Identification and prediction model of placenta-brain axis genes associated with neurodevelopmental delay in moderate and late preterm children

Machine learning model-based preterm birth prediction and clinical nomogram: A big retrospective cohort study

OBJECTIVE

This study sought to develop a multifactorial predictive model for preterm birth risk, with the goal of providing clinical practitioners with early prevention.

METHODS

This retrospective cohort study utilized 2022 and 2018 National Vital Statistics System (NVSS) birth data, with the 2022 cohort arbitrarily split into training (70%) and internal verification (30%) subsets, and the 2018 cohort for external validation. Four machine learning algorithms-logistic regression, adaptive lasso regression, bootstrap forest, and boosted trees-identified features associated with preterm birth. The study then integrated the consensus features identified across the four models to construct a logistic regression-based preterm birth prediction nomogram. To evaluate the model's efficacy, calibration, receiver operating characteristic (ROC), and decision curve analysis were applied to both the internal and external validation sets.

RESULTS

The study included 2 567 040 mother-infant pairs from the 2022 cohort and 2 688 568 mother-infant pairs from the 2018 cohort. All four machine learning models demonstrated high accuracy (area under the curve [AUC] >0.7) in predicting preterm birth, and the internal validation results indicated good model generalizability. Feature selection identified nine common risk factors associated with preterm birth. The prediction nomogram based on these nine common features achieved AUCs of 0.701, 0.702, and 0.704 in the training, internal validation, and external validation sets, respectively. The calibration curves showed good agreement, and the decision curve analysis confirmed the model's net clinical benefits.

CONCLUSION

This study developed a reliable preterm birth prediction tool using large-scale birth cohort data, filling the gap of lacking external validation for existing preterm birth prediction models.

Placental Transcriptomic Signatures of Prenatal Phthalate Exposure and Identification of Placenta-Brain Genes Associated with the Effects of Phthalate Exposure on Neurodevelopment in Children

Prenatal exposure to phthalates may affect placental function and fetal development, but the underlying mechanisms are unclear. The aim of our study was to explore the alterations in the placental transcriptome associated with prenatal phthalate exposure and to further analyze whether the placental-brain axis (PBA) genes play a mediating role in the association between prenatal phthalate exposure and children's neurodevelopment. We included 172 participants from the Ma'anshan Birth Cohort and collected data on seven phthalate metabolites in urine during pregnancy, placental tissue RNA-seq, and neurodevelopment of offspring. Bioinformatics analysis revealed that aberrant regulation of the placental transcriptome was associated with prenatal phthalate exposure. Exposure to phthalates during pregnancy was found to be associated with neurodevelopmental delay in children aged 6, 18, and 48 months using the multiple linear regression model. Meanwhile, employing mediation analysis, nine PBA genes were identified that mediate the association between exposure to phthalates during pregnancy and the neurodevelopment of children. Our study will provide a basis for potential mechanisms by which prenatal exposure to phthalates affects placental function and children's neurodevelopment.

Leveraging Random Effects in Cistrome-Wide Association Studies for Decoding the Genetic Determinants of Prostate Cancer

Cistrome-wide association studies (CWAS) are pivotal for identifying genetic determinants of diseases by correlating genetically regulated cistrome states with phenotypes. Traditional CWAS typically develops a model based on cistrome and genotype data to associate predicted cistrome states with phenotypes. The random effect cistrome-wide association study (RECWAS), reevaluates the necessity of cistrome state prediction in CWAS. RECWAS utilizes either a linear model or marginal effect for initial feature selection, followed by kernel-based feature aggregation for association testing is introduced. Through simulations and analysis of prostate cancer data, a thorough evaluation of CWAS and RECWAS is conducted. The results suggest that RECWAS offers improved power compared to traditional CWAS, identifying additional genomic regions associated with prostate cancer. CWAS identified 102 significant regions, while RECWAS found 50 additional significant regions compared to CWAS, many of which are validated. Validation encompassed a range of biological evidence, including risk signals from the GWAS catalog, susceptibility genes from the DisGeNET database, and enhancer-domain scores. RECWAS consistently demonstrated improved performance over traditional CWAS in identifying genomic regions associated with prostate cancer. These findings demonstrate the benefits of incorporating kernel methods into CWAS and provide new insights for genetic discovery in complex diseases.

