Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review

Hierarchical lncRNA regulatory network in early-onset severe preeclampsia

BACKGROUND

Recent studies have shown that several long non-coding RNAs (lncRNAs) in the placenta are associated with preeclampsia (PE). However, the extent to which lncRNAs may contribute to the pathological progression of PE is unclear.

RESULTS

Here, we report a hierarchical regulatory network involved in early-onset severe PE (EOSPE). We have carried out transcriptome sequencing on the placentae from patients and normal subjects to identify the differentially expressed genes (DEGs), including some lncRNAs (DElncRNAs). We then constructed a high-quality hierarchical regulatory network of lncRNAs, transcription factors (TFs), and target DEGs, containing 1851 lncRNA-TF interactions and 6901 TF-promoter interactions. The lncRNA-to-target regulatory interactions were further validated by the triplex structures between the DElncRNAs and the promoters of the target DEGs. The DElncRNAs in the regulatory network were clustered into 3 clusters, one containing DElncRNAs correlated with the blood pressure, including FLNB-AS1 with targeting 27.89% (869/3116) DEGs in EOSPE. We further demonstrated that FLNB-AS1 could bind the transcription factor JUNB to regulate a series members of the HIF-1 signaling pathway in trophoblast cells.

CONCLUSIONS

Our results suggest that the differential expression of lncRNAs may perturb the lncRNA-TF-DEG hierarchical regulatory network, leading to the dysregulation of many genes involved in EOSPE. Our study provides a new strategy and a valuable resource for studying the mechanism underlying gene dysregulation in EOSPE patients.

Identification of hub glutamine metabolism-associated genes and immune characteristics in pre-eclampsia

OBJECTIVE

Preeclampsia (PE) is a severe complication of unclear pathogenesis associated with pregnancy. This research aimed to elucidate the properties of immune cell infiltration and potential biomarkers of PE based on bioinformatics analysis.

MATERIALS AND METHODS

Two PE datasets were imported from the Gene ExpressioOmnibus (GEO) and screened to identify differentially expressed genes (DEGs). Significant module genes were identified by weighted gene co-expression network analysis (WGCNA). DEGs that interacted with key module genes (GLu-DEGs) were analyzed further by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. The diagnostic value of the genes was assessed using receiver operating characteristic (ROC) curves and protein-protein interaction (PPI) networks were constructed using GeneMANIA, and GSVA analysis was performed using the MSigDB database. Immune cell infiltration was analyzed using the TISIDB database, and StarBase and Cytoscape were used to construct an RBP-mRNA network. The identified hub genes were validated in two independent datasets. For further confirmation, placental tissue from healthy pregnant women and women with PE were collected and analyzed using both RT-qPCR and immunohistochemistry.

RESULTS

A total of seven GLu-DEGs were obtained and were found to be involved in pathways associated with the transport of sulfur compounds, PPAR signaling, and energy metabolism, shown by GO and KEGG analyses. GSVA indicated significant increases in adipocytokine signaling. Furthermore, single-sample Gene Set Enrichment Analysis (ssGSEA) indicated that the levels of activated B cells and T follicular helper cells were significantly increased in the PE group and were negatively correlated with GLu-DEGs, suggesting their potential importance.

CONCLUSION

In summary, the results showed a correlation between glutamine metabolism and immune cells, providing new insights into the understandingPE pathogenesis and furnishing evidence for future advances in the treatment of this disease.

Characteristics of Serum Lipid Metabolism among Women Complicated with Hypertensive Disorders in Pregnancy: A Retrospective Cohort Study in Mainland China

Background

Altered maternal serum lipid metabolism is associated with hypertensive disorders in pregnancy (HDP). However, its range in pregnancy and characteristic among different subgroups of HDPs are unclear.

Methods

Pregnant women with HDP who underwent antenatal care and delivered in Obstetrics and Gynecology Hospital of Fudan University during January 2018 to August 2022 were enrolled. The levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), apolipoprotein (Apo)-A, B, and E, free fatty acids (FFA), and small and dense low-density lipoprotein cholesterol (sdLDL) were measured during 4-16 weeks and 28-42 weeks of pregnancy.

