RNA-binding proteins (RBPs) can form complex regulatory networks by binding to numerous transcripts, thereby exerting precise control over post-transcriptional gene regulation. Defects in their functions contribute to numerous human skeletal disorders by modifying RNA processing and regulation. Advancements in comprehending the molecular mechanisms of RBP functions are facilitating the development of effective therapies. Here, we delineated RBPs involved in bone development and skeletal disorders, highlighting recent advancements in this evolving field, focusing on mechanisms and therapeutic implications.

Precise diagnosis of complex diseases increasingly depends on the integration of multimodal data. However, the high dimensionality of such data makes it difficult for traditional modeling methods to efficiently identify biomarkers, while deep learning approaches, despite their strong predictive power, often lack interpretability. Here, we introduce BPX-Net, a generalizable deep learning framework that learns compact multimodal representations through a biomarker-preserving dropout mechanism, where dropout probabilities are modulated by feature importance scores self-learned from a built-in interpretability module and, when available, further informed by clinical priors. This design enables BPX-Net to make robust predictions during inference by selectively attending to a sparse set of disease-informative predictors, making it insensitive to missing values in less relevant or redundant variables. Across multi-center cohorts covering diverse clinical tasks (disease diagnosis, prognosis, treatment response prediction, and risk stratification), BPX-Net yields substantial performance gains, e.g. achieving an average AUC of 85.43% across four tasks, outperforming baselines by 4% to 20% in the presence of missing data. More importantly, it identifies predictors aligned with established clinical knowledge. Cross-hospital validation further confirms the robustness and clinical relevance of these predictors. Collectively, BPX-Net offers a clinically grounded deep learning framework for multimodal analysis, intrinsically robust to data incompleteness and equipped with built-in interpretability, thereby eliminating reliance on computationally intensive post-hoc tools such as SHAP.

The comprehensive spatiotemporal atlas of gene expression during early human embryonic development is critical for insights into embryogenesis1, organogenesis2 and disease origins3,4. Here, leveraging Stereo-seq technology, we generated spatial transcriptomic profiles across 77 sagittal sections of 13 whole-human embryos ranging from Carnegie stage 12 to 23, integrated with single-nucleus RNA sequencing to elucidate gene expression patterns within defined cellular contexts, revealing the cellular heterogeneity that drives organ-specific differentiation. Our study has established a regulatory profile for the development of 50 organs and 198 substructures, and identified potential tissue-identity regulators. Of note, it uncovered previously uncharacterized gene functions in cardiac and brain development. The atlas not only substantiates and refines the current understanding of human organ development but also highlights key organs susceptible to genetic disorders. Furthermore, we characterized the allelic gene expression within specific organs at different developmental stages. This work presents a comprehensive compilation of genome-wide gene expression profiles for each spatially defined cell population, which can be visualized as a spatial display of the embryonic transcriptional landscape. These results offer the most thorough delineation to data of the spatiotemporal transcriptomic dynamics of human organogenesis.

Mitochondrial function and its regulation within the placenta are critical for maintaining a healthy pregnancy. This study investigated the role of G-protein signaling 12 (RGS12) in placental mitochondrial function and pregnancy outcomes. RGS12 was found to be localized within the mitochondria of placental trophoblast cells. RGS12 knockdown in human placental cells resulted in decreased mitochondrial abundance, impaired oxidative phosphorylation, and reduced antioxidant capacity. Mechanistically, RGS12 enhanced the function of ATP5B, a key mitochondrial enzyme, by promoting its tyrosine phosphorylation. In a mouse model, placental RGS12 deficiency led to reduced tolerance to preterm birth (PTB) challenge, decreased fetal weight, and trophoblast cell death. These adverse effects were associated with diminished ATP synthase activity and activation of the p38MAPK signaling pathway, while restoring RGS12 expression improved the phenotype of mitochondrial dysfunction in placental trophoblast cells. Furthermore, reduced RGS12 expression and impaired mitochondrial function were observed in placentas from cases experiencing PTB. Collectively, these findings provide hitherto undocumented evidence of a specific molecular mechanism by which placental mitochondrial dysfunction contributes to adverse pregnancy outcomes. Our study suggests that RGS12 may represent a novel therapeutic target for improving pregnancy outcomes through its role in regulating placental mitochondrial function.

