Biology of Sex Differences

BackgroundClinical outcomes of acute myocardial infarction (AMI) are known to vary between females and males; however, the nature of this sex dimorphism remains controversial. Most AMI transcriptomic studies have not considered differences between females and males, and combined sexes in their analysis to increase sample size and gain power (canonical approach). Our objective was to (1) use a sex-specific differentially expressed gene meta-analysis (ss-DEGma) in blood and (2) identify sex-specific pathways related to the early phase of AMI. MethodsGene expression data (7 sets) for sex-combined (canonical) and sex-specific analysis (ss-DEGma) were obtained from the publicly-available GEO database. Datasets from whole blood and peripheral blood cells sampled within 3 days post-AMI were analyzed using GEO2R. The massiR tool identified sex in 72% of samples. The top-ranking DEGs were used to identify significant sex-specific biological pathways in the KEGG database (FDR <0.05). ResultsWe performed this meta-analysis in 291 women and 452 men and > 20,000 genes (see Table for identified DEGs). Sex-combined DEGs yielded 100 significant KEGG pathways. Sex-specific DEGs yielded 8/61 (13%) additional new pathways not identified by the sex-combined analysis. Sex-combined pathways were predominantly immunological (35%), while male- and female-specific pathways were 43% and 18% immunological, respectively. Proliferative and metabolic pathways were the next most represented pathways in females, which were not present in males at all. ConclusionWe present 8 new sex-specific AMI-related transcriptional pathways not identified in the canonical sex-combined analysis. Furthermore, we find that 53% of pathways identified in the canonical sex-combined analysis are not shared between sexes. This data underscores an urgent need for prospective sex-specific transcriptomic analysis to define the sex-specific biological difference post-AMI. O_TBL View this table: org.highwire.dtl.DTLVardef@173f223org.highwire.dtl.DTLVardef@11e06bdorg.highwire.dtl.DTLVardef@4c6f2dorg.highwire.dtl.DTLVardef@16f488org.highwire.dtl.DTLVardef@110421b_HPS_FORMAT_FIGEXP M_TBL C_TBL

Single-nucleus RNA sequencing (snRNA-seq) technology offers unprecedented resolution for studying cell type-specific gene expression patterns. However, snRNA-seq poses high costs and technical limitations, often requiring the pooling of independent biological samples and the loss of individual sample-level data. Deconvolution of sample identity using inherent features would enable the incorporation of pooled barcoding and sequencing protocols, thereby increasing data throughput and analytical sample size without requiring increases in experimental sample size and sequencing costs. In this study, we demonstrate a proof of concept that sex-dependent gene expression patterns can be leveraged for the deconvolution of pooled snRNA-seq data. Using previously published snRNA-seq data from the rat ventral tegmental area, we trained a range of machine learning models to classify cell sex using genes differentially expressed in cells from male and female rats. Models that used sex-dependent gene expression predicted cell sex with high accuracy (93-95%) and outperformed simple classification models using only sex chromosome gene expression (88-90%). The generalizability of these models to other brain regions was assessed using an additional published data set from the rat nucleus accumbens. Within this data set, model performance remained highly accurate in cell sex classification (90-92% accuracy) with no additional training. This work provides a model for future snRNA-seq studies to perform sample deconvolution using a two-sex pooled sample sequencing design and benchmarks the performance of various machine learning approaches to deconvolve sample identification from inherent sample features.