Results

A total of 2648 pregnant women were diagnosed with HDP, 1,880 of whom were enrolled for final analysis, including 983 (52.3%) preeclampsia (PE), 676 (36.0%) gestational hypertension (GH), and 221 (11.7%) chronic hypertension (CH). For all HDPs, serum TC, TG, LDLC, HDLC, Apo-A, Apo-B, Apo-E, and sdLDL increased significantly during pregnancy, while FFA decreased significantly. Notably, the levels of TC, LDLC, Apo-B, and sdLDL in PE group were equal to or lower than those in CH group at 4-16 weeks of pregnancy, but increased greatly during pregnancy (P < 0.05).

Conclusions

Maternal serum lipid levels changed through pregnancy among women with HDPs. Women complicated with PE seem to have undergone a more significant serum lipid change compared to those with GH or CH.

First-trimester preterm preeclampsia prediction with metabolite biomarkers: differential prediction according to maternal body mass index

BACKGROUND

Prediction of preeclampsia risk is key to informing effective maternal care. Current screening for preeclampsia at 11 to 13 weeks of gestation using maternal demographic characteristics and medical history with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor can identify approximately 75% of women who develop preterm preeclampsia with delivery at <37 weeks of gestation. Further improvements to preeclampsia screening tests will likely require integrating additional biomarkers. Recent research suggests the existence of distinct maternal risk profiles. Therefore, biomarker evaluation should account for the possibility that a biomarker only predicts preeclampsia in a specific maternal phenotype.

OBJECTIVE

This study aimed to verify metabolite biomarkers as preterm preeclampsia predictors early in pregnancy in all women and across body mass index groups.

STUDY DESIGN

Observational case-control study drawn from a large prospective study on the early prediction of pregnancy complications in women attending their routine first hospital visit at King's College Hospital, London, United Kingdom, in 2010 to 2015. Pregnant women underwent a complete first-trimester assessment, including the collection of blood samples for biobanking. In 11- to 13-week plasma samples of 2501 singleton pregnancies, the levels of preselected metabolites implicated in the prediction of pregnancy complications were analyzed using a targeted liquid chromatography-mass spectrometry method, yielding high-quality quantification data on 50 metabolites. The ratios of amino acid levels involved in arginine biosynthesis and nitric oxide synthase pathways were added to the list of biomarkers. Placental growth factor and pregnancy-associated plasma protein A were also available for all study subjects, serving as comparator risk predictors. Data on 1635 control and 106 pregnancies complicated by preterm preeclampsia were considered for this analysis, normalized using multiples of medians. Prediction analyses were performed across the following patient strata: all subjects and the body mass index classes of <25, 25 to <30, and ≥30 kg/m². Adjusted median levels were compared between cases and controls and between each body mass index class group. Odds ratios and 95% confidence intervals were calculated at the mean ±1 standard deviation to gauge clinical prediction merits.

RESULTS

The levels of 13 metabolites were associated with preterm preeclampsia in the entire study population (P<.05) with particularly significant (P<.01) associations found for 6 of them, namely, 2-hydroxy-(2/3)-methylbutyric acid, 25-hydroxyvitamin D3, 2-hydroxybutyric acid, alanine, dodecanoylcarnitine, and 1-(1Z-octadecenyl)-2-oleoyl-sn-glycero-3-phosphocholine. Fold changes in 7 amino acid ratios, all involving glutamine or ornithine, were also significantly different between cases and controls (P<.01). The predictive performance of some metabolites and ratios differed according to body mass index classification; for example, ornithine (P<.001) and several ornithine-related ratios (P<.0001 to P<.01) were only strongly associated with preterm preeclampsia in the body mass index of <25 kg/m² group, whereas dodecanoylcarnitine and 3 glutamine ratios were particularly predictive in the body mass index of ≥30 kg/m² group (P<.01).

CONCLUSION

Single metabolites and ratios of amino acids related to arginine bioavailability and nitric oxide synthase pathways were associated with preterm preeclampsia risk at 11 to 13 weeks of gestation. Differential prediction was observed according to body mass index classes, supporting the existence of distinct maternal risk profiles. Future studies in preeclampsia prediction should account for the possibility of different maternal risk profiles to improve etiologic and prognostic understanding and, ultimately, clinical utility of screening tests.

