Prenatal Gut Microbiota Predicts Temperament in Offspring at 1-2 Years.

The purpose of this study was to explore whether prenatal gut microbiota (GM) and its functions predict the development of offspring temperament. A total of 53 mothers with a 1-year-old child and 41 mothers with a 2-year-old child were included in this study using a mother-infant cohort from central China. Maternal fecal samples collected during the third trimester were analyzed using 16S rRNA V3-V4 gene sequences. Temperament of the child was measured by self-reported data according to the primary caregiver. The effects of GM in mothers on offspring's temperament were evaluated using multiple linear regression models. The results demonstrated that the alpha diversity index Simpson of prenatal GM was positively associated with the activity level of offspring at 1 year (adj. P = .036). Bifidobacterium was positively associated with high-intensity pleasure characteristics of offspring at 1 year (adj. P = .031). Comparatively, the presence of Bifidobacterium found in the prenatal microbiome was associated with low-intensity pleasure characteristics in offspring at 2 years (adj. P = .031). There were many significant associations noted among the functional pathways of prenatal GM and temperament of offspring at 2 years. Our findings support the maternal-fetal GM axis in the setting of fetal-placental development with subsequent postnatal neurocognitive developmental outcomes, and suggest that early childhood temperament is in part associated with specific GM in the prenatal setting.

Short-term exposures to PM2.5, PM2.5 chemical components, and antenatal depression: Exploring the mediating roles of gut microbiota and fecal short-chain fatty acids.

BACKGROUND: PM2.5 and its chemical components increase health risks and are associated with depression and gut microbiota. However, there is still limited evidence on whether gut microbiota and short-chain fatty acids (SCFAs) mediate the association between PM2.5, PM2.5 chemical components, and antenatal depression. The purpose of this study was to investigate the mediating role of maternal gut microbiota in correlations between short-term exposure to PM2.5, short-term exposure to PM2.5 chemical components, and antenatal depression. METHODS: Demographic information and stool samples were collected from 75 pregnant women in their third trimester. Their exposure to PM2.5 and PM2.5 chemical components was measured. Participants were divided into the non-antenatal depression group or the antenatal depression group according to the cut-off of 10 points on the Edinburgh Postnatal Depression Scale (EPDS). The gut microbiota were analyzed using the 16 S rRNA-V3/V4 gene sequence, and the concentration of PM2.5 and its chemical components was calculated using the Tracking Air Pollution in China (TAP) database. Gas chromatography-mass spectrometry was used to analyze SCFAs in stool samples. In order to assess the mediating effects of gut microbiota and SCFAs, mediation models were utilized. RESULTS: There were significant differences between gut microbial composition and SCFAs concentrations between the non-antenatal depression group and the antenatal depression group. PM2.5 and its chemical components were positively associated with EPDS scores and negatively associated with genera Enterococcus and Enterobacter. Genera Candidatus_Soleaferrea (ß = -7.21, 95%CI -11.00 to -3.43, q = 0.01) and Enterococcus (ß = -2.37, 95%CI -3.87 to -0.87, q = 0.02) were negatively associated with EPDS scores, indicating their potential protective effects against antenatal depression. There was no significant association between SCFAs and EPDS scores. The mediating role of Enterococcus between different lagged periods of PM2.5, PM2.5 chemical component exposure, and antenatal depression was revealed. For instance, Enterococcus explained 29.23% (95%CI 2.16-87.13%, p = 0.04) of associations between PM2.5 exposure level at the day of sampling (lag 0) and EPDS scores. CONCLUSION: Our study highlights that Enterococcus may mediate the associations between PM2.5, PM2.5 chemical components, and antenatal depression. The mediating mechanism through which the gut microbiota influences PM2.5-induced depression in pregnant women still needs to be further studied.

Perinatal depression and infant and toddler neurodevelopment: A systematic review and meta-analysis.

