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Knihtilä HM, Kachroo P, Shadid I, Raissadati A, Peng C, McElrath TF, Litonjua AA, Demeo DL, Loscalzo J, Weiss ST, Mirzakhani H. Cord blood DNA methylation signatures associated with preeclampsia are enriched for cardiovascular pathways: insights from the VDAART trial. EBioMedicine 2023; 98:104890. [PMID: 37995466 PMCID: PMC10709000 DOI: 10.1016/j.ebiom.2023.104890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 11/07/2023] [Accepted: 11/14/2023] [Indexed: 11/25/2023] Open
Abstract
BACKGROUND Preeclampsia has been associated with maternal epigenetic changes, in particular DNA methylation changes in the placenta. It has been suggested that preeclampsia could also cause DNA methylation changes in the neonate. We examined DNA methylation in relation to gene expression in the cord blood of offspring born to mothers with preeclampsia. METHODS This study included 128 mother-child pairs who participated in the Vitamin D Antenatal Asthma Reduction Trial (VDAART), where assessment of preeclampsia served as secondary outcome. We performed an epigenome-wide association study of preeclampsia and cord blood DNA methylation (Illumina 450 K chip). We then examined gene expression of the same subjects for validation and replicated the gene signatures in independent DNA methylation datasets. Lastly, we applied functional enrichment and network analyses to identify biological pathways that could potentially be involved in preeclampsia. FINDINGS In the cord blood samples (n = 128), 263 CpGs were differentially methylated (FDR <0.10) in preeclampsia (n = 16), of which 217 were annotated. Top pathways in the functional enrichment analysis included apelin signaling pathway and other endothelial and cardiovascular pathways. Of the 217 genes, 13 showed differential expression (p's < 0.001) in preeclampsia and 11 had been previously related to preeclampsia (p's < 0.0001). These genes were linked to apelin, cGMP and Notch signaling pathways, all having a role in angiogenic process and cardiovascular function. INTERPRETATION Preeclampsia is related to differential cord blood DNA methylation signatures of cardiovascular pathways, including the apelin signaling pathway. The association of these cord blood DNA methylation signatures with offspring's long-term morbidities due to preeclampsia should be further investigated. FUNDING VDAART is funded by National Heart, Lung, and Blood Institute grants of R01HL091528 and UH3OD023268. HMK is supported by Jane and Aatos Erkko Foundation, Paulo Foundation, and the Pediatric Research Foundation. HM is supported by K01 award from NHLBI (1K01HL146977-01A1). PK is supported by K99HL159234 from NIH/NHLBI.
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Affiliation(s)
- Hanna M Knihtilä
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Priyadarshini Kachroo
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Iskander Shadid
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, the Netherlands
| | - Alireza Raissadati
- Department of Pediatric Cardiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Cheng Peng
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Thomas F McElrath
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Brigham and Women's Hospital, Boston, MA, USA
| | - Augusto A Litonjua
- Division of Pediatric Pulmonary Medicine, Golisano Children's Hospital, University of Rochester Medical Center, Rochester, NY, USA
| | - Dawn L Demeo
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Joseph Loscalzo
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Scott T Weiss
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Hooman Mirzakhani
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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He J, Yang H, Liu Z, Chen M, Ye Y, Tao Y, Li S, Fang J, Xu J, Wu X, Qi H. Elevated expression of glycolytic genes as a prominent feature of early-onset preeclampsia: insights from integrative transcriptomic analysis. Front Mol Biosci 2023; 10:1248771. [PMID: 37818100 PMCID: PMC10561389 DOI: 10.3389/fmolb.2023.1248771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 09/08/2023] [Indexed: 10/12/2023] Open
Abstract
Introduction: Preeclampsia (PE), a notable pregnancy-related disorder, leads to 40,000+ maternal deaths yearly. Recent research shows PE divides into early-onset (EOPE) and late-onset (LOPE) subtypes, each with distinct clinical features and outcomes. However, the molecular characteristics of various subtypes are currently subject to debate and are not consistent. Methods: We integrated transcriptomic expression data from a total of 372 placental samples across 8 publicly available databases via combat algorithm. Then, a variety of strategies including Random Forest Recursive Feature Elimination (RF-RFE), differential analysis, oposSOM, and Weighted Correlation Network Analysis were employed to identify the characteristic genes of the EOPE and LOPE subtypes. Finally, we conducted in vitro experiments on the key gene HK2 in HTR8/SVneo cells to explore its function. Results: Our results revealed a complex classification of PE placental samples, wherein EOPE manifests as a highly homogeneous sample group characterized by hypoxia and HIF1A activation. Among the core features is the upregulation of glycolysis-related genes, particularly HK2, in the placenta-an observation corroborated by independent validation data and single-cell data. Building on the pronounced correlation between HK2 and EOPE, we conducted in vitro experiments to assess the potential functional impact of HK2 on trophoblast cells. Additionally, the LOPE samples exhibit strong heterogeneity and lack distinct features, suggesting a complex molecular makeup for this subtype. Unsupervised clustering analysis indicates that LOPE likely comprises at least two distinct subtypes, linked to cell-environment interaction and cytokine and protein modification functionalities. Discussion: In summary, these findings elucidate potential mechanistic differences between the two PE subtypes, lend support to the hypothesis of classifying PE based on gestational weeks, and emphasize the potential significant role of glycolysis-related genes, especially HK2 in EOPE.
