Maternal SARS-CoV-2 impacts fetal placental macrophage programs and placenta-derived microglial models of neurodevelopment.

BACKGROUND: The SARS-CoV-2 virus activates maternal and placental immune responses. Such activation in the setting of other infections during pregnancy is known to impact fetal brain development. The effects of maternal immune activation on neurodevelopment are mediated at least in part by fetal brain microglia. However, microglia are inaccessible for direct analysis, and there are no validated non-invasive surrogate models to evaluate in utero microglial priming and function. We have previously demonstrated shared transcriptional programs between microglia and Hofbauer cells (HBCs, or fetal placental macrophages) in mouse models. METHODS AND RESULTS: We assessed the impact of maternal SARS-CoV-2 on HBCs isolated from 24 term placentas (N = 10 SARS-CoV-2 positive cases, 14 negative controls). Using single-cell RNA-sequencing, we demonstrated that HBC subpopulations exhibit distinct cellular programs, with specific subpopulations differentially impacted by SARS-CoV-2. Assessment of differentially expressed genes implied impaired phagocytosis, a key function of both HBCs and microglia, in some subclusters. Leveraging previously validated models of microglial synaptic pruning, we showed that HBCs isolated from placentas of SARS-CoV-2 positive pregnancies can be transdifferentiated into microglia-like cells (HBC-iMGs), with impaired synaptic pruning behavior compared to HBC models from negative controls. CONCLUSION: These findings suggest that HBCs isolated at birth can be used to create personalized cellular models of offspring microglial programming.

Hofbauer cells and fetal brain microglia share transcriptional profiles and responses to maternal diet-induced obesity.

Maternal immune activation is associated with adverse offspring neurodevelopmental outcomes, many mediated by in utero microglial programming. As microglia remain inaccessible throughout development, identification of noninvasive biomarkers reflecting fetal brain microglial programming could permit screening and intervention. We used lineage tracing to demonstrate the shared ontogeny between fetal brain macrophages (microglia) and fetal placental macrophages (Hofbauer cells) in a mouse model of maternal diet-induced obesity, and single-cell RNA-seq to demonstrate shared transcriptional programs. Comparison with human datasets demonstrated conservation of placental resident macrophage signatures between mice and humans. Single-cell RNA-seq identified common alterations in fetal microglial and Hofbauer cell gene expression induced by maternal obesity, as well as sex differences in these alterations. We propose that Hofbauer cells, which are easily accessible at birth, provide insights into fetal brain microglial programs and may facilitate the early identification of offspring vulnerable to neurodevelopmental disorders.

Cell-specific imputation of drug connectivity mapping with incomplete data.

Drug repositioning allows expedited discovery of new applications for existing compounds, but re-screening vast compound libraries is often prohibitively expensive. "Connectivity mapping" is a process that links drugs to diseases by identifying compounds whose impact on expression in a collection of cells reverses the disease's impact on expression in disease-relevant tissues. The LINCS project has expanded the universe of compounds and cells for which data are available, but even with this effort, many clinically useful combinations are missing. To evaluate the possibility of repurposing drugs despite missing data, we compared collaborative filtering using either neighborhood-based or SVD imputation methods to two naive approaches via cross-validation. Methods were evaluated for their ability to predict drug connectivity despite missing data. Predictions improved when cell type was taken into account. Neighborhood collaborative filtering was the most successful method, with the best improvements in non-immortalized primary cells. We also explored which classes of compounds are most and least reliant on cell type for accurate imputation. We conclude that even for cells in which drug responses have not been fully characterized, it is possible to identify unassayed drugs that reverse in those cells the expression signatures observed in disease.

Hofbauer cells and fetal brain microglia share transcriptional profiles and responses to maternal diet-induced obesity.

Maternal immune activation is associated with adverse offspring neurodevelopmental outcomes, many mediated by in utero microglial programming. As microglia remain inaccessible throughout development, identification of noninvasive biomarkers reflecting fetal brain microglial programming could permit screening and intervention. We used lineage tracing to demonstrate the shared ontogeny between fetal brain macrophages (microglia) and fetal placental macrophages (Hofbauer cells) in a mouse model of maternal diet-induced obesity, and single-cell RNA-seq to demonstrate shared transcriptional programs. Comparison with human datasets demonstrated conservation of placental resident macrophage signatures between mice and humans. Single-cell RNA-seq identified common alterations in fetal microglial and Hofbauer cell gene expression induced by maternal obesity, as well as sex differences in these alterations. We propose that Hofbauer cells, which are easily accessible at birth, provide novel insights into fetal brain microglial programs, and may facilitate the early identification of offspring vulnerable to neurodevelopmental disorders in the setting of maternal exposures.

hnRNP L is essential for myogenic differentiation and modulates myotonic dystrophy pathologies.

