Biology subjects

Stevenson, D. K.

Publications and source records attributed to Stevenson, D. K..

13 recordsLinked to original sources

bioRxiv2026

Spatial Logic and Evolutionary Innovation in Human Placentation

Human pregnancy unfolds in a unique mosaic tissue context. Embryonic/fetal placental and maternal uterine cells (decidua basalis) coalesce, forming the basal plate where immune tolerance is coordinated and the utero-placental circulation is initiated. The remaining approximately 70% of the maternal-fetal interface is comprised of the chorionic membranes, an epithelial-like layer of placental cells that lies adjacent to but does not coalesce with the overlying decidua capsularis and parietalis. It is unknown how these two regions of the maternal-fetal interface, which are comprised of seemingly similar cell types, diverge anatomically and functionally. Likewise, it is unknown whether the molecular characteristics of the maternal-fetal interface vary across human populations, potentially contributing to population disparities in pregnancy complications. Here, we generated large-scale paired single-nucleus RNA-seq and chromatin-accessibility profiles of the basal plate and chorionic membranes-associated decidual compartments from diverse-ancestry pregnancies, integrated with spatial transcriptomics and multiplexed protein imaging. We show that the two interfaces share a conserved cytotrophoblast differentiation hierarchy, which is deployed differently resulting in the observed distinct architectures. In the chorionic membranes, progenitor, early, and mature extravillous cytotrophoblast (EVT) states form an epithelial-like laminar shell. In the basal plate, this hierarchy is elaborated upon to enable deep placentation: EVTs that arise early in pregnancy invade the farthest into the uterus, while mature EVTs accumulate superficially to sculpt the local maternal immune microenvironment. Comparative analysis identified DSC4, a decidual stromal cell subtype, as an anti-invasive barrier that is densely enriched adjacent to the chorionic membranes but substantially reduced at the basal plate. Population-resolved analysis further identified the DSC4 marker NID2, which encodes the basement-membrane glycoprotein nidogen-2, as an ancestry-associated rheostat of EVT invasion. A specific NID2 promoter haplotype arose on the modern-human lineage, is absent from available archaic-human genomes, and shows evidence of positive selection in Eurasian populations. This haplotype is associated with reduced local chromatin accessibility and lower NID2 expression in DSC4 cells. Consistent with this genetic association, extracellular NID2 directly suppressed the invasion of primary human cytotrophoblasts in vitro. Together, these findings reveal how a shared developmental program is spatially reconfigured across distinct regions of the maternal-fetal interface and identify a recent modern-human regulatory innovation that modulates maternal decidual restraint of fetal trophoblast invasion across populations.

genomics↗

bioRxiv2026

Integrating single-cell and bulk transcriptomic perturbation resources reveals complementary therapeutic spaces for drug repurposing

Transcriptome-based drug repurposing can accelerate therapeutic discovery, but is limited by fragmented resources, inconsistent quality control, and reliance on single perturbation databases. We developed CDRPipe (Computational Drug Repurposing Pipeline), a unified framework that interrogates disease signatures against drug perturbation signatures generated by distinct experimental technologies. Specifically, CDRPipe harmonizes microarray perturbation profiles from the Connectivity Map (CMap; 1,968 quality-filtered experiments) with pseudo-bulk profiles derived from large-scale single-cell RNA sequencing experiments in the Tahoe-100M database (56,827 experiments). CDRPipe standardizes preprocessing, computes rank-based connectivity scores, and evaluates significance using empirical null models. We applied CDRPipe to 233 curated disease signatures from GEO and CREEDS and evaluated performance using known drug-disease associations from Open Targets. Single-cell-derived pseudo-bulk profiles recovered more annotated therapeutics than microarray profiles (median recall 50.0% vs. 6.2%; Wilcoxon p < 10-{superscript 1}{superscript 1}), thought these differences partly reflect differences in drug library composition and clinical annotation coverage. Importantly, the two resources were highly complementary, with only 3.5% overlap in recovered drugs, indicating that integrating predictions across independent perturbation resources expands therapeutic coverage and enables identification of high-confidence consensus candidates. Case studies in autoimmune disease and endometriosis further demonstrate that CDRPipe recovers clinically relevant therapies while revealing technology-dependent patterns of discovery. These results show that integrating heterogeneous transcriptomic perturbation resources improves the robustness and interpretability of transcriptional drug repurposing. One Sentence SummaryIntegrating drug perturbation resources from distinct transcriptomic platforms improves the robustness and accuracy of drug repurposing predictions.

