Cell-free DNA Methylation and Transcriptomic Signature Prediction of Pregnancies with Adverse Outcomes

Genome-wide methylation profiling of maternal cell-free DNA using methylated DNA sequencing (MeD-seq) indicates a placental and immune-cell signature

BACKGROUND

Placental-originated cell-free DNA (cfDNA) provides unique opportunities to study (epi)genetic placental programming remotely, but studies investigating the cfDNA methylome are scarce and usually technologically challenging. Methylated DNA sequencing (MeD-seq) is well compatible with low cfDNA concentrations and has a high genome-wide coverage. We therefore aim to investigate the feasibility of genome-wide methylation profiling of first trimester maternal cfDNA using MeD-seq, by identifying placental-specific methylation marks in cfDNA.

METHODS

We collected cfDNA from nonpregnant controls (female n = 6, male n = 12) and pregnant women (n = 10), first trimester placentas (n = 10), and paired preconceptional and first trimester buffy coats (total n = 20). Differentially methylated regions (DMRs) were identified between pregnant and nonpregnant women. We investigated placental-specific markers in maternal cfDNA, including RASSF1 promoter and Y-chromosomal methylation, and studied overlap with placental and buffy coat DNA methylation.

RESULTS

We identified 436 DMRs between cfDNA from pregnant and nonpregnant women, which were validated using male cfDNA. RASSF1 promoter methylation was higher in maternal cfDNA (fold change 2.87, unpaired t-test p < .0001). Differential methylation of Y-chromosomal sequences could determine fetal sex. DMRs in maternal cfDNA showed large overlap with DNA methylation of these regions in placentas and buffy coats. Sixteen DMRs in maternal cfDNA were specifically found only in placentas. These novel potential placental-specific DMRs were more prominent than RASSF1.

CONCLUSIONS

MeD-seq can detect (novel) genome-wide placental DNA methylation marks and determine fetal sex in maternal cfDNA. Our results indicate a placental and immune-cell contribution to the pregnancy-specific cfDNA methylation signature. This study supports future research into maternal cfDNA methylation.

Discrete placental gene expression signatures accompany diabetic disease classifications during pregnancy

BACKGROUND

Gestational diabetes mellitus affects up to 10% of pregnancies and is classified into subtypes gestational diabetes subtype A1 (GDMA1) (managed by lifestyle modifications) and gestational diabetes subtype A2 (GDMA2) (requiring medication). However, whether these subtypes are distinct clinical entities or more reflective of an extended spectrum of normal pregnancy endocrine physiology remains unclear.

OBJECTIVE

Integrated bulk RNA-sequencing (RNA-seq), single-cell RNA-sequencing (scRNA-seq), and spatial transcriptomics harbors the potential to reveal disease gene signatures in subsets of cells and tissue microenvironments. We aimed to combine these high-resolution technologies with rigorous classification of diabetes subtypes in pregnancy. We hypothesized that differences between preexisting type 2 and gestational diabetes subtypes would be associated with altered gene expression profiles in specific placental cell populations.

STUDY DESIGN

In a large case-cohort design, we compared validated cases of GDMA1, GDMA2, and type 2 diabetes mellitus (T2DM) to healthy controls by bulk RNA-seq (n=54). Quantitative analyses with reverse transcription and quantitative PCR of presumptive genes of significant interest were undertaken in an independent and nonoverlapping validation cohort of similarly well-characterized cases and controls (n=122). Additional integrated analyses of term placental single-cell, single-nuclei, and spatial transcriptomics data enabled us to determine the cellular subpopulations and niches that aligned with the GDMA1, GDMA2, and T2DM gene expression signatures at higher resolution and with greater confidence.

RESULTS

Dimensional reduction of the bulk RNA-seq data revealed that the most common source of placental gene expression variation was the diabetic disease subtype. Relative to controls, we found 2052 unique and significantly differentially expressed genes (-22 thresholds; q<0.05 Wald Test) among GDMA1 placental specimens, 267 among GDMA2, and 1520 among T2DM. Several candidate marker genes (chorionic somatomammotropin hormone 1 [CSH1], period circadian regulator 1 [PER1], phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit beta [PIK3CB], forkhead box O1 [FOXO1], epidermal growth factor receptor [EGFR], interleukin 2 receptor subunit beta [IL2RB], superoxide dismutase 3 [SOD3], dedicator of cytokinesis 5 [DOCK5], suppressor of glucose, and autophagy associated 1 [SOGA1]) were validated in an independent and nonoverlapping validation cohort (q<0.05 Tukey). Functional enrichment revealed the pathways and genes most impacted for each diabetes subtype, and the degree of proximal similarity to other subclassifications. Surprisingly, GDMA1 and T2DM placental signatures were more alike by virtue of increased expression of chromatin remodeling and epigenetic regulation genes, while albumin was the top marker for GDMA2 with increased expression of placental genes in the wound healing pathway. Assessment of these gene signatures in single-cell, single-nuclei, and spatial transcriptomics data revealed high specificity and variability by placental cell and microarchitecture types. For example, at the cellular and spatial (eg, microarchitectural) levels, distinguishing features were observed in extravillous trophoblasts (GDMA1) and macrophages (GDMA2). Lastly, we utilized these data to train and evaluate 4 machine learning models to estimate our confidence in predicting the control or diabetes status of placental transcriptome specimens with no available clinical metadata.

CONCLUSION

Consistent with the distinct association of perinatal outcome risk, placentae from GDMA1, GDMA2, and T2DM-affected pregnancies harbor unique gene signatures that can be further distinguished by altered placental cellular subtypes and microarchitectural niches.

The correlation between sperm DNA methylation and DNA damage: a comparison of comet and TUNEL

Objective

To evaluate the relationship between sperm DNA methylation and DNA damage as determined by the comet or TUNEL assays.

Design

Retrospective research study.

Setting

University-based andrology and in vitro fertilization (IVF) laboratory.

Patients

Data came from 1,470 male partners (ages 18 and older) recruited from heterosexual couples (ages 18-45 years) seeking fertility treatments. These data were analyzed retrospectively from the Folic Acid and Zinc Supplementation Trial (FAZST) study.

Main outcome measures

Comet and TUNEL measures and associations with DNA methylation patterns.

Results

Comet and TUNEL values were correlated with one another across all samples (R 2 = 0.34, P < 0.001); however, when assessing the highest and lowest scores reported from each assay, there was little overlap between patients. This suggests that Comet and TUNEL are identifying key differences that may be meaningful and correlated with other sperm metrics. We compared both comet and TUNEL to methylation array data using a sliding window analysis, which identified far more significantly differentially methylated sites as a function of comet than TUNEL (3,387 vs. 23). Interestingly, sites associated with comet were associated with biological pathways related to DNA methylation involved in germline development, as determined by a GO term analysis. The TUNEL assay, by comparison, produced no relevant biological pathways.