INTRODUCTION: RNA-binding proteins (RBPs) play an important role in skeletal muscle development and disease by regulating RNA splicing. In myotonic dystrophy type 1 (DM1), the RBP MBNL1 (muscleblind-like) is sequestered by toxic CUG repeats, leading to missplicing of MBNL1 targets. Mounting evidence from the literature has implicated other factors in the pathogenesis of DM1. Herein we sought to evaluate the functional role of the splicing factor hnRNP L in normal and DM1 muscle cells. METHODS: Co-immunoprecipitation assays using hnRNPL and MBNL1 expression constructs and splicing profiling in normal and DM1 muscle cell lines were performed. Zebrafish morpholinos targeting hnrpl and hnrnpl2 were injected into one-cell zebrafish for developmental and muscle analysis. In human myoblasts downregulation of hnRNP L was achieved with shRNAi. Ascochlorin administration to DM1 myoblasts was performed and expression of the CUG repeats, DM1 splicing biomarkers, and hnRNP L expression levels were evaluated. RESULTS: Using DM1 patient myoblast cell lines we observed the formation of abnormal hnRNP L nuclear foci within and outside the expanded CUG repeats, suggesting a role for this factor in DM1 pathology. We showed that the antiviral and antitumorigenic isoprenoid compound ascochlorin increased MBNL1 and hnRNP L expression levels. Drug treatment of DM1 muscle cells with ascochlorin partially rescued missplicing of established early biomarkers of DM1 and improved the defective myotube formation displayed by DM1 muscle cells. DISCUSSION: Together, these studies revealed that hnRNP L can modulate DM1 pathologies and is a potential therapeutic target.

A history of opioid exposure in females increases the risk of metabolic disorders in their future male offspring.

Worldwide consumption of opioids remains at historic levels. Preclinical studies report intergenerational effects on the endogenous opioid system of future progeny following preconception morphine exposure. Given the role of endogenous opioids in energy homeostasis, such effects could impact metabolism in the next generation. Thus, we examined diet-induced modifications in F1 male progeny of morphine-exposed female rats (MORF1). When fed a high fat-sugar diet (FSD) for 6 weeks, MORF1 males display features of emerging metabolic syndrome; they consume more food, gain more weight, and develop fasting-induced hyperglycemia and hyperinsulinemia. In the hypothalamus, proteins involved in energy homeostasis are modified and RNA sequencing revealed down-regulation of genes associated with neuronal plasticity, coupled with up-regulation of genes associated with immune, inflammatory, and metabolic processes that are specific to FSD-maintained MORF1 males. Thus, limited preconception morphine exposure in female rats increases the risk of metabolic syndrome/type 2 diabetes in the next generation.

aTEMPO: Pathway-Specific Temporal Anomalies for Precision Therapeutics.

Dynamic processes are inherently important in disease, and identifying disease-related disruptions of normal dynamic processes can provide information about individual patients. We have previously characterized individuals' disease states via pathway-based anomalies in expression data, and we have identified disease-correlated disruption of predictable dynamic patterns by modeling a virtual time series in static data. Here we combine the two approaches, using an anomaly detection model and virtual time series to identify anomalous temporal processes in specific disease states. We demonstrate that this approach can informatively characterize individual patients, suggesting personalized therapeutic approaches.

Assessment of network module identification across complex diseases.

Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the 'Disease Module Identification DREAM Challenge', an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology.

Pathway centrality in protein interaction networks identifies putative functional mediating pathways in pulmonary disease.

Identification of functional pathways mediating molecular responses may lead to better understanding of disease processes and suggest new therapeutic approaches. We introduce a method to detect such mediating functions using topological properties of protein-protein interaction networks. We define the concept of pathway centrality, a measure of communication between disease genes and differentially expressed genes. Using pathway centrality, we identify mediating pathways in three pulmonary diseases (asthma; bronchopulmonary dysplasia (BPD); and chronic obstructive pulmonary disease (COPD)). We systematically evaluate the significance of all identified central pathways using genetic interactions. Mediating pathways shared by all three pulmonary disorders favor innate immune and inflammation-related processes, including toll-like receptor (TLR) signaling, PDGF- and angiotensin-regulated airway remodeling, the JAK-STAT signaling pathway, and interferon gamma. Disease-specific mediators, such as neurodevelopmental processes in BPD or adhesion molecules in COPD, are also highlighted. Some of our findings implicate pathways already in development as drug targets, while others may suggest new therapeutic approaches.

