Gestational diabetes mellitus (GDM) is a comprehensive form of pregnancy-specific glucose intolerance or hyperglycemia that manifests certain degree of glucose intolerance (Plows et al., 2018). Hyperglycemia occurs in approximately 16.7% in pregnancies worldwide, 75%–90% of which is caused by GDM, implying that GDM has become a significant public health concern (IDA, 2021). Although blood glucose level in GDM usually returns to normal after delivery, women are at high risk of acquiring type 2 diabetes later in life, and the risk of metabolic syndrome and insulin resistance in offspring have also increased (Damm et al., 2016), which presents a vicious intergenerational cycle. Compelling evidence suggest that advanced maternal age, family history of diabetes, diet, physical activity or emerging environmental factors are likely to have an impact on the risk of developing GDM (Zhang et al., 2016). However, knowledge concerning the detailed processes governing the initiation and progression of GDM remains unknown.

Although Genome-wide association studies (GWAS) have revealed several genetic loci correlated with the complexity of the disease, the underlying mechanism remain unclear (Kwak et al., 2012). Non-coding RNAs (ncRNAs) are important players in metabolic processes and their deregulated expressions have been observed in several metabolic diseases, including GDM. MicroRNA (miRNA), as a type of generally ubiquitous and multifunctional short non-coding RNAs with 19–22 nucleotides that regulate post-transcriptional gene expression (Brennecke et al., 2005), and participate in a range of biological functions (Du and Zamore, 2005).

Currently, in spite of the presence of discordant data, numerous researches indicate that circulating miRNAs are involved in mediating the key pathophysiological features of GDM, including glucose homeostasis, inflammation, insulin resistance, metabolic adaptations and β-cell dysfunction (Sliwinska et al., 2017; Filardi et al., 2020; Abu Samra et al., 2022). Aberrant levels of miRNA and gene expression in GDM have laid a favorable foundation for personalized target therapy and potential drugs. Compelling studies show that miR-195-5p overexpression in GDM women play an important role in insulin insensitivity regulation (Tagoma et al., 2018; Wang et al., 2020). A study of Filardi et al. identified that miR-222-3p and miR-409-3p signatures were significantly up-regulated in GDM, which are correlated with fasting plasma glucose (Filardi et al., 2022). Concerted efforts are made to gain knowledge about the mechanisms by which metabolic pathways are coordinated by acquired and genetic factors to explore novel insights into GDM treatment.

Although common biomarkers for GDM have been identified previously, the specific molecular mechanisms remain unclear. Genetic susceptibility is represented by gene variants conferring individual differences in response to metabolic-related chronic diseases. Most importantly, few studies have used transcriptome sequencing to explore GDM biomarkers, especially in South-East Chinese population. To the best of our knowledge, systematic regulatory network and pathways have not been well profiled about how alternations of microRNAs and mRNA are related to GDM development integrating with chemical compounds. The understanding of their functions might help unravel the complex pathophysiological mechanisms and identify novel clinical treatment. Early prevention and diagnosis are of great important to avoid adverse effects.

In this present study, a complete transcriptome RNA based on GDM in peripheral blood leukocytes (PBL) was sequenced, and putative hub genes were identified using a stepwise screening approach. The target genes of differentially expressed miRNA (DEMs) were synchronously predicted via online miRNA-target databases. The transcriptome were utilized to reveal molecular pathways and protein-protein interaction (PPI) network of candidate genes and confirmed those hub genes, followed by an external validation on the expression levels through the GSE103552 dataset (11 GDM and 8 normal controls). Simultaneously, by querying through CMap, registered chemicals could be screened and the likelihood of drugs could be obtained, showing gene expression profile that discover potential small molecules targeting diseases. This study aimed to identify pivotal pathways for complex pathophysiological mechanisms for GDM and contextually explore novel potential diagnostic biomarkers for the disease.

Figure 1 depicts a schematic representation of the study design. And, Table 1 summarizes the characteristics of 12 samples. There was no significant difference between GDM patients and healthy controls in terms of age, BMI, 2h-plasma glucose, systolic blood pressure (SBP) and diastolic blood pressure (DBP) (p > 0.05). GDM patients had a statistically significant higher fasting plasma glucose (FPG) and 1h-plasma glucose (p < 0.05) as compared to controls.

