In this study, we observed distinct epigenetic marks, specifically DNA methylation patterns, in saliva samples from children born to mothers with gestational diabetes mellitus (GDM) compared to those from non-GDM mothers. Furthermore, several of these epigenetic differences persisted over the first year of life and were associated with anthropometric variables linked to childhood growth. Additionally, some of these DNA methylation sites are annotated in genes involved in pathways related to inflammation and type 2 diabetes, highlighting their potential role in early metabolic programming.

Previous studies have documented DNA methylation changes in cord blood and placenta of offspring born to GDM mothers, suggesting that these epigenetic modifications may reflect developmental programming of disease mechanisms and their potential role as biomarkers risk for metabolic diseases [2, 8, 24, 25].

While some research has associated DNA methylation profiles in children’s saliva with birth weight, prenatal maternal stress, and potential childhood obesity predictors, studies specifically targeting the offspring of GDM mothers are limited, with most investigations performed on cord blood samples [11, 26,27,28]. For instance, Franzago et al. evaluated DNA methylation levels in MC4R and LPL genes, in children born to mothers with obesity and GDM in different tissues, including placenta, maternal blood, and buccal swab samples. However, their analysis did not yield significant findings in saliva [29]. A recent review carried out by Saucedo et al. [30] examined the role of DNA methylation as a potential biomarker for monitoring fetal growth during pregnancy in women with GDM [30]. They found discrepant results in more than 15 studies that evaluated the role of DNA methylation in relation to birth weight. Most of these studies were conducted using cord blood, placental tissue, and maternal blood samples, with none in buccal (oral) samples. These discrepancies are explained by multiple factors, including sample size, the techniques and approaches used, the specific regions studied, and the inclusion of potential confounding variables.

Additionally, there is a scarcity of research examining the variability of these epigenetic marks over time and their association with children’s growth. The only study to date on this topic focused on GDM, conducted by Emper’s group, found differential DNA methylation profiles in children born to mothers with obesity or GDM compared to controls, with differences maintained over the first year of life in whole blood samples, showing epigenetic signatures enriched in metabolic pathways [31]. Our findings align with these results, revealing that 16 DMPs, in saliva, remained differentially methylated over the first year of life, in the same direction. The observed increase in methylation levels over time likely reflects the dynamic nature of the epigenome during early development, a critical window for epigenetic remodeling. During this period, developmental and environmental factors interact to establish stable epigenetic marks, which may explain the increasing methylation observed at the 1-year follow-up. These changes could be associated with biological processes such as tissue-specific maturation, immune system development, or metabolic programming. The consistency in the direction of methylation across time points may reflect stable epigenetic programming influenced by prenatal exposures, such as gestational diabetes mellitus (GDM).

Of the 16 CpG sites identified in our study, none have previously been associated with GDM in studies conducted on cord blood or placental samples. However, through the EWAS catalogue [32], we observed that several of these CpG sites have been identified in other contexts. Specifically, two CpG sites have been linked to cancer (cg08080145, cg19795817), one has been associated with obesity (cg20935223), and the cg10847603 and cg08446798 have been related to early exposure to environmental factors, such as maternal smoking and socioeconomic status [32].

Some of these 16 CpGs were annotated in genes, such as FARP2, CYTH3, RAB37, and NACC2, which are related to pathways involved in inflammatory processes, insulin signalling, and metabolic regulation, including T2DM. Specifically, CYTH3 has roles in Golgi apparatus function and ADP-ribosylation factor regulation, with genome-wide association studies (GWAS) suggesting its association with BMI and height [33, 34]. A recent study carried out in mice showed for first time that CYTH3 is required for full insulin signalling in mammals and might constitute a novel therapeutic target for weight reduction [35]. Previous research has identified associations between RAB37 gene and HbA1c levels, a key biomarker of long-term glucose control [36]. This suggests potential involvement in glycemic regulation, which could influence diabetes risk in the future. FARP2 enables guanylyl-nucleotide exchange factor activity, and it is involved in Rac protein signal transduction and neuronal remodelling. Polymorphisms of this gene are related to HDL concentrations and height [37, 38]. Recently, a preprint study has identified new genes associated with obesity, including FARP2 and NACC2, that showed strong associations with BMI and related phenotypes such as waist-hip ratio adjusted BMI or fasting insulin-adjusted BMI [39]. In our study, the cg10177795 annotated to FARP2 gene, and the cg12004206 annotated to NACC2 were correlated with head circumference and height percentiles, supporting findings from previous studies and their relevance for metabolic outcomes, and potential biomarkers of adiposity risk in the future.

