011, 6 (1): e16067-10.1371/journal.pone.0016067.
Article
CAS
PubMed
PubMed Central
Google Scholar
Sîrbu A, Ruskin HJ, Crane M: Cross-platform microarray data normalisation for regulatory network inference. PLoS One. 2010, 5 (11): e13822-10.1371/journal.pone.0013822.
Article
PubMed
PubMed Central
Google Scholar
Rudy J, Valafar F: Empirical comparison of cross-platform normalization methods for gene expression data. BMC Bioinforma. 2011, 12: 467-10.1186/1471-2105-12-467.
Article
Google Scholar
Du P, Kibbe WA, Lin SM: nuID: a universal naming scheme of oligonucleotides for illumina, affymetrix, and other microarrays. Biol Direct. 2007, 2: 16-10.1186/1745-6150-2-16.
Article
PubMed
PubMed Central
Google Scholar
Carlson M: hgu133b.db: Affymetrix Human Genome U133 Set annotation data (chip hgu133b). R package version 2.8.0
Langfelder P, Horvath S: WGCNA: an R package for weighted correlation network analysis. BMC Bioinforma. 2008, 9: 559-10.1186/1471-2105-9-559.
Article
Google Scholar
Miller JA, Cai C, Langfelder P, Geschwind DH, Kurian SM, Salomon DR, Horvath S: Strategies for aggregating gene expression data: the collapseRows R function. BMC Bioinforma. 2011, 12: 322-10.1186/1471-2105-12-322.
Article
CAS
Google Scholar
Johnson WE, Li C, Rabinovic A: Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2007, 8: 118-127. 10.1093/biostatistics/kxj037.
Article
PubMed
Google Scholar
Smyth GK: Limma: linear models for microarray data. Bioinformatics and Computational Biology Solutions using R and Bioconductor. Edited by: Gentleman R, Carey V, Dudoit S, Irizarry R, Huber W. 2005, New York: Springer
Google Scholar
Zhang B, Horvath S: A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mo B. 2005, 4 (1): 17.
Google Scholar
Langfelder P, Zhang B, Horvath S: Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R. Bioinformatics. 2007, 24 (5): 719-720.
Article
PubMed
Google Scholar
Ray M, Yunis R, Chen X, Rocke DM: Comparison of low and high dose ionising radiation using topological analysis of gene coexpression networks. BMC Genomics. 2012, 13: 190-10.1186/1471-2164-13-190.
Article
CAS
PubMed
PubMed Central
Google Scholar
Ray M, Zhang W: Analysis of Alzheimer’s disease severity across brain regions by topological analysis of gene co-expression networks. BMC Syst Biol. 2010, 4: 136-10.1186/1752-0509-4-136.
Article
PubMed
PubMed Central
Google Scholar
Huang DW, Sherman BT, Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Protoc. 2009, 4 (1): 44-57.
Article
CAS
Google Scholar
Powe CE, Levine RJ, Karumanchi SA: Preeclampsia, a disease of the maternal endothelium. Circulation. 2011, 123: 2856-2869. 10.1161/CIRCULATIONAHA.109.853127.
Article
PubMed
Google Scholar
McElrath TF, Lim KH, Pare E, Rich-Edwards J, Pucci D, Troisi R, Parry S: Longitudinal evaluation of predictive value for preeclampsia of circulating angiogenic factors through pregnancy. Am J Obstet Gynecol. 2012, 207 (5): 407.e1-7.
Article
PubMed
Google Scholar
Masoura S, Kalogiannidis IA, Gitas G, Goutsioulis A, Koiou E, Athanasiadis A, Vavatsi N: Biomarkers in pre-eclampsia: a novel approach to early detection of the disease. J Obstet Gynaecol. 2012, 32 (7): 609-616. 10.3109/01443615.2012.709290.
Article
CAS
PubMed
Google Scholar
Wang S, Qiao FY, Feng L: High leptin level and leptin receptor Lys656Asn variant are risk factors for preeclampsia. Genet Mol Res. 2013, 4: 12.
