Comparison of serum human pregnancy-specific beta-1-glycoprotein 1 levels in pregnant women with or without preeclampsia

Temür, Muzaffer; Serpim, Gülçin; Tuzluoğlu, Sabiha; Taşgöz, Fatma Nurgül; Şahin, Elif; Üstünyurt, Emin

doi:10.1080/01443615.2019.1679734

Cited by 18 publications

(10 citation statements)

References 22 publications

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“…The protective haplotype also lies within a large cluster of PSG genes, a family of glycoproteins that are primarily synthesized in the syncytiotrophoblast of the human placenta. Several case-control studies have shown that low levels of PSG2 are associated with pre-eclampsia [21], which, in turn, has been suggested to be associated with an increased risk of dementia later in life [22]. Indeed, a recent study demonstrated that inducible pluripotent stem cell (iPSC) derived neurons made from the blood of autopsy confirmed AD patients, had abnormal tau deposition which matched their autopsy findings [23].…”

Section: Plos Geneticsmentioning

confidence: 99%

A locus at 19q13.31 significantly reduces the ApoE ε4 risk for Alzheimer’s Disease in African Ancestry

et al. 2022

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African descent populations have a lower Alzheimer disease risk from ApoE ε4 compared to other populations. Ancestry analysis showed that the difference in risk between African and European populations lies in the ancestral genomic background surrounding the ApoE locus (local ancestry). Identifying the mechanism(s) of this protection could lead to greater insight into the etiology of Alzheimer disease and more personalized therapeutic intervention. Our objective is to follow up the local ancestry finding and identify the genetic variants that drive this risk difference and result in a lower risk for developing Alzheimer disease in African ancestry populations. We performed association analyses using a logistic regression model with the ApoE ε4 allele as an interaction term and adjusted for genome-wide ancestry, age, and sex. Discovery analysis included imputed SNP data of 1,850 Alzheimer disease and 4,331 cognitively intact African American individuals. We performed replication analyses on 63 whole genome sequenced Alzheimer disease and 648 cognitively intact Ibadan individuals. Additionally, we reproduced results using whole-genome sequencing of 273 Alzheimer disease and 275 cognitively intact admixed Puerto Rican individuals. A further comparison was done with SNP imputation from an additional 8,463 Alzheimer disease and 11,365 cognitively intact non-Hispanic White individuals. We identified a significant interaction between the ApoE ε4 allele and the SNP rs10423769_A allele, (β = -0.54,SE = 0.12,p-value = 7.50x10-6) in the discovery data set, and replicated this finding in Ibadan (β = -1.32,SE = 0.52,p-value = 1.15x10-2) and Puerto Rican (β = -1.27,SE = 0.64,p-value = 4.91x10-2) individuals. The non-Hispanic Whites analyses showed an interaction trending in the “protective” direction but failing to pass a 0.05 significance threshold (β = -1.51,SE = 0.84,p-value = 7.26x10-2). The presence of the rs10423769_A allele reduces the odds ratio for Alzheimer disease risk from 7.2 for ApoE ε4/ε4 carriers lacking the A allele to 2.1 for ApoE ε4/ε4 carriers with at least one A allele. This locus is located approximately 2 mB upstream of the ApoE locus, in a large cluster of pregnancy specific beta-1 glycoproteins on chromosome 19 and lies within a long noncoding RNA, ENSG00000282943. This study identified a new African-ancestry specific locus that reduces the risk effect of ApoE ε4 for developing Alzheimer disease. The mechanism of the interaction with ApoEε4 is not known but suggests a novel mechanism for reducing the risk for ε4 carriers opening the possibility for potential ancestry-specific therapeutic intervention.

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Section: Plos Geneticsmentioning

confidence: 99%

A locus at 19q13.31 significantly reduces the ApoE ε4 risk for Alzheimer’s Disease in African Ancestry

et al. 2022

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“…Several studies have reported that expression of CGB5 was essential for pregnancy success [30]. Aberrations of CRH (corticotropin releasing hormone) [31] and PSG1 [32] contribute to preeclampsia occurrence. The expression of CYP19A1 was significantly up regulated in hypertensive disorders of pregnancy [33].…”