Conclusions

Because the comet and TUNEL assays are both used to indicate levels of DNA damage, and outputs of both are correlated to each other, it would seem to follow that both are equally predictive of deviations in DNA methylation patterns. The findings of this study suggest that this is not the case. The comet assay shows a significantly higher association with DNA methylation disruption, and we therefore believe it to be a better indicator of sperm epigenetic health.

The potential of circulating free DNA of methylated IGFBP as a biomarker for type 2 diabetes Mellitus: A Comprehensive review

T2DM detection methods are commonly used in teens and adults but are generally unsuitable to unborn fetuses in the context of non-invasive prenatal testing (NIPT). Biophysical and biochemical tests for fetuses are often invasive, carry risks, and have low sensitivity and specificity, with no direct method available to diagnose T2DM in utero. In contrast, cell-free DNA (cfDNA) is known have high sensitivity (93-98 %) and specificity (94-100 %) for cancer detection and fetal genetic disorders (trisomy 21, 8, and 13) making it applicable for fetal epigenetic and genetic analysis, including T2DM early detection. However, no study has explored its use for this purpose. Our review focuses on the potential of IGFBP methylation levels in cfDNA as biomarkers for NIPT of T2DM. Placental global hypomethylation in GDM may predict T2DM during the prenatal period, and a similar pattern potentially be detected in cfDNA. Targeted genes reliable for NIPT, such as IGFBPs are needed because their significant role in T2DM and GDM. Among these, IGFBP-1 and IGFBP-2 have shown potential as predictive genes, exhibiting hypermethylation in placental tissue from GDM cases. This hypermethylation reduces their expression and the formation of the IGF-1-IGFBP complex, leading to increased levels of free IGF-1, which is associated with T2DM in the fetus. Hypermethylation regions have longer fragment sizes in cfDNA, thus in T2DM cases, hypermethylation of IGFBP-1 and IGFBP-2 from fetus results in longer cfDNA fragments. Therefore, analyzing the methylation levels and fragment sizes of IGFBP-1 or IGFBP-2 cfDNA could be a promising biomarker for identifying fetal T2DM risk non-invasively.

Advancing diagnosis and early risk assessment of preeclampsia through noninvasive cell-free DNA methylation profiling

BACKGROUND

Aberrant embryo implantation and suboptimal placentation can lead to (severe) complications such as preeclampsia and fetal growth restriction later in pregnancy. Current identification of high-risk pregnancies relies on a combination of risk factors, biomarkers, and ultrasound examinations, a relatively inaccurate approach. Previously, aberrant DNA methylation due to placental hypoxia has been identified as a potential marker of placental insufficiency and, hence, potential (future) pregnancy complications. The goal of the Early Prediction of prEgnancy Complications Testing, or the ExPECT study, is to validate a genome-wide, cell-free DNA (cfDNA) methylation strategy to diagnose preeclampsia accurately. More importantly, the predictive potential of this strategy is also explored to reliably identify high-risk pregnancies early in gestation. Furthermore, a longitudinal study was conducted, including sequential blood samples from pregnant individuals experiencing both uneventful and complicated gestations, to assess the methylation dynamics of cfDNA throughout these pregnancies. A significant strength of this study is its enzymatic digest, which enriches CpG-rich regions across the genome without the need for proprietary reagents or prior selection of regions of interest. This makes it useful for the cost-effective discovery of novel markers.

RESULTS

Investigation of methylation patterns throughout pregnancy showed different methylation trends between unaffected and affected pregnancies. We detected differentially methylated regions (DMRs) in pregnancies complicated with preeclampsia as early as 12 weeks of gestation, with distinct differences in the methylation profile between early and late pregnancy. Two classification models were developed to diagnose and predict preeclampsia, demonstrating promising results on a small set of validation samples.

CONCLUSIONS

This study offers valuable insights into methylation changes at specific genomic regions throughout pregnancy, revealing critical differences between normal and complicated pregnancies. The power of noninvasive cfDNA methylation profiling was successfully proven, suggesting the potential to integrate this noninvasive approach into routine prenatal care.

Cell-free placental DNA: What do we really know?

Cell-free placental DNA (cfpDNA) is present in maternal circulation during gestation. CfpDNA carries great potential as a research and clinical tool as it provides a means to investigate the placental (epi)genome across gestation, which previously required invasive placenta sampling procedures. CfpDNA has been widely implemented in the clinical setting for noninvasive prenatal testing (NIPT). Despite this, the basic biology of cfpDNA remains poorly understood, limiting the research and clinical utility of cfpDNA. This review will examine the current knowledge of cfpDNA, including origins and molecular characteristics, highlight gaps in knowledge, and discuss future research directions.

Identification of key ubiquitination-related genes in gestational diabetes mellitus: A bioinformatics-driven study

Background and Aims

Gestational diabetes mellitus (GDM) is characterized by glucose intolerance that occurs during pregnancy. This study aimed to identify key ubiquitination-related genes associated with GDM pathogenesis.

Methods

Microarray data from GSE154377 was analyzed to identify differentially expressed genes (DEGs) in GDM vs normal pregnancy samples. Weighted gene co-expression network analysis was performed on ubiquitination-related genes. Functional enrichment, protein-protein interaction network, and TF-mRNA-miRNA interaction network analyses were conducted on differentially expressed ubiquitination-related genes (DE-URGs).

Results

We identified 2337 DEGs and 65 DE-URGs in GDM. Functional enrichment analysis of the 65 DE-URGs revealed involvement in protein ubiquitination and ubiquitin-dependent catabolic processes. Protein-protein interaction network analysis identified 8 hub genes, including MAP1LC3C, USP26, USP6, UBE2U, USP2, USP43, UCHL1, and USP44. ROC curve analysis showed these hub genes have high diagnostic accuracy for GDM (AUC > 0.6). The TF-mRNA-miRNA interaction network suggested USP2 and UCHL1 may be key ubiquitination genes in GDM.

Conclusion

In conclusion, this study contributes to our understanding of the molecular landscape of GDM by uncovering key ubiquitination-related genes. These findings may serve as a foundation for further investigations, offering potential biomarkers and therapeutic targets for clinical applications in GDM management.

A review on cell-free RNA profiling: Insights into metabolic diseases and predictive value for bariatric surgery outcomes

BACKGROUND

The advent of liquid biopsies presents a novel, minimally invasive methodology for the detection of disease biomarkers, offering a significant advantage over traditional biopsy techniques. Particularly, the analysis of cell-free RNA (cfRNA) has garnered interest due to its dynamic expression profiles and the capability to study various RNA species, including messenger RNA (mRNA) and long non-coding RNA (lncRNA). These attributes position cfRNA as a versatile biomarker with broad potential applications in clinical research and diagnostics.

SCOPE OF REVIEW

This review delves into the utility of cfRNA biomarkers as prognostic tools for obesity-related comorbidities, such as diabetes, dyslipidemia, and non-alcoholic fatty liver disease.

