Exposure to Airborne PM2.5 Water-Soluble Inorganic Ions Induces a Wide Array of Reproductive Toxicity.

Water-soluble inorganic ions (WSIIs, primarily NH4+, SO42-, and NO3-) are major components in ambient PM2.5, but their reproductive toxicity remains largely unknown. An animal study was conducted where parental mice were exposed to PM2.5 WSIIs or clean air during preconception and the gestational period. After delivery, all maternal and offspring mice lived in a clean air environment. We assessed reproductive organs, gestation outcome, birth weight, and growth trajectory of the offspring mice. In parallel, we collected birth weight and placenta transcriptome data from 150 mother-infant pairs from the Rhode Island Child Health Study. We found that PM2.5 WSIIs induced a broad range of adverse reproductive outcomes in mice. PM2.5 NH4+, SO42-, and NO3- exposure reduced ovary weight by 24.22% (p = 0.005), 14.45% (p = 0.048), and 16.64% (p = 0.022) relative to the clean air controls. PM2.5 SO42- exposure reduced the weight of testicle by 5.24% (p = 0.025); further, mice in the PM2.5 SO42- exposure group had 1.81 (p = 0.027) fewer offspring than the control group. PM2.5 NH4+, SO42-, and NO3- exposure all led to lower birth than controls. In mice, 557 placenta genes were perturbed by exposure. Integrative analysis of mouse and human data suggested hypoxia response in placenta as an etiological mechanism underlying PM2.5 WSII exposure's reproductive toxicity.

Polygenic risk score for alcohol drinking behavior improves prediction of inflammatory bowel disease risk.

Epidemiological studies have long recognized risky behaviors as potentially modifiable factors for the onset and flares of inflammatory bowel disease (IBD); yet, the underlying mechanisms are largely unknown. Recently, the genetic susceptibilities to cigarette smoking, alcohol and cannabis use [i.e. substance use (SU)] have been characterized by well-powered genome-wide association studies (GWASs). We aimed to assess the impact of genetic determinants of SU on IBD risk. Using Mount Sinai Crohn's and Colitis Registry (MSCCR) cohort of 1058 IBD cases and 188 healthy controls, we computed the polygenic risk score (PRS) for SU and correlated them with the observed IBD diagnoses, while adjusting for genetic ancestry, PRS for IBD and SU behavior at enrollment. The results were validated in a pediatric cohort with no SU exposure. PRS of alcohol consumption (DrnkWk), smoking cessation and age of smoking initiation, were associated with IBD risk in MSCCR even after adjustment for PRSIBD and actual smoking status. One interquartile range decrease in PRSDrnkWk was significantly associated to higher IBD risk (i.e. inverse association) (with odds ratio = 1.65 and 95% confidence interval: 1.32, 2.06). The association was replicated in a pediatric Crohn's disease cohort. Colocalization analysis identified a locus on chromosome 16 with polymorphisms in IL27, SULT1A2 and SH2B1, which reached genome-wide statistical significance in GWAS (P < 7.7e-9) for both alcohol consumption and IBD risk. This study demonstrated that the genetic predisposition to SU was associated with IBD risk, independent of PRSIBD and in the absence of SU behaviors. Our study may help further stratify individuals at risk of IBD.

Profiling Microbiota from Multiple Sites in the Respiratory Tract to Identify a Biomarker for PM2.5 Nitrate Exposure-Induced Pulmonary Damages.