Sex is a critical biological variable that impacts disease risk, progression, and treatment response across virtually every organ system. However, decades of biomedical research have relied primarily on male study subjects, leaving large gaps in our understanding of female-specific disease biology. Quantifying the extent of this imbalance across thousands of disease areas and millions of publicly available biological samples has remained computationally intractable. Here, we present a multimodal computational framework that infers the biological sex of [~]230,000 publicly available human transcriptome samples and links inferred sex labels to disease terms extracted from [~]9,000 associated study records and [~]5,000 publication abstracts to quantify sex imbalance at scale. Applying this approach revealed that the majority of disease terms with the largest research-derived sex imbalance are skewed toward male representation, including areas with no known biological justification for that imbalance. After adjusting for global sex-specific disease prevalence to isolate biologically unjustified imbalance, up to 58% of all disease terms showed male-leaning association. Diseases including glioblastoma, cirrhosis, idiopathic pulmonary fibrosis, and schizophrenia emerged as critically understudied in females despite affecting both sexes comparably. These findings provide a principled, data-driven basis for prioritizing compensatory research efforts and offer a reusable framework for ongoing monitoring of sex representation in the biomedical literature. HighlightsO_LISkewed male and female study subject representation in biomedical research is the result of decades of studies conducted without adequate female representation. C_LIO_LIWe developed an automated, multimodal framework to estimate the sex imbalance across thousands of disease terms using metadata from [~]230,000 transcriptomics samples and their associated [~]9,000 studies and [~]5,000 publications. C_LIO_LIOur approach identifies non-sex-specific disease research areas that have been studied using an unbalanced sex demographic. These areas need compensatory and balanced studies to understand sex differences. C_LI

Sexually dimorphic traits (i.e. phenotypic differences between males and females) are largely produced by sex-biased gene expression (i.e. differential expression of genes present in both sexes). These expression differences may be the result of sexual selection, although other factors (e.g., relaxed purifying selection, pleiotropy, dosage compensation) also contribute. Given that humans and other primates exhibit sex differences in cognition and neuroanatomy, this implicates sex differences in brain gene expression. Here, we compare sex-biased gene expression in humans and rhesus macaques across 16 brain regions using published RNA-Seq datasets. Our results demonstrate that most sex-biased genes are differentially expressed between species, and that overlap across species is limited. Human brains are relatively more sexually dimorphic and exhibit more male-than female-biased genes. Across species, gene expression is biased in opposite directions in some regions and in the same direction in others, suggesting that the latter may be more relevant in nonhuman primate models of neurological disorders. Finally, the brains of both species exhibit positive correlations between sex effects across regions, higher tissue specificity among sex-biased genes, enrichment of extracellular matrix among male-biased genes, and regulation of sex-biased genes by sex hormones. Taken together, our results demonstrate some conserved mechanisms underlying sex-biased brain gene expression, while also suggesting that increased neurodevelopmental plasticity and/or strong sexual selection on cognitive abilities may have played a role in shaping sex-biased brain gene expression in the human lineage.

miRNA-based transcriptomic analysis of extracellular vesicles (EVs) provide a promising strategy for identifying non-invasive biomarkers and understanding complex pathological mechanisms. Recently, however, urinary extracellular vesicles (uEVs) have emerged as a valuable window into molecular alterations. Despite the high morbidity and mortality associated with alcohol use disorder (AUD), the molecular mechanisms underlying its sex-specific differences remain poorly understood. To address this, we characterize for the first time the uEV miRNome in AUD, revealing its sexually dimorphic profile. We employed uEVs from actively drinking AUD patients of both sexes who did not have advanced liver disease, alongside matched controls. Deep sequencing revealed 14 differentially expressed miRNAs in females (e.g., hsa-miR-197-3p, hsa-miR-19b-3p, hsa-miR-505-3p, hsa-miR-625-5p, and hsa-miR-27a-5p) and 6 in males (e.g., hsa-miR-1290, hsa-miR-1246, hsa-miR-450a-5p, and miR-590-5p). Notably, whereas hsa-miR-4787-5p was consistently overexpressed in uEVs from both sexes, it was absent in plasma-derived EVs, highlighting the specificity of the urinary compartment. Remarkably, the miRNA signatures we uncovered reflect the multiorgan impact of AUD. For instance, hsa-miR-1290 and hsa-miR-197-3p point to alcohol-related liver injury and systemic inflammation, whereas hsa-miR-19b-3p and hsa-miR-1246 signal neuroinflammation and neuronal stress. A subset, including hsa-miR-1290, hsa-miR-1246, and hsa-miR-27a-5p, has been implicated in cancer contexts. Collectively, these findings support the uEV miRNome as a promising sex-informed molecular signature of AUD with biomarker and mechanistic relevance.