bioinformatics↗

bioRxiv2025

Systemic immune dysregulation in hypertensive disorders of pregnancy persists years after delivery

BackgroundHypertensive disorders of pregnancy (HDP), including preeclampsia and gestational hypertension, are associated with an increased risk of cardiovascular disease (CVD) later in life. Mechanisms that link HDP to CVD, however, remain unclear. MethodsWe used a high-dimensional single-cell mass cytometry approach to profile the distribution and functional responses of maternal immune cells in three separate groups of HDP cases and normotensive controls, sampled antepartum, postpartum, and several years postpartum (midlife). We used multivariable sparse modeling to distinguish HDP cases from controls. ResultsWe accurately distinguished HDP cases from controls at all three study timepoints, with area under the receiver operator characteristic (AUROC) curve values of 0.814 for the antepartum group, 0.757 for the postpartum group, and 0.692 for the midlife group. Distinct immune signatures for each model underscore the dynamic dysregulation of the immune system throughout life. In addition, we identified a persistent immune dysregulation signal among HDP cases at all three timepoints, characterized by increased B cell frequency and decreased pSTAT3 response upon cytokine stimulation in classical monocytes. ConclusionsPersistent immune dysregulation among women with a history of an HDP may contribute to elevated long-term risk of CVD development.

immunology↗

bioRxiv2025

Single-cell-level digital twins for preterm birth prevention strategies

Digital twin models can accelerate therapeutic development by enabling low-risk testing of candidate interventions. In preterm labor (PTL), a major pregnancy complication where clinical trials face unique ethical and financial barriers, digital twins are especially valuable for evaluating new therapies targeting immune dysfunctions driving PTL. Yet, current models lack single-cell resolution, limiting detection of cell-type-specific mechanisms, off-target effects, and the design of personalized interventions. We present Simulated Immunome Modeling of Clinical Outcomes (SIMCO), a single-cell-level digital twin framework that models immunomodulatory treatment effects on the timing of labor using immunome-wide, single-cell simulations. SIMCOs digital twins are trained and validated on a newly generated mass cytometry atlas of the pregnant immunome exposed to nine candidate drugs preselected for PTL prevention. Applying SIMCO to an independent cohort of pregnant individuals, we simulate treatment effects on gestational length, screening for candidate drugs that delay labor timing and providing system-level mechanistic insight for each drug candidate. Tetrahydrofolate, maprotiline, and the combination of aspirin and lansoprazole emerged as top candidates for PTL prevention, delaying labor onset primarily through enhanced mTOR signaling in innate immune cells and attenuated JAK/STAT signaling in naive CD4 T cells. The codebase is available at https://github.com/ofondeur/SIMCO/.

immunology↗

bioRxiv2025

A Transcriptomics-Based Computational Drug Repositioning Pipeline Identifies Simvastatin And Primaquine As Novel Therapeutics For Endometriosis Pain