The microbiota present in the respiratory tract (RT) responds to environmental stimuli and engages in a continuous interaction with the host immune system to maintain homeostasis. A total of 40 C57BL/6 mice were divided into four groups and exposed to varying concentrations of PM2.5 nitrate aerosol and clean air. After 10 weeks of exposure, assessments were conducted on the lung and airway microbiome, lung functions, and pulmonary inflammation. Additionally, we analyzed data from both mouse and human respiratory tract (RT) microbiomes to identify possible biomarkers for PM2.5 exposure-induced pulmonary damages. On average, 1.5 and 13.5% inter-individual microbiome variations in the lung and airway were explained by exposure, respectively. In the airway, among the 60 bacterial OTUs (operational taxonomic units) > 0.05% proportion, 40 OTUs were significantly affected by PM2.5 exposure (FDR ≤ 10%). Further, the airway microbiome was associated with peak expiratory flow (PEF) (p = 0.003), pulmonary neutrophil counts (p = 0.01), and alveolar 8-OHdG oxidative lesions (p = 0.0078). The Clostridiales order bacteria showed the strongest signals. For example, the o_Clostridiales;f_;g_ OTU was elevated by PM2.5 nitrate exposure (p = 4.98 × 10-5) and negatively correlated with PEF (r = -0.585 and p = 2.4 × 10-4). It was also associated with the higher pulmonary neutrophil count (p = 8.47 × 10-5) and oxidative lesion (p = 7.17 × 10-3). In human data, we confirmed the association of airway Clostridiales order bacteria with PM2.5 exposure and lung function. For the first time, this study characterizes the impact of PM2.5 exposure on the microbiome of multiple sites in the respiratory tract (RT) and its relevance to airflow obstructive diseases. By analyzing data from both humans and mice, we have identified bacteria belonging to the Clostridiales order as a promising biomarker for PM2.5 exposure-induced decline in pulmonary function and inflammation.

Effects of chronic electronic cigarettes exposure in inducing respiratory function decline and pulmonary tissue injury - A direct comparison to combustible cigarettes.

BACKGROUND: Electronic cigarette (e-cig) use is increasing worldwide, especially among young individuals. Spirometry measures airflow obstruction and is the primary tool for diagnosing/monitoring respiratory diseases in clinical settings. This study aims to assess the effects of chronic e-cig exposure on spirometric traits, and directly compare to conventional combustible-cigarette (c-cig). METHODS: We employed an e- and c-cig aerosol generation system that resembled human smoking/vaping scenario. Fifty 6-week old C57BL/6 mice were equally divided into five groups and exposed to clean air (control), e-cig aerosol (low- and high-dose), and c-cig aerosol (low- and high-dose), respectively, for 10 weeks. Afterwards, growth trajectory, spirometry and pulmonary pathology were analyzed. RESULTS: Both e- and c-cig exposure slowed down growth and weight gain. Low dose e-cig exposure (1 h exposure per day) resulted in minimal respiratory function damage. At high dose (2 h exposure per day), e-cig exposure deteriorated 7 spirometry traits but by a smaller magnitude than c-cig exposure. For example, comparing to clean air controls, high dose e- and c-cig exposure increased inspiratory resistance by 24.3% (p = 0.026) and 66.7% (p = 2.6e-5), respectively. Low-dose e-cig exposure increased alveolar macrophage count but did not lead to airway remodeling. In contrast, even low-dose c-cig caused alveoli break down and thickening of the small airway, hallmarks of airway obstructive disease. CONCLUSIONS: We conducted well-controlled animal exposure experiments assessing chronic e-cig exposure's effects on spirometry traits. Further, mechanistic study characterized airway remodeling, alveolar tissue lesion and inflammation induced by e- and c-cig exposure. Our findings provided scientific and public health insights on e-cig's health consequences, especially in adolescent users.

Ambient Air Pollutants and Traffic Factors Were Associated with Blood and Urine Biomarkers and Asthma Risk.

The UK Biobank (UKBB) is a large population-based cohort that provides a unique opportunity to study the association between environmental exposure and biomarkers and to identify biomarkers as potential instruments for assessing exposure dose, health damage, and disease risks. On 462 063 participants of European ancestry, we characterized the relationship of 38 disease-relevant biomarkers, asthma diagnosis, ambient pollution, traffic factors, and genetic background. The air pollutant exposure on the UKBB cohort was fairly low (e.g., mean PM2.5 concentration at 10.0 µg/m3). Nevertheless, 30 biomarkers were in association with at least one environmental factor; e.g., C-reactive protein levels were positively associated with NO (padj = 2.99 × 10-4), NO2 (padj = 4.15 × 10-4), and PM2.5 (padj = 1.92 × 10-6) even after multiple testing adjustment. Asthma diagnosis was associated with four pollutants (NO, NO2, PM2.5, and PM10). The largest effect size was observed in PM2.5, where a 5 µg/m3 increment of exposure was associated with a 1.52 increase in asthma diagnosis (p = 4.41 × 10-13). Further, environmental exposure and genetic predisposition influenced biomarker levels and asthma diagnosis in an additive model. The exposure-biomarker associations identified in this study could serve as potential indicators for environmental exposure induced health damages. Our results also shed light on possible mechanisms whereby environmental exposure influences disease-causing biomarkers and in turn increases disease risk.