Towards a more molecular taxonomy of disease.

BACKGROUND: Disease taxonomies have been designed for many applications, but they tend not to fully incorporate the growing amount of molecular-level knowledge of disease processes, inhibiting research efforts. Understanding the degree to which we can infer disease relationships from molecular data alone may yield insights into how to ultimately construct more modern taxonomies that integrate both physiological and molecular information. RESULTS: We introduce a new technique we call Parent Promotion to infer hierarchical relationships between disease terms using disease-gene data. We compare this technique with both an established ontology inference method (CliXO) and a minimum weight spanning tree approach. Because there is no gold standard molecular disease taxonomy available, we compare our inferred hierarchies to both the Medical Subject Headings (MeSH) category C forest of diseases and to subnetworks of the Disease Ontology (DO). This comparison provides insights about the inference algorithms, choices of evaluation metrics, and the existing molecular content of various subnetworks of MeSH and the DO. Our results suggest that the Parent Promotion method performs well in most cases. Performance across MeSH trees is also correlated between inference methods. Specifically, inferred relationships are more consistent with those in smaller MeSH disease trees than larger ones, but there are some notable exceptions that may correlate with higher molecular content in MeSH. CONCLUSIONS: Our experiments provide insights about learning relationships between diseases from disease genes alone. Future work should explore the prospect of disease term discovery from molecular data and how best to integrate molecular data with anatomical and clinical knowledge. This study nonetheless suggests that disease gene information has the potential to form an important part of the foundation for future representations of the disease landscape.

Amniotic fluid transcriptomics reflects novel disease mechanisms in fetuses with myelomeningocele.

BACKGROUND: Cell-free RNA in amniotic fluid supernatant reflects developmental changes in gene expression in the living fetus, which includes genes that are specific to the central nervous system. Although it has been previously shown that central nervous system-specific transcripts are present in amniotic fluid supernatant, it is not known whether changes in the amniotic fluid supernatant transcriptome reflect the specific pathophysiologic condition of fetal central nervous system disorders. In myelomeningocele, there is open communication between the central nervous system and amniotic fluid. OBJECTIVES: The purpose of this study was to identify molecular pathophysiologic changes and novel disease mechanisms that are specific to myelomeningocele by the analysis of amniotic fluid supernatant cell-free RNA in fetuses with open myelomeningocele. STUDY DESIGN: Amniotic fluid supernatant was collected from 10 pregnant women at the time of the open myelomeningocele repair in the second trimester (24.5±1.0 weeks); 10 archived amniotic fluid supernatant from sex and gestational age-matched euploid fetuses without myelomeningocele were used as controls (20.9±0.9 weeks). Differentially regulated gene expression patterns were analyzed with the use of human genome expression arrays. RESULTS: Fetuses with myelomeningocele had 284 differentially regulated genes (176 up- and 108 down-regulated) in amniotic fluid supernatant. Known genes that were associated with myelomeningocele (PRICKLE2, GLI3, RAB23, HES1, FOLR1) and novel dysregulated genes were identified in association with neurodevelopment and neuronal regeneration (up-regulated, GAP43 and ZEB1) or axonal growth and guidance (down-regulated, ACAP1). Pathway analysis demonstrated a significant contribution of inflammation to disease and a broad influence of Wnt signaling pathways (Wnt1, Wnt5A, ITPR1). CONCLUSION: Transcriptomic analyses of living fetuses with myelomeningocele with the use of amniotic fluid supernatant cell-free RNA demonstrated differential regulation of specific genes and molecular pathways relevant to this central nervous system disorder, which resulted in a new understanding of pathophysiologic changes. The data also suggested the importance of pathways that involve secondary disease, such as inflammation, in myelomeningocele. These newly identified pathways may lead to hypotheses that can test novel therapeutic targets as adjuncts to fetal surgical repair.

Using Next-Generation Sequencing to Explore Genetics and Race in the High School Classroom.