Google Scholar
Hogg K, Blair JD, von Dadelszen P, Robinson WP: Hypomethylation of the LEP gene in placenta and elevated maternal leptin concentration in early onset pre-eclampsia. Mol Cell Endocrinol. 2013, 367 (1–2): 64-73.
Article
CAS
PubMed
Google Scholar
Guo J, Tian T, Lu D, Xia G, Wang H, Dong M: Alterations of maternal serum and placental follistatin-like 3 and myostatin in pre-eclampsia. J Obstet Gynaecol Res. 2012, 38 (7): 988-996. 10.1111/j.1447-0756.2011.01823.x.
Article
CAS
PubMed
Google Scholar
Founds SA, Terhorst LA, Conrad KP, Hogge WA, Jeyabalan A, Conley YP: Gene expression in first trimester preeclampsia placenta. Biol Res Nurs. 2011, 13 (2): 134-139. 10.1177/1099800410385448.
Article
PubMed
Google Scholar
Pryor-Koishi K, Nishizawa H, Kato T, Kogo H, Murakami T, Tsuchida K, Kurahashi H, Udagawa Y: Overproduction of the follistatin-related gene protein in the placenta and maternal serum of women with pre-eclampsia. BJOG. 2007, 114 (9): 1128-1137. 10.1111/j.1471-0528.2007.01425.x.
Article
CAS
PubMed
Google Scholar
Rohra DK, Zeb A, Qureishi RN, Azam SI, Khan NB, Zuberi HS, Sikandar R: Prediction of pre-eclampsia during early pregnancy in primiparas with soluble fms-like tyrosine kinase-1 and placental growth factor. Natl Med J India. 2012, 25 (2): 68-73.
CAS
PubMed
Google Scholar
Aquilina J, Thompson O, Thilaganathan B, Harrington K: Improved early prediction of pre-eclampsia by combining second-trimester maternal serum inhibin-A and uterine artery Doppler. Ultrasound Obstet Gynecol. 2001, 17 (6): 477-484. 10.1046/j.1469-0705.2001.00382.x.
Article
CAS
PubMed
Google Scholar
Kuc S, Wortelboer EJ, van Rijn BB, Franx A, Visser GH, Schielen PC: Evaluation of 7 serum biomarkers and uterine artery Doppler ultrasound for first-trimester prediction of preeclampsia: a systematic review. Obstet Gynecol Surv. 2011, 66 (4): 225-239. 10.1097/OGX.0b013e3182227027.
Article
PubMed
Google Scholar
Petraglia F, Luisi S, Benedetto C, Zonca M, Florio P, Casarosa E, Volpe A, Bernasconi S, Genazzani AR: Changes of dimeric inhibin B levels in maternal serum throughout healthy gestation and in women with gestational diseases. J Clin Endocrinol Metab. 1997, 82 (9): 2991-2995. 10.1210/jc.82.9.2991.
CAS
PubMed
Google Scholar
Nishizawa H, Ota S, Suzuki M, Kato T, Sekiya T, Kurahashi H, Udagawa Y: Comparative gene expression profiling of placentas from patients with severe pre-eclampsia and unexplained fetal growth restriction. Reprod Biol Endocrinol. 2011, 9: 107-10.1186/1477-7827-9-107.
Article
CAS
PubMed
PubMed Central
Google Scholar
Okazaki S, Sekizawa A, Purwosunu Y, Farina A, Wibowo N, Okai T: Placenta-derived, cellular messenger RNA expression in the maternal blood of preeclamptic women. Obstet Gynecol. 2007, 110 (5): 1130-1136. 10.1097/01.AOG.0000286761.11436.67.
Article
CAS
PubMed
Google Scholar
Choi SJ, Oh SY, Kim JH, Sadovsky Y, Roh CR: Increased expression of N-myc downstream-regulated gene 1 (NDRG1) in placentas from pregnancies complicated by intrauterine growth restriction or preeclampsia. Am J Obstet Gynecol. 2007, 196 (1): 45.e1-7.