Integrative metabolomics-genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease.

Metabolites, the biochemical products of the cellular process, can be used to measure alterations in biochemical pathways related to the pathogenesis of Alzheimer's disease (AD). However, the relationships between systemic abnormalities in metabolism and the pathogenesis of AD are poorly understood. In this study, we aim to identify AD-specific metabolomic changes and their potential upstream genetic and transcriptional regulators through an integrative systems biology framework for analyzing genetic, transcriptomic, metabolomic, and proteomic data in AD. Metabolite co-expression network analysis of the blood metabolomic data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) shows short-chain acylcarnitines/amino acids and medium/long-chain acylcarnitines are most associated with AD clinical outcomes, including episodic memory scores and disease severity. Integration of the gene expression data in both the blood from the ADNI and the brain from the Accelerating Medicines Partnership Alzheimer's Disease (AMP-AD) program reveals ABCA1 and CPT1A are involved in the regulation of acylcarnitines and amino acids in AD. Gene co-expression network analysis of the AMP-AD brain RNA-seq data suggests the CPT1A- and ABCA1-centered subnetworks are associated with neuronal system and immune response, respectively. Increased ABCA1 gene expression and adiponectin protein, a regulator of ABCA1, correspond to decreased short-chain acylcarnitines and amines in AD in the ADNI. In summary, our integrated analysis of large-scale multiomics data in AD systematically identifies novel metabolites and their potential regulators in AD and the findings pave a way for not only developing sensitive and specific diagnostic biomarkers for AD but also identifying novel molecular mechanisms of AD pathogenesis.

Chronic Exposure to PM2.5 Nitrate, Sulfate, and Ammonium Causes Respiratory System Impairments in Mice.

Water-soluble inorganic (WSI) ions are major components of ambient air PM2.5 (particulate matter of diameter ≤2.5 µm); however, their potential health effects are understudied. On C57BL/6 mice, we quantified the effect of three major PM2.5 WSIs (NO3-, SO42-, and NH4+) on respiratory systems. Exposure scenarios include different WSI types, concentrations, animal development stages (young vs adult), and sex. The exposure effects were comprehensively assessed, with special focus on the respiratory function and tissue/cell level changes. Chronic PM2.5 NO3- exposure produced significant respiratory function decline, mainly presented as airflow obstruction. The decline was more profound in young mice than in adult mice. In young mice, exposure to 22 µg/m3 PM2.5 NO3- reduced FEV0.05 (forced expiratory volume in 0.05 s) by 11.3% (p = 9.6 × 10-3) and increased pulmonary neutrophil infiltration by 7.9% (p = 7.1 × 10-3). Causality tests identified that neutrophil infiltration was involved in the biological mechanism underlying PM2.5 NO3- toxicity. In contrast, the effects of PM2.5 SO42- were considerably weaker than NO3-. PM2.5 NO3- exposure was 3.4 times more potent than PM2.5 SO42- in causing reduction of the peak expiratory flow. PM2.5 NH4+ exposure had no statistically significant effects on the respiratory function. In summary, this study provided strong evidence on the adverse impacts of PM2.5 WSIs, where the impacts were most profound in young mice exposed to PM2.5 NO3-. If confirmed in humans, toxicity of PM2.5 WSI will have broad implications in environment health and policy making.

EnsembleCNV: an ensemble machine learning algorithm to identify and genotype copy number variation using SNP array data.