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Affiliation(s)
- Jie He
- Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, Chongqing, China
| | - Huan Yang
- Department of Obstetrics, Chongqing University Three Gorges Hospital, Chongqing, China
| | - Zheng Liu
- Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, Chongqing, China
| | - Miaomiao Chen
- Maternal and Child Health Hospital of Hubei Province, Wuhan, China
| | - Ying Ye
- Department of Cardiothoracic Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yuelan Tao
- Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, Chongqing, China
| | - Shuhong Li
- Department of Oncology, Chengdu Second People’s Hospital, Chengdu, China
| | - Jie Fang
- Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, Chongqing, China
| | - Jiacheng Xu
- Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, Chongqing, China
| | - Xiafei Wu
- Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, Chongqing, China
| | - Hongbo Qi
- Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of Chinese Ministry of Education, Chongqing Medical University, Chongqing, China
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
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Kharb S, Joshi A. Multi-omics and machine learning for the prevention and management of female reproductive health. Front Endocrinol (Lausanne) 2023; 14:1081667. [PMID: 36909346 PMCID: PMC9996332 DOI: 10.3389/fendo.2023.1081667] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 02/06/2023] [Indexed: 02/25/2023] Open
Abstract
Females typically carry most of the burden of reproduction in mammals. In humans, this burden is exacerbated further, as the evolutionary advantage of a large and complex human brain came at a great cost of women's reproductive health. Pregnancy thus became a highly demanding phase in a woman's life cycle both physically and emotionally and therefore needs monitoring to assure an optimal outcome. Moreover, an increasing societal trend towards reproductive complications partly due to the increasing maternal age and global obesity pandemic demands closer monitoring of female reproductive health. This review first provides an overview of female reproductive biology and further explores utilization of large-scale data analysis and -omics techniques (genomics, transcriptomics, proteomics, and metabolomics) towards diagnosis, prognosis, and management of female reproductive disorders. In addition, we explore machine learning approaches for predictive models towards prevention and management. Furthermore, mobile apps and wearable devices provide a promise of continuous monitoring of health. These complementary technologies can be combined towards monitoring female (fertility-related) health and detection of any early complications to provide intervention solutions. In summary, technological advances (e.g., omics and wearables) have shown a promise towards diagnosis, prognosis, and management of female reproductive disorders. Systematic integration of these technologies is needed urgently in female reproductive healthcare to be further implemented in the national healthcare systems for societal benefit.
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Affiliation(s)
- Simmi Kharb
- Department of Biochemistry, Postgraduate Institute of Medical Sciences, Rohtak, Haryana, India
- *Correspondence: Simmi Kharb, ; Anagha Joshi,
| | - Anagha Joshi
- Computational Biology Unit (CBU), Department of Clinical Science, University of Bergen, Bergen, Norway
- *Correspondence: Simmi Kharb, ; Anagha Joshi,
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Sufriyana H, Salim HM, Muhammad AR, Wu YW, Su ECY. Blood biomarkers representing maternal-fetal interface tissues used to predict early-and late-onset preeclampsia but not COVID-19 infection. Comput Struct Biotechnol J 2022; 20:4206-4224. [PMID: 35966044 PMCID: PMC9359600 DOI: 10.1016/j.csbj.2022.08.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 08/04/2022] [Accepted: 08/04/2022] [Indexed: 11/06/2022] Open
Abstract
Endothelial dysfunction misleads blood marker discovery by differential expression. Blood-derived surrogate transcriptome of target-tissue avoids the false discovery. ITGA5 implies polymicrobial infection of maternal-fetal interface in preeclampsia. ITGA5 and IRF6 implies viral co-infection in early-onset preeclampsia. ITGA5, IRF6, and P2RX7 differ imminent preeclampsia from COVID-19 infection.