Many studies have focused on the effect of perinatal depression on neurodevelopment among children and adolescents. However, only a few studies have explored this relationship in infants and toddlers with inconsistent results. We performed a systematic review and meta-analysis to evaluate the association between perinatal depression and infant and toddler neurodevelopment during the first two postnatal years. Twenty-three studies were included in this meta-analysis. Perinatal depression was associated with poorer cognitive (Cohen's d = -0.19, SE= 0.06, 95% CI = -0.30 to -0.08), language (Cohen's d = -0.24, SE = 0.09, 95% CI = -0.40 to -0.07), and motor (Cohen's d = -0.15, SE = 0.05, 95% CI = -0.26 to -0.05) development. Subgroup analyses showed that the types of maternal depression (prenatal depression vs. postnatal depression), the method of measuring maternal depression (rating scale vs. diagnostic interview), and the time interval between assessment of exposure and outcome had an impact on the observed effect about neurodevelopment of infants and toddlers. In addition, the results of our study pointed to a stronger significant association between prenatal depression and cognitive, language, and motor delays in infants and toddlers, whereas the association between postnatal depression and cognitive, language, and motor delays in infants and toddlers was not statistically significant. In conclusion, this study provided convincing evidence that the perinatal window is a sensitive period for offspring neurodevelopment.

Alterations of the gut microbiota and fecal short-chain fatty acids in women undergoing assisted reproduction.

CONTEXT: The community structure of gut microbiota changes during pregnancy, which also affects the synthesis of short-chain fatty acids (SCFAs). However, the distribution of gut microbiota composition and metabolite SCFA levels are poorly understood in women undergoing assisted reproductive technology (ART). AIMS: To evaluate the changes in gut microbiota composition and metabolic SCFAs in women who received assisted reproduction treatment. METHODS: Sixty-three pregnant women with spontaneous pregnancy (SP) and nine with ART pregnancy were recruited to provide fecal samples. Gut microbiota abundance and SCFA levels were determined by 16S ribosomal RNA (rRNA) gene amplicon sequencing and gas chromatography-mass spectrometry (GC-MS). KEY RESULTS: The ART group showed decreased alpha diversity (the species richness or evenness in a sample). The principal coordinates analysis (a method of analysing beta diversity) showed significant difference in gut microbiota between the ART group versus the SP group (unweighted UniFrac distance, R 2 =0.04, P =0.003). Proteobacteria , Blautia and Escherichia-Shigella were enriched in the ART group, whereas the relative abundance of beneficial intestinal bacteria Faecalibacterium was lower than in the SP group. Different modes of conception were associated with several SCFAs (valeric acid (r =-0.280; P =0.017); isocaproic acid (r =-0.330; P =0.005); caproic acid (r =-0.336; P =0.004)). Significantly different SCFAs between the two groups were synchronously associated with the differential gut microbiota. CONCLUSIONS: The diversity and abundance of gut microbiota and the levels of SCFAs in women undergoing ART decreased. IMPLICATIONS: The application of ART shaped the microbial composition and metabolism, which may provide critical information for understanding the biological changes that occur in women with assisted reproduction.

Predictors of body image dissatisfaction among women at different stages of pregnancy:A cross-sectional study.

OBJECTIVE: To explore the levels and predictors of body image dissatisfaction among women at different stages of pregnancy. DESIGN: This was a cross-sectional study design. SETTING AND PARTICIPANTS: A total of 863 Chinese pregnant women were recruited from a tertiary hospital via a convenience sampling method. MEASUREMENT AND FINDINGS: Eligible participants completed a demographic questionnaire and self-reported measures of body image dissatisfaction, pregnancy-related anxiety, prenatal depression, and appearance comparison. Results showed no statistical difference in body image dissatisfaction levels among early-mid pregnancy (47.6 ± 6.17), late-mid pregnancy (47.3 ± 7.56), and late pregnancy stages (48.4 ± 6.22). The generalized linear model showed that gestational weight gain, pregnancy-related anxiety, own/family's perception of pregnancy weight, and current ideal weight change were predictors of body image dissatisfaction in the early-mid pregnancy stage. In addition, pre-pregnancy BMI, appearance comparison, own /family's perception of pregnancy weight, current ideal weight change, and overeating during pregnancy significantly predicted body image dissatisfaction in the late-mid pregnancy stage. Predictors of body image dissatisfaction in the late pregnancy stage comprised planned pregnancy, pre-pregnancy eating disorders, own perception of pregnancy weight, current ideal weight change, pregnancy-related anxiety, and prenatal depression. KEY CONCLUSION AND IMPLICATION FOR PRACTICE: The findings suggest that predictors of body image dissatisfaction differed according to pregnancy stage. Self-perception of pregnancy weight was primary predictor of body image dissatisfaction. Healthcare professionals are recommended to provide prenatal health education to reduce own/family's negative perception of pregnancy weight, so as to alleviate the body image dissatisfaction level of pregnant women.

Association between gut microbiota and its functional metabolites with prenatal depression in women.

