Circulating transcripts in maternal blood reflect a molecular signature of early-onset preeclampsia

Predicting Preterm Birth Using Cell-Free Ribonucleic Acid

Spontaneous preterm birth (sPTB) is a complex and clinically heterogeneous condition that remains incompletely understood, leading to insufficient interventions to effectively prevent it from occurring. Cell-free ribonucleic acid signatures in the maternal circulation have the potential to identify biologically relevant subtypes of sPTB. These could one day be used to predict and prevent sPTB in asymptomatic individuals, and to aid in prognosis and management for individuals presenting with threatened preterm labor and preterm prelabor rupture of membranes.

Decoding bioactive signals of the RNA secretome: the cell-free messenger RNA catalogue

Despite gene-expression profiling being one of the most common methods to evaluate molecular dysregulation in tissues, the utilization of cell-free messenger RNA (cf-mRNA) as a blood-based non-invasive biomarker analyte has been limited compared to other RNA classes. Recent advancements in low-input RNA-sequencing and normalization techniques, however, have enabled characterization as well as accurate quantification of cf-mRNAs allowing direct pathological insights. The molecular profile of the cell-free transcriptome in multiple diseases has subsequently been characterized including, prenatal diseases, neurological disorders, liver diseases and cancers suggesting this biological compartment may serve as a disease agnostic platform. With mRNAs packaged in a myriad of extracellular vesicles and particles, these signals may be used to develop clinically actionable, non-invasive disease biomarkers. Here, we summarize the recent scientific developments of extracellular mRNA, biology of extracellular mRNA carriers, clinical utility of cf-mRNA as disease biomarkers, as well as proposed functions in cell and tissue pathophysiology.

Cell type signatures in cell-free DNA fragmentation profiles reveal disease biology

Circulating cell-free DNA (cfDNA) fragments have characteristics that are specific to the cell types that release them. Current methods for cfDNA deconvolution typically use disease tailored marker selection in a limited number of bulk tissues or cell lines. Here, we utilize single cell transcriptome data as a comprehensive cellular reference set for disease-agnostic cfDNA cell-of-origin analysis. We correlate cfDNA-inferred nucleosome spacing with gene expression to rank the relative contribution of over 490 cell types to plasma cfDNA. In 744 healthy individuals and patients, we uncover cell type signatures in support of emerging disease paradigms in oncology and prenatal care. We train predictive models that can differentiate patients with colorectal cancer (84.7%), early-stage breast cancer (90.1%), multiple myeloma (AUC 95.0%), and preeclampsia (88.3%) from matched controls. Importantly, our approach performs well in ultra-low coverage cfDNA datasets and can be readily transferred to diverse clinical settings for the expansion of liquid biopsy.

Characterizing immune variation and diagnostic indicators of preeclampsia by single-cell RNA sequencing and machine learning

Preeclampsia is a multifactorial and heterogeneous complication of pregnancy. Here, we utilize single-cell RNA sequencing to dissect the involvement of circulating immune cells in preeclampsia. Our findings reveal downregulation of immune response in lymphocyte subsets in preeclampsia, such as reduction in natural killer cells and cytotoxic genes expression, and expansion of regulatory T cells. But the activation of naïve T cell and monocyte subsets, as well as increased MHC-II-mediated pathway in antigen-presenting cells were still observed in preeclampsia. Notably, we identified key monocyte subsets in preeclampsia, with significantly increased expression of angiogenesis pathways and pro-inflammatory S100 family genes in VCAN+ monocytes and IFN+ non-classical monocytes. Furthermore, four cell-type-specific machine-learning models have been developed to identify potential diagnostic indicators of preeclampsia. Collectively, our study demonstrates transcriptomic alternations of circulating immune cells and identifies immune components that could be involved in pathophysiology of preeclampsia.

Terminal modifications independent cell-free RNA sequencing enables sensitive early cancer detection and classification

Cell-free RNAs (cfRNAs) offer an opportunity to detect diseases from a transcriptomic perspective, however, existing techniques have fallen short in generating a comprehensive cell-free transcriptome profile. We develop a sensitive library preparation method that is robust down to 100 µl input plasma to analyze cfRNAs independent of their 5'-end modifications. We show that it outperforms adapter ligation-based method in detecting a greater number of cfRNA species. We perform transcriptome-wide characterizations in 165 lung cancer, 30 breast cancer, 37 colorectal cancer, 55 gastric cancer, 15 liver cancer, and 133 cancer-free participants and demonstrate its ability to identify transcriptomic changes occurring in early-stage tumors. We also leverage machine learning analyses on the differentially expressed cfRNA signatures and reveal their robust performance in cancer detection and classification. Our work sets the stage for in-depth study of the cfRNA repertoire and highlights the value of cfRNAs as cancer biomarkers in clinical applications.

Method for the extraction of circulating nucleic acids based on MOF reveals cell-free RNA signatures in liver cancer

Cell-free RNA (cfRNA) allows assessment of health, status, and phenotype of a variety of human organs and is a potential biomarker to non-invasively diagnose numerous diseases. Nevertheless, there is a lack of highly efficient and bias-free cfRNA isolation technologies due to the low abundance and instability of cfRNA. Here, we developed a reproducible and high-efficiency isolation technology for different types of cell-free nucleic acids (containing cfRNA and viral RNA) in serum/plasma based on the inclusion of nucleic acids by metal-organic framework (MOF) materials, which greatly improved the isolation efficiency and was able to preserve RNA integrity compared with the most widely used research kit method. Importantly, the quality of cfRNA extracted by the MOF method is about 10-fold that of the kit method, and the MOF method isolates more than three times as many different RNA types as the kit method. The whole transcriptome mapping characteristics of cfRNA in serum from patients with liver cancer was described and a cfRNA signature with six cfRNAs was identified to diagnose liver cancer with high diagnostic efficiency (area under curve = 0.905 in the independent validation cohort) using this MOF method. Thus, this new MOF isolation technique will advance the field of liquid biopsy, with the potential to diagnose liver cancer.

