6.
Sovio U, Gaccioli F, Cook E, Charnock-Jones D, Smith G
. Association between adverse pregnancy outcome and placental biomarkers in the first trimester: A prospective cohort study. BJOG. 2023; 131(6):823-831.
DOI: 10.1111/1471-0528.17691.
View
7.
Parry S, Carper B, Grobman W, Wapner R, Chung J, Haas D
. Placental protein levels in maternal serum are associated with adverse pregnancy outcomes in nulliparous patients. Am J Obstet Gynecol. 2022; 227(3):497.e1-497.e13.
PMC: 9420814.
DOI: 10.1016/j.ajog.2022.03.064.
View
8.
Ohwaki A, Nishizawa H, Kato A, Kato T, Miyazaki J, Yoshizawa H
. Placental Genetic Variants in the Upstream Region of the FLT1 Gene in Pre-eclampsia. J Reprod Infertil. 2020; 21(4):240-246.
PMC: 7648866.
DOI: 10.18502/jri.v21i4.4325.
View
9.
Tyrmi J, Kaartokallio T, Lokki A, Jaaskelainen T, Kortelainen E, Ruotsalainen S
. Genetic Risk Factors Associated With Preeclampsia and Hypertensive Disorders of Pregnancy. JAMA Cardiol. 2023; 8(7):674-683.
PMC: 10248811.
DOI: 10.1001/jamacardio.2023.1312.
View
10.
Honigberg M, Truong B, Khan R, Xiao B, Bhatta L, Vy H
. Polygenic prediction of preeclampsia and gestational hypertension. Nat Med. 2023; 29(6):1540-1549.
PMC: 10330886.
DOI: 10.1038/s41591-023-02374-9.
View
11.
Martin F, Amode M, Aneja A, Austine-Orimoloye O, Azov A, Barnes I
. Ensembl 2023. Nucleic Acids Res. 2022; 51(D1):D933-D941.
PMC: 9825606.
DOI: 10.1093/nar/gkac958.
View
12.
Maynard S, Venkatesha S, Thadhani R, Karumanchi S
. Soluble Fms-like tyrosine kinase 1 and endothelial dysfunction in the pathogenesis of preeclampsia. Pediatr Res. 2005; 57(5 Pt 2):1R-7R.
DOI: 10.1203/01.PDR.0000159567.85157.B7.
View
13.
Taliun D, Harris D, Kessler M, Carlson J, Szpiech Z, Torres R
. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature. 2021; 590(7845):290-299.
PMC: 7875770.
DOI: 10.1038/s41586-021-03205-y.
View
14.
Weissgerber T, Rajakumar A, Myerski A, Edmunds L, Powers R, Roberts J
. Vascular pool of releasable soluble VEGF receptor-1 (sFLT1) in women with previous preeclampsia and uncomplicated pregnancy. J Clin Endocrinol Metab. 2014; 99(3):978-87.
PMC: 3942228.
DOI: 10.1210/jc.2013-3277.
View
15.
Zheng X, Levine D, Shen J, Gogarten S, Laurie C, Weir B
. A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics. 2012; 28(24):3326-8.
PMC: 3519454.
DOI: 10.1093/bioinformatics/bts606.
View
16.
Allotey J, Snell K, Smuk M, Hooper R, Chan C, Ahmed A
. Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis. Health Technol Assess. 2020; 24(72):1-252.
PMC: 7780127.
DOI: 10.3310/hta24720.
View
17.
Sun B, Chiou J, Traylor M, Benner C, Hsu Y, Richardson T
. Plasma proteomic associations with genetics and health in the UK Biobank. Nature. 2023; 622(7982):329-338.
PMC: 10567551.
DOI: 10.1038/s41586-023-06592-6.
View
18.
Beaven S, Martin M
. Tales from the crypt: beta-catenin in the development of juvenile polyps: commentary on the article by Iwamoto et al. on page 4. Pediatr Res. 2004; 57(1):1-3.
DOI: 10.1203/01.PDR.0000147571.31868.9B.
View
18.
Das S, Forer L, Schonherr S, Sidore C, Locke A, Kwong A
. Next-generation genotype imputation service and methods. Nat Genet. 2016; 48(10):1284-1287.
PMC: 5157836.
DOI: 10.1038/ng.3656.
View
19.
Bergstrom A, McCarthy S, Hui R, Almarri M, Ayub Q, Danecek P
. Insights into human genetic variation and population history from 929 diverse genomes. Science. 2020; 367(6484).
PMC: 7115999.
DOI: 10.1126/science.aay5012.
View