Vitamin D deficiency in British South Asians, a persistent but avoidable problem associated with many health risks (including rickets, T2DM, CVD, COVID-19 and pregnancy complications): the case for correcting this deficiency

High vitamin D deficiency rates, with rickets and osteomalacia, have been common in South Asians (SAs) arriving in Britain since the 1950s with preventable infant deaths from hypocalcaemic status-epilepticus and cardiomyopathy. Vitamin D deficiency increases common SA disorders (type 2 diabetes and cardiovascular disease), recent trials and non-linear Mendelian randomisation studies having shown deficiency to be causal for both disorders. Ethnic minority, obesity, diabetes and social deprivation are recognised COVID-19 risk factors, but vitamin D deficiency is not, despite convincing mechanistic evidence of it. Adjusting analyses for obesity/ethnicity abolishes vitamin D deficiency in COVID-19 risk prediction, but both factors lower serum 25(OH)D specifically. Social deprivation inadequately explains increased ethnic minority COVID-19 risks. SA vitamin D deficiency remains uncorrected after 70 years, official bodies using 'education', 'assimilation' and 'diet' as 'proxies' for ethnic differences and increasing pressures to assimilate. Meanwhile, English rickets was abolished from ~1940 by free 'welfare foods' (meat, milk, eggs, cod liver oil), for all pregnant/nursing mothers and young children (<5 years old). Cod liver oil was withdrawn from antenatal clinics in 1994 (for excessive vitamin A teratogenicity), without alternative provision. The take-up of the 2006 'Healthy-Start' scheme of food-vouchers for low-income families with young children (<3 years old) has been poor, being inaccessible and poorly publicised. COVID-19 pandemic advice for UK adults in 'lockdown' was '400 IU vitamin D/day', inadequate for correcting the deficiency seen winter/summer at 17.5%/5.9% in White, 38.5%/30% in Black and 57.2%/50.8% in SA people in representative UK Biobank subjects when recruited ~14 years ago and remaining similar in 2018. Vitamin D inadequacy worsens many non-skeletal health risks. Not providing vitamin D for preventing SA rickets and osteomalacia continues to be unacceptable, as deficiency-related health risks increase ethnic health disparities, while abolishing vitamin D deficiency would be easier and more cost-effective than correcting any other factor worsening ethnic minority health in Britain.

Relationship between Maternal Vitamin D Levels and Adverse Outcomes

Vitamin D (VD), a fat-soluble vitamin, has a variety of functions that are important for growth and development, including regulation of cell differentiation and apoptosis, immune system development, and brain development. As such, VD status during pregnancy is critical for maternal health, fetal skeletal growth, and optimal pregnancy outcomes. Studies have confirmed that adverse pregnancy outcomes, such as preeclampsia, low birth weight, neonatal hypocalcemia, poor postnatal growth, skeletal fragility, and increased incidence of autoimmune diseases, can be associated with low VD levels during pregnancy and infancy. Thus, there is growing interest in the role of VD during pregnancy. This review summarizes the potential adverse health outcomes of maternal VD status during pregnancy for both mother and offspring (gestational diabetes mellitus, hypertensive gestational hypertension, intrauterine growth restriction, miscarriage, stillbirth, and preterm birth) and discusses the underlying mechanisms (regulation of cytokine pathways, immune system processing, internal secretion, placental function, etc.) of VD in regulating each of the outcomes. This review aims to provide a basis for public health intervention strategies to reduce the incidence of adverse pregnancies.

Perspectives from metabolomics in the early diagnosis and prognosis of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnant women. The early detection of GDM provides an opportunity for the effective treatment of hyperglycemia in pregnancy, thus decreasing the risk of adverse perinatal outcomes for mothers and newborns. Metabolomics, an emerging technique, offers a novel point of view in understanding the onset and development of diseases and has been repeatedly used in various gestational periods in recent studies of GDM. Moreover, metabolomics provides varied opportunities in the different diagnoses of GDM from prediabetes or predisposition to diabetes, the diagnosis of GDM at a gestational age several weeks earlier than that used in the traditional method, and the assessment of prognosis considering the physiologic subtypes of GDM and clinical indexes. Longitudinal metabolomics truly facilitates the dynamic monitoring of metabolic alterations over the course of pregnancy. Herein, we review recent advancements in metabolomics and summarize evidence from studies on the application of metabolomics in GDM, highlighting the aspects of the diagnosis and differential diagnoses of GDM in an early stage. We also discuss future study directions concerning the physiologic subtypes, prognosis, and limitations of metabolomics.