A cross-sectional analysis of syncytiotrophoblast membrane extracellular vesicles-derived transcriptomic biomarkers in early-onset preeclampsia

Background

Preeclampsia (PE) is a pregnancy-specific hypertensive disorder affecting 2%-8% of pregnancies worldwide. Biomarker(s) for the disorder exists, but while these have excellent negative predictive value, their positive predictive value is poor. Extracellular vesicles released by the placenta into the maternal circulation, syncytiotrophoblast membrane extracellular vesicles (STB-EVs), have been identified as being involved in PE with the potential to act as liquid biopsies.

Objective

The objective of this study was to identify the difference in the transcriptome of placenta and STB-EVs between preeclampsia and normal pregnancy (NP) and mechanistic pathways.

Methods/study design

We performed RNA-sequencing on placental tissue, medium/large and small STB-EVs from PE (n = 6) and NP (n = 6), followed by bioinformatic analysis to identify targets that could be used in the future for EV-based diagnostic tests for preeclampsia. Some of the identified biomarkers were validated with real-time polymerase chain reactions.

Results

Our analysis identified a difference in the transcriptomic STB-EV cargo between PE and NP. We then identified and verified the differential expression of FLNB, COL17A1, SLC45A4, LEP, HTRA4, PAPP-A2, EBI3, HSD17B1, FSTL3, INHBA, SIGLEC6, and CGB3. Our analysis also identified interesting mechanistic processes via an in silico prediction of STB-EV-based mechanistic pathways.

Conclusions

In this study, using comprehensive profiling of differentially expressed/carried genes of three linked sample subtypes in PE, we identified potential biomarkers and mechanistic gene pathways that may be important in the pathophysiology of PE and could be further explored in future studies.

Noninvasive preeclampsia prediction using plasma cell-free RNA signatures

BACKGROUND

Preeclampsia, especially preterm preeclampsia and early-onset preeclampsia, is a life-threating pregnancy disorder, and the heterogeneity and complexity of preeclampsia make it difficult to predict risk and to develop treatments. Plasma cell-free RNA carries unique information from human tissue and may be useful for noninvasive monitoring of maternal, placental, and fetal dynamics during pregnancy.

OBJECTIVE

This study aimed to investigate various RNA biotypes associated with preeclampsia in plasma and to develop classifiers to predict preterm preeclampsia and early-onset preeclampsia before diagnosis.

STUDY DESIGN

We performed a novel, cell-free RNA sequencing method termed polyadenylation ligation-mediated sequencing to investigate the cell-free RNA characteristics of 715 healthy pregnancies and 202 pregnancies affected by preeclampsia before symptom onset. We explored differences in the abundance of different RNA biotypes in plasma between healthy and preeclampsia samples and built preterm preeclampsia and early-onset preeclampsia prediction classifiers using machine learning methods. Furthermore, we validated the performance of the classifiers using the external and internal validation cohorts and assessed the area under the curve and positive predictive value.

RESULTS

We detected 77 genes, including messenger RNA (44%) and microRNA (26%), that were differentially expressed in healthy mothers and mothers with preterm preeclampsia before symptom onset, which could separate participants with preterm preeclampsia from healthy samples and that played critical functional roles in preeclampsia physiology. We developed 2 classifiers for predicting preterm preeclampsia and early-onset preeclampsia before diagnosis based on 13 cell-free RNA signatures and 2 clinical features (in vitro fertilization and mean arterial pressure), respectively. Notably, both classifiers showed enhanced performance when compared with the existing methods. The preterm preeclampsia prediction model achieved 81% area under the curve and 68% positive predictive value in an independent validation cohort (preterm, n=46; control, n=151); the early-onset preeclampsia prediction model had an area under the curve of 88% and a positive predictive value of 73% in an external validation cohort (early-onset preeclampsia, n=28; control, n=234). Furthermore, we demonstrated that downregulation of microRNAs may play vital roles in preeclampsia through the upregulation of preeclampsia-relevant target genes.

CONCLUSION

In this cohort study, a comprehensive transcriptomic landscape of different RNA biotypes in preeclampsia was presented and 2 advanced classifiers with substantial clinical importance for preterm preeclampsia and early-onset preeclampsia prediction before symptom onset were developed. We demonstrated that messenger RNA, microRNA, and long noncoding RNA can simultaneously serve as potential biomarkers of preeclampsia, holding the promise of prevention of preeclampsia in the future. Abnormal cell-free messenger RNA, microRNA, and long noncoding RNA molecular changes may help to elucidate the pathogenic determinants of preeclampsia and open new therapeutic windows to effectively reduce pregnancy complications and fetal morbidity.

Multiomics characterization of cell type repertoires for urine liquid biopsies

Urine is assayed alongside blood in medicine, yet current clinical diagnostic tests utilize only a small fraction of its total biomolecular repertoire, potentially foregoing high-resolution insights into human health and disease. In this work, we characterized the joint landscapes of transcriptomic and metabolomic signals in human urine. We also compared the urine transcriptome to plasma cell-free RNA, identifying a distinct cell type repertoire and enrichment for metabolic signal. Untargeted metabolomic measurements identified a complementary set of pathways to the transcriptomic analysis. Our findings suggest that urine is a promising biofluid yielding prognostic and detailed insights for hard-to-biopsy tissues with low representation in the blood, offering promise for a new generation of liquid biopsies.

