Literature DB >> 27753020

Characterization of Human Pregnancy Specific Glycoprotein (PSG) Gene Copy Number Variations in Pre-eclampsia Patients.

Chia Lin Chang1, Chia Yu Chang2, Da Xian Lee2, Po Jen Cheng2.   

Abstract

Pre-eclampsia is a pregnancy-specific hypertensive disorder that affects 2-8 % of pregnancies. This disorder can lead to seizure, multi-organ failure and maternal death. The best approach to prevent pre-eclampsia-associated adverse outcomes is to be able to prevent pre-eclampsia as early as possible. Unfortunately, current diagnostic methods are ineffective at predicting the risk of pre-eclampsia during early pregnancy. In humans, low levels of a group of placenta-derived Pregnancy Specific Glycoproteins (PSGs) have been associated with intrauterine growth retardation and pre-eclampsia and there is a significant enrichment of cases with deletions in the PSG gene locus in pre-eclampsia patients. Based on these observations, we hypothesize that genomic variations at human PSG locus of maternal and/or fetal genomes may confer increased risks of pre-eclampsia. To test this hypothesis, we have recruited 90 normal control and 30 pre-eclamptic women for the analysis of fetal PSG copy number variations (CNVs).The identification of novel PSG CNV-disease relationships will provide not only a better understanding of the pathology of pre-eclampsia but also a novel opportunity to identify patients with a high risk of developing early-onset pre-eclampsia, which has a five- to tenfold higher risk of life-threatening maternal complications and fetal demise as compared to late-onset pre-eclampsia patients.

Entities:  

Keywords:  Copy number variations; Pre-eclampsia; Pregnancy specific glycoproteins

Mesh:

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Year:  2016        PMID: 27753020     DOI: 10.1007/978-3-319-42044-8_12

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  2 in total

1.  Serum proteins differentially expressed in early- and late-onset preeclampsia assessed using iTRAQ proteomics and bioinformatics analyses.

Authors:  Chengcheng Tu; Feng Tao; Ying Qin; Mingzhu Wu; Ji Cheng; Min Xie; Bing Shen; Junjiao Ren; Xiaohong Xu; Dayan Huang; Hongbo Chen
Journal:  PeerJ       Date:  2020-09-01       Impact factor: 2.984

2.  Modeling preeclampsia using human induced pluripotent stem cells.

Authors:  Mariko Horii; Robert Morey; Tony Bui; Ojeni Touma; Katharine K Nelson; Hee-Young Cho; Hannah Rishik; Louise C Laurent; Mana M Parast
Journal:  Sci Rep       Date:  2021-03-15       Impact factor: 4.379

  2 in total

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