The associations between diseases/traits and copy number variants (CNVs) have not been systematically investigated in genome-wide association studies (GWASs), primarily due to a lack of robust and accurate tools for CNV genotyping. Herein, we propose a novel ensemble learning framework, ensembleCNV, to detect and genotype CNVs using single nucleotide polymorphism (SNP) array data. EnsembleCNV (a) identifies and eliminates batch effects at raw data level; (b) assembles individual CNV calls into CNV regions (CNVRs) from multiple existing callers with complementary strengths by a heuristic algorithm; (c) re-genotypes each CNVR with local likelihood model adjusted by global information across multiple CNVRs; (d) refines CNVR boundaries by local correlation structure in copy number intensities; (e) provides direct CNV genotyping accompanied with confidence score, directly accessible for downstream quality control and association analysis. Benchmarked on two large datasets, ensembleCNV outperformed competing methods and achieved a high call rate (93.3%) and reproducibility (98.6%), while concurrently achieving high sensitivity by capturing 85% of common CNVs documented in the 1000 Genomes Project. Given this CNV call rate and accuracy, which are comparable to SNP genotyping, we suggest ensembleCNV holds significant promise for performing genome-wide CNV association studies and investigating how CNVs predispose to human diseases.

Genetic regulation of the placental transcriptome underlies birth weight and risk of childhood obesity.

GWAS identified variants associated with birth weight (BW), childhood obesity (CO) and childhood BMI (CBMI), and placenta is a critical organ for fetal development and postnatal health. We examined the role of placental transcriptome and eQTLs in mediating the genetic causes for BW, CO and CBMI, and applied integrative analysis (Colocalization and MetaXcan). GWAS loci associated with BW, CO, and CBMI were substantially enriched for placenta eQTLs (6.76, 4.83 and 2.26 folds, respectively). Importantly, compared to eQTLs of adult tissues, only placental eQTLs contribute significantly to both anthropometry outcomes at birth (BW) and childhood phenotypes (CO/CBMI). Eight, six and one transcripts colocalized with BW, CO and CBMI risk loci, respectively. Our study reveals that placental transcription in utero likely plays a key role in determining postnatal body size, and as such may hold new possibilities for therapeutic interventions to prevent childhood obesity.

Genetic architecture of cardiometabolic risks in people living with HIV.

BACKGROUND: Advances in antiretroviral therapies have greatly improved the survival of people living with human immunodeficiency virus (HIV) infection (PLWH); yet, PLWH have a higher risk of cardiovascular disease than those without HIV. While numerous genetic loci have been linked to cardiometabolic risk in the general population, genetic predictors of the excessive risk in PLWH are largely unknown. METHODS: We screened for common and HIV-specific genetic variants associated with variation in lipid levels in 6284 PLWH (3095 European Americans [EA] and 3189 African Americans [AA]), from the Centers for AIDS Research Network of Integrated Clinical Systems cohort. Genetic hits found exclusively in the PLWH cohort were tested for association with other traits. We then assessed the predictive value of a series of polygenic risk scores (PRS) recapitulating the genetic burden for lipid levels, type 2 diabetes (T2D), and myocardial infarction (MI) in EA and AA PLWH. RESULTS: We confirmed the impact of previously reported lipid-related susceptibility loci in PLWH. Furthermore, we identified PLWH-specific variants in genes involved in immune cell regulation and previously linked to HIV control, body composition, smoking, and alcohol consumption. Moreover, PLWH at the top of European-based PRS for T2D distribution demonstrated a > 2-fold increased risk of T2D compared to the remaining 95% in EA PLWH but to a much lesser degree in AA. Importantly, while PRS for MI was not predictive of MI risk in AA PLWH, multiethnic PRS significantly improved risk stratification for T2D and MI. CONCLUSIONS: Our findings suggest that genetic loci involved in the regulation of the immune system and predisposition to risky behaviors contribute to dyslipidemia in the presence of HIV infection. Moreover, we demonstrate the utility of the European-based and multiethnic PRS for stratification of PLWH at a high risk of cardiometabolic diseases who may benefit from preventive therapies.

Sex-specific peripheral and central responses to stress-induced depression and treatment in a mouse model.