Integrated multi-omics and extracellular vesicle (EV) analysis are emerging as powerful, complementary strategies for biomarker discovery. These approaches offer promising tools to enhance early detection, diagnosis, and treatment of alcohol use disorder (AUD). Here we applied an integrated miRNomic and lipidomic approach to analyze plasma EVs from AUD patients and controls of both sexes to gain a comprehensive understanding of the underlying molecular mechanisms. We identified an AUD signature with predictive potential for diagnostic applications. Individual features (e.g., hsa-miR-99b-3p, hsa-miR-556-5p, Cer_NDS-d39:1, and PI18:0_18:2) represented important components; however, the strength of this signature lay in the combined profile rather than isolated markers. We also revealed an AUD-sex signature that provided insight into how biological responses to alcohol differ between females and males (including features such as hsa-miR-1301-3p and PC39:4), which also underscored the power of multi-omic integration. The individual miRNome approach also revealed an opposite functional alteration by sex in various alcohol related systems, such as pathways associated with immunity, oxidative stress, and autophagy. An open-access Shiny web application (https://carpercle.shinyapps.io/SexEVEthOmics/) accompanies this study, providing interactive access to the complete dataset and additional analyses for customized exploration. Together, our findings underscore the added value of multi-omics integration in identifying clinically relevant molecular signatures of disease; this sex-informed approach offers a promising path toward more personalized diagnostic tools and therapeutic strategies in AUD.

Despite longstanding recognition of sex as a biological variable, its integration into biomedical research remains inconsistent. Numerous publishers have introduced policies to improve reporting and inclusion of sex and gender, including Nature, which requires authors to complete a Life Science Reporting Summary documenting sex inclusion. Here, we evaluated the effectiveness of these policies by examining sex inclusion and reporting practices in all original research articles involving humans, vertebrates, or cell lines published in Nature in 2025 (N=513). Nearly two-thirds of articles included both sexes (62.7%); however, inclusion was often nominal. Of these articles reporting inclusion of both sexes, 33% did not maintain inclusion across experiments, used markedly unbalanced sex ratios ([&ge;]2:1), or alternated between male- and female-only experiments. Another 45.5% of these articles reporting inclusion of both sexes did not report sample size by sex, so it cannot be ascertained whether sex inclusion was maintained across experiments or balanced by sex. Single-sex studies accounted for approximately one-fifth of articles. While male-only and female-only studies occurred at similar overall rates, male-only studies were more than four times more likely to address conditions affecting both sexes while female-only studies were more likely to address sex-specific conditions (e.g., ovarian cancer). Only 7% of articles explicitly analyzed sex as a discovery variable for at least some analyses. These findings suggest that transparency-focused reporting summaries alone are insufficient to ensure sex inclusion and/or meaningful analytical integration of sex. As a leading biomedical journal, Nature plays a central role in shaping research norms; without stronger editorial expectations, reporting requirements risk reinforcing male-default assumptions rather than advancing rigor and generalizability.

Reproductive diseases have gone under the radar for many years, resulting in insufficient diagnostics and treatments. Infertility rates are rising, preeclampsia claims over 70 000 maternal and 500 000 neonatal lives globally per year, and endometriosis affects 10% of all reproductive-aged women but is often undiagnosed for many years. Changes in policy have been enacted to mitigate the gender inequality in research investigators and subjects of medical research. However, the disparities in reproductive research advancement still exist. Here, we analyzed the reproductive science research landscape in attempt to quantify the gravity of the current situation. We find that non-reproductive organs are annually researched 5-20 times more than reproductive organs leading to an exponentially increasing relative knowledge gap in reproductive sciences. Additionally, reproductive organs (breast and prostate) are mainly researched when there is a disease-focus, leading to a lack of basic understanding of the reproductive organs. This gap in knowledge affects reproductive syndromes, as well as other bodily systems and research areas, such as cancer biology and regenerative medicine. Action must be taken by current researchers, funding organizations, and educators to combat this longstanding disregard of reproductive science.