As one of the most common complications of pregnancy, the biological mechanism of GDM remains to be clearly elucidated. Exploring the aetiology and progression of GDM, as well as supporting the development of disease-modifying treatments, is a clear and urgent need. miRNAs have potential function in essential biological activities and their dysregulation or dysfunction was revealed in metabolic researches regarding GDM, rendering them a potential role as biomarkers or therapeutic targets. By merging internal RNA-seq data and GEO datasets with integrated bioinformatic analysis, we were able to produce solid evidence to considerably intensify the likelihood of detecting candidate biological markers and tremendously improve the reliability of our findings. In our study, some core modules and critical signaling pathway were discovered and extracted from dysregulated ceRNA that shed a light on plausible etiology of GDM. Collectively, the present study highlighted the effect of dysregulated glycometabolism and hormone-related in GDM and revealed the complexity of miRNAs as important fine tune regulators in the biological processes and their potential as novel biomarkers and treatment targets in GDM.

Our study identified 193 candidate genes by overlapping DEGs and target genes of DEMs. The GO analysis exhibited that candidate genes were primarily involved in post-embryonic eye morphogenesis, paracrine signaling, sequestering of TGF-β in extracellular matrix, platelet-derived growth factor receptor-beta signaling pathway, melanocyte proliferation and glutamine transport. These result indicate that GDM is related to placental development and endocrine. Previously, a study reported that GDM could alter angiogenesis by modulating paracrine factors (Loegl et al., 2017). A study suggested that platelet derived growth factor receptor beta polypeptide (Pdgfrb) expression were decreased in maternal hyperglycemia compared to controls in animal model (Lehtoranta et al., 2016). Wang et al. found glutamine capacity significantly decreased in the fetuses of GDM (Wang et al., 2019). Interestingly, the upregulated genes were mostly found in TGF-β signaling pathway, AGE-RAGE signaling pathway in diabetic complications, Growth hormone synthesis, secretion and action and Pancreatic cancer via KEGG analysis, and these pathways were involved in inflammatory response. It suggests that inflammatory response are also involved in the pathology of GDM development.

Since there are no effective drugs for GDM, the online database was used to aid the prediction of some drugs. The analysis via CMap suggested that the top 10 small molecule compounds could have potential therapeutic effect on GDM. Isoliquiritigenin, as one of the most important chalcone compounds, presents the antidiabetic activity and plays a part in the suppression of inflammatory pathways (Gaur et al., 2014; Gupta et al., 2018; Zhao et al., 2019). Soluble guanylate cyclase (sGC) activator YC-1 mimicked Bradykinin (BK) enhance the uptake of insulin-stimulated glucose (Frigolet et al., 2017). However, more experimental studies are necessary to validate therapeutic effects of these potential drugs on GDM. And, their application to the clinical settings requires extensive basic research and clinical trials in the future.

The PPI network revealed the intercommunication of candidate miRNAs and target genes, among which 13 potential miRNA-target gene regulatory pathways were miR-29b-1-5p-TGFB2, miR-142-3p-TGFB2, miR-9-5p-FBN2, miR-212-5p-FBN2, miR-542-3p-FBN1, miR-9-5p-FBN1, miR-508-3p-FBN1, miR-493-5p-THBS1, miR-29b-3p-COL4A1, miR-432-5p-COL5A2, miR-9-5p-TGFBI, miR-486-3p-SLC7A5 and miR-6515-5p-SLC1A5, respectively. For those upregulated DEMs, plasma miR-486-3p was upregulated in T2DM patients compared to healthy controls (Meerson et al., 2019) and increased concentrations in prepubertal obesity (Prats-Puig et al., 2013), which indicate that miR-486-3p could participate in a metabolism-related mechanism of GDM. Among those downregulated DEMs, miR-9-5p was upregulated in endocrine pancreatic (EN) of pluripotent stem cells (hiPSCs) compared to undifferentiated hiPSCs, and the pancreas has a regulatory role in glycemia (Sebastiani et al., 2017). However, miR-9-5p had higher levels in GDM patients (Martínez-Ibarra et al., 2019). A study reported that miR-29b-3p expression level was decreased in mice obesity model induced by high-fat diet (Zhang et al., 2022), while miR-29b-3p showed higher levels in the early phase of placentation in GDM(6–15 weeks of gestation) (Gillet et al., 2019). These might be related to the differences of sample source and gestation periods. Additionally, miR-542-3p, miR-493-5p, miR-432-5p and miR-6515-5p were reported to participate in the progression of breast cancer (Jiang et al., 2022), diabetic osteoporosis (Zhai et al., 2020), pancreatic ductal adenocarcinoma (Shen et al., 2021), inflammation-related disorders (periodontitis) (Xu et al., 2020). Those critical miRNAs, in particular, play significant roles in regulating biological processes in GDM.