Endometriosis has limited treatment options, prompting the search for novel therapeutics. We previously used a transcriptomics-based computational drug repositioning pipeline to analyze public bulk transcriptomic data of eutopic endometrium from cases and controls and identified several drug candidates. Fenoprofen, our top in silico candidate, was validated in a rat model of endometriosis-associated pain. Building on this, we evaluated herein two additional candidates, simvastatin (a cholesterol-lowering drug) and primaquine (an antimalarial), based on strong endometrial gene expression reversal scores and favorable safety profiles. Using the rat model, we conducted behavioral testing, bulk RNA sequencing, and differential expression analysis to assess their therapeutic potential. We also assessed endometriosis diagnosis among patients prescribed simvastatin in electronic medical records (EMR) across six University of California (UC) healthcare institutions. In vivo validation using a rat model of endometriosis demonstrated that both simvastatin and primaquine significantly reduced vaginal hyperalgesia, a surrogate marker of endometriosis-related pain. RNA-seq of uteri and lesions confirmed reversal of disease-associated gene expression signatures following treatment. Analysis of UC-wide EMR data found lower relative risk of endometriosis among those prescribed simvastatin compared to a matched control group. Overall, simvastatin and primaquine attenuated pain-associated behaviors and reversed endometriosis-related gene expression changes in an animal model. Moreover, simvastatin prescription was associated with a lower relative risk of endometriosis in our retrospective multi-center cohort study. These findings highlight their potential as repurposed therapeutics for endometriosis and support the effectiveness of computational drug repositioning in identifying new treatment strategies. One Sentence SummarySimvastatin and primaquine reduced endometriosis pain and reversed gene signatures, with simvastatin also linked to lower disease risk.

bioinformatics↗

bioRxiv2025

Anticlustering for Sample Allocation To Minimize Batch Effects

High throughput sequencing is a powerful tool for processing large amounts of DNA and RNA samples in batches. Proper experimental design and statistical methods are required to mitigate systematic technical factors due to differences in batches ("batch effects"), as data variation due to these non-biological factors can mask actual biological differences. We propose using anticlustering as an automated method to assign samples to balanced batches. Anticlustering effectively negates differences in (numeric and/or categorical) covariates among batches, and implements user-defined restrictions on the number of batches, the number of samples per batch, and whether to assign certain samples to the same batch ("must-link constraints"). A simulation study shows that anticlustering is better at achieving balance among batches than previous approaches. An application from the UCSF-Stanford Endometriosis Center for Discovery, Innovation, Training and Community Engagement ("ENACT", https://enactcenter.org/) is presented as a real-life example. In the application, multiple samples provided by an individual had to be processed on the same batch, so that comparisons among different samples of the same patient were not diluted by batch effects. The novel Two Phase Must Link (2PML) anticlustering algorithm realized the must-link restrictions while simultaneously obtaining balance among batches regarding disease stage, menstrual cycle phase, case versus control sample, and clinical site. All methods presented here are accessible via the free and open source R package anticlust (https://cran.r-project.org/package=anticlust). An interactive visualization and web-based batch assignment tool are made available in the Rshiny app "anticlust" (https://anticlust.org/).

bioinformatics↗

bioRxiv2024

A Multiomics, Spatiotemporal, and Single Cell Atlas for Mapping Cell-Type-Specific Dysregulation at the Maternal-Fetal Interface

The placenta, the first organ to functionally mature, undergoes disordered development in many pregnancy complications. Molecular investigations have been hampered by the extreme cellular heterogeneity of the placenta, and this complexity is further exaggerated at the maternal-fetal interface where maternal and fetal cells co-mingle. We generated the paired single nucleus epigenomes and transcriptome for each of [~]200,000 cells at the human maternal-fetal interface from early pregnancy to term. These data identified cell-type-specific transcriptional regulatory programs and uncovered key transcription factors driving the lineage differentiation of placental cytotrophoblasts. Integrating spatial single cell proteomics profiling, we localized the observed cell types in situ, and characterized the dynamic stages and distinct features of endothelial cells of maternal spiral arteries remodeled by extravillous cytotrophoblasts. Integrative analyses of the single cell data across gestation enabled fine-mapping of the developmental trajectories of cytotrophoblasts and decidual stromal cells, and defining the signature molecular profiles of known and novel cell (sub)types. To demonstrate clinical value, we integrated the reference single cell data with large-scale population genomes from pregnancy complications and identified the most vulnerable maternal and fetal cell types in preeclampsia, preterm birth, and miscarriage. This study presents the most comprehensive placental and decidual single cell resource across gestation to date, reveals new insights into the drivers of normal human placentation, and uncovers the cellular basis of dysfunction associated with common pregnancy complications.

