Maternal Glycaemic and Insulinemic Status and Newborn DNA Methylation: Findings in Women With Overweight and Obesity

Consistent cord blood DNA methylation signatures of gestational age between South Asian and white European cohorts

BACKGROUND

Epigenetic modifications, particularly DNA methylation (DNAm) in cord blood, are an important biological marker of how external exposures during gestation can influence the in-utero environment and subsequent offspring development. Despite the recognized importance of DNAm during gestation, comparative studies to determine the consistency of these epigenetic signals across different ethnic groups are largely absent. To address this gap, we first performed epigenome-wide association studies (EWAS) of gestational age (GA) using newborn cord blood DNAm comparatively in a white European (n = 342) and a South Asian (n = 490) birth cohort living in Canada. Then, we capitalized on established cord blood epigenetic GA clocks to examine the associations between maternal exposures, offspring characteristics and epigenetic GA, as well as GA acceleration, defined as the residual difference between epigenetic and chronological GA at birth.

RESULTS

Individual EWASs confirmed 1,211 and 1,543 differentially methylated CpGs previously reported to be associated with GA, in white European and South Asian cohorts, respectively, with a similar distribution of effects. We confirmed that Bohlin's cord blood GA clock was robustly correlated with GA in white Europeans (r = 0.71; p = 6.0 × 10-54) and South Asians (r = 0.66; p = 6.9 × 10-64). In both cohorts, Bohlin's clock was positively associated with newborn weight and length and negatively associated with parity, newborn female sex, and gestational diabetes. Exclusive to South Asians, the GA clock was positively associated with the newborn ponderal index, while pre-pregnancy weight and gestational weight gain were strongly predictive of increased epigenetic GA in white Europeans. Important predictors of GA acceleration included gestational diabetes mellitus, newborn sex, and parity in both cohorts.

CONCLUSIONS

These results demonstrate the consistent DNAm signatures of GA and the utility of Bohlin's GA clock across the two populations. Although the overall pattern of DNAm is similar, its connections with the mother's environment and the baby's anthropometrics can differ between the two groups. Further research is needed to understand these unique relationships.

Maternal Obesity and Neonatal Metabolic Health: Insights Into Insulin Resistance

Background Maternal obesity is a global health concern that leads to metabolic alterations in the offspring, making them vulnerable to metabolic disorders in adulthood. Early identification of such neonates would provide opportunities to positively alter modifiable risk factors for non-communicable diseases (NCDs) to prevent their occurrence later in life. Objectives This study aimed to assess and contrast insulin resistance (IR) levels in neonates born to mothers with obesity and those born to healthy, non-obese mothers.  Methods This case-control study was conducted after approval from the institutional ethics committee. A total of 98 healthy, non-obese pregnant females were included in Group 1, and 68 obese pregnant females were included in Group 2. The participants were followed up until delivery and cord blood samples were collected after delivery. Neonatal glucose and insulin concentrations were estimated, and indices of IR such as homeostatic model assessment for insulin resistance (HOMA-IR), quantitative insulin-sensitivity check index (QUICKI), and glucose-to-insulin ratio were calculated. Neonatal IR indices and anthropometric measurements were compared between the groups using the Z test and correlated with the maternal pre-pregnancy body mass index (BMI) using Pearson's correlation. Additionally, Pearson's correlations were examined between neonatal IR indices and anthropometric measurements. Statistical significance was set at p <0.05. Results Neonates in Group 2 exhibited significantly higher anthropometric parameters and IR indices than those in Group 1. A statistically significant positive correlation was identified between maternal pre-pregnancy BMI, neonatal anthropometric parameters, and IR. Furthermore, a statistically significant positive correlation was observed between neonatal IR and the anthropometric parameters. Conclusion Neonates born to obese mothers exhibited higher anthropometric parameters and insulin resistance than those born to non-obese, healthy mothers. Assessment of IR at birth can help identify neonates who are at higher risk of developing NCD in later life. Timely promotion of a healthy lifestyle can reduce the occurrence of NCDs in later life.

Preconception dietary glycemic index and risk for large-for-gestational age births

OBJECTIVES

Diets with a high glycemic index (GI) leading to elevated postprandial glucose levels and hyperinsulinemia during pregnancy have been inconsistently linked to an increased risk for large-for-gestational-age (LGA) births. The effects of prepregnancy dietary GI on LGA risk are, to our knowledge, unknown. We examined the association of prepregnancy dietary GI with LGA births and joint associations of GI and maternal overweight/obesity and infant sex with LGA births among 10 188 infants born without congenital anomalies from 1997 to 2011, using data from the National Birth Defects Prevention Study (NBDPS). The aim of this study was to investigate this association among infants without major congenital anomalies (controls) who participated in the NBDPS and to evaluate how prepregnancy BMI and infant sex may modify this association on the additive scale.