Cis P-tau is a central circulating and placental etiologic driver and therapeutic target of preeclampsia

Preeclampsia (PE) is the leading cause of maternal and fetal mortality globally and may trigger dementia later in life in mothers and their offspring. However, the etiological drivers remain elusive. Cis P-tau is an early etiological driver and blood biomarker in pre-clinical Alzheimer's and after vascular or traumatic brain injury, which can be targeted by stereo-specific antibody, with clinical trials ongoing. Here we find significant cis P-tau in the placenta and serum of PE patients, and in primary human trophoblasts exposed to hypoxia or sera from PE patients due to Pin1 inactivation. Depletion of cis P-tau from PE patient sera by the antibody prevents their ability to disrupt trophoblast invasion and endovascular activity and to cause the PE-like pathological and clinical features in pregnant humanized tau mice. Our studies uncover that cis P-tau is a central circulating etiological driver and its stereo-specific antibody is valuable for early PE diagnosis and treatment.

Care plan for individuals at risk for preeclampsia: shared approach to education, strategies for prevention, surveillance, and follow-up

Preeclampsia is a multisystemic disorder of pregnancy that affects 250,000 pregnant individuals in the United States and approximately 10 million worldwide per annum. Preeclampsia is associated with substantial immediate morbidity and mortality but also long-term morbidity for both mother and offspring. It is now clearly established that a low dose of aspirin given daily, beginning early in pregnancy modestly reduces the occurrence of preeclampsia. Low-dose aspirin seems safe, but because there is a paucity of information about long-term effects on the infant, it is not recommended for all pregnant individuals. Thus, several expert groups have identified clinical factors that indicate sufficient risk to recommend low-dose aspirin preventive therapy. These risk factors may be complemented by biochemical and/or biophysical tests that either indicate increased probability of preeclampsia in individuals with clinical risk factors, or more importantly, identify increased likelihood in those without other evident risk. In addition, the opportunity exists to provide this population with additional care that may prevent or mitigate the short- and long-term effects of preeclampsia. Patient and provider education, increased surveillance, behavioral modification, and other approaches to improve outcomes in these individuals can improve the chance of a healthy outcome. We assembled a group with diverse, relevant expertise (clinicians, investigators, advocates, and public and private stakeholders) to develop a care plan in which providers and pregnant individuals at risk can work together to reduce the risk of preeclampsia and associated morbidities. The plan is for care of individuals at moderate to high risk for developing preeclampsia, sufficient to receive low-dose aspirin therapy, as identified by clinical and/or laboratory findings. The recommendations are presented using the GRADE methodology with the quality of evidence upon which each is based. In addition, printable appendices with concise summaries of the care plan's recommendations for patients and healthcare providers are provided. We believe that this shared approach to care will facilitate prevention of preeclampsia and its attendant short- and long-term morbidity in patients identified as at risk for development of this disorder.

Noninvasive Prenatal Testing Using Circulating DNA and RNA: Advances, Challenges, and Possibilities

Prenatal screening using sequencing of circulating cell-free DNA has transformed obstetric care over the past decade and significantly reduced the number of invasive diagnostic procedures like amniocentesis for genetic disorders. Nonetheless, emergency care remains the only option for complications like preeclampsia and preterm birth, two of the most prevalent obstetrical syndromes. Advances in noninvasive prenatal testing expand the scope of precision medicine in obstetric care. In this review, we discuss advances, challenges, and possibilities toward the goal of providing proactive, personalized prenatal care. The highlighted advances focus mainly on cell-free nucleic acids; however, we also review research that uses signals from metabolomics, proteomics, intact cells, and the microbiome. We discuss ethical challenges in providing care. Finally, we look to future possibilities, including redefining disease taxonomy and moving from biomarker correlation to biological causation.

Integrated analysis of circulating cell free nucleic acids for cancer genotyping and immune phenotyping of tumor microenvironment

The circulating cell-free nucleic acids (ccfNAs) consist of a heterogenous cocktail of both single (ssNA) and double-stranded (dsNA) nucleic acids. These ccfNAs are secreted into the blood circulation by both healthy and malignant cells via various mechanisms including apoptosis, necrosis, and active secretion. The major source of ccfNAs are the cells of hematopoietic system under healthy conditions. These ccfNAs include fragmented circulating cell free DNA (ccfDNA), coding or messenger RNA (mRNA), long non-coding RNA (lncRNA), microRNA (miRNA), and mitochondrial DNA/RNA (mtDNA and mtRNA), that serve as prospective biomarkers in assessment of various clinical conditions. For, e.g., free fetal DNA and RNA migrate into the maternal plasma, whereas circulating tumor DNA (ctDNA) has clinical relevance in diagnostic, prognostic, therapeutic targeting, and disease progression monitoring to improve precision medicine in cancer. The epigenetic modifications of ccfDNA as well as circulating cell-free RNA (ccfRNA) such as miRNA and lncRNA show disease-related variations and hold potential as epigenetic biomarkers. The messenger RNA present in the circulation or the circulating cell free mRNA (ccf-mRNA) and long non-coding RNA (ccf-lncRNA) have gradually become substantial in liquid biopsy by acting as effective biomarkers to assess various aspects of disease diagnosis and prognosis. Conversely, the simultaneous characterization of coding and non-coding RNAs in human biofluids still poses a significant hurdle. Moreover, a comprehensive assessment of ccfRNA that may reflect the tumor microenvironment is being explored. In this review, we focus on the novel approaches for exploring ccfDNA and ccfRNAs, specifically ccf-mRNA as biomarkers in clinical diagnosis and prognosis of cancer. Integrating the detection of circulating tumor DNA (ctDNA) for cancer genotyping in conjunction with ccfRNA both quantitatively and qualitatively, may potentially hold immense promise towards precision medicine. The current challenges and future directions in deciphering the complexity of cancer networks based on the dynamic state of ccfNAs will be discussed.