Preeclampsia (PE) is a pregnancy-specific hypertensive disorder that could lead to serious maternal and fetal complications, yet early identification of women at risk remains challenging because reliable biomarkers are limited. Here we show that generating relatively stable cell-free DNA (cfDNA) fragmentomic metrics, including transcription start site (TSS) coverage, TSS score, and Gini coefficient, required 600 million whole-genome sequencing reads of plasma cfDNA. These metrics exhibited observable differences among genes with varying expression levels in blood cells and placental tissues. In a cohort of 1,058 pregnant women, cfDNA fragmentomics could distinguish pregnancies that subsequently developed PE. When integrated with maternal risk factors, predictive models in two independent test sets achieved mean area under the curves of 0.903 and 0.850 for early-onset and late-onset PE, respectively, with sensitivities of 0.731 and 0.607 at a 10% false positive rate. Importantly, these models also performed well in samples collected before or at 16 weeks of gestation, supporting the potential of cfDNA fragmentomics in early PE risk assessment.

OBJECTIVE:To investigate the current status of clinical genetics specialization development and the diagnostic and therapeutic capabilities for hereditary diseases across medical institutions in Shanghai, and to assess the necessity and feasibility of establishing training bases for clinical genetics specialists. METHODS:By employing a cross-sectional survey design, the Clinical Genetics Committee of Shanghai Medical Association has conducted questionnaire surveys from March to April 2025 across 54 healthcare institutions in Shanghai (including 33 tertiary hospitals and 21 secondary hospitals). The survey involved administrative departments and medical personnel from 15 clinical specialties. The survey has covered current genetic disease diagnosis and treatment practices, relevant and specialised disease types, genetic department establishment, testing capabilities, personnel teams, and training requirements. RESULTS:The results revealed that 78.0% of clinical departments surveyed had treated patients with hereditary disorders. Shanghai possesses diagnostic and therapeutic expertise for over 95% of hereditary diseases listed in its rare disease catalogue, reflecting both the practical clinical demand for such conditions and the city's overall diagnostic and therapeutic strengths in this field. Nevertheless, significant disparities exist in the development of genetics departments across different tiers of healthcare institutions. Resources for genetic testing capabilities (including molecular, cellular, and biochemical testing) are also unevenly distributed across different tiers of hospitals. The survey further revealed that only 26.0% of departments believe that their current physician structure fully meets the diagnostic and treatment demands. Over 90% of departments consider standard training for clinical genetic specialists necessary, with 74.0% expressing willingness to participate in establishing training bases. Based on above findings and thorough deliberation, the Clinical Genetics Committee of the Shanghai Medical Association proposes advancing specialist training and discipline development through establishing a standard training system. The committee has drafted a three-year training protocol featuring a "joint training"-centered model, recommending a pilot-first, dynamically optimized strategy for steadily advancing training base development. CONCLUSION:Shanghai faces substantial demand for genetic disease diagnosis and treatment, yet exhibits shortcomings in clinical genetics specialization development, resource allocation, and talent pipeline cultivation. To establish a standard training system holds significant practical importance and is underpinned by a broad demand.