genomics↗

bioRxiv2022

Longitudinal dynamics of the human vaginal ecosystem across the reproductive cycle

The vaginal ecosystem is closely tied to human health and reproductive outcomes. However, its dynamics in the wake of childbirth remain poorly characterized. Here, we profiled the vaginal microbiota and cytokine milieu of subjects sampled throughout pregnancy (two cohorts; n = 196 pregnancies) and, in a subset, for one year postpartum (one cohort; n = 72 pregnancies). Delivery was associated with a vaginal pro-inflammatory cytokine response and the depletion of dominant taxa - typically, Lactobacillus species. By contrast, neither the progression of gestation nor the approach of labor strongly altered the vaginal ecosystem. At ~9.5 months postpartum (the latest timepoint at which cytokines were analyzed), elevated inflammation was associated with vaginal bacterial communities that had remained perturbed (i.e., highly diverse) from the time of delivery. Using time-to-event analysis, we found that the one-year postpartum probability of transitioning to Lactobacillus dominance was 49.4% (95% confidence interval (CI) [33.6%, 61.5%]; n = 58 at-risk cases, 86.2% of whom experienced this state prior to delivery). As diversity and inflammation declined postpartum, dominance by L. crispatus, the quintessential health-associated state, failed to recover: its prevalence before, immediately after, and one year after delivery was 41%, 4%, and 9%, respectively. Over the same period, states quasi-dominated by non-Lactobacillus species grew more common. Prompted by these findings, we revisited our pre-delivery data, discovering that a history of prior live birth was associated with a lower odds of L. crispatus dominance in pregnant subjects (odds ratio (OR) 0.14; 95% CI [0.06, 0.32]; P < 0.001) - an outcome modestly tempered by a longer (>18-month) interpregnancy interval. Our results suggest that reproductive history and childbirth in particular remodel the vaginal ecosystem and that the timing and degree of recovery from delivery may help determine the subsequent health of the woman and of future pregnancies.

microbiology↗

bioRxiv2020

Integration of Mechanistic Immunological Knowledge into a Machine Learning Pipeline Increases Predictive Power

The dense network of interconnected cellular signaling responses quantifiable in peripheral immune cells provide a wealth of actionable immunological insights. While high-throughput single-cell profiling techniques, including polychromatic flow and mass cytometry, have matured to a point that enables detailed immune profiling of patients in numerous clinical settings, limited cohort size together with the high dimensionality of data increases the possibility of false positive discoveries and model overfitting. We introduce a machine learning platform, the immunological Elastic-Net (iEN), which incorporates immunological knowledge directly into the predictive models. Importantly, the algorithm maintains the exploratory nature of the high-dimensional dataset, allowing for the inclusion of immune features with strong predictive power even if not consistent with prior knowledge. In three independent studies our method demonstrates improved predictive power for clinically-relevant outcomes from mass cytometry data generated from whole blood, as well as a large simulated dataset.

bioinformatics↗

bioRxiv2020

Quantitative LCMS for ceramides/dihydroceramides: pregnancy baseline biomarkers and potential metabolic messengers