METHODS

Dietary intake was ascertained using a 58-item food frequency questionnaire. We dichotomized dietary GI into high and low categories using spline regression models. Infants with a birth weight at or above the 90th percentile for gestational age and sex, according to a U.S. population reference, were considered LGA. We used logistic regression to obtain odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Of the infants, 859 (9%) had a high dietary GI (cut-point: 59), and 1244 infants (12%) were born LGA. Unadjusted analysis suggested an inverse association between high dietary GI and LGA (OR, 0.79; 95% CI, 0.62-0.99). No association was observed in multivariable models when comparing high dietary GI intake between LGA births and all other births (OR, 0.94; 95% CI, 0.74-1.20) or when excluding small-for-gestational-age (SGA) births (OR, 0.94; 95% CI, 0.73-1.19). No joint associations with maternal overweight/obesity or infant sex were observed.

CONCLUSION

High prepregnancy maternal GI was not associated with LGA births independently of or jointly with other factors.

Multigenerational diabetes mellitus

Gestational diabetes (GDM) changes the maternal metabolic and uterine environment, thus increasing the risk of short- and long-term adverse outcomes for both mother and child. Children of mothers who have GDM during their pregnancy are more likely to develop Type 2 Diabetes (T2D), early-onset cardiovascular disease and GDM when they themselves become pregnant, perpetuating a multigenerational increased risk of metabolic disease. The negative effect of GDM is exacerbated by maternal obesity, which induces a greater derangement of fetal adipogenesis and growth. Multiple factors, including genetic, epigenetic and metabolic, which interact with lifestyle factors and the environment, are likely to contribute to the development of GDM. Genetic factors are particularly important, with 30% of women with GDM having at least one parent with T2D. Fetal epigenetic modifications occur in response to maternal GDM, and may mediate both multi- and transgenerational risk. Changes to the maternal metabolome in GDM are primarily related to fatty acid oxidation, inflammation and insulin resistance. These might be effective early biomarkers allowing the identification of women at risk of GDM prior to the development of hyperglycaemia. The impact of the intra-uterine environment on the developing fetus, "developmental programming", has a multisystem effect, but its influence on adipogenesis is particularly important as it will determine baseline insulin sensitivity, and the response to future metabolic challenges. Identifying the critical window of metabolic development and developing effective interventions are key to our ability to improve population metabolic health.

The Effect of Maternal Diet and Physical Activity on the Epigenome of the Offspring

The aim of this review was to examine the current literature regarding the effect of maternal lifestyle interventions (i.e., diet and physical activity) on the epigenome of the offspring. PubMed, Scopus and Cochrane-CENTRAL were screened until 8 July 2023. Only randomized controlled trials (RCTs) where a lifestyle intervention was compared to no intervention (standard care) were included. Outcome variables included DNA methylation, miRNA expression, and histone modifications. A qualitative approach was used for the consideration of the studies' results. Seven studies and 1765 mother-child pairs were assessed. The most common types of intervention were dietary advice, physical activity, and following a specific diet (olive oil). The included studies correlated the lifestyle and physical activity intervention in pregnancy to genome-wide or gene-specific differential methylation and miRNA expression in the cord blood or the placenta. An intervention of diet and physical activity in pregnancy was found to be associated with slight changes in the epigenome (DNA methylation and miRNA expression) in fetal tissues. The regions involved were related to adiposity, metabolic processes, type 2 diabetes, birth weight, or growth. However, not all studies showed significant differences in DNA methylation. Further studies with similar parameters are needed to have robust and comparable results and determine the biological role of such modifications.