Background A well-known blood biomarker (soluble fms-like tyrosinase-1 [sFLT-1]) for preeclampsia, i.e., a pregnancy disorder, was found to predict severe COVID-19, including in males. True biomarker may be masked by more-abrupt changes related to endothelial instead of placental dysfunction. This study aimed to identify blood biomarkers that represent maternal-fetal interface tissues for predicting preeclampsia but not COVID-19 infection. Methods The surrogate transcriptome of tissues was determined by that in maternal blood, utilizing four datasets (n = 1354) which were collected before the COVID-19 pandemic. Applying machine learning, a preeclampsia prediction model was chosen between those using blood transcriptome (differentially expressed genes [DEGs]) and the blood-derived surrogate for tissues. We selected the best predictive model by the area under the receiver operating characteristic (AUROC) using a dataset for developing the model, and well-replicated in datasets both with and without an intervention. To identify eligible blood biomarkers that predicted any-onset preeclampsia from the datasets but that were not positive in the COVID-19 dataset (n = 47), we compared several methods of predictor discovery: (1) the best prediction model; (2) gene sets of standard pipelines; and (3) a validated gene set for predicting any-onset preeclampsia during the pandemic (n = 404). We chose the most predictive biomarkers from the best method with the significantly largest number of discoveries by a permutation test. The biological relevance was justified by exploring and reanalyzing low- and high-level, multiomics information. Results A prediction model using the surrogates developed for predicting any-onset preeclampsia (AUROC of 0.85, 95 % confidence interval [CI] 0.77 to 0.93) was the only that was well-replicated in an independent dataset with no intervention. No model was well-replicated in datasets with a vitamin D intervention. None of the blood biomarkers with high weights in the best model overlapped with blood DEGs. Blood biomarkers were transcripts of integrin-α5 (ITGA5), interferon regulatory factor-6 (IRF6), and P2X purinoreceptor-7 (P2RX7) from the prediction model, which was the only method that significantly discovered eligible blood biomarkers (n = 3/100 combinations, 3.0 %; P =.036). Most of the predicted events (73.70 %) among any-onset preeclampsia were cluster A as defined by ITGA5 (Z-score ≥ 1.1), but were only a minority (6.34 %) among positives in the COVID-19 dataset. The remaining were predicted events (26.30 %) among any-onset preeclampsia or those among COVID-19 infection (93.66 %) if IRF6 Z-score was ≥-0.73 (clusters B and C), in which none was the predicted events among either late-onset preeclampsia (LOPE) or COVID-19 infection if P2RX7 Z-score was <0.13 (cluster C). Greater proportions of predicted events among LOPE were cluster A (82.85 % vs 70.53 %) compared to early-onset preeclampsia (EOPE). The biological relevance by multiomics information explained the biomarker mechanism, polymicrobial infection in any-onset preeclampsia by ITGA5, viral co-infection in EOPE by ITGA5-IRF6, a shared prediction with COVID-19 infection by ITGA5-IRF6-P2RX7, and non-replicability in datasets with a vitamin D intervention by ITGA5. Conclusions In a model that predicts preeclampsia but not COVID-19 infection, the important predictors were genes in maternal blood that were not extremely expressed, including the proposed blood biomarkers. The predictive performance and biological relevance should be validated in future experiments.
