Placental genomic and epigenomic signatures associated with infant birth weight highlight mechanisms involved in collagen and growth factor signaling

Epigenetic Responses to Nonchemical Stressors: Potential Molecular Links to Perinatal Health Outcomes

PURPOSE OF REVIEW

We summarize the recent literature investigating exposure to four nonchemical stressors (financial stress, racism, psychosocial stress, and trauma) and DNA methylation, miRNA expression, and mRNA expression. We also highlight the relationships between these epigenetic changes and six critical perinatal outcomes (preterm birth, low birth weight, preeclampsia, gestational diabetes, childhood allergic disease, and childhood neurocognition).

RECENT FINDINGS

Multiple studies have found financial stress, psychosocial stress, and trauma to be associated with DNA methylation and/or miRNA and mRNA expression. Fewer studies have investigated the effects of racism. The majority of studies assessed epigenetic or genomic changes in maternal blood, cord blood, or placenta. Several studies included multi-OMIC assessments in which DNA methylation and/or miRNA expression were associated with gene expression. There is strong evidence for the role of epigenetics in driving the health outcomes considered. A total of 22 biomarkers, including numerous HPA axis genes, were identified to be epigenetically altered by both stressors and outcomes. Epigenetic changes related to inflammation, the immune and endocrine systems, and cell growth and survival were highlighted across numerous studies. Maternal exposure to nonchemical stressors is associated with epigenetic and/or genomic changes in a tissue-specific manner among inflammatory, immune, endocrine, and cell growth-related pathways, which may act as mediating pathways to perinatal health outcomes. Future research can test the mediating role of the specific biomarkers identified as linked with both stressors and outcomes. Understanding underlying epigenetic mechanisms altered by nonchemical stressors can provide a better understanding of how chemical and nonchemical exposures interact.

A multi-omic approach identifies an autism spectrum disorder (ASD) regulatory complex of functional epimutations in placentas from children born preterm

Children born preterm are at heightened risk of neurodevelopmental impairments, including Autism Spectrum Disorder (ASD). The placenta is a key regulator of neurodevelopmental processes, though the precise underlying molecular mechanisms remain unclear. Here, we employed a multi-omic approach to identify placental transcriptomic and epigenetic modifications related to ASD diagnosis at age 10, among children born preterm. Working with the extremely low gestational age (ELGAN) cohort, we hypothesized that a pro-inflammatory placental environment would be predictive of ASD diagnosis at age 10. Placental messenger RNA (mRNA) expression, CpG methylation, and microRNA (miRNA) expression were compared among 368 ELGANs (28 children diagnosed with ASD and 340 children without ASD). A total of 111 genes displayed expression levels in the placenta that were associated with ASD. Within these ASD-associated genes is an ASD regulatory complex comprising key genes that predicted ASD case status. Genes with expression that predicted ASD case status included Ewing Sarcoma Breakpoint Region 1 (EWSR1) (OR: 6.57 (95% CI: 2.34, 23.58)) and Bromodomain Adjacent To Zinc Finger Domain 2A (BAZ2A) (OR: 0.12 (95% CI: 0.03, 0.35)). Moreover, of the 111 ASD-associated genes, nine (8.1%) displayed associations with CpG methylation levels, while 14 (12.6%) displayed associations with miRNA expression levels. Among these, LRR Binding FLII Interacting Protein 1 (LRRFIP1) was identified as being under the control of both CpG methylation and miRNAs, displaying an OR of 0.42 (95% CI: 0.17, 0.95). This gene, as well as others identified as having functional epimutations, plays a critical role in immune system regulation and inflammatory response. In summary, a multi-omic approach was used to identify functional epimutations in the placenta that are associated with the development of ASD in children born preterm, highlighting future avenues for intervention.