Major depressive disorder affects ~20% of the world population and is characterized by strong sexual dimorphism with females being two to three times more likely to develop this disorder. Previously, we demonstrated that a combination therapy with dihydrocaffeic acid and malvidin-glucoside to synergistically target peripheral inflammation and stress-induced synaptic maladaptation in the brain was effective in alleviating chronic social defeat stress (CSDS)-induced depression-like phenotype in male mice. Here, we test the combination therapy in a female CSDS model for depression and compared sex-specific responses to stress in the periphery and the central nervous system. Similar to male mice, the combination treatment is also effective in promoting resilience against the CSDS-induced depression-like behavior in female mice. However, there are sex-specific differences in peripheral immune responses and differential gene regulation in the prefrontal cortex to chronic stress and to the treatment. These data indicate that while therapeutic approaches to combat stress-related disorders may be effective in both sexes, the mechanisms underlying these effects differ, emphasizing the need for inclusion of both sexes in preclinical studies using animal models.

Prenatal exposure to ambient air multi-pollutants significantly impairs intrauterine fetal development trajectory.

BACKGROUND: Impaired in utero fetal growth trajectory may have long term health consequences of the newborns and increase risk of adulthood metabolic diseases. Prenatal exposure to air pollution has been linked to fetal development restriction; however, the impact of exposure to ambient air pollutants on the entire course of intrauterine fetal development has not been comprehensively investigated. METHODS: During 2015-2018, two cohorts of mother-infant dyads (N = 678 and 227) were recruited in Shanghai China, from which three categories of data were systematically collected: (1) daily exposure to six air pollutants during pregnancy, (2) fetal biometry in the 2nd (gestational week 24, [GW24]) and 3rd trimester (GW36), and (3) neonatal outcomes at birth. We investigated the impact of prenatal exposure to air pollutant mixture on the trajectory of fetal development during the course of gestation, adjusting for a broad set of potential confounds. RESULTS: Prenatal exposure to PM2.5, PM10, SO2 and O3 significantly reduced fetal biometry at GW24, where SO2 had the most potent effect. For every 10 µg/m3 increment increase of daily SO2 exposure during the 1st trimester shortened femur length by 2.20 mm (p = 6.7E-21) translating to 5.3% reduction from the average of the study cohort. Prenatal air pollution exposure also decreased fetal biometry at GW36 with attenuated effect size. Comparing to the lowest exposed quartile, fetus in the highest exposed quartile had 6.3% (p = 3.5E-5) and 2.1% (p = 2.4E-3) lower estimated intrauterine weight in GW24 and GW36, respectively; however, no difference in birth weight was observed, indicating a rapid catch-up growth in the 3rd trimester. CONCLUSIONS: To our knowledge, for the first time, we demonstrated the impact of prenatal exposure to ambient air pollutants on the course of intrauterine fetal development. The altered growth trajectory and rapid catch-up growth in associated with high prenatal exposure may lead to long-term predisposition for adulthood metabolic disorders.

Airway microbiome is associated with respiratory functions and responses to ambient particulate matter exposure.

BACKGROUND: Ambient particulate matter (PM) exposure has been associated with respiratory function decline in epidemiological studies. We hypothesize that a possible underlying mechanism is the perturbation of airway microbiome by PM exposure. METHODS: During October 2016-October 2017, on two human cohorts (n = 115 in total) in Shanghai China, we systematically collected three categories of data: (1) respiratory functions, (2) airway microbiome from sputum, and (3) PM2.5 (PM of ≤ 2.5 µm in diameter) level in ambient air. We investigated the impact of PM2.5 on airway microbiome as well as the link between airway microbiome and respiratory functions using linear mixed regression models. RESULTS: The respiratory function of our primary interest includes forced vital capacity (FVC) and forced expiratory volume in 1st second (FEV1). FEV1/FVC, an important respiratory function trait and key diagnosis criterion of COPD, was significantly associated with airway bacteria load (p = 0.0038); and FEV1 was associated with airway microbiome profile (p = 0.013). Further, airway microbiome was significantly influenced by PM2.5 exposure (p = 4.48E-11). CONCLUSIONS: To our knowledge, for the first time, we demonstrated the impact of PM2.5 on airway microbiome, and reported the link between airway microbiome and respiratory functions. The results expand our understanding on the scope of PM2.5 exposure's influence on human respiratory system, and point to novel etiological mechanism of PM2.5 exposure induced diseases.

Bio3Air, an integrative system for monitoring individual-level air pollutant exposure with high time and spatial resolution.