Pregnancy loss is an increasingly serious global health concern driven by complex genetic and environmental interactions. Phthalates, a common class of endocrine-disrupting chemicals, have been implicated in adverse reproductive outcomes, yet their role in pregnancy loss remains unclear. In this study, we adopted a multidisciplinary approach integrating epidemiological analysis, bioinformatics, and animal experiments to investigate the association between phthalate exposure and pregnancy loss. Analysis of 1445 women from NHANES data showed that higher mono(carboxynonyl) phthalate (MCNP) concentrations were associated with increased odds of pregnancy loss (OR3rd=1.43, 95% CI: 1.10-1.86; P-trend = 0.007) and recurrent pregnancy loss (OR3rd=1.50, 95% CI: 1.08-2.10; P-trend = 0.008). In mixture modeling, overall phthalate exposure was linked to greater likelihood of pregnancy loss, with MCNP contributing substantially. Exploratory mediation analysis indicated that bilirubin, interpreted as a potential intermediary biomarker, accounted for a modest proportion of the statistical association. Integration of toxicological databases with placental transcriptomic data from recurrent pregnancy loss cases highlighted oxidative stress and inflammation-related pathways. In a mouse model, maternal oral exposure to DiDP, a parent compound associated with MCNP formation, was associated with increased fetal resorption and altered placental structure and signaling responses, including changes in PI3K-Akt-mTOR-related markers. Collectively, our findings suggest that phthalate exposure, particularly higher MCNP levels, is associated with pregnancy loss and that systemic metabolic and placental responses may contribute to this association. These results underscore the importance of reducing phthalate exposure among women of reproductive age.

Genomic sequencing can identify nucleotide changes for underlying monogenic disorders, making it a promising newborn screening method for enabling early intervention and reducing false positives. Here, in this prospective study, we enrolled 9,992 newborns from the West Coast New District of Qingdao, China, within 3 days after birth; positive cases were followed until 31 March 2025 to assess the effectiveness of whole-genome sequencing (WGS) in neonatal screening. Among 9,992 newborns screened by WGS, 268 (2.7%) were positive. By the date of follow-up, 19 were clinically confirmed (11 hearing loss, 3 glucose-6-phosphate dehydrogenase deficiency, 2 Wilson disease, 2 phenylketonuria and 1 methylmalonic aciduria), of which 8 were missed by traditional screening. Among 19 symptomatic infants who underwent reanalysis, 8 (42.1%) were diagnosed with potentially pathogenic or pathogenic variants associated with the phenotype. Our findings indicate that integrating WGS into routine newborn screening could substantially improve early detection of monogenic diseases and enhance clinical outcomes in China. In a prospective cohort study of 9,992 newborns in Qingdao, China, whole-genome sequencing (WGS) identified 268 screen-positive cases and clinically confirmed 19 disorders, 8 of which were missed by traditional newborn screening. These findings highlight that WGS can detect monogenic conditions more effectively than standard methods and could improve early diagnosis in routine neonatal screening.

In recent years, the incidence of gestational diabetes mellitus (GDM) has been steadily increasing, posing risks to the long-term health of both mother and child. We aim to characterize blood glucose levels of pregnant women and predict the risk of GDM during early pregnancy through plasma cell-free mRNA and non-coding RNA (cfRNA). Here, we collected plasma samples from 108 pregnant women (54 with GDM and 54 controls) at around 16 weeks of gestation. Following high-throughput sequencing, we performed differentially abundant genes analysis and evaluated correlations between cfRNA profiles and blood glucose levels. Based on these findings, we developed a predictive model utilizing cf-mRNA and cf-lncRNA signatures. We found that ribosomal genes (RPL/RPS) are decreased in GDM, negatively correlated with 1hGlu and 2hGlu, and enriched in protein synthesis metabolic pathways. Additionally, placental-derived cfRNA contributed less to plasma in GDM, with placental-specific gene IGF2 significantly negatively correlated with blood glucose. Furthermore, 35 blood glucose correlated-cfRNA genes accurately predict GDM, with area under the curve of 0.84 in internal testing and 0.73 in external validation cohort. Our study reveals significant alterations in protein metabolic pathways and placenta-derived RNAs in plasma cfRNA prior to GDM diagnosis.