Metal mixtures modeling identifies birth weight-associated gene networks in the placentas of children born extremely preterm

Prenatal exposure to toxic metals is linked to numerous adverse birth and later-in-life outcomes. These outcomes are tied to disrupted biological processes in fetal-derived tissues including the placenta and umbilical cord yet the precise pathways are understudied in these target tissues. We set out to examine the relationship between metal concentrations in umbilical cord and altered gene expression networks in placental tissue. These novel relationships were investigated in a subset of the Extremely Low Gestational Age Newborn (ELGAN) cohort (n = 226). Prenatal exposure to 11 metals/metalloids was measured using inductively coupled plasma tandem-mass spectrometry (ICP-MS/MS) in cord tissue, ensuring passage through the placental barrier. RNA-sequencing was used to quantify >37,000 mRNA transcripts. Differentially expressed genes (DEGs) were identified with respect to each metal. Weighted gene co-expression analysis identified gene networks modulated by metals. Two innovative mixtures modeling techniques, namely principal components analysis and quantile-based g-computation, were employed to identify genes/gene networks associated with multi-metal exposure. Individually, lead was associated with the strongest genomic response of 191 DEGs. Joint lead and cadmium exposure was related to 657 DEGs, including DNA Methyl Transferase 1 (DNMT1). These genes were enriched for the Eukaryotic Initiation Factor 2 (EIF2) pathway. Four gene networks, each containing genes within a Nuclear Factor kappa-light-chain-enhancer of Activated B Cells (NF-kB)-mediated network, were significantly increased in average expression level in relation to increases in all metal concentrations. All four of these metal mixture-associated gene networks were negatively correlated with important predictors of neonatal health including birth weight, placenta weight, and fetal growth. Bringing together novel methodologies from epidemiological mixtures analyses and toxicogenomics, applied to a unique cohort of extremely preterm children, the present study highlighted critical genes and pathways in the placenta dysregulated by prenatal metal mixtures. These represent potential mechanisms underlying the developmental origins of metal-induced disease.

Wildfire Variable Toxicity: Identifying Biomass Smoke Exposure Groupings through Transcriptomic Similarity Scoring

The prevalence of wildfires continues to grow globally with exposures resulting in increased disease risk. Characterizing these health risks remains difficult due to the wide landscape of exposures that can result from different burn conditions and fuel types. This study tested the hypothesis that biomass smoke exposures from variable fuels and combustion conditions group together based on similar transcriptional response profiles, informing which wildfire-relevant exposures may be considered as a group for health risk evaluations. Mice (female CD-1) were exposed via oropharyngeal aspiration to equal mass biomass smoke condensates produced from flaming or smoldering burns of eucalyptus, peat, pine, pine needles, or red oak species. Lung transcriptomic signatures were used to calculate transcriptomic similarity scores across exposures, which informed exposure groupings. Exposures from flaming peat, flaming eucalyptus, and smoldering eucalyptus induced the greatest responses, with flaming peat grouping with the pro-inflammatory agent lipopolysaccharide. Smoldering red oak and smoldering peat induced the least transcriptomic response. Groupings paralleled pulmonary toxicity markers, though they were better substantiated by higher data dimensionality and resolution provided through -omic-based evaluation. Interestingly, groupings based on smoke chemistry signatures differed from transcriptomic/toxicity-based groupings. Wildfire-relevant exposure groupings yield insights into risk assessment strategies to ultimately protect public health.

Non-coding RNAs: The link between maternal malnutrition and offspring metabolism

Early life nutrition is associated with the development and metabolism in later life, which is known as the Developmental Origin of Health and Diseases (DOHaD). Epigenetics have been proposed as an important explanation for this link between early life malnutrition and long-term diseases. Non-coding RNAs (ncRNAs) may play a role in this epigenetic programming. The expression of ncRNAs (such as long non-coding RNA H19, microRNA-122, and circular RNA-SETD2) was significantly altered in specific tissues of offspring exposed to maternal malnutrition. Changes in these downstream targets of ncRNAs lead to abnormal development and metabolism. This review aims to summarize the existing knowledge on ncRNAs linking the maternal nutrition condition and offspring metabolic diseases, such as obesity, type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD).

The placenta epigenome-brain axis: placental epigenomic and transcriptomic responses that preprogram cognitive impairment

Aim: The placenta-brain axis reflects a developmental linkage where disrupted placental function is associated with impaired neurodevelopment later in life. Placental gene expression and the expression of epigenetic modifiers such as miRNAs may be tied to these impairments and are understudied. Materials & methods: The expression levels of mRNAs (n = 37,268) and their targeting miRNAs (n = 2083) were assessed within placentas collected from the ELGAN study cohort (n = 386). The ELGAN adolescents were assessed for neurocognitive function at age 10 and the association with placental mRNA/miRNAs was determined. Results: Placental mRNAs related to inflammatory and apoptotic processes are under miRNA control and associated with cognitive impairment at age 10. Conclusion: Findings highlight key placenta epigenome-brain relationships that support the developmental origins of health and disease hypothesis.