Sex hormone fluctuations modulate structural and functional brain dynamics, yet little is known how sex steroid levels map onto the expression of sex differences in the brain. Here, we trained machine learning models for brain sex classification based on anatomical structures in cross-sectional data of N = 1090 individuals (50% females, age matched). Applied to dense sampled data of one male and two females in different hormonal states (naturally cycling, oral contraceptive user, pregnancy), we linked inter- and intra-individual fluctuations in brain sex to neuroendocrine modulation. We found lower variation in brain sex across time in the male compared to the female subjects. Oral contraceptive use was associated with a more female-like brain, while (inverted) U-shaped brain sex trajectories emerged across menstrual cycle phases and pregnancy trimesters. Overall, our findings suggest that changes in brain sex capture hormone-related plasticity over time in dense sampled individuals.

Sex differences in mental health become more evident across adolescence, with a two-fold increase of prevalence of mood disorders in females compared to males. The brain underpinnings remain understudied. Here, we investigated the role of age, puberty and mental health in determining the longitudinal development of sex differences in brain structure. We captured sex differences in limbic and non-limbic structures using machine learning models trained in cross-sectional brain imaging data of 1132 youths, yielding limbic and non-limbic estimates of brain sex. Applied to two independent longitudinal samples (total: 8184 youths), our models revealed pronounced sex differences in brain structure with increasing age. For females, brain sex was sensitive to pubertal development (menarche) over time and, for limbic structures, to mood-related mental health. Our findings highlight the limbic system as a key contributor to the development of sex differences in the brain and the potential of machine learning models for brain sex classification to investigate sex-specific processes relevant to mental health.

Environmental exposures co-occurring during early life have a profound influence on neurodevelopment. Our previous work in rats suggests that postnatal maternal care modulates the effects of prenatal exposure to bisphenols, an estrogenic endocrine disrupting chemical, on offspring neurodevelopment. Elevated postnatal maternal licking/grooming and prenatal bisphenol exposure have known opposing effects on estrogen receptor alpha (Esr1) expression in the medial preoptic area (MPOA) of the hypothalamus, which could impact expression of estrogen-responsive genes. Based on this previous work, we hypothesized that postnatal maternal licking/grooming would mitigate the effects of prenatal bisphenol exposure on Esr1 expression and estrogen-responsive genes in the developing MPOA. In addition, we hypothesized that there would be interactive effects of prenatal bisphenol exposure and postnatal maternal licking/grooming on DNA methylation, particularly nearby estrogen responsive elements. Our results suggest that maternal postnatal licking/grooming normalized prenatal bisphenol-induced upregulation of estrogen-related receptor gamma (Esrrg) expression in female pups. These mitigating impacts were also evident in co-expression gene profiles in female pups; the majority of which were enriched for estrogen-responsive genes. Finally, DNA methylation analyses indicated that adding postnatal maternal licking/grooming as a covariate influenced the number of differentially methylated regions for prenatal bisphenol-exposed male and female pups. These differentially methylated regions were enriched for binding sites for transcription factors that are known to interact with estrogen receptors, suggesting some secondary effects on postnatal gene regulation. These results suggest a novel biological mechanism in which postnatal maternal care can mitigate the negative neurodevelopmental impacts of prenatal bisphenol exposure. These results also suggest that postnatal tactile stimulation might be a potential intervention strategy to mitigate the neurodevelopmental risks from prenatal endocrine disrupting chemical exposure. Author SummaryNeurodevelopment can be shaped by both aversive and positive experiences early in life, in part due to epigenetic mechanisms such as DNA methylation. Here, we follow up on our previous studies that suggest high levels of postnatal maternal care could mitigate the negative impacts of prenatal bisphenol exposure, an estrogenic endocrine disrupting chemical. We focused on gene expression and DNA methylation changes in the developing medial preoptic area, a brain area that is enriched in estrogen receptors and important for sex-specific social behaviors. We found that maternal postnatal licking/grooming normalized prenatal bisphenol-induced upregulation of estrogen-related receptor gamma (Esrrg) expression in female pups only. We find similar patterns in multiple co-expressed gene networks that are enriched in estrogen-responsive genes. Finally, postnatal maternal licking/grooming influenced DNA methylation patterns for prenatal bisphenol-exposed male and female pups. These results suggest a novel biological mechanism in which postnatal maternal care can mitigate the negative neurodevelopmental impacts of prenatal bisphenol exposure. This is important because it suggests that postnatal tactile stimulation could be an effective intervention against the negative neurodevelopmental impacts from prenatal endocrine disrupting chemical exposure.