Background and Objective: Accurate instance segmentation of clustered cells in microscopy images remains a major bottleneck, as traditional methods often break down when objects of varying sizes and shapes touch or overlap. We introduce A2B-IS, a novel one-stage framework that represents each cell with a pixel-level mask and a rotated bounding box, specifically designed to improve segmentation quality in densely packed regions. Methods: A2B-IS decouples mask and box prediction into parallel branches to simplify the pipeline and reduce error propagation. We incorporate a Gaussian skeleton map that (1) guides anchor placement to focus computations on likely cell centers and suppress background noise, and (2) corrects box predictions near instance boundaries to prevent merged or fragmented detections. To enrich feature representations, we embed an Atrous Attention Block that captures fine-grained, multiscale details at high resolution. Finally, a semi-supervised learning strategy leverages unlabeled images alongside annotated data to further boost model robustness and generalization. The code and dataset are available at https://github.com/wangjuncongyu/A2B-Net. Results: On two large-scale cell microscopy datasets, A2B-IS consistently outperformed leading one- and two-stage segmentation approaches. Compared to baseline models, it achieved higher average precision and recall, with particularly strong gains in densely clustered regions and for small or irregularly shaped cells. Conclusions: By combining pixel-level masks, rotated boxes, skeleton-guided anchors, attention-based feature extraction, and semi-supervised training, A2B-IS delivers substantial improvements in challenging microscopy segmentation tasks. This advance paves the way for more reliable automated analysis of cell populations without extensive per-image calibration.

Gestational diabetes mellitus (GDM) remains a prevalent and heterogeneous pregnancy complication with limited strategies for early identification. We aimed to investigate efficient approaches for early prediction of GDM with clinical and genetic risk factors. A previously developed machine-learning model based on clinical characteristics achieved an area under the curve (AUC) of 0.77. To improve predictive accuracy, we further collected non-invasive prenatal testing (NIPT) results from 595 pregnant women (295 with GDM, 300 without). A cumulative polygenic risk score (PRS) was calculated using 1,170 selected single nucleotide variants (SNVs). Logistic regression, support vector machines, random forest, decision tree, linear model and naïve Bayes machine learning models were employed. External validation was performed with an additional 2,350 blood samples independently collected from two other centers. Logistic regression analysis showed that the PRS alone achieved an AUC of 0.75 for GDM discrimination. From cell-free DNA (cfDNA) sequencing performed during NIPT, we identified 357 gene transcripts with differential coverage at transcription start sites. A cfDNA-based linear model achieved an AUC of 0.83 using a subset of 166 signature genes, which reached 0.85 when combined with clinical features. Integration of clinical features, cfDNA, and SNVs yielded the highest performance using a random forest model (AUC = 0.89, specificity = 0.74, sensitivity = 0.89). For external validation, a clinically practical model incorporating clinical features and cfDNA achieved an AUC of 0.83 using linear approach. Our GDM prediction model has reached high accuracy fully using accessible clinical and genetic data routinely generated from current antenatal testing, enabling early screening and interventions for women at risk.

Currently, the American College of Medical Genetics and Genomics (ACMG) carrier screening (CS) guidelines do not recommend routinely screening for conditions with carrier frequencies ≤ 1:200. Advances in DNA sequencing and declining costs, alongside growing awareness, make it increasingly feasible to expand CS to cover a broader spectrum of conditions. We aimed to design a CS panel regardless of carrier frequency to evaluate its utility in less common disease. We developed a large CS panel through gene curation, phenotypic severity evaluation, independent of carrier frequency. A cohort of 2010 couples across 24 Chinese cities underwent couple-based simultaneous screening. Gene carrier rate (GCR) was calculated, with subsequent assessment of at-risk couple rate (ACR) across varying GCR thresholds. The results obtained from testing 1736 genes were presented. Among 2010 couples undergoing CS, 106 were identified as having an increased risk of offspring with at least one genetic condition. The initial ACR is 5.3