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Affiliation(s)
- Herdiantri Sufriyana
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, 250 Wu-Xing Street, Taipei 11031, Taiwan.,Department of Medical Physiology, Faculty of Medicine, Universitas Nahdlatul Ulama Surabaya, 57 Raya Jemursari Road, Surabaya 60237, Indonesia
| | - Hotimah Masdan Salim
- Department of Molecular Biology, Faculty of Medicine, Universitas Nahdlatul Ulama Surabaya, 57 Raya Jemursari Road, Surabaya 60237, Indonesia
| | - Akbar Reza Muhammad
- Faculty of Medicine, Universitas Nahdlatul Ulama Surabaya, 57 Raya Jemursari Road, Surabaya 60237, Indonesia
| | - Yu-Wei Wu
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, 250 Wu-Xing Street, Taipei 11031, Taiwan.,Clinical Big Data Research Center, Taipei Medical University Hospital, 250 Wu-Xing Street, Taipei 11031, Taiwan
| | - Emily Chia-Yu Su
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, 250 Wu-Xing Street, Taipei 11031, Taiwan.,Clinical Big Data Research Center, Taipei Medical University Hospital, 250 Wu-Xing Street, Taipei 11031, Taiwan.,Research Center for Artificial Intelligence in Medicine, Taipei Medical University, 250 Wu-Xing Street, Taipei 11031, Taiwan
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5
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Yao T, Liu Q, Tian W. Deconvolution of a Large Cohort of Placental Microarray Data Reveals Clinically Distinct Subtypes of Preeclampsia. Front Bioeng Biotechnol 2022; 10:917086. [PMID: 35910034 PMCID: PMC9326345 DOI: 10.3389/fbioe.2022.917086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 06/13/2022] [Indexed: 11/28/2022] Open
Abstract
It has been well established that the dysfunctional placenta plays an important role in the pathogenesis of preeclampsia (PE), a hypertensive disorder in pregnancy. However, it is not well understood how individual cell types in the placenta are involved in placenta dysfunction because of limited single-cell studies of placenta with PE. Given that a high-resolution single-cell atlas in the placenta is now available, deconvolution of publicly available bulk PE transcriptome data may provide us with the opportunity to investigate the contribution of individual placental cell types to PE. Recent benchmark studies on deconvolution have provided suggestions on the strategy of marker gene selection and the choice of methodologies. In this study, we experimented with these suggestions by using real bulk data with known cell-type proportions and established a deconvolution pipeline using CIBERSORT. Applying the deconvolution pipeline to a large cohort of PE placental microarray data, we found that the proportions of trophoblast cells in the placenta were significantly different between PE and normal controls. We then predicted cell-type-level expression profiles for each sample using CIBERSORTx and found that the activities of several canonical PE-related pathways were significantly altered in specific subtypes of trophoblasts in PE. Finally, we constructed an integrated expression profile for each PE sample by combining the predicted cell-type-level expression profiles of several clinically relevant placental cell types and identified four clusters likely representing four PE subtypes with clinically distinct features. As such, our study showed that deconvolution of a large cohort of placental microarray provided new insights about the molecular mechanism of PE that would not be obtained by analyzing bulk expression profiles.
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Affiliation(s)
- Tian Yao
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, Department of Computational Biology, School of Life Sciences, Fudan University, Shanghai, China
- Human Phenome Institute, Fudan University, Shanghai, China
| | - Qiming Liu
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, Department of Computational Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Weidong Tian
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, Department of Computational Biology, School of Life Sciences, Fudan University, Shanghai, China
- Children’s Hospital of Fudan University, Shanghai, China
- Qilu Children’s Hospital of Shandong University, Jinan, China
- *Correspondence: Weidong Tian,
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Zhao D, Liu Y, Jia S, He Y, Wei X, Liu D, Ma W, Luo W, Gu H, Yuan Z. Influence of maternal obesity on the multi-omics profiles of the maternal body, gestational tissue, and offspring. Biomed Pharmacother 2022; 151:113103. [PMID: 35605294 DOI: 10.1016/j.biopha.2022.113103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/25/2022] [Accepted: 05/10/2022] [Indexed: 11/28/2022] Open
Abstract
Epidemiological studies show that obesity during pregnancy affects more than half of the pregnancies in the developed countries and is associated with obstetric problems and poor outcomes. Obesity tends to increase the incidence of complications. Furthermore, the resulting offspring are also adversely affected. However, the molecular mechanisms of obesity leading to poor pregnancy outcomes remain unclear. Omics methods are used for genetic diagnosis and marker discovery. The aim of this review was to summarize the maternal and fetal pathophysiological alterations induced by gestational obesity,identified using multi-omics detection techniques, and to generalize the biological functions and potential mechanisms of the differentially expressed molecules.