Regarding BMI, we observed a higher BMI at one year of follow-up in the group of children born to mothers without GDM, contrary to what has been commonly described in the literature [40]. This finding could be explained by greater dietary control among women with GDM in our sample [12], the small sample size, or the shorter follow-up period. Indeed, several studies have found no significant differences in BMI between GDM and non-GDM offspring in the first 4–5 years of life, suggesting that the potential impact of maternal GDM exposure may not manifest until later in childhood [41, 42]. Epidemiological studies have demonstrated higher rates of T2DM in offspring exposed to maternal GDM, with the HAPO follow-up study showing increased adiposity and future risk of glucose metabolism disorders, likely as a consequence of adverse intrauterine programming [43]. In our study, we identified three CpG sites (cg20963866, cg02349186 and cg17052441) that were correlated with BMI at 1 year of age. This finding underscores the potential of these CpG sites as non-invasive biomarkers for early metabolic risk. Identifying such biomarkers is particularly important, as BMI is not only a predictor of future obesity and adiposity in children but also a well-established indicator of increased risk for type 2 diabetes.

To date, most studies have focused on identifying potential epigenetic markers in newborns through cord blood samples. However, the use of saliva samples offers several advantages, including the ability to conduct longitudinal follow-ups and improved applicability in clinical practice due to their non-invasive collection method and ethical suitability for paediatric research. Increasing evidence supports the use of saliva-based methylation studies, with established links between DNA methylation patterns and maternal BMI, gestational glucose levels, and various metabolic parameters [44,45,46]. The correlations observed in our study between CpG sites and child anthropometric measures underscore the potential of saliva-derived epigenetic markers as accessible indicators of growth patterns, supporting their utility in non-invasive metabolic health monitoring.

Our study presents several strengths that contribute to its significance and potential clinical applicability. Firstly, the use of saliva samples provides a minimally invasive method for analyzing DNA methylation patterns, which is particularly advantageous for longitudinal studies in pediatric populations. This approach also enhances ethical considerations and facilitates the collection of samples over time, allowing for the monitoring of stable epigenetic markers. Secondly, our longitudinal design enables the assessment of DNA methylation changes across critical early life stages, revealing several persistent epigenetic differences between children of mothers with and without GDM, thus highlighting potential biomarkers of early metabolic risk. Importantly, the association of these methylation sites with anthropometric measures, such as weight, height, and BMI, underscores the potential of these markers to serve as indicators of growth patterns. Additionally, by focusing on an underexplored sample type—saliva—our study fills a gap in the literature, as most prior research has been limited to cord blood, placental, or maternal blood samples.

This study also presents some limitations. Due to the exploratory nature of our study and its small sample size, we used uncorrected p-values in our analysis. As a result, we acknowledge that the findings should be interpreted with caution. These results require replication in larger and independent cohorts to confirm their robustness and applicability. We encourage other researchers to further explore the associations identified in our study.

In conclusion, our study identifies a different DNA methylation pattern between children born to mothers with GDM and non-GDM across time, in saliva samples. Some of these epigenetic marks.

are associated with key anthropometric measurements, such as weight, height, head circumference, annual growth and BMI, indicating potential use as biomarkers risk of childhood obesity in the future. Notably, this is one of the few studies to analyze DNA methylation over time using saliva samples, which offer an accessible, non-invasive method for longitudinal studies.

The findings contribute to a growing body of evidence supporting the utility of saliva samples in epigenetic research and underscore their potential as non-invasive biomarkers for monitoring the developmental impact of maternal GDM and other prenatal exposures.