The Zinc Finger X-Linked Duplicate B (ZXDB) gene is one of a pair of replicated zinc finger genes on chromosome Xp11.21. The homologous gene of ZXDB in mice is Zxdb. Recent studies have found that Zxdb plays a role in the spermatogenic process of mice; however, its impact on the female reproductive system has not yet been explored. In our study, we found, for the first time, that the loss of function of Zxdb leads to reduced decidualization rates and a decrease in litter size in female mice. Secondly, we found that maternal loss of Zxdb is the determinant of these phenotypes. Thirdly, the transcriptional and proteomic differential expression genes in the uterine tissues of wild-type (WT) and Zxdb knockout (Zxdb-KO) mice were significantly enriched in signaling pathways such as adhesion molecules. Finally, we demonstrated that the disorder of expression and uneven distribution of adhesion molecules in mouse uterine tissue may be the main reason for the decline in embryo implantation rate. In conclusion, we have established for the first time a link between the Zxdb gene and reduced female fertility. This study will help provide guidance and genetic counseling for future common clinical complications such as Recurrent Spontaneous Abortion (RSA) or Recurrent Implantation Failure (RIF).

Background/Objectives: Non-invasive prenatal testing (NIPT) for fetal aneuploidy requires accurate trisomy detection together with reliable fetal fraction assessment. This study evaluated the clinical feasibility of a 106-plex digital PCR (dPCR) NIPT assay for trisomies 13, 18, and 21 with internal fetal fraction quantification. Methods: We consecutively recruited 470 women with high-risk singleton pregnancies. Fetal trisomies were detected using dPCR-NIPT and confirmed by invasive prenatal diagnosis. Pregnancies with negative prenatal diagnostic results were followed to birth. Analytical performance and quality control were assessed using trisomic DNA. The euploid cut-off and diagnostic performance were evaluated in two independent maternal plasma sample sets, using invasive diagnosis and clinical outcome as the reference standard. Results: dPCR-NIPT measured fetal fraction irrespective of fetal sex and detected trisomies at fetal fractions ≥3% using 5 ng DNA. A total of 12 of 470 plasma samples failed cell-free DNA quality control and were excluded before dPCR testing. Of the remaining 458 samples, 5 had fetal fractions below 3% and were classified as failed tests, yielding a nonreportable rate of 1.1%. Using a cut-off of 6.9 established in 103 training samples, no false-positive or false-negative trisomy calls were observed in the 350-sample testing set, corresponding to 100% sensitivity (95% confidence interval [CI], 85.18–100%) and 100% specificity (95% CI, 98.88–100%) for 23 confirmed trisomies. Conclusions: This proof-of-principle study supports the feasibility of fetal fraction-informed dPCR-NIPT for trisomy detection in high-risk singleton pregnancies. Larger prospective studies in average-risk and earlier-gestation populations are required.

To investigate whether the noninvasive preimplantation genetic testing (niPGT) complement conventional preimplantation genetic testing (PGT) in the embryos for aneuploidy. 40 spent culture medium (SCM) samples from routine embryo culture were collected, and half of each SCM (10 µL) sample was used for whole genome amplification, while the other half was stored at -80 °C for 3–6 months. Thirty-six out of 40 fresh SCM samples were successfully amplified and sequenced. Thirty-six paired frozen-thawed SCM samples showed 100

Objective: To analyze the prenatal diagnostic results in families with de novo monogenic diseases and the mutation origins in affected children from families with reproductive history of children with recurrent de novo mutations (DNMs). Methods: This study was a cross-sectional study. A total of 41 cases with adverse pregnancy history of de novo monogenic diseases who underwent genetic counseling and prenatal diagnosis from January 2021 to December 2023 at the Obstetrics and Gynecology Hospital of Fudan University were included. Prenatal diagnosis and other clinical data were reviewed, and peripheral blood of the parents, peripheral blood or tissue of the probands, and amniotic fluid or chorionic villus were collected. For families with reproductive history of children with recurrent DNMs, additional saliva and semen were collected from all the parents. Targeted high-throughput sequencing was performed to assess parental somatic mosaicism and male germline mosaicism. As for the cases in which the mutation was undetected in the semen, Sanger sequencing was utilized to search for single nucleotide polymorphism (SNP) sites upstream and downstream of the mutation site and clarify the mutation origins in combination with TA cloning. Results: A total of 41 families were included, with male age of (34.1±3.9) years (41 cases) and female age of (33.0±3.9) years (41 cases). Moreover, 32 causative genes were involved, with neurodevelopmental disorders, hereditary myopathies, hereditary bone diseases, hereditary ophthalmopathies, hereditary cardiovascular diseases and other multisystem diseases accounting for 53.7% (22/41), 12.2% (5/41), 7.3% (3/41), 4.9% (2/41), 2.4% (1/41), and 19.5% (8/41), respectively. One DNMs was detected in 37 families who underwent prenatal diagnosis during the second trimester. Four families with reproductive history of children with recurrent DNMs were analyzed for the mutation origins, of which two families had a low proportion of mosaicism detected in paternal semen, with variant allele fraction (VAF) of 3.7% and 12.8%, respectively, and the origins were from the parents detected by Sanger sequencing in combination with TA cloning in another two families. Conclusions: DNMs are at risk of recurrence. The"targeted high-throughput sequencing+Sanger sequencing+TA cloning"process is conducive to identifying the parental origin of the mutation.