Expression Profile of New Marker Genes Involved in Differentiation of Human Wharton's Jelly-Derived Mesenchymal Stem Cells into Chondrocytes, Osteoblasts, Adipocytes and Neural-like Cells

Wharton's jelly (WJ) contains mesenchymal stem cells (MSCs) exhibiting broad immunomodulatory properties and differentiation capacity, which makes them a promising tool for cellular therapies. Although the osteogenic, chondrogenic and adipogenic differentiation is a gold standard for proper identification of MSCs, it is important to elucidate the exact molecular mechanisms governing these processes to develop safe and efficient cellular therapies. Umbilical cords were collected from healthy, full-term deliveries, for subsequent MSCs (WJ-MSCs) isolation. WJ-MSCs were cultivated in vitro for osteogenic, chondrogenic, adipogenic and neurogenic differentiation. The RNA samples were isolated and the transcript levels were evaluated using NovaSeq platform, which led to the identification of differentially expressed genes. Expression of H19 and SLPI was enhanced in adipocytes, chondrocytes and osteoblasts, and NPPB was decreased in all analyzed groups compared to the control. KISS1 was down-regulated in adipocytes, chondrocytes, and neural-like cells compared to the control. The most of identified genes were already implicated in differentiation of MSCs; however, some genes (PROK1, OCA2) have not yet been associated with initiating final cell fate. The current results indicate that both osteo- and adipo-induced WJ-MSCs share many similarities regarding the most overexpressed genes, while the neuro-induced WJ-MSCs are quite distinctive from the other three groups. Overall, this study provides an insight into the transcriptomic changes occurring during the differentiation of WJ-MSCs and enables the identification of novel markers involved in this process, which may serve as a reference for further research exploring the role of these genes in physiology of WJ-MSCs and in regenerative medicine.

Implication of DNA methylation during lifestyle mediated weight loss

Over the past 50 years, the number of overweight/obese people increased significantly, making obesity a global public health challenge. Apart from rare monogenic forms, obesity is a multifactorial disease, most likely resulting from a concerted interaction of genetic, epigenetic and environmental factors. Although recent studies opened new avenues in elucidating the complex genetics behind obesity, the biological mechanisms contributing to individual's risk to become obese are not yet fully understood. Non-genetic factors such as eating behaviour or physical activity are strong contributing factors for the onset of obesity. These factors may interact with genetic predispositions most likely via epigenetic mechanisms. Epigenome-wide association studies or methylome-wide association studies are measuring DNA methylation at single CpGs across thousands of genes and capture associations to obesity phenotypes such as BMI. However, they only represent a snapshot in the complex biological network and cannot distinguish between causes and consequences. Intervention studies are therefore a suitable method to control for confounding factors and to avoid possible sources of bias. In particular, intervention studies documenting changes in obesity-associated epigenetic markers during lifestyle driven weight loss, make an important contribution to a better understanding of epigenetic reprogramming in obesity. To investigate the impact of lifestyle in obesity state specific DNA methylation, especially concerning the development of new strategies for prevention and individual therapy, we reviewed 19 most recent human intervention studies. In summary, this review highlights the huge potential of targeted interventions to alter disease-associated epigenetic patterns. However, there is an urgent need for further robust and larger studies to identify the specific DNA methylation biomarkers which influence obesity.

DGA-5mC: A 5-methylcytosine site prediction model based on an improved DenseNet and bidirectional GRU method

The 5-methylcytosine (5mC) in the promoter region plays a significant role in biological processes and diseases. A few high-throughput sequencing technologies and traditional machine learning algorithms are often used by researchers to detect 5mC modification sites. However, high-throughput identification is laborious, time-consuming and expensive; moreover, the machine learning algorithms are not so advanced. Therefore, there is an urgent need to develop a more efficient computational approach to replace those traditional methods. Since deep learning algorithms are more popular and have powerful computational advantages, we constructed a novel prediction model, called DGA-5mC, to identify 5mC modification sites in promoter regions by using a deep learning algorithm based on an improved densely connected convolutional network (DenseNet) and the bidirectional GRU approach. Furthermore, we added a self-attention module to evaluate the importance of various 5mC features. The deep learning-based DGA-5mC model algorithm automatically handles large proportions of unbalanced data for both positive and negative samples, highlighting the model's reliability and superiority. So far as the authors are aware, this is the first time that the combination of an improved DenseNet and bidirectional GRU methods has been used to predict the 5mC modification sites in promoter regions. It can be seen that the DGA-5mC model, after using a combination of one-hot coding, nucleotide chemical property coding and nucleotide density coding, performed well in terms of sensitivity, specificity, accuracy, the Matthews correlation coefficient (MCC), area under the curve and Gmean in the independent test dataset: 90.19%, 92.74%, 92.54%, 64.64%, 96.43% and 91.46%, respectively. In addition, all datasets and source codes for the DGA-5mC model are freely accessible at https://github.com/lulukoss/DGA-5mC.