Early-life microbiome development influences somatic growth, yet the role of maternal-to-infant microbial transmission in shaping growth trajectories remains unclear. In a prospective birth cohort of 2,090 mother–infant dyads (13,729 fecal samples, from the first trimester of pregnancy through infancy to 3 years of age), infants were classified into physiological regulation (Trajectory 1), stable (Trajectory 2), and catch-up (Trajectory 3) growth trajectories. We found growth trajectories were significantly associated with maternal microbiome composition before delivery; Bacteroides thetaiotaomicron was enriched in mothers in Trajectory 1 and in their offspring. In contrast, Bifidobacterium pseudocatenulatum exhibited a complex pattern: despite significantly lower maternal abundance and transmission in Trajectory 3, infants in Trajectory 3 displayed comparable or higher abundance by 36 months. Functionally, transmitted B. pseudocatenulatum genomes from Trajectory 3 dyads carried higher counts of glycoside hydrolase and glycosyltransferase genes, which correlated positively with bacterial abundance and offspring somatic growth. Together, we identify a compensatory colonization process in which a limited number of transmitted B. pseudocatenulatum strains with extensive carbohydrate metabolic capacity are selectively retained and amplified.

BACKGROUND:Cell-free DNA (cfDNA) is non-randomly fragmented in human body fluids. Analyzing such fragmentation patterns of cfDNA holds great promise for liquid biopsy. Whole-genome bisulfite sequencing (WGBS) is widely used for cfDNA methylation profiling. However, its applicability for studying fragmentomic characteristics remains largely unexplored. METHODS:We performed paired WGBS and whole-genome sequencing (WGS) on 66 peripheral plasma samples from 58 pregnant women. Then, we systematically compared the fragmentation patterns of cell-free nuclear DNA and mitochondrial DNA (mtDNA) sequenced from these two approaches. Additionally, we evaluated the extent of the size shortening in fetal-derived cfDNA and estimated the fetal DNA fraction in maternal plasma using both sequencing methods. RESULTS:Compared to WGS samples, WGBS samples demonstrated a significantly lower genome coverage and higher GC content in cfDNA. They also showed a significant decrease in the size of cell-free nuclear DNA, along with alterations in the end motif pattern that were specifically associated with CpG and "CC" sites. While there was a slight shift in the inferred nucleosome footprint from cfDNA coverages in WGBS samples, the cfDNA coverage patterns in CTCF and TSS regions remained highly consistent between these two sequencing methods. Both methods accurately reflected gene expression levels through their TSS coverages. Additionally, WGBS samples exhibited an increased abundance and longer length of mtDNA in plasma. Furthermore, we observed the size shortening of fetal cfDNA in plasma consistently, with a highly correlated fetal DNA fraction inferred by cfDNA coverage between WGBS and WGS samples (r = 0.996). However, the estimated fetal cfDNA fraction in WGBS samples was approximately 7 % lower than in WGS samples. CONCLUSIONS:We confirmed that WGBS can introduce artificial breakages to cfDNA, leading to altered fragmentomic patterns in both nuclear and mitochondrial DNA. However, WGBS cfDNA remains suitable for analyzing certain cfDNA fragmentomic characteristics, such as coverage in genome regulation regions and the essential characteristics of fetal DNA in maternal plasma.

Plasma cell-free DNA (cfDNA) is a promising biomarker for liquid biopsy, essential for diagnosing and monitoring diseases. Current methods for estimating tissue contributions primarily rely on methylation markers, which can damage cfDNA, limiting clinical use. While research shows cfDNA coverage near transcription start sites (TSS) of actively transcribed genes decreases due to open chromatin, a comprehensive cross-tissue atlas has been lacking. Here, we identify 2549 tissue-specific, highly expressed genes across 12 human tissues and develop the Tissue Contribution Index (TCI) to quantify tissue contributions to plasma cfDNA using TSS coverage. TCI is validated in cfDNA origin models, including pregnant women and transplant recipients, demonstrating high accuracy. We establish reference intervals using plasma cfDNA from 460 healthy individuals and explore TCI's diagnostic utility in monitoring tissue damage and predicting outcomes. This study presents a simple, cost-effective method for tissue deconvolution of cfDNA, advancing liquid biopsy for disease detection and personalized medicine.