Detecting a sex difference in response to a treatment or intervention, often reported as a "sex-specific effect," requires statistical comparison of the response across sex. Here, we investigated analytical approaches used to test for such effects in the behavioral and brain sciences. Of 200 recent articles containing terms such as sex-specific or gender-dependent in their titles, only 24% presented appropriate evidence supporting the claim: the effect was compared statistically across sex and results consistent with the claim were reported. In most articles (58%), no test was conducted that could have supported the title claim. Only 15% of studies on non-human animals supported the claim with appropriate evidence, which was significantly less frequently than studies on human participants (34%; p = 0.002). The use of appropriate analytical approaches was unrelated to journal rank or the citation impact of the article. We conclude that claims of sex/gender-dependent effects in the behavioral and brain sciences are only infrequently supported by appropriate evidence.

Males and females possess genomes that are almost identical but differ in morbidity, prevalence, severity, response to therapies and mortality of many diseases. We comprehensively analyzed gene expression data in seven tissues from BXD recombinant inbred (RI) mouse strains. We found that there were considerable differences in the numbers and functions among different tissues and between autosomal and sex chromosomes. Among sex differential genes, those on autosomal chromosomes mainly function to regulate metabolic pathways related to their host organs, while those on sex chromosomes mainly regulate nuclear proteins required for DNA replication or transcription during early development. Kidney possessed the fewest sex differential genes on sex chromosomes. The sexually dimorphic genes expressed on X chromosomes were all related to perception, while genes on the autosomal chromosomes were related to metabolism. These patterns of gene expression do not translate into similarity of protein structures, rather they are grouping with function.

BackgroundPrevious pharmacovigilance studies and a retroactive review of cancer clinical trial studies identified that women were more likely to experience drug adverse events (i.e., any unintended effects of medication), and men were more likely to experience adverse events that resulted in hospitalization or death. These sex-biased adverse events (SBAEs) are due to many factors not entirely understood, including differences in body mass, hormones, pharmacokinetics, and liver drug metabolism enzymes and transporters. MethodsWe first identified drugs associated with SBAEs from the FDA Adverse Event Reporting System (FAERS) database. Next, we evaluated sex-specific gene expression of the known drug targets and metabolism enzymes for those SBAE-associated drugs. We also constructed sex-specific tissue gene-regulatory networks to determine if these known drug targets and metabolism enzymes from the SBAE-associated drugs had sex-specific gene-regulatory network properties and predicted regulatory relationships. ResultsWe identified liver-specific gene-regulatory differences for drug metabolism genes between males and females, which could explain observed sex differences in pharmacokinetics and pharmacodynamics. In addition, we found that [~]85% of SBAE-associated drug targets had sex-biased gene expression or were core genes of sex- and tissue-specific network communities, significantly higher than randomly selected drug targets. Lastly, we provide the sex-biased drug-adverse event pairs, drug targets, and drug metabolism enzymes as a resource for the research community. ConclusionsOverall, we provide evidence that many SBAEs are associated with drug targets and drug metabolism genes that are differentially expressed and regulated between males and females. These SBAE-associated drug metabolism enzymes and drug targets may be useful for future studies seeking to explain or predict SBAEs.