Integrative exposomic, transcriptomic, epigenomic analyses of human placental samples links understudied chemicals to preeclampsia

BACKGROUND

Environmental health research has recently undergone a dramatic shift, with ongoing technological advancements allowing for broader coverage of exposure and molecular biology signatures. Approaches to integrate such measures are still needed to increase understanding between systems-level exposure and biology.

OBJECTIVES

We address this gap by evaluating placental tissues to identify novel chemical-biological interactions associated with preeclampsia. This study tests the hypothesis that understudied chemicals are present in the human placenta and associated with preeclampsia-relevant disruptions, including overall case status (preeclamptic vs. normotensive patients) and underlying transcriptomic/epigenomic signatures.

METHODS

A non-targeted analysis based on high-resolution mass spectrometry was used to analyze placental tissues from a cohort of 35 patients with preeclampsia (n = 18) and normotensive (n = 17) pregnancies. Molecular feature data were prioritized for confirmation based on association with preeclampsia case status and confidence of chemical identification. All molecular features were evaluated for relationships to mRNA, microRNA, and CpG methylation (i.e., multi-omic) signature alterations involved in preeclampsia.

RESULTS

A total of 183 molecular features were identified with significantly differentiated abundance in placental extracts of preeclamptic patients; these features clustered into distinct chemical groupings using unsupervised methods. Of these features, 53 were identified (mapping to 40 distinct chemicals) using chemical standards, fragmentation spectra, and chemical metadata. In general, human metabolites had the largest feature intensities and strongest associations with preeclampsia-relevant multi-omic changes. Exogenous drugs were second most abundant and had fewer associations with multi-omic changes. Other exogenous chemicals (non-drugs) were least abundant and had the fewest associations with multi-omic changes.

CONCLUSIONS

These global data trends suggest that human metabolites are heavily intertwined with biological processes involved in preeclampsia etiology, while exogenous chemicals may still impact select transcriptomic/epigenomic processes. This study serves as a demonstration of merging systems exposures with systems biology to better understand chemical-disease relationships.

Wildfires and extracellular vesicles: Exosomal MicroRNAs as mediators of cross-tissue cardiopulmonary responses to biomass smoke

INTRODUCTION

Wildfires are a threat to public health world-wide that are growing in intensity and prevalence. The biological mechanisms that elicit wildfire-associated toxicity remain largely unknown. The potential involvement of cross-tissue communication via extracellular vesicles (EVs) is a new mechanism that has yet to be evaluated.

METHODS

Female CD-1 mice were exposed to smoke condensate samples collected from the following biomass burn scenarios: flaming peat; smoldering peat; flaming red oak; and smoldering red oak, representing lab-based simulations of wildfire scenarios. Lung tissue, bronchoalveolar lavage fluid (BALF) samples, peripheral blood, and heart tissues were collected 4 and 24 h post-exposure. Exosome-enriched EVs were isolated from plasma, physically characterized, and profiled for microRNA (miRNA) expression. Pathway-level responses in the lung and heart were evaluated through RNA sequencing and pathway analyses.

RESULTS

Markers of cardiopulmonary tissue injury and inflammation from BALF samples were significantly altered in response to exposures, with the greatest changes occurring from flaming biomass conditions. Plasma EV miRNAs relevant to cardiovascular disease showed exposure-induced expression alterations, including miR-150, miR-183, miR-223-3p, miR-30b, and miR-378a. Lung and heart mRNAs were identified with differential expression enriched for hypoxia and cell stress-related pathways. Flaming red oak exposure induced the greatest transcriptional response in the heart, a large portion of which were predicted as regulated by plasma EV miRNAs, including miRNAs known to regulate hypoxia-induced cardiovascular injury. Many of these miRNAs had published evidence supporting their transfer across tissues. A follow-up analysis of miR-30b showed that it was increased in expression in the heart of exposed mice in the absence of changes to its precursor molecular, pri-miR-30b, suggesting potential transfer from external sources (e.g., plasma).

DISCUSSION

This study posits a potential mechanism through which wildfire exposures induce cardiopulmonary responses, highlighting the role of circulating plasma EVs in intercellular and systems-level communication between tissues.