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Affiliation(s)
- Duan Zhao
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang 110004, China.
| | - Yusi Liu
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang 110004, China.
| | - Shanshan Jia
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang 110004, China.
| | - Yiwen He
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang 110004, China.
| | - Xiaowei Wei
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang 110004, China.
| | - Dan Liu
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang 110004, China.
| | - Wei Ma
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang 110004, China.
| | - Wenting Luo
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang 110004, China.
| | - Hui Gu
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang 110004, China.
| | - Zhengwei Yuan
- Key Laboratory of Health Ministry for Congenital Malformation, Shengjing Hospital, China Medical University, Shenyang 110004, China.
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Deng Y, Zhou Y, Shi J, Yang J, Huang H, Zhang M, Wang S, Ma Q, Liu Y, Li B, Yan J, Yang H. Potential genetic biomarkers predict adverse pregnancy outcome during early and mid-pregnancy in women with systemic lupus erythematosus. Front Endocrinol (Lausanne) 2022; 13:957010. [PMID: 36465614 PMCID: PMC9708709 DOI: 10.3389/fendo.2022.957010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 11/01/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Effectively predicting the risk of adverse pregnancy outcome (APO) in women with systemic lupus erythematosus (SLE) during early and mid-pregnancy is a challenge. This study was aimed to identify potential markers for early prediction of APO risk in women with SLE. METHODS The GSE108497 gene expression dataset containing 120 samples (36 patients, 84 controls) was downloaded from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was performed, and differentially expressed genes (DEGs) were screened to define candidate APO marker genes. Next, three individual machine learning methods, random forest, support vector machine-recursive feature elimination, and least absolute shrinkage and selection operator, were combined to identify feature genes from the APO candidate set. The predictive performance of feature genes for APO risk was assessed using area under the receiver operating characteristic curve (AUC) and calibration curves. The potential functions of these feature genes were finally analyzed by conventional gene set enrichment analysis and CIBERSORT algorithm analysis. RESULTS We identified 321 significantly up-regulated genes and 307 down-regulated genes between patients and controls, along with 181 potential functionally associated genes in the WGCNA analysis. By integrating these results, we revealed 70 APO candidate genes. Three feature genes, SEZ6, NRAD1, and LPAR4, were identified by machine learning methods. Of these, SEZ6 (AUC = 0.753) showed the highest in-sample predictive performance for APO risk in pregnant women with SLE, followed by NRAD1 (AUC = 0.694) and LPAR4 (AUC = 0.654). After performing leave-one-out cross validation, corresponding AUCs for SEZ6, NRAD1, and LPAR4 were 0.731, 0.668, and 0.626, respectively. Moreover, CIBERSORT analysis showed a positive correlation between regulatory T cell levels and SEZ6 expression (P < 0.01), along with a negative correlation between M2 macrophages levels and LPAR4 expression (P < 0.01). CONCLUSIONS Our preliminary findings suggested that SEZ6, NRAD1, and LPAR4 might represent the useful genetic biomarkers for predicting APO risk during early and mid-pregnancy in women with SLE, and enhanced our understanding of the origins of pregnancy complications in pregnant women with SLE. However, further validation was required.
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Affiliation(s)
- Yu Deng
- Department of Obstetrics and Gynecology, Peking University First Hospital, Beijing, China
- Beijing Key Laboratory of Maternal Fetal Medicine of Gestational Diabetes Mellitus, Beijing, China
| | - Yiran Zhou
- Department of Medicinal Chemistry, School of Pharmaceutical Sciences, Peking University, Beijing, China
| | - Jiangcheng Shi
- School of Life Sciences, Tiangong University, Tianjin, China
| | - Junting Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Hong Huang
- Department of Rheumatology and Clinical Immunology, Peking University First Hospital, Beijing, China
| | - Muqiu Zhang
- Department of Obstetrics and Gynecology, Peking University First Hospital, Beijing, China