Limited studies demonstrated the relationships between first-trimester maternal dyslipidemia and adverse pregnancy-offspring complications. This investigation aimed to probe (1) the relationships of first-trimester maternal dyslipidemia with adverse pregnancy and birth outcomes, and (2) the potential influence of first-trimester maternal lipid profiles on offspring growth trajectories. A prospective observational investigation was conducted within the structure of the Tianjin Birth Cohort, in which maternal blood samples were acquired (median at 11th gestational week) to measure lipid levels. Group-based trajectory modeling was employed to classify latent offspring growth trajectories. Poisson regression incorporating robust standard error was employed to analyze the associations of maternal dyslipidemia with adverse pregnancy-offspring complications. First-trimester maternal dyslipidemia significantly increased gestational diabetes mellitus risk after adjustment for confounders (relative risk: 1.36, 1.20–1.54), but did not link to gestational hypertension (1.13, 0.89–1.43) risk. In addition, first-trimester maternal dyslipidemia elevated preterm birth (1.24, 1.03–1.49) and large for gestational age (1.27, 1.12–1.43) risks. However, first-trimester maternal dyslipidemia showed no significant link with either small for gestational age risk (0.83, 0.67–1.03) or offspring growth trajectories from birth to 24 months (lower growth trajectory: 0.99, 0.93–1.06; higher growth trajectory: 0.97, 0.88–1.08). First-trimester maternal dyslipidemia elevated adverse pregnancy and offspring status risks, specifically maternal gestational diabetes mellitus, as well as offspring preterm birth, and large for gestational age, but did not link to maternal gestational hypertension, small for gestational age, or variations in offspring growth trajectories from birth to 24 months.

Monitoring biochemical phenotypes during pregnancy is vital for maternal and fetal health, allowing early detection and management of pregnancy-related conditions to ensure safety for both. Here, we conducted a genetic analysis of 104 pregnancy phenotypes in 20,900 Chinese women. The genome-wide association study (GWAS) identified a total of 410 trait-locus associations, with 71.71% reported previously. Among the 116 novel hits for 45 phenotypes, 83 were successfully replicated. Among them, 31 were defined as potentially pregnancy-specific associations, including creatine and HELLPAR and neutrophils and ESR1, with subsequent analysis revealing enrichments in estrogen-related pathways and female reproductive tissues. The partitioning heritability underscored the significant roles of fetal blood, embryoid bodies, and female reproductive organs in pregnancy hematology and birth outcomes. Pathway analysis confirmed the intricate interplay of hormone and immune regulation, metabolism, and cell cycle during pregnancy. This study contributes to the understanding of genetic influences on pregnancy phenotypes and their implications for maternal health.

Metabolites are key indicators of health and therapeutic targets, but their genetic underpinnings during pregnancy-a critical period for human reproduction-are largely unexplored. Using genetic data from non-invasive prenatal testing, we performed a genome-wide association study on 84 metabolites, including 37 amino acids, 24 elements, 13 hormones, and 10 vitamins, involving 34,394 pregnant Chinese women, with sample sizes ranging from 6,394 to 13,392 for specific metabolites. We identified 53 metabolite-gene associations, 23 of which are novel. Significant differences in genetic effects between pregnant and non-pregnant women were observed for 16.7%-100% of these associations, indicating gene-environment interactions. Additionally, 50.94% of genetic associations exhibited pleiotropy among metabolites and between six metabolites and eight pregnancy phenotypes. Mendelian randomization revealed potential causal relationships between seven maternal metabolites and 15 human traits and diseases. These findings provide new insights into the genetic basis of maternal plasma metabolites during pregnancy.

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.