Biomarker screening in preeclampsia: an RNA-sequencing approach based on data from multiple studies

OBJECTIVE

Biomarkers have become important in the prognosis and diagnosis of various diseases. High-throughput methods, such as RNA sequencing facilitate the detection of differentially expressed genes (DEGs), hence potential biomarker candidates. Individual studies suggest long lists of DEGs, hampering the identification of clinically relevant ones. Concerning preeclampsia - a major obstetric burden with high risk for adverse maternal and/or neonatal outcomes - limitations in diagnosis and prediction are still important issues. We, therefore, developed a workflow to facilitate the screening for biomarkers.

METHODS

On the basis of the tool DESeq2, a comprehensive workflow for identifying DEGs was established, analyzing data from several publicly available RNA-sequencing studies. We applied it to four RNA-sequencing datasets (one blood, three placenta) analyzing patients with preeclampsia and normotensive controls. We compared our results with other published approaches and evaluated their performance.

RESULTS

We identified 110 genes that are dysregulated in preeclampsia, observed in at least three of the studies analyzed, six even in all four studies. These included FLT-1, TREM-1, and FN1, which either represent established biomarkers at protein level, or promising candidates based on recent studies. For comparison, using a published meta-analysis approach, 5240 DEGs were obtained.

CONCLUSION

This study presents a data analysis workflow for preeclampsia biomarker screening, capable of identifying promising biomarker candidates, while drastically reducing the numbers of candidates. Moreover, we were also able to confirm its performance for heart failure. This approach can be applied to additional diseases for biomarker identification, and the set of DEGs identified in preeclampsia represents a resource for further studies.

Evaluating the Effects of Storage Conditions on Multiple Cell-Free RNAs in Plasma by High-Throughput Sequencing

Background: Plasma cell-free RNAs (cfRNAs) can serve as noninvasive biomarkers for the diagnosis and monitoring of diseases. However, the delay in blood processing may lead to unreliable results. Therefore, an unbiased evaluation based on the whole transcriptome under different storage conditions is needed. Methods: Here, blood samples were collected in ethylenediaminetetraacetic acid tubes and processed immediately (0 hour), or stored at room temperature (RT) or 4°C for different time intervals (2, 6, and 24 hours) before plasma separation. High-throughput sequencing was applied to assess the effects of storage conditions on the transcript profiles and fragment characteristics of plasma cell-free mRNA, long noncoding RNA (lncRNA), and small RNAs. Results: More genes changed their expression levels with time when blood was stored at RT compared with those at 4°C. Cell-free mRNA and lncRNA were relatively stable in blood preserved at 4°C for 6 hours, while cell-free microRNA (miRNA) and piwi-interacting RNA (piRNA) remained stable at 4°C for 24 hours. After 24 hours, more contamination of the leukocyte-derived RNAs occurred at RT, possibly due to apoptosis. Meanwhile, significant changes were also observed regarding the characteristics of the RNA fragments, including fragment size, the proportion of intron, and the pyrimidine frequency of the fragmented 3' end. Fifteen tissue-enriched genes were detected in the plasma but not expressed in leukocytes. The expression level and fragment length of these genes gradually decreased during storage, suggesting the degradation of the cfRNA and the dilution of leukocyte-derived RNA with other tissue-derived cfRNA. Conclusions: Our results suggest that the contamination of leukocyte-derived RNA and the degradation of original cfRNA contribute to the changes in the cfRNA expression profiles and the fragment characteristics during short-term storage. The storage of blood at 4°C for 6 hours allows plasma cfRNA to remain relatively stable, which will be useful for further studies or clinical applications where adequate quantification or the fragment signature of cfRNA is required.

Phase 2 of extracellular RNA communication consortium charts next-generation approaches for extracellular RNA research

The extracellular RNA communication consortium (ERCC) is an NIH-funded program aiming to promote the development of new technologies, resources, and knowledge about exRNAs and their carriers. After Phase 1 (2013-2018), Phase 2 of the program (ERCC2, 2019-2023) aims to fill critical gaps in knowledge and technology to enable rigorous and reproducible methods for separation and characterization of both bulk populations of exRNA carriers and single EVs. ERCC2 investigators are also developing new bioinformatic pipelines to promote data integration through the exRNA atlas database. ERCC2 has established several Working Groups (Resource Sharing, Reagent Development, Data Analysis and Coordination, Technology Development, nomenclature, and Scientific Outreach) to promote collaboration between ERCC2 members and the broader scientific community. We expect that ERCC2's current and future achievements will significantly improve our understanding of exRNA biology and the development of accurate and efficient exRNA-based diagnostic, prognostic, and theranostic biomarker assays.