BACKGROUND: Air pollution is a leading cause of global disease burden. Lack of suitable methods for long term measuring exposure level at individual level is crippling environmental epidemiology research of air pollution. METHODS: We report an integrative system, Bio3Air, for long term measurement of individual level air pollution exposure, currently focusing on ambient particulate matter (PM). The novel system in real-time quantifies individual's outdoor/indoor status, geological location, lung ventilation rate and PM concentration of individual's surrounding environment, and these metrics are subsequently incorporated in calculating PM exposure. RESULTS: The system is fully developed and tested in China, USA and Canada, and has been successfully applied in epidemiology study. Bio3Air offers high reliability, sensitivity, reproducibility (>99%) and accuracy. It has high time- and spatial- resolution (≤ 2 min and ≤ 20 m, respectively). Bio3Air achieved 91.89% consistency with "gold-standard" method (membrane collection and off-line analysis). CONCLUSIONS: Bio3Air represents a substantial methodological advance in environmental health research of air pollution. It captures information relevant in measuring individual's PM exposure (e.g. real-time outdoor/indoor status, location and lung ventilation rate). Such information is typically missed by conventional approaches. Additional features of Bio3Air include easy-to-use, cost-effectiveness and automated data collection, making it a powerful tool facilitating studies of air pollution exposure and health consequences.

A Comprehensive Database and Analysis Framework To Incorporate Multiscale Data Types and Enable Integrated Analysis of Bioactive Polyphenols.

The development of a given botanical preparation for eventual clinical application requires extensive, detailed characterizations of the chemical composition, as well as the biological availability, biological activity, and safety profiles of the botanical. These issues are typically addressed using diverse experimental protocols and model systems. Based on this consideration, in this study we established a comprehensive database and analysis framework for the collection, collation, and integrative analysis of diverse, multiscale data sets. Using this framework, we conducted an integrative analysis of heterogeneous data from in vivo and in vitro investigation of a complex bioactive dietary polyphenol-rich preparation (BDPP) and built an integrated network linking data sets generated from this multitude of diverse experimental paradigms. We established a comprehensive database and analysis framework as well as a systematic and logical means to catalogue and collate the diverse array of information gathered, which is securely stored and added to in a standardized manner to enable fast query. We demonstrated the utility of the database in (1) a statistical ranking scheme to prioritize response to treatments and (2) in depth reconstruction of functionality studies. By examination of these data sets, the system allows analytical querying of heterogeneous data and the access of information related to interactions, mechanism of actions, functions, etc., which ultimately provide a global overview of complex biological responses. Collectively, we present an integrative analysis framework that leads to novel insights on the biological activities of a complex botanical such as BDPP that is based on data-driven characterizations of interactions between BDPP-derived phenolic metabolites and their mechanisms of action, as well as synergism and/or potential cancellation of biological functions. Out integrative analytical approach provides novel means for a systematic integrative analysis of heterogeneous data types in the development of complex botanicals such as polyphenols for eventual clinical and translational applications.

Meta-eQTL: a tool set for flexible eQTL meta-analysis.

BACKGROUND: Increasing number of eQTL (Expression Quantitative Trait Loci) datasets facilitate genetics and systems biology research. Meta-analysis tools are in need to jointly analyze datasets of same or similar issue types to improve statistical power especially in trans-eQTL mapping. Meta-analysis framework is also necessary for ChrX eQTL discovery. RESULTS: We developed a novel tool, meta-eqtl, for fast eQTL meta-analysis of arbitrary sample size and arbitrary number of datasets. Further, this tool accommodates versatile modeling, eg. non-parametric model and mixed effect models. In addition, meta-eqtl readily handles calculation of chrX eQTLs. CONCLUSIONS: We demonstrated and validated meta-eqtl as fast and comprehensive tool to meta-analyze multiple datasets and ChrX eQTL discovery. Meta-eqtl is a set of command line utilities written in R, with some computationally intensive parts written in C. The software runs on Linux platforms and is designed to intelligently adapt to high performance computing (HPC) cluster. We applied the novel tool to liver and adipose tissue data, and revealed eSNPs underlying diabetes GWAS loci.