Early prenatal diagnosis of genetic diseases allows for timely intervention or prevention of  the diseases in newborns. Conventional prenatal diagnosis of most genetic diseases relies on testing fetal DNA obtained by invasive procedures such as amniocentesis or chorionic villus sampling, which are associated with small risks of fetal loss. Maternal circulating blood contains cell-free DNA (cfDNA) from the fetal genome and can thus be used to noninvasively detect fetal genetic diseases such as chromosomal abnormalities, copy number variants, and single gene diseases. However, due to the presence of a high level of maternal cfDNA in the maternal blood stream, a relative haplotype dosage (RHDO) analysis is required to detect the mutant loci in the fetal genome when performing noninvasive prenatal diagnosis (NIPD) by massively parallel sequencing (MPS) of cfDNA. In this chapter, we describe a protocol utilizing the RHDO strategy for NIPD of any gene of interest associating with single gene diseases.

Objective To define the lipidomic profile in plasma across pregnancy, and identify lipid biomarkers for gestational diabetes mellitus (GDM) prediction in early pregnancy. Design Case-control study. Setting Tertiary referral maternity unit. Population or Sample Plasma samples from 100 GDM and 100 normal glucose tolerance (NGT) women, divided into a training set (GDM first trimester = 50, GDM second trimester = 40, NGT first trimester = 50, NGT second trimester = 50) and a validation set (GDM first trimester = 45, GDM second trimester = 34, NGT first trimester = 44, NGT second trimester = 40). Methods Plasma samples were collected in the first (11(+0) to 13(+6) weeks), second (19(+0) to 24(+6) weeks), and third trimesters (30(+0) to 34(+6) weeks), and tested by ultra-high-performance liquid chromatography coupled with electrospray ionisation-quadrupole-time of flight-mass spectrometry; The GDM prediction model was established by the machine-learning method of random forest. Main outcome measures Gestational diabetes mellitus. Results In both the GDM and NGT group, lyso-glycerophospholipids were down-regulated, whereas ceramides, sphingomyelins, cholesteryl ester, diacylglycerols (DGs) and triacylglycerols (TGs) and glucosylceramide were up-regulated across the three trimesters of pregnancy. In the training dataset, seven TGs and five DGs demonstrated good performance in the prediction of GDM in the first and second trimesters (area under the curve [AUC] = 0.96 with 95% confidence interval [CI] of 0.93-1 and AUC = 0.97 with 95% CI of 0.95-1, respectively), independent of maternal body mass index (BMI) and ethnicity. In the validation dataset, the predictive model achieved an AUC of 0.88 and 0.94 at the first and second trimesters, respectively. Conclusions Our results have proposed new lipid biomarkers for the first trimester prediction of GDM, independent of ethnicity and BMI.

阐述我国母婴出生队列特色生物样本库的建设意义和现状,基于母婴出生队列"样本类型多样、样本来源关联、研究范围广泛"特点及法律规范,从管理体系、设施设备与人员、过程控制、样本利用等角度,结合自动化和信息化手段,探讨我国母婴出生队列特色生物样本库规范化建设及管理方法,助力妊娠期高血压、糖尿病、流产、早产、出生缺陷等发病机制研究,推动母婴特色资源合作与共享.

Background: The existence of maternal malignancy may cause false-positive results or failed tests of NIPT. Though recent studies have shown multiple chromosomal aneuploidies (MCA) are associated with malignancy, there is still no effective solution to identify maternal cancer patients from pregnant women with MCA results using NIPT. We aimed to develop a new method to effectively detect maternal cancer in pregnant women with MCA results using NIPT and a random forest classifier to identify the tissue origin of common maternal cancer types.Methods: For examination, 496 participants with MCA results via NIPT were enrolled from January 2016 to June 2019 at BGI. Cancer and non-cancer participants were confirmed through the clinical follow-up. The cohort comprising 42 maternal cancer cases and 294 non-cancer cases enrolled from January 2016 to December 2017 was utilized to develop a method named mean of the top five chromosome z scores (MTOP5Zscores). The remaining 160 participants enrolled from January 2018 to June 2019 were used to validate the performance of MTOP5Zscores. We established a random forest model to classify three common cancer types using normalized Pearson correlation coefficient (NPCC) values, z scores of 22 chromosomes, and seven plasma tumor markers (PTMs) as predictor variables.Results: 62 maternal cancer cases were confirmed with breast cancer, liver cancer, and lymphoma, the most common cancer types. MTOP5Zscores showed a sensitivity of 85% (95% confidence interval (CI), 62.11-96.79%) and specificity of 80% (95% CI, 72.41-88.28%) in the detection of maternal cancer among pregnant women with MCA results. The sensitivity of the classifier was 93.33, 66.67, and 50%, while specificity was 66.67, 90, and 97.06%, and positive predictive value (PPV) was 60.87, 72.73, and 80% for the prediction of breast cancer, liver cancer, and lymphoma, respectively.Conclusion: This study presents a solution to identify maternal cancer patients from pregnant women with MCA results using NIPT, indicating it as a value-added application of NIPT in the detection of maternal malignancies in addition to screening for fetal aneuploidies with no extra cost.

