Abundant serum proteins potentially discriminate normal and GDM pregnancy: from peptidome to intact proteins

Gestational diabetes mellitus (GDM) is a common pregnancy complication due to the onset of glucose intolerance, which presents a significant risk for both mother and offspring. However, GDM diagnosis at early state is still a tough challenge even though several modern technologies have been involved in this frontier. Herein, we propose that screening of the disease-related peptidome in blood is worth a try to explore the biomarker set of GDM, because the technology effectively avoids the interference of abundant proteins in blood, while its results lead to discovery of peptide biomarkers or verification of intact protein changes in response to GDM.

A total of 179 sera were collected, including 83 GDM and 96 health pregnant women. The serum peptides were enriched by hydrophilic-lipophilic balanced materials coated on magnetic solid phase. The bound peptides were processed through a MGI liquid automatic transfer and were finally eluted by 70% acetonitrile. The peptides without treatment of trypsin digestion were directly loaded onto an UltiMate 3000 HPLC that was mounted on Lumos Orbitrap mass spectrometer with acquisition mode at DDA. And the acquired MS/MS raw data was analyzed using MaxQuant searching against databases of human proteome with default parameter of non-tryptic digestion. The quantities of serum proteins derived from the differential peptides were further confirmed by Acquity UPLC I that was coupled with SCIEX Triple Quad 6500 mass spectrometer with acquisition mode at MRM. Finally, a discriminator was built up to distinguish the health pregnant from the GDM sera.

Totally 11849 peptides were identified by mass spectrometer, while after a strict cutoff (Fold>1.5, p<0.05, and Missing value<0.33), the abundance of 206 peptides in GDM was found significantly different from that in health pregnant sera. Focusing on these peptides, 151 peptides globally detected were further implemented to stridently quantitative measurement with two approaches at PRM and MRM mode. At PRM, 10 peptides were confirmed significant abundance differences between health and GDM, while these are derived from 6 intact human proteins, such as FIBA, FIBB, TTHY, KISS1, HEP2, and LEGL. At MRM, 151 peptides were theoretically checked their precursor proteins at first, resulting in them come from 65 proteins. Of these proteins, 27 proteins with specific MRM signals that have been evaluated by PQ500 study were selected for further experiments. In these serum samples, 20 proteins were satisfied with their MRM signals and were quantified based on calibration curves. Finally, these quantified proteins were taken into construction of a discriminator by machine learning. Combination of the quantitative signals of four serum proteins (A2MG, CO3, KNG1 and HEP2) in ROC could well distinguish the two serum samples of health pregnant and GDM with AUC at 0.871. All the data, from peptides to proteins, suggests the abundance of some serum proteins sensitive to GDM status.