Section: Discussionmentioning

confidence: 99%

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus

Vastrad¹,

Vastrad²,

Tengli

2021

Preprint

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Gestational diabetes mellitus (GDM) is one of the metabolic diseases during pregnancy. The identification of the central molecular mechanisms liable for the disease pathogenesis might lead to the advancement of new therapeutic options. The current investigation aimed to identify central differentially expressed genes (DEGs) in GDM. The transcription profiling by array data (E-MTAB-6418) was obtained from the ArrayExpress database. The DEGs between GDM samples and non GDM samples were analyzed with limma package. Gene ontology (GO) and REACTOME enrichment analysis were performed using ToppGene. Then we constructed the protein-protein interaction (PPI) network of DEGs by the Search Tool for the Retrieval of Interacting Genes database (STRING) and module analysis was performed. Subsequently, we constructed the miRNA-hub gene network and TF-hub gene regulatory network by the miRNet database and NetworkAnalyst database. The validation of hub genes was performed through receiver operating characteristic curve (ROC). Finally, the candidate small molecules as potential drugs to treat GDM were predicted by using molecular docking. Through transcription profiling by array data, a total of 869 DEGs were detected including 439 up regulated and 430 down regulated genes. Biological process analysis of GO enrichment analysis showed these DEGs were mainly enriched in reproduction, nuclear outer membrane-endoplasmic reticulum membrane network, identical protein binding, cell adhesion, supramolecular complex and signaling receptor binding. Signaling pathway enrichment analysis indicated that these DEGs played a vital in cell surface interactions at the vascular wall and extracellular matrix organization. Ten genes, HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3, and PRKCA in the center of the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network were associated with GDM, according to ROC analysis. Finally, the most significant small molecules were predicted based on molecular docking. Our results indicated that HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3, and PRKCA could be the potential novel biomarkers for GDM diagnosis, prognosis and the promising therapeutic targets. The current might be essential to understanding the molecular mechanism of GDM initiation and development.

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“…It is also associated with significant fetal morbidity and mortality, including intrauterine growth restriction, placental abruption, oligohydramnios, stillbirth, and fetal death ( 4 , 5 ). The exact etiology of PE remains unclear ( 4 ), but hypotheses include abnormal placental implantation ( 4 ), angiogenic pathways ( 4 , 9 , 10 ), cardiovascular maladaptation and vasoconstriction ( 4 ), genetic predisposition ( 4 ), immunology ( 4 ), oxidative stress ( 4 , 5 , 11 ), autocrine/paracrine factors ( 12 , 13 ), and capillary rarefaction ( 14 ). Clinical practice guidelines strongly recommend low-dose aspirin at 12–16 weeks’ gestation for pregnant women at high risk of PE ( 15 , 16 ).…”

Section: Introductionmentioning

confidence: 99%

Development and validation of the prediction models for preeclampsia: a retrospective, single-center, case-control study

Chen¹,

Li²,

Ji³

et al. 2022

Ann Transl Med

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Background: Preeclampsia (PE) is a major cause of adverse maternal and infant outcomes. Accurate screening of PE is currently the focus of clinical attention. This study aimed to develop a model for predicting PE.Methods: A retrospective case-control study was conducted with 916 pregnant women who received care at the Second Hospital of Tianjin Medical University (October 2018 to July 2020). Women were randomly divided into the training (n=680) and testing (n=236) sets based on a ratio of 3:1. Demographic and clinical data of women were collected. In training set, logistic regression (LR), classification tree model (CT), and random forest algorithm (RF) were used to develop prediction models for PE. Using the testing set was to validate these prediction models. The predictive performance of three models were assessed by the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).Results: Of the total 916 women, 237 had PE. The family history of hypertension, pre-pregnancy body mass index (pBMI), blood pressure (BP) ≥130/80 mmHg in early pregnancy, age, chronic hypertension, and duration of hypertension were the predictors of PE. The AUCs for the LR, CT, and RF models were 0.778, 0.850, and 0.871, respectively (all P<0.05 for all pair-wise comparisons). The RF had the best predictive efficiency with sensitivity, specificity, PPV, and NPV of 79.6%, 94.7%, 79.6%, and 94.7%, respectively. Conclusions:The RF model could be a practical screening approach for predicting PE, which is helpful for clinicians to identify high-risk individuals and prevent the occurrence of adverse pregnancy outcomes.

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Comparison of serum human pregnancy-specific beta-1-glycoprotein 1 levels in pregnant women with or without preeclampsia

Cited by 18 publications

References 22 publications

A locus at 19q13.31 significantly reduces the ApoE ε4 risk for Alzheimer’s Disease in African Ancestry

A locus at 19q13.31 significantly reduces the ApoE ε4 risk for Alzheimer’s Disease in African Ancestry

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus

Development and validation of the prediction models for preeclampsia: a retrospective, single-center, case-control study

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