We investigated whether screening by whole genome sequencing (WGS) in unselected newborns provides more information of potentially curable or treatable medical conditions than routine newborn screening (NBS). We demonstrated that compared with routine NBS, WGS produced fewer false positive results and identified more actionable pathogenic or likely pathogenic variants in the selective 246 genes. Previously, WGS has been used to identify mutated genes in newborn children with a suspected disease.1 However, sequencing of apparently healthy newborns has remained controversial due to technical concerns and ethical issues.2 In this study, 321 non-pre-selected newborns from a cohort of pregnant women in Qingdao, China were recruited (Table 1). DNA from 303 umbilical cord blood samples and 18 umbilical cords was extracted for 40X WGS. For data interpretation, we selected 251 genes associated with 59 Mendelian disorders, 164 primary immunodeficiency diseases (PIDs) and five pharmacogenetic (PGx) genes, following the guidelines by the Recommended Uniform Screening Panel (RUSP), the International Union of Immunologic Societies (IUIS) Expert Committee for Primary Immunodeficiency, the Dutch Pharmacogenetics Working Group (DPWG), and the Clinical Pharmacogenetics Implementation Consortium (CPIC).3-5 Sequencing protocol, data analysis pipeline, and criteria for sequence variants interpretation following the ACMG/AMP guidelines are described in the Supporting Information. The WGS results were compared with NBS results, including the mandatory checks of hearing impairment and four metabolic diseases, the metabolic testing of 48 inherited metabolic diseases (IMDs), and the genetic screening for 20 hearing loss loci incorporated into the local NBS program in China.6, 7 Among the analysed DNA samples of 321 newborns, the average sequencing depth was 47.42X (28.84X–82.90X) and the average coverage was 99.48% (99.01%–99.89%) (Figure 1A). For the 59 Mendelian disorders, a total of 131 pathogenic or likely pathogenic (P/LP) mutations and 5 pathogenic copy number variations were detected in 107 of the 321 newborns (33.33%), corresponding to 106 carriers of 28 diseases and 1 patient with phenylketonuria (PKU) (Figure 1B and Table 2). The 25.23% of newborns (n = 81) carried one P/LP mutations, and 7.17% and 0.93% of newborns (n = 23 and n = 3) carried two or three P/LP mutations, respectively. Hearing loss, methylmalonic acidemia (MMA), primary congenital hypothyroidism (CH), and PKU were diseases with the most carriers, while GJB2 (28/321, 8.72%), MMACHC (11/321, 3.43%), DUOX2 (10/321, 3.12%), PAH (8/321, 2.49%) and SLC26A4 (8/321, 2.49%) were the top five genes with the highest carrier frequencies of P/LP mutations (Table 2). For the 164 PIDs, 9 heterozygous P/LP variants in 6 genes were identified in 9 newborns (2.80%), all in a heterozygous state (Table 2). Four newborns were shown to carry heterozygous variant of unknown significance (VUS) in the gene SLC25A13 (c.2T>C, p.M1T), which was predicted as start loss and likely affecting the initiator methionine of the SLC25A13 mRNA. Two newborns carried a VUS in ASS1(c.-4C>T, p.?). Although these VUSs were not included in the final report to the participants, follow-up of the children with VUSs will be conducted till 3 years of age. Sanger sequencing confirmed 143 out of 145 mutations identified by WGS, resulting in an accuracy of 98.62%. Carriers of SMN1 mutations were validated by multiplex ligation-dependent probe amplification and real-time quantitative PCR, showing that five out of the six predicted carriers were true. Of the 321 newborns, 312 (97.20%) had the results of 48 IMDs screening and genetic hearing loss screening on 20 loci, which identified one newborn with PKU and one infant with increased blood level of isovalerylcarnitine (Table 1). In addition, 18 carriers harbouring 20 pathogenic mutations causing hearing impairment were detected by genetic hearting loss screening, albeit all 321 children passed the physical hearing screening at hospital (Supporting Information). The newborn WGS also identified the PKU case and 18 hearing loss carriers (Figure 2A). However, the child with increased level of isovalerylcarnitine was confirmed to be a carrier of 3-methylcrotonyl-CoA carboxylase deficiency by WGS. In addition, WGS identified two infants carrying compound heterozygous P/LP variants in GJB2 (Figure 3) and four children carrying pathogenic mutations in MT-RNR1 (c1095T > C), suggesting an increased risk of late-onset deafness or drug-induced hearing loss, respectively. Although currently non-symptomatic, the two newborns with GJB2 variants were