MAJOR CONCLUSIONS

We evaluate the efficacy of cfRNA in forecasting metabolic outcomes associated with obesity and in identifying patients likely to experience favorable clinical outcomes following bariatric surgery. Additionally, this review synthesizes evidence from studies examining circulating cfRNA across different physiological and pathological states, with a focus on its role in diabetes, including disease progression monitoring and treatment efficacy assessment. Through this exploration, we underscore the emerging relevance of cfRNA signatures in the context of obesity and its comorbidities, setting the stage for future investigative efforts in this rapidly advancing domain.

Deciphering DNA Methylation in Gestational Diabetes Mellitus: Epigenetic Regulation and Potential Clinical Applications

Gestational diabetes mellitus (GDM) represents a prevalent complication during pregnancy, exerting both short-term and long-term impacts on maternal and offspring health. This review offers a comprehensive outline of DNA methylation modifications observed in various maternal and offspring tissues affected by GDM, emphasizing the intricate interplay between DNA methylation dynamics, gene expression, and the pathogenesis of GDM. Furthermore, it explores the influence of environmental pollutants, maternal nutritional supplementation, and prenatal gut microbiota on GDM development through alterations in DNA methylation profiles. Additionally, this review summarizes recent advancements in DNA methylation-based diagnostics and predictive models in early GDM detection and risk assessment for subsequent type 2 diabetes. These insights contribute significantly to our understanding of the epigenetic mechanisms underlying GDM development, thereby enhancing maternal and fetal health outcomes and advocating further efforts in this field.

Longitudinal integrative cell-free DNA analysis in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) presents varied manifestations throughout pregnancy and poses a complex clinical challenge. High-depth cell-free DNA (cfDNA) sequencing analysis holds promise in advancing our understanding of GDM pathogenesis and prediction. In 299 women with GDM and 299 matched healthy pregnant women, distinct cfDNA fragment characteristics associated with GDM are identified throughout pregnancy. Integrating cfDNA profiles with lipidomic and single-cell transcriptomic data elucidates functional changes linked to altered lipid metabolism processes in GDM. Transcription start site (TSS) scores in 50 feature genes are used as the cfDNA signature to distinguish GDM cases from controls effectively. Notably, differential coverage of the islet acinar marker gene PRSS1 emerges as a valuable biomarker for GDM. A specialized neural network model is developed, predicting GDM occurrence and validated across two independent cohorts. This research underscores the high-depth cfDNA early prediction and characterization of GDM, offering insights into its molecular underpinnings and potential clinical applications.

DNA methylation landscape in pregnancy-induced hypertension: progress and challenges

Gestational hypertension (PIH), especially pre-eclampsia (PE), is a common complication of pregnancy. This condition poses significant risks to the health of both the mother and the fetus. Emerging evidence suggests that epigenetic modifications, particularly DNA methylation, may play a role in initiating the earliest pathophysiology of PIH. This article describes the relationship between DNA methylation and placental trophoblast function, genes associated with the placental microenvironment, the placental vascular system, and maternal blood and vascular function, abnormalities of umbilical cord blood and vascular function in the onset and progression of PIH, as well as changes in DNA methylation in the progeny of PIH, in terms of maternal, fetal, and offspring. We also explore the latest research on DNA methylation-based early detection, diagnosis and potential therapeutic strategies for PIH. This will enable the field of DNA methylation research to continue to enhance our understanding of the epigenetic regulation of PIH genes and identify potential therapeutic targets.

Prediction of preeclampsia using maternal circulating mRNAs in early pregnancy

PURPOSE

Preeclampsia (PE) is one of the most common and serious complications of pregnancy, and novel methods for the early prediction of PE are needed for clinical application.

METHODS

In this study, a circulating cell-free RNA (cfRNA) panel of target genes for PE prediction was designed and validated in a case-control cohort and a nested case-control cohort. The QPCR was applied to quantify the copy number of cfRNA, and the data were normalized as multiples of the median. Ratios of serum placental growth factor (PIGF) and soluble fms-like tyrosine kinase 1 (sFLT-1) were also measured, and transabdominal ultrasonography was conducted for subjects in the prospective cohort. Binary logistic regression models for PE prediction were constructed and tested.

RESULTS

Our results revealed that the women with PE showed significant alterations in serum cfRNA profiles from early pregnancy onward and before the onset of PE symptoms. Compared with PIGF/sFLT-1 measurement and ultrasonographic imaging, cfRNA test can detect PE at a very early stage of pregnancy. The predictive model exhibited the best performance at gestation week 32, with a detection rate of 100%. At 12 weeks of gestation, the model still manifested an area under curve (AUC) of 0.9144, and sensitivity of 1.0000. If combined with clinical parameters and ultrasonographic indicators, the model can achieve the highest AUC for PE prediction at early gestation.

CONCLUSION

Measurement of cfRNA can be used to effectively predict PE with high performance, providing an additional method for monitoring PE throughout the course of pregnancy.

A Description of the Imaging Innovations for Placental Assessment in Response to Environmental Pollution Study

OBJECTIVE

The aim of Placental Assessment in Response to Environmental Pollution Study (PARENTs) was to determine whether imaging of the placenta by novel multiparametric magnetic resonance imaging (MRI) techniques in early pregnancy could help predict adverse pregnancy outcomes (APOs) due to ischemic placental disease (IPD). Additionally, we sought to determine maternal characteristics and environmental risk factors that contribute to IPD and secondary APOs.

STUDY DESIGN

Potential patients in their first trimester of pregnancy, who agreed to MRI of the placenta and measures of assessment of environmental pollution, were recruited into PARENTs, a prospective population-based cohort study. Participants were seen at three study visits during pregnancy and again at their delivery from 2015 to 2019. We collected data from interviews, chart abstractions, and imaging. Maternal biospecimens (serum, plasma, and urine) at antepartum study visits and delivery specimens (placenta, cord, and maternal blood) were collected, processed, and stored. The primary outcome was a composite of IPD, which included any of the following: placental abruption, hypertensive disease of pregnancy, fetal growth restriction, or a newborn of small for gestational age.

RESULTS

In this pilot cohort, of the 190 patients who completed pregnancy to viable delivery, 50 (26%) developed IPD. Among demographic characteristics, having a history of prior IPD in multiparous women was associated with the development of IPD. In the multiple novel perfusion measurements taken of the in vivo placenta using MRI, decreased high placental blood flow (mL/100 g/min) in early pregnancy (between 14 and 16 weeks) was found to be significantly associated with the later development of IPD.

CONCLUSION

Successful recruitment of the PARENTs prospective cohort demonstrated the feasibility and acceptability of the use of MRI in human pregnancy to study the placenta in vivo and at the same time collect environmental exposure data. Analysis is ongoing and we hope these methods will assist researchers in the design of prospective imaging studies of pregnancy.