Background: The gut microbiota may affect mood through the microbiota-gut-brain axis. The purpose of this study was to examine the effect of the gut microbiota and its metabolites, such as short-chain fatty acids (SCFAs), on prenatal depression and to determine the role of 5-hydroxytryptamine (5-HT) on prenatal depression in association with the gut microbiota and its metabolites (i.e. SCFAs). Methods: Eighty-six pregnant women in the third trimester were recruited. Prenatal depression was determined by a score of 10 via the Edinburgh Postpartum Depression Scale. Demographic data, stool, and blood samples were collected. The gut microbiota and its metabolites SCFAs were determined by 16S rRNA gene sequencing and liquid chromatography-mass spectrometry analysis. Plasma 5-HT was determined by gas chromatography-mass spectrometry analysis. Results: After controlling relevant covariates, our results found the higher the abundance of Candidatus_Soleaferrea, the lower the risk of prenatal depression; the higher the concentration of propanoic acid, the higher risk of prenatal depression. Our results also found the lower the plasma 5-HT, the higher the risk of prenatal depression, and 5-HT was related to unclassified_c_Clostridia and NK4A214_group. However, results of this study did not support the moderating effect of plasma 5-HT on the association of Candidatus_Soleaferrea or propionic acid with prenatal depression. Conclusions: Results of this study supported that changes in certain gut microbiota, SCFAs, and plasma 5-HT during pregnancy were associated with prenatal depression. This finding provides new ideas for interventions based on diet or probiotics to regulate mood during pregnancy.

Enhancing length of stay prediction by learning similarity-aware representations for hospitalized patients.

This paper focuses on predicting the length of stay for patients on the first day of admission and propose a predictive model named DGLoS. In order to capture the influence of various complex factors on the length of stay as well as the dependencies among various factors, DGLoS uses a deep neural network to model both the patient information and diagnostic information. Targeting at different attribution types, we utilize different coding methods to convert raw data to the input features. Besides, we find that similar patients have closer lengths of stay. Therefore, we further design a module based on graph representation learning to generate patients' similarity-aware representations, capturing the similarity between patients and therefore enhancing predictions. These similarity-aware representations are incorporated into the output of the deep neural network to jointly perform the prediction. We have conducted comprehensive experiments on a real-world hospitalization dataset. The performance comparison shows that our proposed DGLoS model improves predictive performance and the significance test demonstrates the improvement is significant. The ablation study verifies the effectiveness of each of the proposed components and the hyper-parameter investigation shows the robustness of the proposed model.

Effects of psychosocial sleep interventions on improving infant sleep and maternal sleep and mood: A systematic review and meta-analysis.

Infant sleep problems are prevalent and have a negative impact on infant growth and development, maternal sleep, and maternal mood. The effects of psychosocial sleep interventions on infant sleep and maternal sleep and mood are unclear. This study aimed to systematically evaluate the effects of psychosocial sleep interventions on improving infant sleep, including nocturnal total sleep time, daytime total sleep, total sleep time, night wakings, and maternal sleep and mood problems (ie, depression and fatigue). We searched PubMed, Web of Science, Cochrane Library, Embase, EBSCO, OpenGrey, DeepBlue, China National Knowledge Infrastructure, and Wanfang databases. We focused on randomized controlled trials examining the effectiveness of psychosocial sleep interventions on infant sleep. The study was preregistered at the International Prospective Register of Systematic Reviews (CRD42022301654). Thirteen studies from 5889 articles were included in the review, which found that psychosocial sleep interventions improved infant nocturnal total sleep time (0.28 [0.04-0.52], p < 0.05, I2 = 83.9%) and maternal depression (-0.10 [-0.28 to -0.08], p < 0.05, I2 = 8.7%). To test and explore heterogeneity, we used the I2 statistic, influence analysis, subgroup analyses, and subgroup meta-analyses. Funnel plots and Egger's tests revealed no evidence of publication bias. Psychosocial sleep interventions improved infant nocturnal total sleep time and maternal depression. Future research should include more randomized controlled trials examining the effect of psychosocial sleep interventions on the improvement of maternal sleep and fatigue.

Cumulative and lagged effects of varying-sized particulate matter exposure associates with toddlers' gut microbiota.