Polyadenylation ligation-mediated sequencing (PALM-Seq) characterizes cell-free coding and non-coding RNAs in human biofluids

Background

Cell‐free messenger RNA (cf‐mRNA) and long non‐coding RNA (cf‐lncRNA) are becoming increasingly important in liquid biopsy by providing biomarkers for disease prediction, diagnosis and prognosis, but the simultaneous characterization of coding and non‐coding RNAs in human biofluids remains challenging.

Methods

Here, we developed polyadenylation ligation‐mediated sequencing (PALM‐Seq), an RNA sequencing strategy employing treatment of RNA with T4 polynucleotide kinase to generate cell‐free RNA (cfRNA) fragments with 5′ phosphate and 3′ hydroxyl and RNase H to deplete abundant RNAs, achieving simultaneous quantification and characterization of cfRNAs.

Results

Using PALM‐Seq, we successfully identified well‐known differentially abundant mRNA, lncRNA and microRNA in the blood plasma of pregnant women. We further characterized cfRNAs in blood plasma, saliva, urine, seminal plasma and amniotic fluid and found that the detected numbers of different RNA biotypes varied with body fluids. The profiles of cf‐mRNA reflected the function of originated tissues, and immune cells significantly contributed RNA to blood plasma and saliva. Short fragments (<50 nt) of mRNA and lncRNA were major in biofluids, whereas seminal plasma and amniotic fluid tended to retain long RNA. Body fluids showed distinct preferences of pyrimidine at the 3′ end and adenine at the 5′ end of cf‐mRNA and cf‐lncRNA, which were correlated with the proportions of short fragments.

Conclusion

Together, PALM‐Seq enables a simultaneous characterization of cf‐mRNA and cf‐lncRNA, contributing to elucidating the biology and promoting the application of cfRNAs.

Detection of Embryonic Trisomy 21 in the First Trimester Using Maternal Plasma Cell-Free RNA

Prenatal trisomy 21 (T21) screening commonly involves testing a maternal blood sample for fetal DNA aneuploidy. It is reliable but poses a cost barrier to universal screening. We hypothesized maternal plasma RNA screening might provide similar reliability but at a lower cost. Discovery experiments used plasma cell-free RNA from 20 women 11−13 weeks tested by RNA and miRNA microarrays followed by qRT-PCR. Thirty-six mRNAs and 18 small RNAs of the discovery cDNA were identified by qPCR as potential markers of embryonic T21. The second objective was validation of the RNA predictors in 998 independent pregnancies at 11−13 weeks including 50 T21. Initial analyses identified 9−15 differentially expressed RNA with modest predictive power (AUC < 0.70). The 54 RNAs were then subjected to machine learning. Eleven algorithms were trained on one partition and tested on an independent partition. The three best algorithms were identified by Kappa score and the effects of training/testing partition size and dataset class imbalance on prediction were evaluated. Six to ten RNAs predicted T21 with AUCs up to 1.00. The findings suggest that maternal plasma collected at 11−13 weeks, tested by qRT-PCR, and classified by machine learning, may accurately predict T21 for a lower cost than plasma DNA, thus opening the door to universal screening.

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.

The Role of Non-Coding RNAs in the Human Placenta

Non-coding RNAs (ncRNAs) play a central and regulatory role in almost all cells, organs, and species, which has been broadly recognized since the human ENCODE project and several other genome projects. Nevertheless, a small fraction of ncRNAs have been identified, and in the placenta they have been investigated very marginally. To date, most examples of ncRNAs which have been identified to be specific for fetal tissues, including placenta, are members of the group of microRNAs (miRNAs). Due to their quantity, it can be expected that the fairly larger group of other ncRNAs exerts far stronger effects than miRNAs. The syncytiotrophoblast of fetal origin forms the interface between fetus and mother, and releases permanently extracellular vesicles (EVs) into the maternal circulation which contain fetal proteins and RNA, including ncRNA, for communication with neighboring and distant maternal cells. Disorders of ncRNA in placental tissue, especially in trophoblast cells, and in EVs seem to be involved in pregnancy disorders, potentially as a cause or consequence. This review summarizes the current knowledge on placental ncRNA, their transport in EVs, and their involvement and pregnancy pathologies, as well as their potential for novel diagnostic tools.

Predictive RNA profiles for early and very early spontaneous preterm birth

BACKGROUND

Spontaneous preterm birth remains the main driver of childhood morbidity and mortality. Because of an incomplete understanding of the molecular pathways that result in spontaneous preterm birth, accurate predictive markers and target therapeutics remain elusive.

OBJECTIVE

This study sought to determine if a cell-free RNA profile could reveal a molecular signature in maternal blood months before the onset of spontaneous preterm birth.

STUDY DESIGN

Maternal samples (n=242) were obtained from a prospective cohort of individuals with a singleton pregnancy across 4 clinical sites at 12-24 weeks (nested case-control; n=46 spontaneous preterm birth <35 weeks and n=194 term controls). Plasma was processed via a next-generation sequencing pipeline for cell-free RNA using the Mirvie RNA platform. Transcripts that were differentially expressed in next-generation sequencing cases and controls were identified. Enriched pathways were identified in the Reactome database using overrepresentation analysis.