KEY POINTS

· MRI was acceptable and feasible for the study of the human placenta in vivo.. · Functional imaging of the placenta by MRI showed a significant decrease in high placental blood flow.. · Measures of environmental exposures are further being analyzed to predict IPD..

Transcriptomic analysis delineates preterm prelabor rupture of membranes from preterm labor in preterm fetal membranes

BACKGROUND

Globally, preterm birth remains the leading cause of death in children younger than 5 years old. Spontaneous preterm birth is comprised of two events that may or may not occur simultaneously: preterm labor and preterm prelabor rupture of membranes (PPROM). To further explore the concept that spontaneous preterm birth can result from the initializing of two separate but overlapping pathological events, we compared fetal membrane tissue from preterm labor deliveries to fetal tissue from preterm labor with PPROM deliveries. We hypothesized that the fetal membrane tissue from preterm labor with PPROM cases will have an RNA-seq profile divergent from the fetal membrane tissue from preterm labor controls.

METHODS

Chorioamnion, separated into amnion and chorion, was collected from eight gestationally age-matched cases and controls within 15 min of birth, and analyzed using RNA sequencing. Pathway enrichment analyses and functional annotations of differentially expressed genes were performed using KEGG and Gene Ontogeny Pathway enrichment analyses.

RESULTS

A total of 1466 genes were differentially expressed in the amnion, and 484 genes were differentially expressed in the chorion (log2 fold change > 1, FDR < 0.05) in cases (preterm labor with PPROM), versus controls (preterm labor only). In the amnion, the most significantly enriched (FDR < 0.01) KEGG pathway among down-regulated genes was the extracellular matrix receptor interaction pathway. Seven of the most significantly enriched pathways were comprised of multiple genes from the COL family, including COL1A, COL3A1, COL4A4, and COL4A6. In the chorion, the most significantly enriched KEGG pathways in up-regulated genes were chemokine, NOD receptor, Toll-like receptor, and cytokine-cytokine receptor signaling pathways. Similarly, KEGG pathway enrichment analysis for up-regulated genes in the amnion included three inflammatory pathways: cytokine-cytokine interaction, TNF signaling and the CXCL family. Six genes were significantly up regulated in chorionic tissue discriminated between cases (preterm labor with PPROM) and controls (preterm labor only) including GBP5, CXCL9, ALPL, S100A8, CASP5 and MMP25.

CONCLUSIONS

In our study, transcriptome analysis of preterm fetal membranes revealed distinct differentially expressed genes for PPROM, separate from preterm labor. This study is the first to report transcriptome data that reflects the individual pathophysiology of amnion and chorion tissue from PPROM deliveries.

Global DNA methylation and miR-126-3p expression in Mexican women with gestational diabetes mellitus: a pilot study

BACKGROUND

Gestational diabetes mellitus (GDM), a type of diabetes that occurs for the first time during pregnancy, may predispose the development of chronic degenerative diseases and metabolic alterations in mother and offspring. DNA methylation and microRNA (miRNA) expression are regulatory mechanisms of gene expression that may contribute to the pathogenesis of GDM. Therefore, we determined global DNA methylation and miR-126-3p expression levels in 8 and 7 Mexican women with and without GDM, respectively.

METHODS AND RESULTS

Global DNA methylation was assessed by measuring the percentage of 5-methylcytosine (5-mC) in placenta, umbilical cord, and plasma DNA samples, whereas miR-126-3p expression was quantified by real-time PCR using the 2-ΔCt method of the corresponding RNA samples. A significant increase in the percentage of 5-mC was detected in placenta samples from GDM patients compared to healthy women, while plasma samples showed a significant decrease. Conversely, miR-126-3p expression levels were significantly higher in plasma from the GDM group, while placenta and umbilical cord samples showed no significant differences across experimental groups. Furthermore, DNA methylation correlated significantly with glucose levels in placenta and plasma. Likewise, miR-126-3p expression correlated significantly with plasma glucose, in addition to maternal body mass index (BMI at first trimester).

CONCLUSION

The results indicate that GDM is associated with alterations in global DNA methylation levels and miR-126-3p expression in placenta and/or plasma, providing insights into future novel approaches to diagnose and/or prevent this pathology.

Cell-free DNA as a plausible biomarker of chronic kidney disease

Circulating cell-free DNA (cf-DNA) is released from dead and/or apoptotic leukocytes and due to neutrophil extracellular traps contributing to an inflammatory response. Previous clinical studies have reported that the peak concentrations and dynamic changes of cf-DNA may be used as a noninvasive biomarker of worsening kidney function as well as a guide to the management of kidney allograft rejection. We hypothesized that the pattern and dynamic changes of cf-DNA might be a plausible predictive biomarker for patients at risk of chronic kidney disease (CKD), including individuals with type 2 diabetes mellitus, heart failure, cardiovascular disease and established CKD. Along with it, pre- and posthemodialysis levels of serum cf-DNA appear to be a independent predictor for all-cause mortality in patients with end-stage kidney disease.

Comprehensive analysis of circulating cell-free RNAs in blood for diagnosing non-small cell lung cancer

Early screening and detection of non-small cell lung cancer (NSCLC) is crucial due to the significantly low survival rate in advanced stages. Blood-based liquid biopsy is non-invasive test to assistant disease diagnosis, while cell-free RNA is one of the promising biomarkers in blood. However, the disease related signatures have not been explored completely for most cell-free RNA transcriptome sequencing (cfRNA-Seq) datasets. To address this gap, we developed a comprehensive cfRNA-Seq pipeline for data analysis and constructed a machine learning model to facilitate noninvasive early diagnosis of NSCLC. The results of our study have demonstrated the identification of differential mRNA, lncRNAs and miRNAs from cfRNA-Seq, which have exhibited significant association with development and progression of lung cancer. The classifier based on gene expression signatures achieved an impressive area under the curve (AUC) of up to 0.9, indicating high specificity and sensitivity in both cross-validation and independent test. Furthermore, the analysis of T cell and B cell immune repertoire extracted from cfRNA-Seq have provided insights into the immune status of cancer patients, while the microbiome analysis has revealed distinct bacterial and viral profiles between NSCLC and normal samples. In our future work, we aim to validate the existence of cancer associated T cell receptors (TCR)/B cell receptors (BCR) and microorganisms, and subsequently integrate all identified signatures into diagnostic model to improve the prediction accuracy. This study not only provided a comprehensive analysis pipeline for cfRNA-Seq dataset but also highlights the potential of cfRNAs as promising biomarkers and models for early NSCLC diagnosis, emphasizing their importance in clinical settings.

Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring

Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

Maternal and fetal mitochondrial gene dysregulation in hypertensive disorders of pregnancy

Mitochondrial dysfunction has been implicated in pregnancy-induced hypertension (PIH). The role of mitochondrial gene dysregulation in PIH, and consequences for maternal-fetal interactions, remain elusive. Here, we investigated mitochondrial gene expression and dysregulation in maternal and placental tissues from pregnancies with and without PIH; further, we measured circulating mitochondrial DNA (mtDNA) mutational load, an index of mtDNA integrity. Differential gene expression analysis followed by Time Course Gene Set Analysis (TcGSA) was conducted on publicly available high throughput sequencing transcriptomic data sets. Mutational load analysis was carried out on peripheral mononuclear blood cells from healthy pregnant individuals and individuals with preeclampsia. Thirty mitochondrial differentially expressed genes (mtDEGs) were detected in the maternal cell-free circulating transcriptome, whereas nine were detected in placental transcriptome from pregnancies with PIH. In PIH pregnancies, maternal mitochondrial dysregulation was associated with pathways involved in inflammation, cell death/survival, and placental development, whereas fetal mitochondrial dysregulation was associated with increased production of extracellular vesicles (EVs) at term. Mothers with preeclampsia did not exhibit a significantly different degree of mtDNA mutational load. Our findings support the involvement of maternal mitochondrial dysregulation in the pathophysiology of PIH and suggest that mitochondria may mediate maternal-fetal interactions during healthy pregnancy.NEW & NOTEWORTHY This study identifies aberrant maternal and fetal expression of mitochondrial genes in pregnancies with gestational hypertension and preeclampsia. Mitochondrial gene dysregulation may be a common etiological factor contributing to the development of de novo hypertension in pregnancy-associated hypertensive disorders.

Cell type deconvolution of methylated cell-free DNA at the resolution of individual reads

Cell-free DNA (cfDNA) are DNA fragments originating from dying cells that are detectable in bodily fluids, such as the plasma. Accelerated cell death, for example caused by disease, induces an elevated concentration of cfDNA. As a result, determining the cell type origins of cfDNA molecules can provide information about an individual's health. In this work, we aim to increase the sensitivity of methylation-based cell type deconvolution by adapting an existing method, CelFiE, which uses the methylation beta values of individual CpG sites to estimate cell type proportions. Our new method, CelFEER, instead differentiates cell types by the average methylation values within individual reads. We additionally improved the originally reported performance of CelFiE by using a new approach for finding marker regions that are differentially methylated between cell types. We show that CelFEER estimates cell type proportions with a higher correlation (r = 0.94 ± 0.04) than CelFiE (r = 0.86 ± 0.09) on simulated mixtures of cell types. Moreover, we show that the cell type proportion estimated by CelFEER can differentiate between ALS patients and healthy controls, between pregnant women in their first and third trimester, and between pregnant women with and without gestational diabetes.

Maternal Plasma RNA in First Trimester Nullipara for the Prediction of Spontaneous Preterm Birth ≤ 32 Weeks: Validation Study

The first-trimester prediction of spontaneous preterm birth (sPTB) has been elusive, and current screening is heavily dependent on obstetric history. However, nullipara lack a relevant history and are at higher risk for spontaneous (s)PTB ≤ 32 weeks compared to multipara. No available objective first-trimester screening test has proven a fair predictor of sPTB ≤ 32 weeks. We questioned whether a panel of maternal plasma cell-free (PCF) RNAs (PSME2, NAMPT, APOA1, APOA4, and Hsa-Let-7g) previously validated at 16-20 weeks for the prediction of sPTB ≤ 32 weeks might be useful in first-trimester nullipara. Sixty (60) nulliparous women (40 with sPTB ≤ 32 weeks) who were free of comorbidities were randomly selected from the King's College Fetal Medicine Research Institute biobank. Total PCF RNA was extracted and the expression of panel RNAs was quantitated by qRT-PCR. The analysis employed, primarily, multiple regression with the main outcome being the prediction of subsequent sPTB ≤ 32 weeks. The test performance was judged by the area under the curve (AUC) using a single threshold cut point with observed detection rates (DRs) at three fixed false positive rates (FPR). The mean gestation was 12.9 ± 0.5 weeks (range 12.0-14.1 weeks). Two RNAs were differentially expressed in women destined for sPTB ≤ 32 weeks: APOA1 (p < 0.001) and PSME2 (p = 0.05). APOA1 testing at 11-14 weeks predicted sPTB ≤ 32 weeks with fair to good accuracy. The best predictive model generated an AUC of 0.79 (95% CI 0.66-0.91) with observed DRs of 41%, 61%, and 79% for FPRs of 10%, 20%, and 30%, including crown-rump length, maternal weight, race, tobacco use, and age.

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

Intrauterine growth restriction (IUGR) and preeclampsia (PE) are placental pathologies known to complicate pregnancy and cause neonatal disorders. To date, there is a limited number of studies on the genetic similarity of these conditions. DNA methylation is a heritable epigenetic process that can regulate placental development. Our objective was to identify methylation patterns in placental DNA from normal, PE and IUGR-affected pregnancies. DNA was extracted, and bisulfite was converted, prior to being hybridized for the methylation array. Methylation data were SWAN normalized and differently methylated regions were identified using applications within the USEQ program. UCSC's Genome browser and Stanford's GREAT analysis were used to identify gene promoters. The commonality among affected genes was confirmed by Western blot. We observed nine significantly hypomethylated regions, two being significantly hypomethylated for both PE and IGUR. Western blot confirmed differential protein expression of commonly regulated genes. We conclude that despite the uniqueness of methylation profiles for PE and IUGR, the similarity of some methylation alterations in pathologies could explain the clinical similarities observed with these obstetric complications. These results also provide insight into the genetic similarity between PE and IUGR and suggest possible gene candidates plausibly involved in the onset of both conditions.

Targeted bisulfite resequencing of differentially methylated cytosines in pre-eclampsia reveals a skewed dynamic balance in the DNA methylation of enhancers

Pre-eclampsia (PE) is a major hypertensive disorder of pregnancy. Widespread differentially methylated cytosines (DMCs) with modest changes in methylation level are associated with PE, whereas their cause and biological significance remain unknown. We aimed to clarify DNA methylation patterns around DMCs in 103 placentas using MethylCap targeted bisulfite re-sequencing (MethylCap-seq) assays of 690 selected DMCs. We verified the MethylCap-seq method, then validated 677 (98.1%) of DMCs (vDMCs) in an independent cohort. The validated DMCs were strongly enriched in active placenta-specific enhancers and showed highly dynamic methylation levels. We found high epigenetic heterogeneity between vDMCs and adjacent CpG sites (r2 < 0.2) and a significant decrease in PE in the discovery and replication cohorts (P = 2.00 × 10-24 and 6.43 × 10-9, respectively). We replicated the methylation changes in a hypoxia/reoxygenation cell model. We constructed 112 methylation haplotype blocks and found that the frequencies of unmethylated haplotypes (UMHs) were dynamic with gestational age (GA) and were altered in maternal plasma of patients with PE. Our results uncovered additional DNA methylation features in PE placentas and suggested a model of skewed DNA methylation balance of enhancers in PE.