Particulate matter (PM) is an important component of air pollutants and is associated with various health risks. However, the impact of PM on toddlers' gut microbiota is rarely investigated. This study aimed to assess the cumulative and lagged effects of varying-sized PMs on toddlers' gut microbiota. We collected demographic information, stool samples, and exposure to PM from 36 toddlers aged 2-3 years. The toddlers were divided into warm season group and cooler season group according to the collection time of stool samples. The gut microbiota was processed and analyzed using 16S rRNA V3-V4 gene regions. The concentration of PM was calculated using China High Air Pollutants (CHAP) database. To assess the mixed effects of varying-sized PM, multiple-PM models were utilized. There were significant differences between the community composition, α- and ß-diversity between two groups. In multiple-PM models, there was a significant effect of weight quantile sum (PM1, PM2.5, and PM10) on α-diversity indices. In weight quantile sum models, after adjusting for a priori confounders, we found a negative effect of weight quantile sum on Enterococcus (ß = -0.134, 95% CI -0.263 to -0.006), positive effects of weight quantile sum on unclassified_f__Ruminococcaceae (ß = 0.247, 95% CI 0.102 to 0.393), Ruminococcus_1 (ß = 0.444, 95% CI 0.238 to 0.650), unclassified_f__Lachnospiraceae (ß = 0.278, 95% CI 0.099 to 0.458), and Family_XIII_AD_3011_group (ß = 0.254, 95% CI 0.086 to 0.422) in WSG and CSG. In lagged weight quantile sum models, the correlation between lag time PM levels and the gut microbiota showed seasonal trends, and weights of PM changed with lag periods. This is the first study to highlight that cumulative and lagged effects of PMs synergistically affect the diversities (α- and ß-diversity) and abundance of the gut microbiota in toddlers. Further research is needed to explore the mediating mechanism of varying-sized PMs exposure on the gut microbiota in toddlers.

Inflammatory cytokines and prenatal depression: Is there a mediating role of maternal gut microbiota?

OBJECTIVE: The mechanism of levels of inflammatory cytokines that affects brain function and mood through gut microbiota has not been fully elucidated. This study aimed to investigate the potential mediating role of gut microbiota between maternal inflammatory cytokines levels and prenatal depression. DESIGN: There were 29 women in the prenatal depression group and 27 women in the control group enrolled in this study. The Edinburgh Postnatal Depression Scale (EPDS) score of 10 was considered the cut-off value for prenatal depression. We collected demographic information, stool and blood samples. The gut microbiota was profiled using V3-V4 gene sequence of 16S rRNA, and the concentration of inflammatory cytokines were analyzed. The mediation model was analyzed by using the model 4 in the process procedure for SPSS. RESULTS: There were significance differences in the concentration of interleukin-1beta (IL-1ß)(Z = -2.383, P = 0.017) and IL-17A (Z = -2.439, P = 0.015) between the prenatal depression group and control group. There was no significant difference in α- diversity and ß-diversity between the two groups. Intestinibacter (OR: 0.012; 95% CI, 0.001-0.195) and Escherichia_Shigella (OR: 0.103; 95% CI, 0.014-0.763) were protective factors for prenatal depression, while Tyzzerella (OR: 17.941; 95% CI, 1.764-182.445) and Unclassified_f_Ruminococcaceae (OR: 22.607; 95% CI, 1.242-411.389) were risk factors. And Intestinibacter play a mediation effect between IL-17A and prenatal depression. CONCLUSION: Maternal gut microbiota is a significant mediator of the relationship between inflammatory cytokines and prenatal depression. Further research is still needed in exploring the mediating mechanisms of gut microbiota between inflammatory cytokines and depression.

Does PM1 exposure during pregnancy impact the gut microbiota of mothers and neonates?