Ceramides and dihydroceramides are sphingolipids that present in abundance at the cellular membrane of eukaryotes. Although their metabolic dysregulation has been implicated in many diseases, our knowledge about circulating ceramide changes during the pregnancy remains limited. In this study, we present the development and validation of a high-throughput liquid chromatography-tandem mass spectrometric (LC/MS/MS) method for simultaneous quantification of 16 ceramides and 10 dihydroceramides in human serum within 5 mins by using stable isotope-labeled ceramides as internal standards (ISs). This method employs a protein precipitation method for high throughput sample preparation, reverse phase isocratic elusion for chromatographic separation, and Multiple Reaction Monitoring (MRM) for mass spectrometric detection. To qualify for clinical applications, our assay was validated against the FDA guidelines: the Lower Limit of Quantitation (LLOQ as low as 1 nM), linearity (R2>0.99), precision (Coefficient of Variation<15%), accuracy (Percent Error<15%), extraction recovery (>90%), stability (>85%), and carryover (<0.1%). With enhanced sensitivity and specificity from this method, we have, for the first time, determined the serological levels of ceramides and dihydroceramides to reveal unique temporal gestational patterns. Our approach could have value in providing insights into disorders of pregnancy.

biochemistry↗

bioRxiv2018

Metagenomic analysis with strain-level resolution reveals fine-scale variation in the human pregnancy microbiome

Recent studies suggest that the microbiome has an impact on gestational health and outcome. However, characterization of the pregnancy-associated microbiome has largely relied on 16S rRNA gene amplicon-based surveys. Here, we describe an assembly-driven, metagenomics-based, longitudinal study of the vaginal, gut, and oral microbiomes in 292 samples from ten subjects sampled every three weeks throughout pregnancy. 1.53 Gb of non-human sequence was assembled into scaffolds, and functional genes were predicted for gene-and pathway-based analyses. Vaginal assemblies were binned into 97 draft quality genomes. Redundancy analysis (RDA) of microbial community composition at all three body sites revealed gestational age to be a significant source of variation in patterns of gene abundance. In addition, health complications were associated with variation in community functional gene composition in the mouth and gut. The diversity of Lactobacillus iners-dominated communities in the vagina, unlike most other vaginal community types, significantly increased with gestational age. The genomes of co-occurring Gardnerella vaginalis strains with predicted distinct functions were recovered in samples from two subjects. In seven subjects, gut samples contained strains of the same Lactobacillus species that dominated the vaginal community of that same subject, and not other Lactobacillus species; however, these within-host strains were divergent. CRISPR spacer analysis suggested shared phage and plasmid populations across body sites and individuals. This work underscores the dynamic behavior of the microbiome during pregnancy and suggests the potential importance of understanding the sources of this behavior for fetal development and gestational outcome.

microbiology↗

bioRxiv2017

A Noninvasive Molecular Clock for Fetal Development Predicts Gestational Age and Preterm Delivery

We performed a high time-resolution, longitudinal study of normal pregnancy development by measuring cell-free RNA (cfRNA) in blood from women during each week of pregnancy. Analysis of tissue-specific transcripts in these samples enabled us to follow fetal and placental development with high resolution and sensitivity, and also to detect gene-specific responses of the maternal immune system to pregnancy. We established a \"clock\" for normal pregnancy development and enabled a direct molecular approach to determine expected delivery dates with comparable accuracy to ultrasound, creating the basis for a portable, inexpensive fetal dating method. We also identified a related gene set that accurately discriminated women at risk for spontaneous preterm delivery up to two months in advance of labor, forming the basis of a potential screening test for risk of preterm delivery.

bioengineering↗

bioRxiv2017

Humans are colonized by many uncharacterized and highly divergent microbes

Blood circulates throughout the entire body and contains molecules drawn from virtually every tissue, including the microbes and viruses which colonize the body. Through massive shotgun sequencing of circulating cell-free DNA from the blood, we identified hundreds of new bacteria and viruses which represent previously unidentified members of the human microbiome. Analysing cumulative sequence data from 1,351 blood samples collected from 188 patients enabled us to assemble 7,190 contiguous regions (contigs) larger than 1 kbp, of which 3,761 are novel with little or no sequence homology in any existing databases. The vast majority of these novel contigs possess coding sequences, and we have validated their existence both by finding their presence in independent experiments and by performing direct PCR amplification. When their nearest neighbors are located in the tree of life, many of the organisms represent entirely novel taxa, showing that microbial diversity within the human body is substantially broader than previously appreciated.

microbiology↗