Utility of In Vivo Magnetic Resonance Imaging Is Predictive of Gestational Diabetes Mellitus During Early Pregnancy

CONTEXT

Gestational diabetes (GDM) imposes long-term adverse health effects on the mother and fetus. The role of magnetic resonance imaging (MRI) during early gestation in GDM has not been well-studied.

OBJECTIVE

To investigate the role of quantitative MRI measurements of placental volume and perfusion, with distribution of maternal adiposity, during early gestation in GDM.

METHODS

At UCLA outpatient antenatal obstetrics clinics, ∼200 pregnant women recruited in the first trimester were followed temporally through pregnancy until parturition. Two placental MRI scans were prospectively performed at 14 to 16 weeks and 19 to 24 weeks gestational age (GA). Placental volume and blood flow (PBF) were calculated from placental regions of interest; maternal adiposity distribution was assessed by subcutaneous fat area ratio (SFAR) and visceral fat area ratio (VFAR). Statistical comparisons were performed using the two-tailed t test. Predictive logistic regression modeling was evaluated by area under the curve (AUC).

RESULTS

Of a total 186 subjects, 21 subjects (11.3%) developed GDM. VFAR was higher in GDM vs the control group, at both time points (P < 0.001 each). Placental volume was greater in GDM vs the control group at 19 to 24 weeks GA (P = 0.01). Combining VFAR, placental volume and perfusion, improved the AUC to 0.83 at 14 to 16 weeks (positive predictive value [PPV] = 0.77, negative predictive value [NPV] = 0.83), and 0.81 at 19 to 24 weeks GA (PPV = 0.73, NPV = 0.86).

CONCLUSION

A combination of MRI-based placental volume, perfusion, and visceral adiposity during early pregnancy demonstrates significant changes in GDM and provides a proof of concept for predicting the subsequent development of GDM.

Hypertensive disorders of pregnancy share common cfDNA methylation profiles

Hypertensive disorders of pregnancy (HDP) contribute substantially to perinatal morbidity and mortality. Epigenetic changes point towards cardio-metabolic dysregulation for these vascular disorders. In early pregnancy, epigenetic changes using cell free DNA (cfDNA) are largely unexplored. We aimed to investigate these in HDP between 11 and 14 weeks of gestation by analysis of cfDNA methylation profiles in patients with hypertensive disorders. We identified patients without chronic hypertension but with subsequent development of preeclampsia (PE) (n = 11), with chronic hypertension (HT) but without PE development (n = 14), and lacking both PE and HT (n = 422). We matched patients according to PE risk factors into three groups (n = 5 each group): (1) PE: no HT but PE development, (2) HT: chronic hypertension but no PE and (3) Control: no PE or HT. We successfully optimized our cfDNA isolation process prior to whole genome bisulfite sequencing. Analysis of cfDNA methylation changes indicate a common predisposition in PE and HT groups, chiefly of maternal origin. Assessment of significant differentially methylated regions and annotated genes point towards a common cardiovascular predisposition in preeclampsia and hypertension groups in the first trimester. We postulate the pivotal role of the maternal cardiovascular system in HDP, which is already evident in the first trimester.

Global Trends in Research on Cell-Free Nucleic Acids in Obstetrics and Gynecology during 2017–2021

Objectives. The objectives of this study were to identify global trends in research on cell-free deoxyribonucleic acid (cfDNA) from a bibliometric perspective and provide researchers with new research hotspots. Methods. In all, we extracted 5038 pieces of literature from PubMed and 527 articles from the Web of Science Core Collection (WoSCC) database related to cfDNA published from 1 January 2017 to 31 December 2021. For PubMed literature, we employed co-word, biclustering, and strategic diagram analysis to describe the trends in research on cfDNA in the said five years. Then, we used VOSviewer analysis for the WoSCC database to display the trends in research on cfDNA in obstetrics and gynecology during 2017–2021. Results. Strategy diagram analysis of 95 major Medical Subject Headings terms extracted from 5038 pieces of literature indicated that cfDNA sequence analysis for non-invasive prenatal and genetic testing and its application in the fields of neoplasm genetics and diagnosis is a newly emerging immature theme of cfDNA. VOSviewer analysis of 527 articles showed the global trends in research on cfDNA in obstetrics and gynecology, for example, in terms of most influential authors, institutions, countries, journals, and five research hotspots: (1) cfDNA application in prenatal screening and prenatal diagnosis, (2) cfDNA application in assisted reproductive technology, (3) cfDNA application in pre-eclampsia, DNA methylation, etc., (4) cfDNA application in placental dysfunction and fetal growth restriction, and (5) cfDNA application in fetal chromosomal abnormalities (fetal aneuploidy). Conclusions. Comprehensive visual analysis provides information regarding authors, organizations, countries/regions, journals, research hotspots, and emerging topics in the field of cfDNA for obstetrics and gynecology research. This comprehensive study could make it easier to find a partner for project development and build a network of knowledge on this emerging topic.

The role of maternal DNA methylation in pregnancies complicated by gestational diabetes

Diabetes in pregnancy is associated with adverse pregnancy outcomes and poses a serious threat to the health of mother and child. Although the pathophysiological mechanisms that underlie the association between maternal diabetes and pregnancy complications have not yet been elucidated, it has been suggested that the frequency and severity of pregnancy complications are linked to the degree of hyperglycemia. Epigenetic mechanisms reflect gene-environment interactions and have emerged as key players in metabolic adaptation to pregnancy and the development of complications. DNA methylation, the best characterized epigenetic mechanism, has been reported to be dysregulated during various pregnancy complications, including pre-eclampsia, hypertension, diabetes, early pregnancy loss and preterm birth. The identification of altered DNA methylation patterns may serve to elucidate the pathophysiological mechanisms that underlie the different types of maternal diabetes during pregnancy. This review aims to provide a summary of existing knowledge on DNA methylation patterns in pregnancies complicated by pregestational type 1 (T1DM) and type 2 diabetes mellitus (T2DM), and gestational diabetes mellitus (GDM). Four databases, CINAHL, Scopus, PubMed and Google Scholar, were searched for studies on DNA methylation profiling in pregnancies complicated with diabetes. A total of 1985 articles were identified, of which 32 met the inclusion criteria and are included in this review. All studies profiled DNA methylation during GDM or impaired glucose tolerance (IGT), while no studies investigated T1DM or T2DM. We highlight the increased methylation of two genes, Hypoxia‐inducible Factor‐3α (HIF3α) and Peroxisome Proliferator-activated Receptor Gamma-coactivator-Alpha (PGC1-α), and the decreased methylation of one gene, Peroxisome Proliferator Activated Receptor Alpha (PPARα), in women with GDM compared to pregnant women with normoglycemia that were consistently methylated across diverse populations with varying pregnancy durations, and using different diagnostic criteria, methodologies and biological sources. These findings support the candidacy of these three differentially methylated genes as biomarkers for GDM. Furthermore, these genes may provide insight into the pathways that are epigenetically influenced during maternal diabetes and which should be prioritized and replicated in longitudinal studies and in larger populations to ensure their clinical applicability. Finally, we discuss the challenges and limitations of DNA methylation analysis, and the need for DNA methylation profiling to be conducted in different types of maternal diabetes in pregnancy.