RESULTS

Twenty five transcripts associated with an increased risk of spontaneous preterm birth were identified. A logistic regression model was developed using these transcripts to predict spontaneous preterm birth with an area under the curve =0.80 (95% confidence interval, 0.72-0.87) (sensitivity=0.76, specificity=0.72). The gene discovery and model were validated through leave-one-out cross-validation. A unique set of 39 genes was identified from cases of very early spontaneous preterm birth (<25 weeks, n=14 cases with time to delivery of 2.5±1.8 weeks); a logistic regression classifier on the basis of these genes yielded an area under the curve=0.76 (95% confidence interval, 0.63-0.87) in leave-one-out cross validation. Pathway analysis for the transcripts associated with spontaneous preterm birth revealed enrichment of genes related to collagen or the extracellular matrix in those who ultimately had a spontaneous preterm birth at <35 weeks. Enrichment for genes in insulin-like growth factor transport and amino acid metabolism pathways were associated with spontaneous preterm birth at <25 weeks.

CONCLUSION

Second trimester cell-free RNA profiles in maternal blood provide a noninvasive window to future occurrence of spontaneous preterm birth. The systemic finding of changes in collagen and extracellular matrix pathways may serve to identify individuals at risk for premature cervical remodeling, with growth factor and metabolic pathways implicated more often in very early spontaneous preterm birth. The use of cell-free RNA profiles has the potential to accurately identify those at risk for spontaneous preterm birth by revealing the underlying pathophysiology, creating an opportunity for more targeted therapeutics and effective interventions.

Cell types of origin of the cell-free transcriptome

Cell-free RNA from liquid biopsies can be analyzed to determine disease tissue of origin. We extend this concept to identify cell types of origin using the Tabula Sapiens transcriptomic cell atlas as well as individual tissue transcriptomic cell atlases in combination with the Human Protein Atlas RNA consensus dataset. We define cell type signature scores, which allow the inference of cell types that contribute to cell-free RNA for a variety of diseases.

Cell types affected by various diseases are inferred from cell-free RNA.

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.

Using Machine Learning to Predict Complications in Pregnancy: A Systematic Review

Introduction: Artificial intelligence is widely used in medical field, and machine learning has been increasingly used in health care, prediction, and diagnosis and as a method of determining priority. Machine learning methods have been features of several tools in the fields of obstetrics and childcare. This present review aims to summarize the machine learning techniques to predict perinatal complications.

Objective: To identify the applicability and performance of machine learning methods used to identify pregnancy complications.

Methods: A total of 98 articles were obtained with the keywords “machine learning,” “deep learning,” “artificial intelligence,” and accordingly as they related to perinatal complications (“complications in pregnancy,” “pregnancy complications”) from three scientific databases: PubMed, Scopus, and Web of Science. These were managed on the Mendeley platform and classified using the PRISMA method.

Results: A total of 31 articles were selected after elimination according to inclusion and exclusion criteria. The features used to predict perinatal complications were primarily electronic medical records (48%), medical images (29%), and biological markers (19%), while 4% were based on other types of features, such as sensors and fetal heart rate. The main perinatal complications considered in the application of machine learning thus far are pre-eclampsia and prematurity. In the 31 studies, a total of sixteen complications were predicted. The main precision metric used is the AUC. The machine learning methods with the best results were the prediction of prematurity from medical images using the support vector machine technique, with an accuracy of 95.7%, and the prediction of neonatal mortality with the XGBoost technique, with 99.7% accuracy.

Conclusion: It is important to continue promoting this area of research and promote solutions with multicenter clinical applicability through machine learning to reduce perinatal complications. This systematic review contributes significantly to the specialized literature on artificial intelligence and women’s health.

A Novel Circular RNA CircBRAP May Be Used as an Early Predictor of Preeclampsia and Its Potential Mechanism

Preeclampsia (PE), a pregnancy-related multisystem syndrome, is one of the leading causes of maternal and fetal mortality worldwide. The aim of this study was to combine the plasma protein soluble Fms-related tyrosine kinase 1 (sFLT1) levels with uterine artery Doppler ultrasound findings and CircBRAP levels during the first trimester to predict the occurrence of preeclampsia and to explore the potential mechanism by which CircBRAP functions in preeclampsia. Here, we used qRT-PCR to investigate the expression of CircBRAP in forty-nine pairs of plasma specimens and placental tissues from preeclampsia patients and control subjects. The uterine artery (UtA) pulsatility index (PI) was measured using four-dimensional color Doppler ultrasound, and the sFLT1 levels were evaluated by human immunoassay. Exogenous upregulation or downregulation of CircBRAP expression in TEV-1 trophoblast cells was performed to investigate the role of CircBRAP in cell biological behavior. Mechanistically, luciferase reporter, RNA immunoprecipitation (RIP), and biotin-coupled RNA pull-down assays were conducted to verify the relationship between CircBRAP and sFLT1 in TEV-1 cells. The results showed that the predictive power was strengthened when the plasma sFLT1 and CircBRAP levels were combined with the UtA-PI to predict preeclampsia occurrence. Our study also revealed that CircBRAP may regulate miR-106b and the HIF-2α axis to modulate the proliferation, invasion, and apoptosis of TEV-1 trophoblast cells. In summary, placenta-derived CircBRAP in plasma may be a novel biomarker for preeclampsia that, together with plasma sFLT1 levels and uterine artery Doppler ultrasound findings, can more effectively predict preeclampsia, and CircBRAP may play a potential role in preeclampsia.