- Beijing Key Laboratory of Maternal Fetal Medicine of Gestational Diabetes Mellitus, Beijing, China
| | - Shuxian Wang
- Department of Obstetrics and Gynecology, Peking University First Hospital, Beijing, China
- Beijing Key Laboratory of Maternal Fetal Medicine of Gestational Diabetes Mellitus, Beijing, China
| | - Qian Ma
- Department of Clinical Laboratory, Peking University First Hospital, Beijing, China
| | - Yingnan Liu
- Department of Obstetrics and Gynecology, Peking University First Hospital, Beijing, China
- Beijing Key Laboratory of Maternal Fetal Medicine of Gestational Diabetes Mellitus, Beijing, China
| | - Boya Li
- Department of Obstetrics and Gynecology, Peking University First Hospital, Beijing, China
- Beijing Key Laboratory of Maternal Fetal Medicine of Gestational Diabetes Mellitus, Beijing, China
| | - Jie Yan
- Department of Obstetrics and Gynecology, Peking University First Hospital, Beijing, China
- Beijing Key Laboratory of Maternal Fetal Medicine of Gestational Diabetes Mellitus, Beijing, China
| | - Huixia Yang
- Department of Obstetrics and Gynecology, Peking University First Hospital, Beijing, China
- Beijing Key Laboratory of Maternal Fetal Medicine of Gestational Diabetes Mellitus, Beijing, China
- *Correspondence: Huixia Yang,
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Ge C, Xu D, Yu P, Fang M, Guo J, Xu D, Qiao Y, Chen S, Zhang Y, Wang H. P-gp expression inhibition mediates placental glucocorticoid barrier opening and fetal weight loss. BMC Med 2021; 19:311. [PMID: 34876109 PMCID: PMC8653610 DOI: 10.1186/s12916-021-02173-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Accepted: 10/26/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Prenatal adverse environments can cause fetal intrauterine growth retardation (IUGR) and higher susceptibility to multiple diseases after birth, related to multi-organ development programming changes mediated by intrauterine overexposure to maternal glucocorticoids. As a glucocorticoid barrier, P-glycoprotein (P-gp) is highly expressed in placental syncytiotrophoblasts; however, the effect of P-gp on the occurrence of IUGR remains unclear. METHODS Human placenta and fetal cord blood samples of IUGR fetuses were collected, and the related indexes were detected. Pregnant Wistar rats were administered with 30 mg/kg·d (low dose) and 120 mg/kg·d (high dose) caffeine from gestational day (GD) 9 to 20 to construct the rat IUGR model. Pregnant mice were administered with caffeine (120 mg/kg·d) separately or combined with sodium ferulate (50 mg/kg·d) from gestational day GD 9 to 18 to confirm the intervention target on fetal weight loss caused by prenatal caffeine exposure (PCE). The fetal serum/placental corticosterone level, placental P-gp expression, and related indicator changes were analyzed. In vitro, primary human trophoblasts and BeWo cells were used to confirm the effect of caffeine on P-gp and its mechanism. RESULTS The placental P-gp expression was significantly reduced, but the umbilical cord blood cortisol level was increased in clinical samples of the IUGR neonates, which were positively and negatively correlated with the neonatal birth weight, respectively. Meanwhile, in the PCE-induced IUGR rat model, the placental P-gp expression of IUGR rats was decreased while the corticosterone levels of the placentas/fetal blood were increased, which were positively and negatively correlated with the decreased placental/fetal weights, respectively. Combined with the PCE-induced IUGR rat model, in vitro caffeine-treated placental trophoblasts, we confirmed that caffeine decreased the histone acetylation and expression of P-gp via RYR/JNK/YB-1/P300 pathway, which inhibited placental and fetal development. We further demonstrated that P-gp inducer sodium ferulate could reverse the inhibitory effect of caffeine on the fetal body/placental weight. Finally, clinical specimens and other animal models of IUGR also confirmed that the JNK/YB-1 pathway is a co-regulatory mechanism of P-gp expression inhibition, among which the expression of YB-1 is the most stable. Therefore, we proposed that YB-1 could be used as the potential early warning target for the opening of the placental glucocorticoid barrier, the occurrence of IUGR, and the susceptibility of a variety of diseases. CONCLUSIONS This study, for the first time, clarified the critical role and epigenetic regulation mechanism of P-gp in mediating the opening mechanism of the placental glucocorticoid barrier, providing a novel idea for exploring the early warning, prevention, and treatment strategies of IUGR.