Exosomes and exosomal non‑coding RNAs throughout human gestation (Review)

In recent years, research on exosomes and their content has been intensive, which has revealed their important role in cell-to-cell communication, and has implicated exosomal biomolecules in a broad spectrum of physiological processes, as well as in the pathogenesis of various diseases. Pregnancy and its normal progression rely highly on the efficient communication between the mother and the fetus, mainly mediated by the placenta. Recent studies have established the placenta as an important source of circulating exosomes and have demonstrated that exosome release into the maternal circulation gradually increases during pregnancy, starting from six weeks of gestation. This orchestrates maternal-fetal crosstalk, including maternal immune tolerance and pregnancy-associated metabolic adaptations. Furthermore, an increased number of secreted exosomes, along with altered patterns of exosomal non-coding RNAs (ncRNAs), especially microRNAs and long non-coding RNAs (lncRNAs), have been observed in a number of pregnancy complications, such as gestational diabetes mellitus and preeclampsia. The early detection of exosomes and specific exosomal ncRNAs in various biological fluids during pregnancy highlights them as promising candidate biomarkers for the diagnosis, prognosis and treatment of numerous pregnancy disorders in adolescents and adults. The present review aimed to provide insight into the current knowledge regarding the potential, only partially elucidated, role of exosomes and exosomal cargo in the regulation and progression of normal pregnancy, as well as their potential dysregulation and contribution to pathological pregnancy situations.

Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research

Research in environmental health is becoming increasingly reliant upon data science and computational methods that can more efficiently extract information from complex datasets. Data science and computational methods can be leveraged to better identify relationships between exposures to stressors in the environment and human disease outcomes, representing critical information needed to protect and improve global public health. Still, there remains a critical gap surrounding the training of researchers on these in silico methods. We aimed to address this gap by developing the inTelligence And Machine lEarning (TAME) Toolkit, promoting trainee-driven data generation, management, and analysis methods to “TAME” data in environmental health studies. Training modules were developed to provide applications-driven examples of data organization and analysis methods that can be used to address environmental health questions. Target audiences for these modules include students, post-baccalaureate and post-doctorate trainees, and professionals that are interested in expanding their skillset to include recent advances in data analysis methods relevant to environmental health, toxicology, exposure science, epidemiology, and bioinformatics/cheminformatics. Modules were developed by study coauthors using annotated script and were organized into three chapters within a GitHub Bookdown site. The first chapter of modules focuses on introductory data science, which includes the following topics: setting up R/RStudio and coding in the R environment; data organization basics; finding and visualizing data trends; high-dimensional data visualizations; and Findability, Accessibility, Interoperability, and Reusability (FAIR) data management practices. The second chapter of modules incorporates chemical-biological analyses and predictive modeling, spanning the following methods: dose-response modeling; machine learning and predictive modeling; mixtures analyses; -omics analyses; toxicokinetic modeling; and read-across toxicity predictions. The last chapter of modules was organized to provide examples on environmental health database mining and integration, including chemical exposure, health outcome, and environmental justice indicators. Training modules and associated data are publicly available online (https://uncsrp.github.io/Data-Analysis-Training-Modules/). Together, this resource provides unique opportunities to obtain introductory-level training on current data analysis methods applicable to 21st century science and environmental health.

The Placental Epigenome as a Molecular Link Between Prenatal Exposures and Fetal Health Outcomes Through the DOHaD Hypothesis

Purpose of Review

The developmental origins of health and disease (DOHaD) hypothesis posits that the perinatal environment can impact fetal and later life health. The placenta is uniquely situated to assess prenatal exposures in the context of DOHaD because it is an essential ephemeral fetal organ that manages the transport of oxygen, nutrients, waste, and endocrine signals between the mother and fetus. The purpose of this review is to summarize recent studies that evaluated the DOHaD hypothesis in human placentas using epigenomics, including DNA methylation and transcriptomic studies of mRNA, lncRNA, and microRNAs.

Recent Findings

Between 2016 and 2021, 28 articles evaluated associations between prenatal exposures and placental epigenomics across broad exposure categories including maternal smoking, psychosocial stressors, chemicals, air pollution, and metals. Sixteen of these studies connected exposures to health outcome such as birth weight, fetal growth, or infant neurobehavior through mediation analysis, identification of shared associations between exposure and outcome, or network analysis. These aspects of infant and childhood health serve as a foundation for future studies that aim to use placental epigenetics to understand relationships between the prenatal environment and perinatal complications (such as preterm birth or fetal growth restriction) or later life childhood health.