RNA profiles reveal signatures of future health and disease in pregnancy

Maternal morbidity and mortality continue to rise, and pre-eclampsia is a major driver of this burden1. Yet the ability to assess underlying pathophysiology before clinical presentation to enable identification of pregnancies at risk remains elusive. Here we demonstrate the ability of plasma cell-free RNA (cfRNA) to reveal patterns of normal pregnancy progression and determine the risk of developing pre-eclampsia months before clinical presentation. Our results centre on comprehensive transcriptome data from eight independent prospectively collected cohorts comprising 1,840 racially diverse pregnancies and retrospective analysis of 2,539 banked plasma samples. The pre-eclampsia data include 524 samples (72 cases and 452 non-cases) from two diverse independent cohorts collected 14.5 weeks (s.d., 4.5 weeks) before delivery. We show that cfRNA signatures from a single blood draw can track pregnancy progression at the placental, maternal and fetal levels and can robustly predict pre-eclampsia, with a sensitivity of 75% and a positive predictive value of 32.3% (s.d., 3%), which is superior to the state-of-the-art method2. cfRNA signatures of normal pregnancy progression and pre-eclampsia are independent of clinical factors, such as maternal age, body mass index and race, which cumulatively account for less than 1% of model variance. Further, the cfRNA signature for pre-eclampsia contains gene features linked to biological processes implicated in the underlying pathophysiology of pre-eclampsia.

Patterns of Maternal Neutrophil Gene Expression at 30 Weeks of Gestation, but Not DNA Methylation, Distinguish Mild from Severe Preeclampsia

Neutrophils are activated and extensively infiltrate blood vessels in preeclamptic women. To identify genes that contribute to neutrophil activation and infiltration, we analyzed the transcriptomes of circulating neutrophils from normal pregnant and preeclamptic women. Neutrophils were collected at 30 weeks’ gestation and RNA and DNA were isolated for RNA sequencing and 5-hydroxy-methylcytosine (5-hmC) sequencing as an index of dynamic changes in neutrophil DNA methylation. Women with normal pregnancy who went on to develop mild preeclampsia at term had the most uniquely expressed genes (697) with 325 gene ontology pathways upregulated, many related to neutrophil activation and function. Women with severe preeclampsia who delivered prematurely had few pathways up- or downregulated. Cluster analysis revealed that gene expression in women with severe preeclampsia was an inverse mirror image of gene expression in normal pregnancy, while gene expression in women who developed mild preeclampsia was remarkably different from both. DNA methylation marks, key regulators of gene expression, are removed by the action of ten-eleven translocation (TET) enzymes, which oxidize 5-methylcytosines (5mCs), resulting in locus-specific reversal of DNA methylation. DNA sequencing for 5-hmC revealed no differences among the three groups. Genome-wide DNA methylation revealed extremely low levels in circulating neutrophils suggesting they are de-methylated. Collectively, these data demonstrate that neutrophil gene expression profiles can distinguish different preeclampsia phenotypes, and in the case of mild preeclampsia, alterations in gene expression occur well before clinical symptoms emerge. These findings serve as a foundation for further evaluation of neutrophil transcriptomes as biomarkers of preeclampsia phenotypes. Changes in DNA methylation in circulating neutrophils do not appear to mediate differential patterns of gene expression in either mild or severe preeclampsia.

Disrupted PGR-B and ESR1 signaling underlies defective decidualization linked to severe preeclampsia

Background:

Decidualization of the uterine mucosa drives the maternal adaptation to invasion by the placenta. Appropriate depth of placental invasion is needed to support a healthy pregnancy; shallow invasion is associated with the development of severe preeclampsia (sPE). Maternal contribution to sPE through failed decidualization is an important determinant of placental phenotype. However, the molecular mechanism underlying the in vivo defect linking decidualization to sPE is unknown.

Methods:

Global RNA sequencing was applied to obtain the transcriptomic profile of endometrial biopsies collected from nonpregnant women who suffer sPE in a previous pregnancy and women who did not develop this condition. Samples were randomized in two cohorts, the training and the test set, to identify the fingerprinting encoding defective decidualization in sPE and its subsequent validation. Gene Ontology enrichment and an interaction network were performed to deepen in pathways impaired by genetic dysregulation in sPE. Finally, the main modulators of decidualization, estrogen receptor 1 (ESR1) and progesterone receptor B (PGR-B), were assessed at the level of gene expression and protein abundance.

Results:

Here, we discover the footprint encoding this decidualization defect comprising 120 genes—using global gene expression profiling in decidua from women who developed sPE in a previous pregnancy. This signature allowed us to effectively segregate samples into sPE and control groups. ESR1 and PGR were highly interconnected with the dynamic network of the defective decidualization fingerprint. ESR1 and PGR-B gene expression and protein abundance were remarkably disrupted in sPE.

Conclusions:

Thus, the transcriptomic signature of impaired decidualization implicates dysregulated hormonal signaling in the decidual endometria in women who developed sPE. These findings reveal a potential footprint that could be leveraged for a preconception or early prenatal screening of sPE risk, thus improving prevention and early treatments.

Funding:

This work has been supported by the grant PI19/01659 (MCIU/AEI/FEDER, UE) from the Spanish Carlos III Institute awarded to TGG. NCM was supported by the PhD program FDGENT/2019/008 from the Spanish Generalitat Valenciana. IMB was supported by the PhD program PRE2019-090770 and funding was provided by the grant RTI2018-094946-B-100 (MCIU/AEI/FEDER, UE) from the Spanish Ministry of Science and Innovation with CS as principal investigator. This research was funded partially by Igenomix S.L.

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.