Placental DNA Methylation in pregnancies complicated by maternal diabetes and/or obesity: State of the Art and research gaps

SUMMARYMaternal diabetes and/or obesity in pregnancy are undoubtedly associated with later disease-risk in the offspring. The placenta, interposed between the mother and the fetus, is a potential mediator of this risk through epigenetic mechanisms, including DNA methylation. In recent years, multiple studies have identified differentially methylated CpG sites in the placental tissue DNA in pregnancies complicated by diabetes and obesity. We reviewed all published original research relevant to this topic and analyzed our findings with the focus of identifying overlaps, contradictions and gaps. Most studies focused on the association of gestational diabetes and/or hyperglycemia in pregnancy and DNA methylation in placental tissue at term. We identified overlaps in results related to specific candidate genes, but also observed a large research gap of pregnancies affected by type 1 diabetes. Other unanswered questions relate to analysis of specific placental cell types and the timing of DNA methylation change in response to diabetes and obesity during pregnancy. Maternal metabolism is altered already in the first trimester involving structural and functional changes in the placenta, but studies into its effects on placental DNA methylation during this period are lacking and urgently needed. Fetal sex is also an important determinant of pregnancy outcome, but only few studies have taken this into account. Collectively, we provide a reference work for researchers working in this large and evolving field. Based on the results of the literature review, we formulate suggestions for future focus of placental DNA methylation studies in pregnancies complicated by diabetes and obesity.

Influence of maternal obesity on the multi-omics profiles of the maternal body, gestational tissue, and offspring

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.

Evaluation of a Maternal Plasma RNA Panel Predicting Spontaneous Preterm Birth and Its Expansion to the Prediction of Preeclampsia

Preterm birth is the principal contributor to neonatal death and morbidity worldwide. We previously described a plasma cell-free RNA panel that between 16 and 20 weeks of pregnancy had potential to predict spontaneous preterm birth (sPTB) ≤ 32 weeks caused by preterm labor (PTL) or preterm premature rupture of membranes (PPROM). The present study had three objectives: (1) estimate the RNA panel prognostic accuracy for PTL/PPROM ≤ 32 weeks in a larger series; (2) improve accuracy by adding clinical characteristics to the predictive model; and (3) examine the association of the RNA panel with preeclampsia. We studied 289 women from Memphis TN prospectively sampled 16.0-20.7 weeks and found: (1) PSME2 and Hsa-Let 7g were differentially expressed in cases of PTL/PPROM ≤ 32 weeks and together provided fair predictive accuracy with AUC of 0.76; (2) combining the two RNAs with clinical characteristics improved good predictive accuracy for PTL/PPROM ≤ 32 weeks (AUC 0.83); (3) NAMPT and APOA1 were differentially expressed in women with 'early-onset preeclampsia' (EOP) and together provided good predictive accuracy with AUC of 0.89; and (4) combining the two RNAs with clinical characteristics provided excellent predictive accuracy (AUC 0.96). Our findings suggest an underlying common pathophysiological relationship between PTL/PPROM ≤ 32 weeks and EOP and open inroads for the prognostication of high-risk pregnancies.

Circulating extracellular vesicles exhibit a differential miRNA profile in gestational diabetes mellitus pregnancies

We undertook a prospective temporal study collecting blood samples from consenting pregnant women, to test the hypothesis that circulating extracellular vesicles (EVs) carrying specific non-coding microRNA signatures can underlie gestational diabetes mellitus (GDM). To test this hypothesis, miRNA cargo of isolated and characterized EVs revealed contributions from the placenta and differential expression at all three trimesters and at delivery between pregnant and non-pregnant states. Many miRNAs originate from the placental-specific chromosome 19 microRNA cluster (19MC) and chromosome 14 microRNA cluster (14MC). Further a positive correlation emerged between third trimester and at delivery EVs containing miRNAs and those expressed by the corresponding post-parturient placentas (R value = 0.63 to 0.69, p value = 2.2X10-16), in normal and GDM. In addition, distinct differences at all trimesters emerged between women who subsequently developed GDM. Analysis by logistic regression with leave-one-out-cross validation revealed the optimal combination of miRNAs using all the circulating miRNAs (miR-92a-3p, miR-192-5p, miR-451a, miR-122-5p), or using only the differentially expressed miRNAs (has-miR-92a-3p, hsa-miR-92b-3p, hsa-miR-100-5p and hsa-miR-125a-3p) in GDM during the first trimester. As an initial step, both sets of miRNAs demonstrated a predictive probability with an area under the curve of 0.95 to 0.96. These miRNAs targeted genes involved in cell metabolism, proliferation and immune tolerance. In particular genes of the P-I-3-Kinase, FOXO, insulin signaling and glucogenic pathways were targeted, suggestive of placental connectivity with various maternal organs/cells, altering physiology along with pathogenic mechanisms underlying the subsequent development of GDM. We conclude that circulating EVs originating from the placenta with their miRNA cargo communicate and regulate signaling pathways in maternal organs, thereby predetermining development of GDM.

Integrated analysis of an in vivo model of intra-nasal exposure to instilled air pollutants reveals cell-type specific responses in the placenta

The placenta is a heterogeneous organ whose development involves complex interactions of trophoblasts with decidual, vascular, and immune cells at the fetal-maternal interface. It maintains a critical balance between maternal and fetal homeostasis. Placental dysfunction can lead to adverse pregnancy outcomes including intra-uterine growth restriction, pre-eclampsia, or pre-term birth. Exposure to environmental pollutants contributes to the development of placental abnormalities, with poorly understood molecular underpinning. Here we used a mouse (C57BL/6) model of environmental pollutant exposure by administration of a particulate matter (SRM1649b at 300 μg/day/mouse) suspension intra-nasally beginning 2 months before conception and during gestation, in comparison to saline-exposed controls. Placental transcriptomes, at day 19 of gestation, were determined using bulk RNA-seq from whole placentas of exposed (n = 4) and control (n = 4) animals and scRNAseq of three distinct placental layers, followed by flow cytometry analysis of the placental immune cell landscape. Our results indicate a reduction in vascular placental cells, especially cells responsible for structural integrity, and increase in trophoblast proliferation in animals exposed to particulate matter. Pollution-induced inflammation was also evident, especially in the decidual layer. These data indicate that environmental exposure to air pollutants triggers changes in the placental cellular composition, mediating adverse pregnancy outcomes.