With the development of new sequencing and bioinformatics technologies, concepts relating to personal genomics play an increasingly important role in our society. To promote interest and understanding of sequencing and bioinformatics in the high school classroom, we developed and implemented a laboratory-based teaching module called "The Genetics of Race." This module uses the topic of race to engage students with sequencing and genetics. In the experimental portion of this module, students isolate their own mitochondrial DNA using standard biotechnology techniques and collect next-generation sequencing data to determine which of their classmates are most and least genetically similar to themselves. We evaluated the efficacy of this module by administering a pretest/posttest evaluation to measure student knowledge related to sequencing and bioinformatics, and we also conducted a survey at the conclusion of the module to assess student attitudes. Upon completion of our Genetics of Race module, students demonstrated significant learning gains, with lower-performing students obtaining the highest gains, and developed more positive attitudes toward scientific research.

Personal microbiomes and next-generation sequencing for laboratory-based education.

Sequencing and bioinformatics technologies have advanced rapidly in recent years, driven largely by developments in next-generation sequencing (NGS) technology. Given the increasing importance of these advances, there is a growing need to incorporate concepts and practices relating to NGS into undergraduate and high school science curricula. We believe that direct access to sequencing and bioinformatics will improve the ability of students to understand the information obtained through these increasingly ubiquitous research tools. In this commentary, we discuss approaches and challenges for bringing NGS into the classroom based on our experiences in developing and running a microbiome project in high school and undergraduate courses. We describe strategies for maximizing student engagement through establishing personal relevance and utilizing an inquiry-based structure. Additionally, we address the practical issues of incorporating cutting edge technologies into an established curriculum. Looking forward, we anticipate that NGS educational experiments will become more commonplace as sequencing costs continue to decrease and the workflow becomes more user friendly.

Time is Money: Designing Cost-Effective Time Series Experiments.

A new theoretical model helps to evaluate the tradeoffs between running technical replicates in high-throughput experiments and sampling at more time points.

The fetal brain transcriptome and neonatal behavioral phenotype in the Ts1Cje mouse model of Down syndrome.

Human fetuses with Down syndrome demonstrate abnormal brain growth and reduced neurogenesis. Despite the prenatal onset of the phenotype, most therapeutic trials have been conducted in adults. Here, we present evidence for fetal brain molecular and neonatal behavioral alterations in the Ts1Cje mouse model of Down syndrome. Embryonic day 15.5 brain hemisphere RNA from Ts1Cje embryos (n = 5) and wild type littermates (n = 5) was processed and hybridized to mouse gene 1.0 ST arrays. Bioinformatic analyses were implemented to identify differential gene and pathway regulation during Ts1Cje fetal brain development. In separate experiments, the Fox scale, ultrasonic vocalization and homing tests were used to investigate behavioral deficits in Ts1Cje pups (n = 29) versus WT littermates (n = 64) at postnatal days 3-21. Ts1Cje fetal brains displayed more differentially regulated genes (n = 71) than adult (n = 31) when compared to their age-matched euploid brains. Ts1Cje embryonic brains showed up-regulation of cell cycle markers and down-regulation of the solute-carrier amino acid transporters. Several cellular processes were dysregulated at both stages, including apoptosis, inflammation, Jak/Stat signaling, G-protein signaling, and oxidoreductase activity. In addition, early behavioral deficits in surface righting, cliff aversion, negative geotaxis, forelimb grasp, ultrasonic vocalization, and the homing tests were observed. The Ts1Cje mouse model exhibits abnormal gene expression during fetal brain development, and significant neonatal behavioral deficits in the pre-weaning period. In combination with human studies, this suggests that the Down syndrome phenotype manifests prenatally and provides a rationale for prenatal therapy to improve perinatal brain development and postnatal neurocognition.

The pathway not taken: understanding 'omics data in the perinatal context.