Summary

Placental DNA methylation and RNA expression have been linked to numerous prenatal exposures, such as PM2.5 air pollution, metals, and maternal smoking, as well as infant and childhood health outcomes, including fetal growth and birth weight. Placental epigenomics provides a unique opportunity to expand the DOHaD premise, particularly if research applies novel methodologies such as multi-omics analysis, sequencing of non-coding RNAs, mixtures analysis, and assessment of health outcomes beyond early childhood.

Comparing the Predictivity of Human Placental Gene, microRNA, and CpG Methylation Signatures in Relation to Perinatal Outcomes

Molecular signatures are being increasingly integrated into predictive biology applications. However, there are limited studies comparing the overall predictivity of transcriptomic vs. epigenomic signatures in relation to perinatal outcomes. This study set out to evaluate mRNA and microRNA (miRNA) expression and cytosine-guanine dinucleotide (CpG) methylation signatures in human placental tissues and relate these to perinatal outcomes known to influence maternal/fetal health; namely, birth weight, placenta weight, placental damage, and placental inflammation. The following hypotheses were tested: (1) different molecular signatures will demonstrate varying levels of predictivity towards perinatal outcomes, and (2) these signatures will show disruptions from an example exposure (i.e., cadmium) known to elicit perinatal toxicity. Multi-omic placental profiles from 390 infants in the Extremely Low Gestational Age Newborns cohort were used to develop molecular signatures that predict each perinatal outcome. Epigenomic signatures (i.e., miRNA and CpG methylation) consistently demonstrated the highest levels of predictivity, with model performance metrics including R^2 (predicted vs. observed) values of 0.36-0.57 for continuous outcomes and balanced accuracy values of 0.49-0.77 for categorical outcomes. Top-ranking predictors included miRNAs involved in injury and inflammation. To demonstrate the utility of these predictive signatures in screening of potentially harmful exogenous insults, top-ranking miRNA predictors were analyzed in a separate pregnancy cohort and related to cadmium. Key predictive miRNAs demonstrated altered expression in association with cadmium exposure, including miR-210, known to impact placental cell growth, blood vessel development, and fetal weight. These findings inform future predictive biology applications, where additional benefit will be gained by including epigenetic markers.

Peroxisome Proliferator-Activated Receptors (PPAR), fatty acids and microRNAs: Implications in women delivering low birth weight babies

Low birth weight (LBW) babies are associated with neonatal morbidity and mortality and are at increased risk for noncommunicable diseases (NCDs) in later life. However, the molecular determinants of LBW are not well understood. Placental insufficiency/dysfunction is the most frequent etiology for fetal growth restriction resulting in LBW and placental epigenetic processes are suggested to be important regulators of pregnancy outcome. Early life exposures like altered maternal nutrition may have long-lasting effects on the health of the offspring via epigenetic mechanisms like DNA methylation and microRNA (miRNA) regulation. miRNAs have been recognized as major regulators of gene expression and are known to play an important role in placental development. Angiogenesis in the placenta is known to be regulated by transcription factor peroxisome proliferator-activated receptor (PPAR) which is activated by ligands such as long-chain-polyunsaturated fatty acids (LCPUFA). In vitro studies in different cell types indicate that fatty acids can influence epigenetic mechanisms like miRNA regulation. We hypothesize that maternal fatty acid status may influence the miRNA regulation of PPAR genes in the placenta in women delivering LBW babies. This review provides an overview of miRNAs and their regulation of PPAR gene in the placenta of women delivering LBW babies.Abbreviations: AA - Arachidonic Acid; Ago2 - Argonaute2; ALA - Alpha-Linolenic Acid; ANGPTL4 - Angiopoietin-Like Protein 4; C14MC - Chromosome 14 miRNA Cluster; C19MC - Chromosome 19 miRNA Cluster; CLA - Conjugated Linoleic Acid; CSE - Cystathionine γ-Lyase; DHA - Docosahexaenoic Acid; EFA - Essential Fatty Acids; E2F3 - E2F transcription factor 3; EPA - Eicosapentaenoic Acid; FGFR1 - Fibroblast Growth Factor Receptor 1; GDM - Gestational Diabetes Mellitus; hADMSCs - Human Adipose Tissue-Derived Mesenchymal Stem Cells; hBMSCs - Human Bone Marrow Mesenchymal Stem Cells; HBV - Hepatitis B Virus; HCC - Hepatocellular Carcinoma; HCPT - Hydroxycamptothecin; HFD - High-Fat Diet; Hmads - Human Multipotent Adipose-Derived Stem; HSCS - Human Hepatic Stellate Cells; IUGR - Intrauterine Growth Restriction; LA - Linoleic Acid; LBW - Low Birth Weight; LCPUFA - Long-Chain Polyunsaturated Fatty Acids; MEK1 - Mitogen-Activated Protein Kinase 1; MiRNA - MicroRNA; mTOR - Mammalian Target of Rapamycin; NCDs - NonCommunicable Diseases; OA - Oleic Acid; PASMC - Pulmonary Artery Smooth Muscle Cell; PLAG1 - Pleiomorphic Adenoma Gene 1; PPAR - Peroxisome Proliferator-Activated Receptor; PPARα - PPAR alpha; PPARγ - PPAR gamma; PPARδ - PPAR delta; pre-miRNA - precursor miRNA; RISC - RNA-Induced Silencing Complex; ROS - Reactive Oxygen Species; SAT - Subcutaneous Adipose Tissue; WHO - World Health Organization.