DLRAPom: a hybrid pipeline of Optimized XGBoost-guided integrative multiomics analysis for identifying targetable disease-related lncRNA-miRNA-mRNA regulatory axes

The lack of a reliable and easy-to-operate screening pipeline for disease-related noncoding RNA regulatory axis is a problem that needs to be solved urgently. To address this, we designed a hybrid pipeline, disease-related lncRNA-miRNA-mRNA regulatory axis prediction from multiomics (DLRAPom), to identify risk biomarkers and disease-related lncRNA-miRNA-mRNA regulatory axes by adding a novel machine learning model on the basis of conventional analysis and combining experimental validation. The pipeline consists of four parts, including selecting hub biomarkers by conventional bioinformatics analysis, discovering the most essential protein-coding biomarkers by a novel machine learning model, extracting the key lncRNA-miRNA-mRNA axis and validating experimentally. Our study is the first one to propose a new pipeline predicting the interactions between lncRNA and miRNA and mRNA by combining WGCNA and XGBoost. Compared with the methods reported previously, we developed an Optimized XGBoost model to reduce the degree of overfitting in multiomics data, thereby improving the generalization ability of the overall model for the integrated analysis of multiomics data. With applications to gestational diabetes mellitus (GDM), we predicted nine risk protein-coding biomarkers and some potential lncRNA-miRNA-mRNA regulatory axes, which all correlated with GDM. In those regulatory axes, the MALAT1/hsa-miR-144-3p/IRS1 axis was predicted to be the key axis and was identified as being associated with GDM for the first time. In short, as a flexible pipeline, DLRAPom can contribute to molecular pathogenesis research of diseases, effectively predicting potential disease-related noncoding RNA regulatory networks and providing promising candidates for functional research on disease pathogenesis.

Early prediction of preeclampsia in pregnancy with cell-free RNA

Liquid biopsies that measure circulating cell-free RNA (cfRNA) offer an opportunity to study the development of pregnancy-related complications in a non-invasive manner and to bridge gaps in clinical care1-4. Here we used 404 blood samples from 199 pregnant mothers to identify and validate cfRNA transcriptomic changes that are associated with preeclampsia, a multi-organ syndrome that is the second largest cause of maternal death globally5. We find that changes in cfRNA gene expression between normotensive and preeclamptic mothers are marked and stable early in gestation, well before the onset of symptoms. These changes are enriched for genes specific to neuromuscular, endothelial and immune cell types and tissues that reflect key aspects of preeclampsia physiology6-9, suggest new hypotheses for disease progression and correlate with maternal organ health. This enabled the identification and independent validation of a panel of 18 genes that when measured between 5 and 16 weeks of gestation can form the basis of a liquid biopsy test that would identify mothers at risk of preeclampsia long before clinical symptoms manifest themselves. Tests based on these observations could help predict and manage who is at risk for preeclampsia-an important objective for obstetric care10,11.

Development and validation of a transcriptomic signature-based model as the predictive, preventive, and personalized medical strategy for preterm birth within 7 days in threatened preterm labor women

Preterm birth (PTB) is the leading cause of neonatal death. The essential strategy to prevent PTB is the accurate identification of threatened preterm labor (TPTL) women who will have PTB in a short time (< 7 days). Here, we aim to propose a clinical model to contribute to the effective prediction, precise prevention, and personalized medical treatment for PTB < 7 days in TPTL women through bioinformatics analysis and prospective cohort studies. In this study, the 1090 key genes involved in PTB < 7 days in the peripheral blood of TPTL women were ascertained using WGCNA. Based on this, the biological basis of immune-inflammatory activation (e.g., IFNγ and TNFα signaling) as well as immune cell disorders (e.g., monocytes and Th17 cells) in PTB < 7 days were revealed. Then, four core genes (JOSD1, IDNK, ZMYM3, and IL1B) that best represent their transcriptomic characteristics were screened by SVM and LASSO algorithm. Therefore, a prediction model with an AUC of 0.907 was constructed, which was validated in a larger population (AUC = 0.783). Moreover, the predictive value (AUC = 0.957) and clinical feasibility of this model were verified through the clinical prospective cohort we established. In conclusion, in the context of Predictive, Preventive, and Personalized Medicine (3PM), we have developed and validated a model to predict PTB < 7 days in TPTL women. This is promising to greatly improve the accuracy of clinical prediction, which would facilitate the personalized management of TPTL women to precisely prevent PTB < 7 days and improve maternal-fetal outcomes.

Function Follows Form: Gene Expression and Prenatal Screening

To date, prenatal testing has relied on imaging to determine fetal 'form' (anatomy). 'Function', as ascertained by measuring fetal or placental mRNA transcripts in maternal blood, has the potential to more precisely determine which pregnancies need closer monitoring and which babies should be delivered in special care settings.

Epigenetics, fragmentomics, and topology of cell-free DNA in liquid biopsies

Liquid biopsies that analyze cell-free DNA in blood plasma are used for noninvasive prenatal testing, oncology, and monitoring of organ transplant recipients. DNA molecules are released into the plasma from various bodily tissues. Physical and molecular features of cell-free DNA fragments and their distribution over the genome bear information about their tissues of origin. Moreover, patterns of DNA methylation of these molecules reflect those of their tissue sources. The nucleosomal organization and nuclease content of the tissue of origin affect the fragmentation profile of plasma DNA molecules, such as fragment size and end motifs. Besides double-stranded linear fragments, other topological forms of cell-free DNA also exist-namely circular and single-stranded molecules. Enhanced by these features, liquid biopsies hold promise for the noninvasive detection of tissue-specific pathologies with a range of clinical applications.

Epigenetic Regulation of Adipogenesis in Development of Metabolic Syndrome

Obesity is one of the biggest public health concerns identified by an increase in adipose tissue mass as a result of adipocyte hypertrophy and hyperplasia. Pertaining to the importance of adipose tissue in various biological processes, any alteration in its function results in impaired metabolic health. In this review, we discuss how adipose tissue maintains the metabolic health through secretion of various adipokines and inflammatory mediators and how its dysfunction leads to the development of severe metabolic disorders and influences cancer progression. Impairment in the adipocyte function occurs due to individuals' genetics and/or environmental factor(s) that largely affect the epigenetic profile leading to altered gene expression and onset of obesity in adults. Moreover, several crucial aspects of adipose biology, including the regulation of different transcription factors, are controlled by epigenetic events. Therefore, understanding the intricacies of adipogenesis is crucial for recognizing its relevance in underlying disease conditions and identifying the therapeutic interventions for obesity and metabolic syndrome.

Investigating Pregnancy and Its Complications Using Circulating Cell-Free RNA in Women's Blood During Gestation

In recent years, there have been major advances in the application of non-invasive techniques to predict pregnancy-related complications, for example by measuring cell-free RNA (cfRNA) in maternal blood. In contrast to cell-free DNA (cfDNA), which is already in clinical use to diagnose fetal aneuploidy, circulating RNA levels can correspond with tissue-specific gene expression and provide a snapshot of prenatal health across gestation. Here, we review the physiologic origins of cfRNA and its novel applications and corresponding challenges to monitor fetal and maternal health and predict pregnancy-related complications.