The pituitary gland regulates essential physiological processes such as growth, pubertal onset, stress response, metabolism, reproduction, and lactation. While sex biases in these functions and hormone production have been described, the underlying identity, temporal deployment, and cell-type specificity of sex-biased pituitary gene regulatory networks are not fully understood. To capture sex differences in pituitary gene regulation dynamics during postnatal development, we performed 3 untranslated region sequencing and small RNA sequencing to ascertain gene and microRNA expression respectively across five postnatal ages (postnatal days 12, 22, 27, 32, 37) that span the pubertal transition in female and male C57BL/6J mouse pituitaries (n=5-6 biological replicates for each sex at each age). We observed over 900 instances of sex-biased gene expression and 17 sex-biased microRNAs, with the majority of sex differences occurring with puberty. Using miRNA-gene target interaction databases, we identified 18 sex-biased genes that were putative targets of 5 sex-biased microRNAs. In addition, by combining our bulk RNA-seq with publicly available male and female mouse pituitary single-nuclei RNA-seq data, we obtained evidence that cell-type proportion sex differences exist prior to puberty and persist post-puberty for three major hormone-producing cell types: somatotropes, lactotropes, and gonadotropes. Finally, we predicted sex-biased genes in these three pituitary cell types after accounting for cell-type proportion differences between sexes. Our study reveals the identity and postnatal developmental trajectory of sex-biased gene expression in the mouse pituitary. This work also highlights the importance of considering sex biases in cell-type composition when understanding sex differences in the processes regulated by the pituitary gland. HighlightsO_LIMale and female mouse pituitary gland gene and miRNA expression was profiled across five postnatal ages spanning pubertal development C_LIO_LIAbundant sex differences in pituitary gene expression exist prior to puberty and become more prominent upon puberty C_LIO_LICombining expression data from genes and miRNAs revealed 18 putative sex-biased gene targets of 5 sex-biased miRNAs C_LIO_LISex differences in the proportions of somatotropes, lactotropes, and gonadotropes are predicted to occur prior to puberty C_LI

Although the neuroanatomy of transgender persons is slowly being charted, findings are presently discrepant. One important factor is the issue of power and low signal-to-noise (SNR) ratio in neuroimaging studies of rare study populations including endocrine or neurological patient groups. The present study assessed whether the reliability of findings across structural anatomical measures including thickness, volume, and surface area could be increased by using two back-to-back within session structural MRI scans in 40 transgender men (TM), 40 transgender women (TW), 30 cisgender men (CM), and 30 cisgender women (CW). Overall, findings in transgender persons were more consistent with at-birth assigned sex in brain volume and surface area while no group differences emerged for cortical thickness. Repeated measures analysis also indicated that having a second scan increased SNR in all ROIs, most notably bilateral frontal poles, accumbens nuclei and putamina. Furthermore, additional significant group differences emerged in cortical surface area when age and ICV were used as covariates. The results suggest that a simple time and cost effective measure to improve signal to noise ratio in rare clinical populations with low prevalence rates is a second anatomical scan when structural MRI is of interest.

In recent years, there has been a strong drive to improve the inclusion of animals of both sex during in vivo research, driven by a need to improve sex representation in fundamental biology and drug development. This has resulted in inclusion mandates by funding bodies and journals, alongside numerous published manuscripts highlighting the issue and providing guidance to scientists. However, progress is slow and blockers to the routine use of both sexes remain. From a statistical and experimental design perspective, concerns include difficulty selecting and conducting an appropriate analysis and the perceived need for a higher sample size to achieve an equivalent level of statistical power. When both sexes are included, analysis errors are frequent, including inappropriate pooling or sex-disaggregation of the data. These mistakes result in a failure to properly account for the variation in the data that arises from sex, and subsequently lead to poor inference regarding the biological impact of sex. The purpose of this manuscript is to address frequently cited blockers and analysis errors, thus providing a practical guide to support scientists in the design of in vivo studies which include both sexes. Primarily, we demonstrate that there is no loss of power to detect treatment effects when splitting the sample size across sexes in most common biological scenarios, providing that the data are analysed appropriately. In the rare situations where power is lost, the benefit of understanding the role of sex outweighs the power considerations. When estimating a generalisable translatable effect, where exploring sex differences are not the primary scientific objective, we recommend splitting the sample size across male and female mice as a standard strategy. We also demonstrate an optimal analysis pipeline for analysing data gathered using both sexes which is designed to help address common analysis errors.