Noncoding RNAs: Regulatory Molecules of Host-Microbiome Crosstalk

Recent emerging evidence has revealed that regulatory noncoding RNAs (microRNAs, circular RNAs) modulate host-microbe interactions and they have been proposed as potential biomarkers of the host's response to microbiome-linked pathologies such as cancers, obesity, and neurodegenerative diseases. Interactions between microRNAs and circular RNAs, however, increase the complexity of the mechanisms that modulate host-microbe interactions. Current knowledge on these noncoding RNAs (ncRNAs) is mainly generated from well controlled germ-free or knockout (small) animal models. Application of such knowledge to effective modulation outcomes in humans (and livestock) is challenging due to the complex nature of microbiome-linked pathologies in larger outbred animals that constantly interact with the changing environment. This review critically discusses the findings of regulatory noncoding RNAs and their roles in microbiome-linked pathologies in small and large animals and provides insights on their roles as potential therapeutic agents to improve human (and livestock) health.

Developmental and Early Life Origins of Cardiometabolic Risk Factors: Novel Findings and Implications

The intent of this review is to critically consider the data that support the concept of programming and its implications. Birth weight and growth trajectories during childhood are associated with cardiometabolic disease in adult life. Both extremes, low and high birth weight coupled with postnatal growth increase the early presence of cardiometabolic risk factors and vascular imprinting, crucial elements of this framework. Data coming from epigenetics, proteomics, metabolomics, and microbiota added relevant information and contribute to better understanding of mechanisms as well as development of biomarkers helping to move forward to take actions. Research has reached a stage in which sufficiently robust data calls for new initiatives focused on early life. Prevention starting early in life is likely to have a very large impact on reducing disease incidence and its associated effects at the personal, economic, and social levels.

Placental programming, perinatal inflammation, and neurodevelopment impairment among those born extremely preterm

Individuals born extremely preterm are at significant risk for impaired neurodevelopment. After discharge from the neonatal intensive care, associations between the child's well-being and factors in the home and social environment become increasingly apparent. Mothers' prenatal health and socioeconomic status are associated with neurodevelopmental outcomes, and emotional and behavioral problems. Research on early life risk factors and on mechanisms underlying inter-individual differences in neurodevelopment later in life can inform the design of personalized approaches to prevention. Here, we review early life predictors of inter-individual differences in later life neurodevelopment among those born extremely preterm. Among biological mechanisms that mediate relationships between early life predictors and later neurodevelopmental outcomes, we highlight evidence for disrupted placental processes and regulated at least in part via epigenetic mechanisms, as well as perinatal inflammation. In relation to these mechanisms, we focus on four prenatal antecedents of impaired neurodevelopment, namely, (1) fetal growth restriction, (2) maternal obesity, (3) placental microorganisms, and (4) socioeconomic adversity. In the future, this knowledge may inform efforts to detect and prevent adverse outcomes in infants born extremely preterm. IMPACT: This review highlights early life risk factors and mechanisms underlying inter-individual differences in neurodevelopment later in life. The review emphasizes research on early life risk factors (fetal growth restriction, maternal obesity, placental microorganisms, and socioeconomic adversity) and on mechanisms (disrupted placental processes and perinatal inflammation) underlying inter-individual differences in neurodevelopment later in life. The findings highlighted here may inform efforts to detect and prevent adverse outcomes in infants born extremely preterm.