BACKGROUND: Ambient air pollutant exposure can change the composition of gut microbiota at 6-months of age, but there is no epidemiological evidence on the impacts of exposure to particulate matter with an aerodynamic diameter ≤1 µm (PM1) during pregnancy on gut microbiota in mothers and neonates. We aimed to determine if gestational PM1 exposure is associated with the gut microbiota of mothers and neonates. METHODS: Leveraging a mother-infant cohort from the central region of China, we estimated the exposure concentrations of PM1 during pregnancy based on residential address records. The gut microbiota of mothers and neonates was analyzed using 16 S rRNA V3-V4 gene sequences. Functional pathway analyses of 16 S rRNA V3-V4 bacterial communities were conducted using Tax4fun. The impact of PM1 exposure on α-diversity, composition, and function of gut microbiota in mothers and neonates was evaluated using multiple linear regression, controlling for nitrogen dioxide (NO2) and ozone (O3). Permutation multivariate analysis of variance (PERMANOVA) was used to analyze the interpretation degree of PM1 on the sample differences at the OTU level using the Bray-Curtis distance algorithm. RESULTS: Gestational PM1 exposure was positively associated with the α-diversity of gut microbiota in neonates and explained 14.8% (adj. P = 0.026) of the differences in community composition among neonatal samples. In contrast, gestational PM1 exposure had no impact on the α- and ß-diversity of gut microbiota in mothers. Gestational PM1 exposure was positively associated with phylum Actinobacteria of gut microbiota in mothers, and genera Clostridium_sensu_stricto_1, Streptococcus, Faecalibacterium of gut microbiota in neonates. At Kyoto Encyclopedia of Genes and Genomes pathway level 3, the functional analysis results showed that gestational PM1 exposure significantly down-regulated Nitrogen metabolism in mothers, as well as Two-component system and Pyruvate metabolism in neonates. While Purine metabolism, Aminoacyl-tRNA biosynthesis, Pyrimidine metabolism, and Ribosome in neonates were significantly up-regulated. CONCLUSIONS: Our study provides the first evidence that exposure to PM1 has a significant impact on the gut microbiota of mothers and neonates, especially on the diversity, composition, and function of neonatal meconium microbiota, which may have important significance for maternal health management in the future.

Changes in the gut microbiome in the first two years of life predicted the temperament in toddlers.

BACKGROUND: Temperament has been shown to be associated with the change of gut microbiome. There were no longitudinal studies to explore the role of gut microbiome changes in the development of temperament in toddlers. METHODS: This study used longitudinal cohort to investigate the associations between changes in gut microbiome and temperament in toddlers in the first two years of life. Linear regression analysis and microbiome multivariate association with linear models were used to investigate the associations between the gut microbiome and toddlers' temperament. RESULTS: In total, 41 toddlers were analyzed. This study found both Shannon and Chao-1 indices at birth were negatively correlated with the sadness dimension; the higher the Shannon and Chao-1 indices at 6 months, the lower the surgency/extraversion dimension scores; the higher the Shannon and Chao-1 indices at 2 years of ages, the lower the cuddliness dimension scores. After adjusting for covariates, beta diversity at birth was strongly associated with the negative affectivity dimension; beta diversity at 1 year of age was strongly associated with the activity level dimension; and beta diversity at 2 years of age was strongly associated with the discomfort and soothability dimension. Compared to Bifidobacterium cluster, this study also found Bacteroides cluster was associated with lower negative affectivity and its sub-dimensions frustration and sadness scores in toddlers. LIMITATIONS: Generalizability of the results remains to be determined. CONCLUSION: Results of this study confirmed the associations between changes in the gut microbiome diversity and composition in the first two years of life and toddlers' temperament.

The associations of maternal and children's gut microbiota with the development of atopic dermatitis for children aged 2 years.

Background: It is critical to investigate the underlying pathophysiological mechanisms in the development of atopic dermatitis. The microbiota hypothesis suggested that the development of allergic diseases may be attributed to the gut microbiota of mother-offspring pairs. The purpose of this study was to investigate the relationship among maternal-offspring gut microbiota and the subsequent development of atopic dermatitis in infants and toddlers at 2 years old. Methods: A total of 36 maternal-offspring pairs were enrolled and followed up to 2 years postpartum in central China. Demographic information and stool samples were collected perinatally from pregnant mothers and again postpartum from their respective offspring at the following time intervals: time of birth, 6 months, 1 year and 2 years. Stool samples were sequenced with the 16S Illumina MiSeq platform. Logistic regression analysis was used to explore the differences in gut microbiota between the atopic dermatitis group and control group. Results: Our results showed that mothers of infants and toddlers with atopic dermatitis had higher abundance of Candidatus_Stoquefichus and Pseudomonas in pregnancy and that infants and toddlers with atopic dermatitis had higher abundance of Eubacterium_xylanophilum_group at birth, Ruminococcus_gauvreauii_group at 1 year and UCG-002 at 2 years, and lower abundance of Gemella and Veillonella at 2 years. Additionally, the results demonstrated a lower abundance of Prevotella in mothers of infants and toddlers with atopic dermatitis compared to mothers of the control group, although no statistical difference was found in the subsequent analysis. Conclusion: The results of this study support that gut microbiota status among mother-offspring pairs appears to be associated with the pathophysiological development of pediatric atopic dermatitis.