BackgroundPrenatal cannabis use is becoming increasingly more commonplace. However, cannabis exposure is linked to adverse pregnancy outcomes, including gestational hypertension, preeclampsia, and preterm birth. The aim of this study was to determine the morphological and molecular effects of prenatal cannabinoid exposure on the placenta. MethodsPregnant Sprague-Dawley rats were exposed daily to vaporized THC (100 mg/mL) starting at gestational day (GD)5 until GD19 when dams were sacrificed and fetuses and placentas collected. Fetuses were genotyped for genetic sex and transcriptomic analysis was performed on male and female THC-exposed and control placentas. ResultsOn GD19, both the fetuses and placentas from the THC group were significantly larger than the control. When separated by sex, both male and female THC fetuses were significantly larger; however, only male THC placentas were significantly larger than male control placentas with no significant difference in placental weight between female control and THC placentas. RNA-sequencing revealed enriched biological processes related to nutrient transport and lipid catabolism, protein-lipid complex formation, and lipoprotein particle remodeling and organization. Further transcriptomic analysis determined that the differentially expressed genes and enriched biological processes related to lipid metabolism were preferentially enriched in the female THC placentas compared to the male, suggesting a sex-specific effect. DiscussionCollectively, these data present sex-specific effects of prenatal cannabinoid exposure on placental growth and global gene expression. These data also suggest that sex influences gene expression of genes related to lipid metabolism in the THC-exposed placentas.

Folate is crucial for various biological processes, with deficiencies during pregnancy being linked to increased risk for neural tube defects and neurodevelopmental disorders. As a proactive measure, folic acid fortification in foods has been mandated in many countries, in addition to dietary supplementation recommendations during pregnancy. However, the risks of excess prenatal folic acid supply have yet to be fully understood. To better appreciate in utero molecular changes in mouse brain exposed to 5-fold folic acid excess over normal supplementation, we investigated the transcriptome and methylome for alterations in gene networks. RNA-seq analysis of cerebral cortex collected at birth, revealed significant expression differences in 646 genes with major roles in protein translation. Whole genome bisulfite sequencing revealed 910 significantly differentially methylated regions with functions enriched in glutamatergic synapse and glutathione pathways. To explore the physiological consequences of excess prenatal folic acid exposure, we applied high-density microelectrode arrays to record network-level firing patterns of dissociated cortical neurons. Folic acid excess-derived cortical neurons exhibited significantly altered network activity, characterized by reduced burst amplitude and increased burst frequency, indicating compromised network synchronization. These functional deficits align with the observed molecular alterations in glutamatergic synapse pathways, underscoring the potential for excess prenatal folic acid exposure to disrupt developing metabolic and neurological pathways.

Estrogens are global regulators of cellular signaling pathways, impacting fundamental processes and phenotypes that are essential for tissue remodeling and homeostasis. Traditional cell culture media contains estrogen-mimetic compounds, including phenol red and endogenous estrogen in fetal bovine serum (FBS). However, the potential of these compounds to bias in vitro studies, particularly when considering sex as a biological variable, remains unclear. This gap in understanding critically impacts the culture of human mesenchymal stromal cells (hMSCs), whose basic functions and differentiation potential, central to cell therapy and tissue engineering, are sensitive to perturbations in the culture conditions. Despite this, the effect of estrogens from cell culture media on male and female hMSCs is not currently considered in cell processing for clinical trials. As such, a baseline understanding of these estrogen-mimetic media influences on hMSCs is critical for clinical efficacy and adequate study design in research. To this end, we investigated the effects of phenol red and fetal bovine serum on the proliferation, metabolism, senescence, and differentiation capacity of male and female hMSCs. Phenol red, FBS, donor sex, and 17{beta}-estradiol (E2) supplementation all had significant impacts on hMSC health and differentiation potential in culture. Notably, dosing with estrogen at the levels found in FBS did not recover most of the hMSC metrics tested. The only outcomes that were not significantly different based on donor sex were senescence and mRNA transcripts for RUNX2 and PPARG, transcriptional regulators for osteogenesis and adipogenesis. Overall, these findings reveal the sex-biased effects of estrogen and estrogen-mimetic compounds in traditional culture media, underscoring a current gap in considering sex as a biological variable in cell therapy and tissue engineering research and manufacturing.