Unique gene signatures reported across diabetes subtypes

Unique gene signatures reported across diabetes subtypes | Image Credit: © Pixel-Shot - © Pixel-Shot - stock.adobe.com.

Introduction

There are unique gene signatures in placentae from gestational diabetes subtype A1 (GDMA1), gestational diabetes subtype A2 (GDMA2), and type 2 diabetes mellitus (T2DM)-affected pregnancies that may be further distinguished, according to a recent study published in the American Journal of Obstetrics & Gynecology.¹

Gestational diabetes mellitus (GDM) impacts approximately 10% of US pregnancies per year.² GDMA1 is defined by management through lifestyle, nonmedication intervention, while GDMA2 requires medications for management.¹ According to investigators, it may be difficult to differentiate between these 2 subtypes, as well as T2DM.

“Distinguishing between T2DM and GDM poses a significant challenge, as both conditions are characterized by peripheral insulin resistance and a relative deficiency in insulin secretion, and the challenge can become further compounded by unequal access to health care and racial health disparities,” wrote investigators.

Study design

The study was conducted to determine the efficacy of differentiating between diabetes subtypes in pregnancy using disease gene signatures in placentae. Participants included pregnant individuals aged at least 18 years providing a placental sample at delivery after giving consent. Electronic medical records were assessed to obtain patients’ clinical data.

Uniform established international criteria was referenced to diagnose diabetes using Carpenter-Coustan glucose tolerance test (GTT). Diagnostic criteria for pregestational diabetes included having a diabetes diagnosis before pregnancy, positive GTT, or elevated hemoglobin A1C in early pregnancy.

Personnel with perinatal and placental pathology training performed sample collection following the standard obstetrical procedure. Collection occurred within 1 hour of delivery, with samples stored at −80°C until messenger ribonucleic acid (RNA) extraction. RNA extraction was performed using the Machery Nagel Nucleospin 2 kit.

The kit was also used to purify total RNA isolated from the placental tissue, after which the RNA was reverse transcribed. Real-time polymerase chain reaction was performed using commercially available primer and probe sets.

Investigators evaluated GDMA1, GDMA2, and T2DM gene signatures found within bulk RNA-seq data. Machine learning allowed for genes to be filtered, followed by copying of datasets into individual data frames for each group. Afterward, data frames were sliced into 80% training and 20% testing.

Patient demographics and results

Most characteristics were similar between cases and controls. However, cases had a reduced gestational age at delivery, and T2DM patients had a significant increase in the rate of hypertensive disorders of pregnancy. Most patients were Hispanic and multiparous.

Independently parsed gene expression was found based on diabetes type, with 8749 unique differentially expressed genes reported for each diabetes subtype when compared to controls. Reliable diabetic disease classification was performed with 9 of the top markers from the discovery phase.

Significant differences in chorionic somatomammotropin hormone 1 and period circadian regulator 1 expression were reported between T2DM cases and controls, GDMA2 cases, and GDMA1 cases. Epidermal growth factor receptor expression also significantly differed between T2DM cases and controls.

Differences were also reported in suppressor of glucose, and autophagy associated 1 expression between controls, GDMA1 cases, and GDMA2 cases. When compared to GDMA2 and T2DM subjects, GDMA1 subjected also presented with different superoxide dismutase 3 expression.

Conclusion

These differences, alongside those of other gene signatures, highlighted variations in placental pathology based on diabetes subtype. Differences were observed between gestational diabetes, nongestational diabetes, and nondiabetic controls.

“This lends credence to the current classification of pregestational and gestational diabetes and potentially lays the groundwork for the future development of distinct clinical algorithms aimed at earlier and more accurate screening for and treatment of underlying diabetic pathology,” concluded investigators.

References

1. Barrozoa ER, Racusina DA, Jochum MD, et al. Discrete placental gene expression signatures accompany diabetic disease classifications during pregnancy. Am J Obstet Gynecol. 2025;232:326.e1-15. doi:10.1016/j.ajog.2024.05.014
2. Wang H, Li N, Chivese T. IDF Diabetes Atlas: Estimation of global and regional gestational diabetes mellitus prevalence for 2021 by International Association of Diabetes in pregnancy study group’s criteria. Diabetes Research and Clinical Practice. 2021;183. doi:10.1016/j.diabres.2021.109050