scheduled to undergo hearing tests every 6 months, and the four newborns with the m.1095T mutation in MT-RNR1 were advised to avoid using aminoglycosides. Interestingly, we observed that 313 newborns (97.51%) carried at least one actionable PGx variant (Figure 1C). This result is in line with a European 44 000 biobank participants study, where 99.8% of the participants had a genotype associated with increased risks to at least one medication.8 Furthermore, we found three common PGx variants in the Qingdao cohort, CYP2D6*10 (48.60%), NUDT15*3 (13.08%) and UGT1A1*6 (21.18%) (Figure 2B and Table 3), that showed significant frequency differences as compared to East Asian populations (p < 0.05). An important aspect when screening for disorders in a given population is the use of a matched control database as variants can be highly specific for a given ethnic group.9 Most databases published to date are based on individuals of European descent and many populations have limited or poor representation. Limitations of the current study are the small sample size and restricted metabolic tests. A large-scale NBS effort is needed to validate our findings and fully investigate the treatable or curable medical conditions in newborns. The technical challenge of newborn WGS is to screen genes with high homology due to the misalignment of short-read sequencing. Therefore, the customized pipeline is needed to improve the accuracy and sensitivity of SNVs at genes with high-level homology. Albeit the present cost and turnaround time of WGS is several times more than the present NBS methods, in the forseeable future the pitfalls of WGS cost and turnaround time will likely facilitate the application of newborn WGS in NBS programs. In our study, selective identification of genomic data, where therapeutic options are available, did not violate the Wilson–Jungner criteria10. Our work provides a basis for future research on expanding screening genes and diseases in newborn screening program. Given adequate cost-effectiveness, WGS should be considered in future newborn screening programs. Further discussion of the interpretation accuracy and ethical use of genomic information needs to take place on a global scale. We appreciate the participation of the volunteers and their families. Without their support, this work would not have been possible. This work was also supported by the China National GeneBank (CNGB). This study was funded by the National Natural Science Foundation of China (No.31800765), the Shenzhen Municipal Government of China (JCY20170817145047361) and the Guangdong Provincial Key Laboratory of Genome Read and Write (No. 2017B030301011). The authors declare no conflict of interest. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Background: Non-invasive prenatal diagnosis (NIPD) can identify monogenic diseases early during pregnancy with negligible risk to fetus or mother, but the haplotyping methods involved sometimes cannot infer parental inheritance at heterozygous maternal or paternal loci or at loci for which haplotype or genome phasing data are missing. This study was performed to establish a method that can effectively recover the whole fetal genome using maternal plasma cell-free DNA (cfDNA) and parental genomic DNA sequencing data, and validate the method’s effectiveness in noninvasively detecting single nucleotide variations (SNVs), insertions and deletions (indels).Methods: A Bayesian model was developed to determine fetal genotypes using the plasma cfDNA and parental genomic DNA from five couples of healthy pregnancy. The Bayesian model was further integrated with a haplotype-based method to improve the inference accuracy of fetal genome and prediction outcomes of fetal genotypes. Five pregnancies with high risks of monogenic diseases were used to validate the effectiveness of this haplotype-assisted Bayesian approach for noninvasively detecting indels and pathogenic SNVs in fetus.Results: Analysis of healthy fetuses led to the following accuracies of prediction: maternal homozygous and paternal heterozygous loci, 96.2 ± 5.8%; maternal heterozygous and paternal homozygous loci, 96.2 ± 1.4%; and maternal heterozygous and paternal heterozygous loci, 87.2 ± 4.7%. The respective accuracies of predicting insertions and deletions at these types of loci were 94.6 ± 1.9%, 80.2 ± 4.3%, and 79.3 ± 3.3%. This approach detected pathogenic single nucleotide variations and deletions with an accuracy of 87.5% in five fetuses with monogenic diseases.Conclusions: This approach was more accurate than methods based only on Bayesian inference. Our method may pave the way to accurate and reliable NIPD.

