Predicting gestational diabetes mellitus risk at 11-13 weeks' gestation: the role of extrachromosomal circular DNA

Abstract

Background: Gestational diabetes mellitus (GDM) significantly impacts maternal and infant health both immediately and over the long term, yet effective early diagnostic biomarkers are currently lacking. Thus, it is essential to identify early diagnostic biomarkers for GDM risk screening. Extrachromosomal circular DNA (eccDNA), being more stable than linear DNA and involved in disease pathologies, is a viable biomarker candidate for diverse conditions. In this study, eccDNA biomarkers identified for early diagnosis and assessment of GDM risk were explored.

Methods: Using Circle-seq, we identified plasma eccDNA profiles in five pregnant women who later developed GDM and five matched healthy controls at 11-13 weeks of gestation. These profiles were subsequently analyzed through bioinformatics and validated through outward PCR combined with Sanger sequencing. Furthermore, candidate eccDNA was validated by quantitative PCR (qPCR) in a larger cohort of 70 women who developed GDM and 70 normal glucose-tolerant (NGT) subjects. A ROC curve assessed the eccDNA's diagnostic potential for GDM.

Results: 2217 eccDNAs were differentially detected between future GDM patients and controls, with 1289 increased and 928 decreased in abundance. KEGG analysis linked eccDNA genes mainly to GDM-related pathways such as Rap1, MAPK, and PI3K-Akt, and Insulin resistance, among others. Validation confirmed a significant decrease in eccDNA PRDM16^circle in the plasma of 70 women who developed GDM compared to 70 NGT women, consistent with the eccDNA-seq results. PRDM16^circle showed significant diagnostic value in 11-13 weeks of gestation (AUC = 0.941, p < 0.001).

Conclusions: Our study first demonstrats that eccDNAs are aberrantly produced in women who develop GDM, including PRDM16^circle, which can predict GDM at an early stage of pregnancy, indicating its potential as a biomarker.

Trial registration: ChiCTR2300075971, http://www.chictr.org.cn . Registered 20 September 2023.

Keywords: Extrachromosomal circular DNA; Gestational diabetes mellitus; Predictive biomarker.

Fig. 1

The workflow for plasma eccDNA biomarker discovery for GDM. A Plasma samples collected from participants were stored at − 80 °C for later analysis. B DNA, including both linear and circular forms, was extracted from plasma, followed by the digestion of linear DNA using exonuclease V and subsequent RCA of eccDNAs. The samples were then analyzed using Circle-Seq, offering detailed insights into the eccDNA profiles. C Verification involved outward PCR targeting specific eccDNA junctions, followed by Sanger sequencing to confirm sequence accuracy, and qPCR to quantify the presence of eccDNA. D The eccDNA biomarker was validated in 70 women who developed GDM and 70 NGT subjects. GDM, gestational diabetes mellitus; NGT, normal glucose tolerance; RCA, rolling circle amplification

Fig. 2

The profiles of eccDNAs in women categorized by future GDM development. A Venn diagram showing the overlap of eccDNAs between GDM and NGT groups, with a total of 4,726 shared eccDNAs. B Bar graph depicting the frequency of eccDNAs per megabase across all chromosomes, differentiated between GDM and NGT groups, indicating genomic distribution. C Scatter plot illustrating a significant correlation between the counts of coding genes and eccDNAs (p < 0.001), suggesting a potential regulatory or structural relationship. D Box plots showing the distribution of eccDNAs in different genomic regions (such as 5′UTR, 3′UTR, exonic, intronic, and intergenic) for both GDM and NGT groups, comparing the genomic context of eccDNA localization. E Stacked bar chart representing the proportion of eccDNA mapping to various repeat classes, including LINEs, SINEs, satellite DNA, tRNA, snRNA, LTR, simple repeats, and low complexity regions, for each group, highlighting the diversity of eccDNA origins. F Distribution curve of eccDNA length, with separate curves for GDM and NGT groups, showing the frequency of eccDNAs at various lengths, indicating differences in eccDNA size distribution. G Cumulative frequency curve for eccDNA size, comparing GDM and NGT groups with a significant size variation marked by a p-value of less than 0.001, suggesting distinct physical properties of eccDNAs between groups. H Scatter plot comparing eccDNA counts in the GDM group against the NGT group, illustrating individual variability and group trends. I Volcano plot showing differential abundant of eccDNAs between GDM and NGT groups, marked by log-fold changes and p-values, to identify significantly upregulated or downregulated eccDNAs. J Heatmap with hierarchical clustering of eccDNA features distinguishing GDM from NGT samples. eccDNA: extrachromosomal circular DNA, GDM: gestational diabetes mellitus, NGT: normal glucose tolerance

Fig. 3

GO analyses of eccDNAs based on future GDM development. A–C Display significant GO terms for increased eccDNAs across BP, CC, and MF, respectively. D–F Similar displays for decreased eccDNAs across BP, CC, and MF, detailing enrichment scores and gene counts. ‘Sig’ stands for ‘Significant’, indicating GO terms with p-values less than 0.05. GO, gene ontology; BP, biological process; CC, cellular component; MF, molecular function

Fig. 4

Plasma eccDNA PRDM16^circle level is decreased in women who developed GDM later. A Integrative Genomics Viewer (IGV) depicted for eccDNAs derived from the prdm16 gene. B Visualization of eccDNA PRDM16^circle at Chr1:3092613–3092863. Junction site of eccDNA PRDM16^circle identified as TCCA. C Gel electrophoresis validation of PRDM16^circle. D qPCR validation of PRDM16^circle level in 10 sequenced samples. E qPCR validations of eccDNA PRDM16^circle level in plasma obtained from 70 women who developed GDM compared to 70 NGT women. ***p < 0.001. GDM, gestational diabetes mellitus; NGT, normal glucose tolerance

Fig. 5

Forest plot of predictive factors for GDM in early pregnancy. This forest plot illustrates the ORs and 95% CIs for various predictive factors linked to GDM risk. Each line represents a different predictor analyzed in the study, including gestational age at sampling, maternal age, pre-pregnancy BMI, HbA1c, HOMA-IR, insulin levels, fasting plasma glucose, and PRDM16^circle. GDM, gestational diabetes mellitus; NGT, normal glucose tolerance; OR, odds ratio; CI, confidence interval; BMI, body mass index; HbA1c, glycated hemoglobin; HOMA-IR, homeostatic model assessment of insulin resistance

Fig. 6

ROC curves for various predictors of GDM. A ROC curves for the capacity of the plasma eccDNA PRDM16^circle and other clinical parameters to differentiate GDM patients from NGT subjects. B The AUC showed no significant difference between the nomogram model and the eccDNA PRDM16^circle predictive model (p = 0.74). ROC, receiver operating characteristic; AUC, area under the curve; GDM, gestational diabetes mellitus; NGT, normal glucose tolerance