Article
PubMed
Google Scholar
Li L, Weinberg RC: Gene selection and sample classification using a genetic algorithm and k-Nearest neighbor method. A Practical Approach to Microarray Data Analysis. Edited by: Berrar DP, Dubitzky W, Granzow M. 2003, Kluwer Academic Publishers, 216-229.
Chapter
Google Scholar
Saposnik B, Peynaud-Debayle E, Stepanian A, Baron G, Simansour M, Mandelbrot L, de Prost D, Gandrille S: Elevated soluble endothelial cell protein C receptor (sEPCR) levels in women with preeclampsia: a marker of endothelial activation/damage?. Thromb Res. 2012, 129 (2): 152-157. 10.1016/j.thromres.2011.07.023.
Article
CAS
PubMed
Google Scholar
Marzioni D, Lorenzi T, Altobelli E, Giannubilo SR, Paolinelli F, Tersigni C, Crescimanno C, Monsurrò V, Tranquilli AL, Di Simone N, Castellucci M: Alterations of maternal plasma HTRA1 level in preeclampsia complicated by IUGR. Placenta. 2012, 33 (12): 1036-1038. 10.1016/j.placenta.2012.09.011.
Article
CAS
PubMed
Google Scholar
Yu L, Li D, Liao QP, Yang HX, Cao B, Fu G, Ye G, Bai Y, Wang H, Cui N, Liu M, Li YX, Li J, Peng C, Wang YL: High levels of activin A detected in preeclamptic placenta induce trophoblast cell apoptosis by promoting nodal signaling. J Clin Endocrinol Metab. 2012, 97 (8): E1370-E1379. 10.1210/jc.2011-2729.
Article
CAS
PubMed
Google Scholar
Akolekar R, Etchegaray A, Zhou Y, Maiz N, Nicolaides KH: Maternal serum activin a at 11–13 weeks of gestation in hypertensive disorders of pregnancy. Fetal Diagn Ther. 2009, 25 (3): 320-327. 10.1159/000235878.
Article
PubMed
Google Scholar
Jonsson PF, Bates PA: Global topological features on cancer proteins in the human interactome. Bioinformatics. 2006, 22: 2291-2297. 10.1093/bioinformatics/btl390.
Article
CAS
PubMed
PubMed Central
Google Scholar
Wachi S, Yoneda K, Wu R: Interactome-transcriptome analysis reveals high centrality of genes differentially expressed in lung cancer tissue. Bioinformatics. 2005, 21: 4205-4208. 10.1093/bioinformatics/bti688.
Article
CAS
PubMed
PubMed Central
Google Scholar
Lian IA, Toft JH, Olsen GD, Langaas M, Bjørge L, Eide IP, Børdahl PE, Austgulen R: Matrix metalloproteinase 1 in pre-eclampsia and fetal growth restriction: reduced gene expression in decidual tissue and protein expression in extravillous trophoblasts. Placenta. 2010, 31 (7): 615-620. 10.1016/j.placenta.2010.04.003.
Article
CAS
PubMed
Google Scholar
Mousa AA, Cappello RE, Estrada-Gutierrez G, Shukla J, Romero R, Strauss JF, Walsh SW: Preeclampsia is associated with alterations in DNA methylation of genes involved in collagen metabolism. Am J Pathol. 2012, 181 (4): 1455-1463. 10.1016/j.ajpath.2012.06.019.
Article
CAS
PubMed
PubMed Central
Google Scholar
Lian IA, Løset M, Mundal SB, Fenstad MH, Johnson MP, Eide IP, Bjørge L, Freed KA, Moses EK, Austgulen R: Increased endoplasmic reticulum stress in decidual tissue from pregnancies complicated by fetal growth restriction with and without pre-eclampsia. Placenta. 2011, 32 (11): 823-829. 10.1016/j.placenta.2011.08.005.
Article
CAS
PubMed
PubMed Central
Google Scholar