Objectives To determine the temporal persistence of the residual cell-free DNA (cfDNA) of the deceased cotwin in maternal circulation after selective fetal reduction and evaluate its long persistence in noninvasive prenatal testing (NIPT). Methods Dichorionic diamniotic twins (N = 5) undergoing selective fetal reduction because of a trisomy were recruited. After informed consent, maternal blood was collected immediately before reduction and periodically after reduction until birth. The plasma cfDNA of each sample was sequenced and analyzed for fetal aneuploidy and fetal fractions. Results In all pregnancies, the fetal fraction of the cfDNA of the deceased fetus increased to peak at 7-9 weeks after fetal reduction, and subsequently decreased gradually to almost undetectable during the late third trimester. The NIPT T-scores persistently reflected the detection of fetal trisomy up to 16 (median 9.5) weeks after fetal reduction. Conclusions Residual cfDNA from the deceased cotwin after selective reduction at 14-17 gestational weeks led to the persistent generation of false-positive NIPT results for up to 16 weeks postdemise. Thus, providing NIPT for pregnancies with a cotwin demise in early second trimester is prone to misleading results and not recommended.

Introduction: The sequencing-based noninvasive prenatal testing (NIPT) has been successfully integrated into clinical practice and facilitated the early detection of fetal chromosomal anomalies. However, a comprehensive reference material to evaluate and quality control NIPT services from different NIPT providers remains unavailable. Methods: In this study, we established a set of NIPT reference material consisting of 192 simulated samples. Most of the potential factors influencing the accuracy of NIPT, such as fetal fraction, mosaicism, and interfering substances, were included in the reference material. We compared the performance of chromosomal abnormalities detection on 3 widely used sequencers (NextSeq 500, BGISEQ-500, and Ion Proton) based on the reference material. Results: All 3 sequencers provided highly accurate and reliable results to samples with ≥3.5% fetal fractions and high percentage of mosaicism. Conclusions: The established reference material can serve as a universal standard quality control for the current and new-coming NIPT providers based on various sequencers.

Preterm birth is the main cause of infant death worldwide and results in a high societal economic burden associated with newborn care. Recent studies have shown that extracellular vesicles play an important role in fetal development during pregnancy. Here, we fully investigated differences in lipids in plasma, microvesicles and exosomes between 27 preterm and 66 full-term pregnant women in the early second trimester (12-24 weeks) using an untargeted lipidomics approach. Independent of other characteristics of samples, we detected 97, 58 and 10 differential features (retention time (RT) and m/z) with identification by multivariate and univariate statistical analyses in plasma, microvesicles and exosomes, respectively. These altered lipids were involved in the formation of the bacterial cell wall and chronic low-level inflammation and oxidative stress. Furthermore, lipids in microvesicles could distinguish patients who experienced preterm labor from controls better than lipids in plasma and exosomes. The candidate lipid biomarkers in microvesicles were also validated by the pseudotargeted lipidomics method. The validation set included 41 preterm and 42 healthy pregnant women. PS (34:0) in microvesicles was able to distinguish preterm birth from healthy pregnancy with higher accuracy. Our study shows that differences in lipids in plasma, microvesicles and exosomes are useful for understanding the underlying mechanisms, early clinical diagnosis and intervention of preterm birth.