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Affiliation(s)
- Caiyun Ge
- Department of Obstetrics and Gynaecology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Dan Xu
- Department of Pharmacology, Basic Medical School of Wuhan University, 185 Donghu Road, Wuchang District, Wuhan, 430071, China.,Hubei Provincial Key Laboratory of Developmentally Originated Diseases, 185 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Pengxia Yu
- Department of Pharmacology, Basic Medical School of Wuhan University, 185 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Man Fang
- Department of Obstetrics and Gynaecology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Juanjuan Guo
- Department of Obstetrics and Gynaecology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuchang District, Wuhan, 430071, China.,Hubei Provincial Key Laboratory of Developmentally Originated Diseases, 185 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Dan Xu
- Department of Obstetrics and Gynaecology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuchang District, Wuhan, 430071, China.,Hubei Provincial Key Laboratory of Developmentally Originated Diseases, 185 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Yuan Qiao
- Department of Obstetrics and Gynaecology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuchang District, Wuhan, 430071, China.,Hubei Provincial Key Laboratory of Developmentally Originated Diseases, 185 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Sijia Chen
- Department of Pharmacology, Basic Medical School of Wuhan University, 185 Donghu Road, Wuchang District, Wuhan, 430071, China
| | - Yuanzhen Zhang
- Department of Obstetrics and Gynaecology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuchang District, Wuhan, 430071, China. .,Hubei Provincial Key Laboratory of Developmentally Originated Diseases, 185 Donghu Road, Wuchang District, Wuhan, 430071, China.
| | - Hui Wang
- Department of Obstetrics and Gynaecology, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuchang District, Wuhan, 430071, China. .,Department of Pharmacology, Basic Medical School of Wuhan University, 185 Donghu Road, Wuchang District, Wuhan, 430071, China. .,Hubei Provincial Key Laboratory of Developmentally Originated Diseases, 185 Donghu Road, Wuchang District, Wuhan, 430071, China.
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Kumar M, Saadaoui M, Elhag DA, Murugesan S, Al Abduljabbar S, Fagier Y, Ortashi O, Abdullahi H, Ibrahim I, Alberry M, Abbas A, Ahmed SR, Hendaus MA, Kalache K, Terranegra A, Al Khodor S. Omouma: a prospective mother and child cohort aiming to identify early biomarkers of pregnancy complications in women living in Qatar. BMC Pregnancy Childbirth 2021; 21:570. [PMID: 34412611 PMCID: PMC8377974 DOI: 10.1186/s12884-021-04029-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 07/29/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Pregnancy is governed by multiple molecular and cellular processes, which might influence pregnancy health and outcomes. Failure to predict and understand the cause of pregnancy complications, adverse pregnancy outcomes, infant's morbidity and mortality, have limited effective interventions. Integrative multi-omics technologies provide an unbiased platform to explore the complex molecular interactions with an unprecedented depth. The objective of the present protocol is to build a longitudinal mother-baby cohort and use multi-omics technologies to help identify predictive biomarkers of adverse pregnancy outcomes, early life determinants and their effect on child health. METHODS/DESIGN One thousand pregnant women with a viable pregnancy in the first trimester (6-14 weeks of gestation) will be recruited from Sidra Medicine hospital. All the study participants will be monitored every trimester, at delivery, and one-year post-partum. Serial high-frequency sampling, including blood, stool, urine, saliva, skin, and vaginal swabs (mother only) from the pregnant women and their babies, will be collected. Maternal and neonatal health, including mental health and perinatal growth, will be recorded using a combination of questionnaires, interviews, and medical records. Downstream sample processing including microbial profiling, vaginal immune response, blood transcriptomics, epigenomics, and metabolomics will be performed. DISCUSSION It is expected that the present study will provide valuable insights into predicting pregnancy complications and neonatal health outcomes. Those include whether specific microbial and/or epigenomics signatures, immune profiles are associated with a healthy pregnancy and/or complicated pregnancy and poor neonatal health outcome. Moreover, this non-interventional cohort will also serve as a baseline dataset to understand how familial, socioeconomic, environmental and lifestyle factors interact with genetic determinants to influence health outcomes later in life. These findings will hold promise for the diagnosis and precision-medicine interventions.
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Affiliation(s)
- Manoj Kumar
- Research Department, Sidra Medicine, Doha, Qatar
| | | | | | | | | | - Yassin Fagier
- Obstetrics and Gynecology, Sidra Medicine, Doha, Qatar
| | - Osman Ortashi
- Obstetrics and Gynecology, Sidra Medicine, Doha, Qatar
| | | | | | | | - Anthony Abbas
- Maternal Fetal Medicine, Sidra Medicine, Doha, Qatar
| | | | | | - Karim Kalache
- Maternal Fetal Medicine, Sidra Medicine, Doha, Qatar
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