Inflammation in Preeclampsia: Genetic Biomarkers, Mechanisms, and Therapeutic Strategies

Abstract

ObjectivePreeclampsia is a common and serious complication of pregnancy, posing a threat to maternal and fetal safety due to the lack of effective biomarkers and treatment strategies. This study aimed to identify potential biomarkers that can be used to predict preeclampsia and identify the molecular mechanisms of preeclampsia pathogenesis and drug prediction at the transcriptome level.MethodsWe analyzed differential expression genes (DEGs) in preeclampsia and non-preeclampsia groups in the GSE75010 dataset, cross-linking with extracted inflammatory response-related genes to obtain differentially expressed inflammation-related genes (DINRGs). Enrichment analysis and protein-protein interaction (PPI) networks were constructed to understand the functions and enrichment pathways. Machine learning models were used to identify key genes associated with preeclampsia and build a nomogram in the training set, which was validated in the validation set. The R package RcisTarget was used to predict transcription factors, and Cytoscape was used to construct miRNA-mRNA pathways, which could identify the molecular mechanisms. Then, we conducted molecular docking of the obtained key genes INHBA (inhibin subunit beta A), OPRK1 (opioid receptor kappa 1), and TPBG (trophoblast glycoprotein), as well as predicted transcription factors with drug molecules. Additionally, the CIBERSORT method explored the differences in immune cell infiltration between preeclampsia and non-preeclampsia samples based on the GSE75010 dataset.ResultsA total of 69 DINRGs associated with preeclampsia patients were screened. INHBA, OPRK1, and TPBG were the key genes based on machine learning models. A nomogram for prediction was further constructed, and the receiver operating curves (ROCs) showed good performance. Based on the transcriptome level of key genes, we proposed that RELA-miR-548K/miR-1206-TPBG may be a potential RNA regulatory pathway regulating the progression of early preeclampsia. Molecular docking suggested the effectiveness of curcumin in the treatment of preeclampsia. Additionally, regulatory T cells (Tregs) and resting mast cells were significantly different between the two groups.ConclusionIn summary, we identified three key inflammation-associated genes, namely INHBA, OPRK1, and TPBG, which can be used as potential genetic biomarkers for preeclampsia prediction and treatment, and established a nomogram as a predictive model. Additionally, we provided insights into the mechanisms of preeclampsia development at the transcriptome level and performed corresponding drug predictions.

The relationship between arginine vasopressin gene polymorphisms and plasma copeptin and hypertensive disorders of pregnancy: a nested case-control study

“…Consistent with our results, a cohort study [24] exploring the effect of AVP gene variation and plasma copeptin on the risk of diabetes did not find a significant association between the polymorphisms of rs3761249 and rs2282018 and copeptin concentration in women but found an association between the polymorphisms of two loci and copeptin in men. The genetic contributions to preeclampsia are likely to be complex, in addition, to directly causing preeclampsia by encoding proteins, the genes involved may alter the expression of RNA or lower a woman's biological threshold at which she would develop the condition [25,26]. However, the current study has not detected the expression of RNA, so it is unavailable to analyze whether the variation of the AVP gene affects the occurrence of GH and PE through the expression amount of the gene.…”

“…A case-control study from Turkey [17] reported that plasma levels of copeptin in the third trimester of pregnancy were 0.31AE0.09ng/ml, 0.62 AE 0.16 ng/ml, and 0.85 AE 0.18 ng/ml among women with normal blood pressure, mild preeclampsia and severe preeclampsia (P < 0.001), respectively. Yeung et al [14] measured serum copeptin three times using samples collected longitudinally during pregnancy among controls (n ¼ 136), cases of preeclampsia (n ¼ 169), and gestational hypertension (n ¼ 101) in the Calcium for Preeclampsia Prevention Trial, the results showed that copeptin levels at the baseline (<22 GW), second (22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32) and third (33-38GW) measures positively associated with risk of PE, but were not associated with risk of GH. Marek et al [18] reported that the concentrations of copeptin in the second and third trimesters were significantly different between pregnancy-induced hypertension and the controls, but not in the first trimester.…”

Altered Epigenetic Profiles in the Placenta of Preeclamptic and Intrauterine Growth Restriction Patients

“…NAPRT1 is a cellular metabolic enzyme expressed in the placental trophoblast, which is known to prevent oxidative stress in several diseases including cancer [ 29 ]. This is important because the PE placenta is known to have high oxidative stress during this disease [ 48 , 49 ]. The fact that the NAPRT1 protein was decreased could drive the idea that this protein may be involved in the increased oxidative stress leading to the increased reactive oxidative species observed in this disease.…”

Combination of single-nucleus and bulk RNA-seq reveals the molecular mechanism of thalamus haemorrhage-induced central poststroke pain

“…In addition to the motifs annotated by the source data, further annotation files were inferred based on motif similarity and gene sequences. The first step in estimating the overexpression of each motif across a gene set is to calculate the area under the curve (AUC) for each motif-motif-set pair ( 31 ). This calculation was performed based on the recovery curve calculation of the gene set versus motif ordering.…”