The transcriptomic and biochemical responses of blood clams (Tegillarca granosa) to prolonged intermittent hypoxia.

The blood clam (Tegillarca granosa), a marine bivalve of ecological and economic significance, often encounters intermittent hypoxia in mudflats and aquatic environments. To study the response of blood clam foot to prolonged intermittent hypoxia, the clams were exposed to intermittent hypoxia conditions (0.5 mg/L dissolved oxygen, with a 12-h interval) for 31 days. Initially, transcriptomic analysis was performed, uncovering a total of 698 differentially expressed genes (DEGs), with 236 upregulated and 462 downregulated. These genes show enrichments in signaling pathways related to glucose metabolism, sugar synthesis and responses to oxidative stress. Furthermore, the activity of the enzyme glutathione peroxidase (GPx) and the levels of gpx1 mRNA showed gradual increases, reaching their peak on the 13th day of intermittent hypoxia exposure. This observation suggests an indirect protective role of GPx against oxidative stress. The results of this study make a significantly contribute to our broader comprehensive of the physiological, biochemical responses, and molecular reactions governing the organization of foot muscle tissue in marine bivalves exposed to prolonged intermittent hypoxic conditions.

RNA-seq analysis reveals prenatal alcohol exposure is associated with placental inflammatory cells and gene expression.

BACKGROUND: Fetal alcohol spectrum disorders (FASD) are the most common preventable cause of birth defects and neurodevelopmental disorders worldwide. The placenta is the crucial interface between mother and fetus. Prenatal alcohol exposure (PAE) has been shown to alter placental structure and expression of genes in bulk placental tissue samples, but prior studies have not examined effects on placental cell-type composition or taken cell-type into consideration in transcriptome analyses. METHODS: We leveraged an existent placenta single-cell RNA-seq dataset to perform cell-type deconvolution of bulk placental RNA-seq data from 35 heavy drinking pregnant women and 33 controls in a prospective birth cohort in Cape Town, South Africa. We used bivariate analyses and multivariable adjusted linear regression models to assess the relation of PAE on inferred placental cell-type proportions. We also examined differential expression of inflammatory response genes and PAE, using multivariable adjusted linear models. RESULTS: Deconvolution analyses showed heterogeneous placenta cell-type composition in which stromal (27 %), endothelial (26 %) and cytotrophoblasts (18 %) were the predominant cell-types. PAE around conception was associated with a higher proportion of Hofbauer cells (B = 0.51, p = 0.035) in linear models adjusted for maternal age, infant sex, and gestational age. Among the 652 inflammatory genes examined, 35 were differential expressed in alcohol exposed placentas (FDR p < 0.05). CONCLUSIONS: Our findings suggest that heavy alcohol exposure during pregnancy can influence the proportion of fetal placental villi macrophages (Hofbauer cells) and increased expression of inflammatory genes. Future studies are needed to further characterize these effects and to assess the potential functional roles of placental inflammation in FASD.

Prenatal alcohol exposure is associated with changes in placental gene co-expression networks.

Alcohol consumption during pregnancy can result in a range of adverse postnatal outcomes among exposed children. However, identifying at-risk children is challenging given the difficulty to confirm prenatal alcohol exposure and the lack of early diagnostic tools. Placental surveys present an important opportunity to uncover early biomarkers to identify those at risk. Here, we report the first transcriptome-wide evaluation to comprehensively evaluate human placental pathways altered by fetal alcohol exposure. In a prospective longitudinal birth cohort in Cape Town, South Africa, we performed bulk tissue RNAseq in placenta samples from 32 women reporting heavy drinking during pregnancy and 30 abstainers/light drinkers. Weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis were performed to assess associations between fetal alcohol exposure and placental gene expression patterns at a network-wide and single gene level, respectively. The results revealed altered expression in genes related to erythropoiesis and angiogenesis, which are implicated in established postnatal phenotypes related to alcohol exposure, including disruptions in iron homeostasis, growth, and neurodevelopment. The reported findings provide insights into the molecular pathways affected by prenatal alcohol exposure and highlight the potential of placental biomarkers for detecting and understanding the effects of alcohol on fetal development.