OBJECTIVE: 'Omics analysis of large datasets has an increasingly important role in perinatal research, but understanding gene expression analyses in the fetal context remains a challenge. We compared the interpretation provided by a widely used systems biology resource (ingenuity pathway analysis [IPA]) with that from gene set enrichment analysis (GSEA) with functional annotation curated specifically for the fetus (Developmental FunctionaL Annotation at Tufts [DFLAT]). STUDY DESIGN: Using amniotic fluid supernatant transcriptome datasets previously produced by our group, we analyzed 3 different developmental perturbations: aneuploidy (Trisomy 21 [T21]), hemodynamic (twin-twin transfusion syndrome [TTTS]), and metabolic (maternal obesity) vs sex- and gestational age-matched control subjects. Differentially expressed probe sets were identified with the use of paired t-tests with the Benjamini-Hochberg correction for multiple testing (P < .05). Functional analyses were performed with IPA and GSEA/DFLAT. Outputs were compared for biologic relevance to the fetus. RESULTS: Compared with control subjects, there were 414 significantly dysregulated probe sets in T21 fetuses, 2226 in TTTS recipient twins, and 470 in fetuses of obese women. Each analytic output was unique but complementary. For T21, both IPA and GSEA/DFLAT identified dysregulation of brain, cardiovascular, and integumentary system development. For TTTS, both analytic tools identified dysregulation of cell growth/proliferation, immune and inflammatory signaling, brain, and cardiovascular development. For maternal obesity, both tools identified dysregulation of immune and inflammatory signaling, brain and musculoskeletal development, and cell death. GSEA/DFLAT identified substantially more dysregulated biologic functions in fetuses of obese women (1203 vs 151). For all 3 datasets, GSEA/DFLAT provided more comprehensive information about brain development. IPA consistently provided more detailed annotation about cell death. IPA produced many dysregulated terms that pertained to cancer (14 in T21, 109 in TTTS, 26 in maternal obesity); GSEA/DFLAT did not. CONCLUSION: Interpretation of the fetal amniotic fluid supernatant transcriptome depends on the analytic program, which suggests that >1 resource should be used. Within IPA, physiologic cellular proliferation in the fetus produced many "false positive" annotations that pertained to cancer, which reflects its bias toward adult diseases. This study supports the use of gene annotation resources with a developmental focus, such as DFLAT, for 'omics studies in perinatal medicine.

CSAX: Characterizing Systematic Anomalies in eXpression Data.

Methods for translating gene expression signatures into clinically relevant information have typically relied upon having many samples from patients with similar molecular phenotypes. Here, we address the question of what can be done when it is relatively easy to obtain healthy patient samples, but when abnormalities corresponding to disease states may be rare and one-of-a-kind. The associated computational challenge, anomaly detection, is a well-studied machine-learning problem. However, due to the dimensionality and variability of expression data, existing methods based on feature space analysis or individual anomalously expressed genes are insufficient. We present a novel approach, CSAX, that identifies pathways in an individual sample in which the normal expression relationships are disrupted. To evaluate our approach, we have compiled and released a compendium of public expression data sets, reformulated to create a test bed for anomaly detection. We demonstrate the accuracy of CSAX on the data sets in our compendium, compare it to other leading methods, and show that CSAX aids in both identifying anomalies and explaining their underlying biology. We describe an approach to characterizing the difficulty of specific expression anomaly detection tasks. We then illustrate CSAX's value in two developmental case studies. Confirming prior hypotheses, CSAX highlights disruption of platelet activation pathways in a neonate with retinopathy of prematurity and identifies, for the first time, dysregulated oxidative stress response in second trimester amniotic fluid of fetuses with obese mothers. Our approach provides an important step toward identification of individual disease patterns in the era of precision medicine.

Finding novel molecular connections between developmental processes and disease.

Identifying molecular connections between developmental processes and disease can lead to new hypotheses about health risks at all stages of life. Here we introduce a new approach to identifying significant connections between gene sets and disease genes, and apply it to several gene sets related to human development. To overcome the limits of incomplete and imperfect information linking genes to disease, we pool genes within disease subtrees in the MeSH taxonomy, and we demonstrate that such pooling improves the power and accuracy of our approach. Significance is assessed through permutation. We created a web-based visualization tool to facilitate multi-scale exploration of this large collection of significant connections (http://gda.cs.tufts.edu/development). High-level analysis of the results reveals expected connections between tissue-specific developmental processes and diseases linked to those tissues, and widespread connections to developmental disorders and cancers. Yet interesting new hypotheses may be derived from examining the unexpected connections. We highlight and discuss the implications of three such connections, linking dementia with bone development, polycystic ovary syndrome with cardiovascular development, and retinopathy of prematurity with lung development. Our results provide additional evidence that TGFB lays a key role in the early pathogenesis of polycystic ovary syndrome. Our evidence also suggests that the VEGF pathway and downstream NFKB signaling may explain the complex relationship between bronchopulmonary dysplasia and retinopathy of prematurity, and may form a bridge between two currently-competing hypotheses about the molecular origins of bronchopulmonary dysplasia. Further data exploration and similar queries about other gene sets may generate a variety of new information about the molecular relationships between additional diseases.