Increased blood pressure and triglyceride (TG) levels are linked to adverse pregnancy outcomes. Although the widespread acknowledgment that stage 2 hypertension serves as a significant predictor of preeclampsia, the prognostic significance of elevations in other blood pressure categories remains a subject of debate. Consequently, we intended to evaluate the joint influence of increased blood pressure and TG levels in the initial stages of pregnancy on preeclampsia risk and to identify a high-risk subgroup of individuals who require clinical attention. We conducted a retrospective cohort study including 78,016 individuals with singleton births at the Shanghai International Peace Maternity and Child Health Hospital (IPMCH) between January 2014 and December 2019. The study was approved by the IPMCH Institutional Review Board. Patients were classified into four groups on the basis of blood pressure readings taken during early stages of pregnancy: normotensive, elevated, stage 1 hypertension and stage 2 hypertension, stratified by TG levels (below or above the 90th percentile). Analysis using generalized additive models and logistic regression models was conducted to investigate the relationships among blood pressure, TG levels, and preeclampsia risk. Among the 78,016 patients, 2,204 (2.83

Background:The aim of the present study was to investigate whether the CGG repeat length and AGG interruption patterns on the FMR1 gene affect female fecundity. Methods:A total of 266 infertile patients and 276 fertile controls were included in the study. All participants received FMR1 testing using triplet repeat primed PCR and capillary electrophoresis. The allele with the smaller number of CGG repeats was defined as "allele 1", and the allele with the larger number of CGG repeats was defined as "allele 2". Results:The mean number of CGG repeat length at allele 2 in the secondary infertility group was higher than that in the control group (33.1 ± 6.7 vs 30.9 ± 3.3, Bonferroni corrected p=0.003). The proportion of 35-44 CGG repeat at both FMR1 alleles showed a higher trend in the secondary infertility group as compared to the control group after adjusting for age, education, smoking status, cohort and the CGG repeats of the other FMR1 allele (aOR=7.812, 95% CI 0.884-69.001; p=0.064 for allele 1; aOR=3.657, 95% CI 2.193-6.098; p<0.001 for allele 2, respectively). Lower AMH levels were associated with increased CGG repeat length at allele 1 in infertile patients (Adjusted R2 = 0.178, p=0.003) after adjusting for age, education, smoking status, infertility type and the CGG repeats of FMR1 allele 2. However, no significant correlation was found between the number of CGG repeats at allele 2 and AMH levels (Adjusted R2 = 0.150, p=0.086). Although the difference was not statistically significant, there was a higher proportion of 3 AGG interruptions at both alleles in the secondary infertility group as compared to the control group (6.1% vs 0%, p=0.146 for allele 1, 30.6% vs 11.3%, p=0.099 for allele 2). Patients with 35-44 CGG repeat length showed a higher carrier rate of 3 AGG interruptions at both alleles (p<0.001 for both). Conclusions:Overall, the high normal sized (35-44 CGG) repeat length at both FMR1 alleles may serve a promoting role in the development of secondary infertility in Asian women. In addition, the CGG repeat length at allele 1 appears to have a mild correlation with AMH levels in infertile patients.