Developing Novel Tests to Screen for Fetal Growth Restriction

Fetal growth restriction (FGR) is a major determinant of global morbidity and mortality. There is an unmet need for methods to stratify the pregnant population on the basis of FGR risk. Despite evolutionary divergence in mammalian reproduction, studies of genetically modified mice have identified biomarkers that have been validated in women, and a systematic screen for genes that control fetal growth in animals could help identify novel clinical biomarkers. Current approaches to biomarker identification using human samples include both targeted and discovery approaches (omics). Application of omic methods to the placenta and maternal blood has yielded promising results, but comes with logistical, experimental, and analytical challenges and all studies are limited by the lack of a gold standard for disease.

Cell-free fetal DNA coming in all sizes and shapes

Cell‐free fetal DNA analysis has an established role in prenatal assessments. It serves as a source of fetal genetic material that is accessible non‐invasively from maternal blood. Through the years, evidence has accumulated to show that cell‐free fetal DNA molecules are derived from placental tissues, are mainly of short DNA fragments and have rapid post‐delivery clearance profiles. But questions regarding how they come to being short molecules from placental cells and in which physical forms do they exist remained largely unanswered until recently. We now know that the distributions of ending sites of cell‐free DNA molecules are non‐random across the genome and bear correlations with the chromatin structures of cells from which they have originated. Such an insight offers ways to deduce the tissue‐of‐origin of these molecules. Besides, the physical nature and sequence characteristics of the ends of each cell‐free DNA molecule provide tell‐tale signs of how the DNA fragmentation processes are orchestrated by nuclease enzymes. These realizations offered opportunities to develop methods for enriching cell‐free fetal DNA to facilitate non‐invasive prenatal diagnostics. Here we aimed to collate what is known about the biological and physical characteristics of cell‐free fetal DNA into one article and explain the implications of these observations.

What’s already known about this topic?

Cell‐free fetal DNA originates from placental tissues and circulates in maternal plasma as a minor population in the form of short fragments which disappears from maternal circulation rapidly after delivery.

What does this study add?

Cell‐free DNA studies at the per molecule per nucleotide level documented the detailed genomic distributions, fragment end characteristics and physical forms of cell‐free DNA unveiling the fine feature differences between maternal and fetal DNA as well as their intricate relationships with the chromatin structure of the cells‐of‐origin. These studies have substantially bridged the knowledge gaps in the biology of cell‐free fetal DNA and may provide insights on how to enhance prenatal tests based on their analyses.

The relationship between polymorphisms of microRNA and preeclampsia: A protocol for meta-analysis and bioinformatics prediction

BACKGROUND

Preeclampsia has genetic correlation. Many studies have shown that microRNA (miRNA) polymorphism is highly associated with preeclampsia, but the results are inconsistent. The purpose of this study is to systematically evaluate the relationship between miRNA polymorphism and preeclampsia.

METHODS

In this study, the search time is set from the establishment of the database on January 2021. The search database include China National Knowledge Infrastructure (CNKI), Wanfang, VIP and China Biology Medicine disc (CBM), PubMed, EMBASE, and Web of Science, and the Cochrane Library. The subjects are case-control studies on the relationship between miRNA polymorphism and preeclampsia. The language is limited to English and Chinese. The data of the included study are extracted and the literature quality is evaluated by 2 researchers independently. The data are statistically analyzed through Stata 16.0 software. We also predicted the miRNA secondary structure and the binding sites of miRNA interaction with its target genes.

RESULTS

This review will be disseminated in print by peer-review.

CONCLUSION

This study will provide evidence-based medicine to elucidate the genetic tendency of preeclampsia.

ETHICS AND DISSEMINATION

Private information from individuals will not be published. This systematic review also does not involve endangering participant rights. Ethical approval will not be required. The results may be published in a peer-reviewed journal or disseminated at relevant conferences.

OSF REGISTRATION NUMBER

DOI 10.17605/OSF.IO/MJY2X.

Noninvasive stratification of nonalcoholic fatty liver disease by whole transcriptome cell-free mRNA characterization

Hepatic fibrosis stage is the most important determinant of outcomes in patients with nonalcoholic fatty liver disease (NAFLD). There is an urgent need for noninvasive tests that can accurately stage fibrosis and determine efficacy of interventions. Here, we describe a novel cell-free (cf)-mRNA sequencing approach that can accurately and reproducibly profile low levels of circulating mRNAs and evaluate the feasibility of developing a cf-mRNA-based NAFLD fibrosis classifier. Using separate discovery and validation cohorts with biopsy-confirmed NAFLD (n = 176 and 59, respectively) and healthy subjects (n = 23), we performed serum cf-mRNA RNA-Seq profiling. Differential expression analysis identified 2,498 dysregulated genes between patients with NAFLD and healthy subjects and 134 fibrosis-associated genes in patients with NAFLD. Comparison between cf-mRNA and liver tissue transcripts revealed significant overlap of fibrosis-associated genes and pathways indicating that the circulating cf-mRNA transcriptome reflects molecular changes in the livers of patients with NAFLD. In particular, metabolic and immune pathways reflective of known underlying steatosis and inflammation were highly dysregulated in the cf-mRNA profile of patients with advanced fibrosis. Finally, we used an elastic net ordinal logistic model to develop a classifier that predicts clinically significant fibrosis (F2-F4). In an independent cohort, the cf-mRNA classifier was able to identify 50% of patients with at least 90% probability of clinically significant fibrosis. We demonstrate a novel and robust cf-mRNA-based RNA-Seq platform for noninvasive identification of diverse hepatic molecular disruptions and for fibrosis staging with promising potential for clinical trials and clinical practice.NEW & NOTEWORTHY This work is the first study, to our knowledge, to utilize circulating cell-free mRNA sequencing to develop an NAFLD diagnostic classifier.

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.