In our study, interestingly, the expression of 9 genes (TGFB2, FBN2, FBN1, THBS1, COL4A1, COL5A2, TGFBI, SLC7A5, SLC1A5), being consistent with the result in GSE103552, were further verified. TGFB2 encodes a secreted ligand of the transforming growth factor-beta (TGF-β) superfamily of proteins, which is involved in the pathogenesis of diabetes and complications. Zhou et al. reported that TGFB2 is an upregulated gene in the plasma of GDM patients and correlated with FBG levels in GDM patients (Zhou et al., 2021), which suggested that TGFB2 might play vital roles in the pathogenesis of GDM. FBN2 encodes a peptide hormone placensin, which stimulates cAMP-PKA signaling, glucose secretion and trophoblast invasion in human trophoblastic cells. During third trimester, serum placensin levels of GDM patients are increased to a bigger extent compared to healthy pregnant women (Yu et al., 2020). FBN1 can encode the protein hormone asprosin, which is involved in regulating glucose homeostasis (Goodarzi et al., 2021). Zhong et al. reported that asprosin was highly expressed in the plasma of GDM patients and their offspring (Zhong et al., 2020). The protein encoded by THBS1 is an adhesive glycoprotein and proinflammatory cytokine that promotes insulin resistance. A study suggested that THBS1 in obesity or type 2 diabetes mellitus was highly expressed than healthy controls (Tang et al., 2020). COL4A1 was involved in diabetic tubulointerstitial injury (Zeng et al., 2019) and COL5A2 participated in the progression of uterine fibroids (Giri et al., 2017) and colon adenocarcinoma (Wei et al., 2020), although their functions were not fully understood for GDM development. TGFBI, upregulated in the placenta and the plasma of GDM, was positively associated with FBG levels in GDM patients (Han et al., 2014; Zhou et al., 2021). SLC7A5 enables L-leucine/L-tryptophan transmembrane transporter activity and is a part of amino acid transport complex. One study reported the uptake of ¹⁴C-l-methionine by human trophoblasts derived from normal pregnancies is mainly mediated by L-type amino acid transporter 1 [LAT1 (L), SLC7A5]. However, the process exposed to the high glucose environment of GDM may alter the nature of transporters involved in the uptake process (Araújo et al., 2013). The study of HOLM et al. reported that SLC1A5 was involved in sphingolipid metabolism that contributes to genetic predisposition to type 1 diabetes, whereas there has been no direct evidence of the association between SLC1A5 and GDM risk (Holm et al., 2018).

Our study has obvious merits. We have systematically analyzed the miRNAs expression and their target genes between 6 GDM and 6 healthy controls integrating with public GEO dataset. The sample size of the integrated analysis is adequate to explore and verify those candidate miRNAs and key genes. Furthermore, we investigated the biological functions and potential therapeutic small molecule compounds of miRNA-target genes, as well as obtained pivotal genes through bioinformatics analysis. More importantly, when being compared with placenta, collecting blood samples is actually more accessible in clinical practice as early screening and diagnosis.

Also, there are some limitations that need be considered. First, due to the availability of GSE103552, our study did not analyze the association between clinical data (clinical parameters and prognosis) and genetic change. Additionally, as the statistical power based on its relatively larger sample size, GSE103552 were chosen as the external validation dataset. Second, we acknowledge the relatively low sample size of internal screening dataset as limitation of our study. We integrated internal samples and the 3 diverse public databases to comprehensively screen the critical miRNAs and key genes, and this could present a comprehensive screening results and predictions. However, external experimental verifications are further needed to elucidate the molecular mechanisms of GDM in the future.

In conclusion, this study demonstrated a series of aberrantly differentially expressed miRNAs and genes that are associated with epigenetic alternations of miRNAs in GDM by overlapping DEGs and targets of DEMs. A multitude of novel miRNA-targeting genes and regulatory pathways were identified that might serve as high priority targets for therapeutic interventions (miR-29b-1-5p-TGFB2, miR-142-3p-TGFB2, miR-9-5p-FBN2, miR-212-5p-FBN2, miR-542-3p-FBN1, miR-9-5p-FBN1, miR-508-3p-FBN1, miR-493-5p-THBS1, miR-29b-3p-COL4A1, miR-432-5p-COL5A2, miR-9-5p-TGFBI, miR-486-3p-SLC7A5 and miR-6515-5p-SLC1A5). Furthermore, ten chemicals were identified as putative therapeutic agents for GDM. Precise diagnosis and therapeutic targets of GDM would be further explored through putative genes in the future.