Preterm birth is the leading cause of infant death worldwide and results in a high societal economic burden associated with newborn care. Recent studies have shown that extracellular vesicles (EVs) play an important role in fetal development during pregnancy. Lipids in EVs related to preterm birth remain undefined. Here, we fully investigated differences in lipids in plasma, microvesicles (MVs), and exosomes (Exos) between 27 preterm and 66 full-term pregnant women in the early second trimester (12-24 weeks) using an untargeted lipidomics approach. Independent of other characteristics of samples, we detected 97, 58, and 10 differential features (retention time (RT) and m/z) with identification in plasma, MVs, and Exos, respectively. A panel of five lipids from MVs has an area under the receiver operating characteristic curve (AUC) of 0.87 for the prediction of preterm birth. One lipid of the panel (PS (34:0)) was validated in an additional 83 plasma samples (41 preterm and 42 full-term deliveries) by the pseudotargeted lipidomics method (AUC = 0.71). Our results provide useful information about the early prediction of preterm birth, as well as a better understanding of the underlying mechanisms and intervention of preterm birth. The MS data have been deposited in the CNSA (https://db.cngb.org/cnsa/) of CNGBdb with accession code CNP0001076.

Objectives: To determine the temporal persistence of residual cell-free DNA (cfDNA) of deceased co-twin in maternal circulation after selective fetal reduction and evaluate its long-lasting effect on noninvasive prenatal testing (NIPT) results. Design: Prospective observational study Setting: The Third Affiliated Hospital of Guangzhou Medical University Population: Dichorionic diamniotic twins (n=5) underwent selective fetal reduction of a co-twin with trisomy. Methods: With consent, maternal blood was collected immediately before reduction and periodically after reduction until birth. CfDNA of each maternal blood sample was sequenced for NIPT and analyzed for fetal trisomies and fetal fractions. Main Outcome Measured: Detectable T-scores for trisomy identification and three types of fetal fractions including the total fetal fraction, the fetal fraction of the deceased co-twin, and the fetal fraction of the surviving co-twin.

Background During human pregnancy, placental trophectoderm cells release extracellular vesicles (EVs) into maternal circulation. Trophoblasts also give rise to cell-free DNA (cfDNA) in maternal blood, and has been used for noninvasive prenatal screening for chromosomal aneuploidy. We intended to prove the existence of DNA in the EVs (evDNA) of maternal blood, and compared evDNA with plasma cfDNA in terms of genome distribution, fragment length, and the possibility of detecting genetic diseases. Methods Maternal blood from 20 euploid pregnancies, 9 T21 pregnancies, 3 T18 pregnancies, 1 T13 pregnancy, and 2 pregnancies with FGFR3 mutations were obtained. EVs were separated from maternal plasma, and confirmed by transmission electronic microscopy (TEM), western blotting, and flow cytometry (FACS). evDNA was extracted and its fetal origin was confirmed by quantitative PCR (qPCR). Pair-end (PE) whole genome sequencing was performed to characterize evDNA, and the results were compared with that of cfDNA. The fetal risk of aneuploidy and monogenic diseases was analyzed using the evDNA sequencing data. Results EVs separated from maternal plasma were confirmed with morphology by TEM, and protein markers of CD9, CD63, CD81 as well as the placental specific protein placental alkaline phosphatase (PLAP) were confirmed by western blotting or flow cytometry. EvDNA could be successfully extracted for qPCR and sequencing from the plasma EVs. Sequencing data showed that evDNA span on all 23 pairs of chromosomes and mitochondria, sharing a similar distribution pattern and higher GC content comparing with cfDNA. EvDNA showed shorter fragments yet lower fetal fraction than cfDNA. EvDNA could be used to correctly determine fetal gender, trisomies, and de novo FGFR3 mutations. Conclusions We proved that fetal DNA could be detected in EVs separated from maternal plasma. EvDNA shared some similar features to plasma cfDNA, and could potentially be used to detect genetic diseases in fetus.