Paternal aging impacts expression and epigenetic markers as early as the first embryonic tissue lineage differentiation

BACKGROUND

Advanced paternal age (APA) is associated with adverse outcomes to offspring health, including increased risk for neurodevelopmental disorders. The aim of this study was to investigate the methylome and transcriptome of the first two early embryonic tissue lineages, the inner cell mass (ICM) and the trophectoderm (TE), from human blastocysts in association with paternal age and disease risk. High quality human blastocysts were donated with patient consent from donor oocyte IVF cycles from either APA (≥ 50 years) or young fathers. Blastocysts were mechanically separated into ICM and TE lineage samples for both methylome and transcriptome analyses.

RESULTS

Significant differential methylation and transcription was observed concurrently in ICM and TE lineages of APA-derived blastocysts compared to those from young fathers. The methylome revealed significant enrichment for neuronal signaling pathways, as well as an association with neurodevelopmental disorders and imprinted genes, largely overlapping within both the ICM and TE lineages. Significant enrichment of neurodevelopmental signaling pathways was also observed for differentially expressed genes, but only in the ICM. In stark contrast, no significant signaling pathways or gene ontology terms were identified in the trophectoderm. Despite normal semen parameters in aged fathers, these significant molecular alterations can adversely contribute to downstream impacts on offspring health, in particular neurodevelopmental disorders like autism spectrum disorder and schizophrenia.

CONCLUSIONS

An increased risk for neurodevelopmental disorders is well described in children conceived by aged fathers. Using blastocysts derived from donor oocyte IVF cycles to strategically control for maternal age, our data reveals evidence of methylation dysregulation in both tissue lineages, as well as transcription dysregulation in neurodevelopmental signaling pathways associated with APA fathers. This data also reveals that embryos derived from APA fathers do not appear to be compromised for initial implantation potential with no significant pathway signaling disruption in trophectoderm transcription. Collectively, our work provides insights into the complex molecular mechanisms that occur upon paternal aging during the first lineage differentiation in the preimplantation embryo. Early expression and epigenetic markers of APA-derived preimplantation embryos highlight the susceptibility of the future fetus to adverse health outcomes.

The association between prenatal bisphenol F exposure and infant neurodevelopment: The mediating role of placental estradiol

BACKGROUND

There are limited population studies on the neurodevelopmental effects of bisphenol F (BPF), a substitute for bisphenol A. Furthermore, the role of placental estradiol as a potential mediator linking these two factors remains unclear.

OBJECTIVE

To examine the association between maternal prenatal BPF exposure and infant neurodevelopment in a prospective cohort study and to explore the mediating effects of placental estradiol between BPF exposure and neurodevelopment in a nested case-control study.

METHODS

The prospective cohort study included 1077 mother-neonate pairs from the Wuhu city cohort study in China. Maternal BPF was determined using the liquid/liquid extraction and Ultra-performance liquid chromatography tandem mass spectrometry method. Children's neurodevelopment was assessed at ages 3, 6, and 12 months using Ages and Stages Questionnaires. The nested case-control study included 150 neurodevelopmental delay cases and 150 healthy controls. Placental estradiol levels were measured using enzyme-linked immunosorbent assay kits. Generalized estimating equation models and robust Poisson regression models were used to examine the associations between BPF exposure and children's neurodevelopment. In the nested case-control study, causal mediation analysis was conducted to assess the role of placental estradiol as a mediator in multivariate models.

RESULTS

In the prospective cohort study, the pregnancy-average BPF concentration was positively associated with developmental delays in gross-motor, fine-motor, and problem-solving ( ORtotal ASQ: 1.14(1.05, 1.25), ORgross-motor: 1.22(1.10, 1.36), ORfine-motor: 1.19(1.07, 1.31), ORproblem-solving: 1.11(1.01, 1.23)). After sex-stratified analyses, pregnancy-average BPF concentration was associated with an increased risk of neurodevelopmental delays in the gross-motor (ORgross-motor:1.30(1.12, 1.51)) and fine-motor (ORfine-motor: 1.22(1.06, 1.40)) domains in boys. In the nested case-control study, placental estradiol mediated 16.6% (95%CI: 4.4%, 35.0%) of the effects of prenatal BPF exposure on developmental delay.

CONCLUSIONS

Our study supports an inverse relationship between prenatal BPF exposure and child neurodevelopment in infancy, particularly in boys. Decreased placental estradiol may be an underlying biological pathway linking prenatal BPF exposure to neurodevelopmental delay in offspring.