Magnetic Bead-Based Serum Peptidome Profiling in Patients with Gestational Diabetes Mellitus. Biomed Res Int. 2015;2015:586309. [PMID: 26090425 PMCID: PMC4450277 DOI: 10.1155/2015/586309]

Proteomic analysis of plasma total exosomes and placenta-derived exosomes in patients with gestational diabetes mellitus in the first and second trimesters

Gestational diabetes mellitus (GDM) is the first spontaneous hyperglycemia during pregnancy. Early diagnosis and intervention are important for the management of the disease. This study compared and analyzed the proteins of total plasma exosomes (T-EXO) and placental-derived exosomes (PLAP-EXO) in pregnant women who subsequently developed GDM (12-16 weeks), GDM patients (24-28 weeks) and their corresponding controls to investigate the pathogenesis and biomarkers of GDM associated with exosomes. The exosomal proteins were extracted and studied by proteomics approach, then bioinformatics analysis was applied to the differentially expressed proteins (DEPs) between the groups. At 12-16 and 24-28 weeks of gestation, 36 and 21 DEPs were identified in T-EXO, while 34 and 20 DEPs were identified in PLAP-EXO between GDM and controls, respectively. These proteins are mainly involved in complement pathways, immunity, inflammation, coagulation and other pathways, most of them have been previously reported as blood or exosomal proteins associated with GDM. The findings suggest that the development of GDM is a progressive process and that early changes promote the development of the disease. Maternal and placental factors play a key role in the pathogenesis of GDM. These proteins especially Hub proteins have the potential to become predictive and diagnostic biomarkers for GDM.

Mass spectrometry-based "omics" technologies for the study of gestational diabetes and the discovery of new biomarkers

Gestational diabetes (GDM) is one of the most common complications occurring during pregnancy. Diagnosis is performed by oral glucose tolerance test, but harmonized testing methods and thresholds are still lacking worldwide. Short-term and long-term effects include obesity, type 2 diabetes, and increased risk of cardiovascular disease. The identification and validation of sensitidve, selective, and robust biomarkers for early diagnosis during the first trimester of pregnancy are required, as well as for the prediction of possible adverse outcomes after birth. Mass spectrometry (MS)-based omics technologies are nowadays the method of choice to characterize various pathologies at a molecular level. Proteomics and metabolomics of GDM were widely investigated in the last 10 years, and various proteins and metabolites were proposed as possible biomarkers. Metallomics of GDM was also reported, but studies are limited in number. The present review focuses on the description of the different analytical methods and MS-based instrumental platforms applied to GDM-related omics studies. Preparation procedures for various biological specimens are described and results are briefly summarized. Generally, only preliminary findings are reported by current studies and further efforts are required to determine definitive GDM biomarkers.

Proteomics Studies in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis

Gestational Diabetes Mellitus (GDM) is the most common metabolic complication during pregnancy and is associated with serious maternal and fetal complications such as pre-eclampsia and stillbirth. Further, women with GDM have approximately 10 times higher risk of diabetes later in life. Children born to mothers with GDM also face a higher risk of childhood obesity and diabetes later in life. Early prediction/diagnosis of GDM leads to early interventions such as diet and lifestyle, which could mitigate the maternal and fetal complications associated with GDM. However, no biomarkers identified to date have been proven to be effective in the prediction/diagnosis of GDM. Proteomic approaches based on mass spectrometry have been applied in various fields of biomedical research to identify novel biomarkers. Although a number of proteomic studies in GDM now exist, a lack of a comprehensive and up-to-date meta-analysis makes it difficult for researchers to interpret the data in the existing literature. Thus, we undertook a systematic review and meta-analysis on proteomic studies and GDM. We searched MEDLINE, EMBASE, Web of Science and Scopus from inception to January 2022. We searched Medline, Embase, CINHAL and the Cochrane Library, which were searched from inception to February 2021. We included cohort, case-control and observational studies reporting original data investigating the development of GDM compared to a control group. Two independent reviewers selected eligible studies for meta-analysis. Data collection and analyses were performed by two independent reviewers. The PROSPERO registration number is CRD42020185951. Of 120 articles retrieved, 24 studies met the eligibility criteria, comparing a total of 1779 pregnant women (904 GDM and 875 controls). A total of 262 GDM candidate biomarkers (CBs) were identified, with 49 CBs reported in at least two studies. We found 22 highly replicable CBs that were significantly different (nine CBs were upregulated and 12 CBs downregulated) between women with GDM and controls across various proteomic platforms, sample types, blood fractions and time of blood collection and continents. We performed further analyses on blood (plasma/serum) CBs in early pregnancy (first and/or early second trimester) and included studies with more than nine samples (nine studies in total). We found that 11 CBs were significantly upregulated, and 13 CBs significantly downregulated in women with GDM compared to controls. Subsequent pathway analysis using Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resources found that these CBs were most strongly linked to pathways related to complement and coagulation cascades. Our findings provide important insights and form a strong foundation for future validation studies to establish reliable biomarkers for GDM.

Potential biomarkers identified in plasma of patients with gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a common complication during pregnancy. Looking for reliable diagnostic markers for early diagnosis can reduce the impact of the disease on the fetus OBJECTIVE: The present study is designed to find plasma metabolites that can be used as potential biomarkers for GDM, and to clarify GDM-related mechanisms METHODS: By non-target metabolomics analysis, compared with their respective controls, the plasma metabolites of GDM pregnant women at 12-16 weeks and 24-28 weeks of pregnancy were analyzed. Multiple reaction monitoring (MRM) analysis was performed to verify the potential marker RESULTS: One hundred and seventy-two (172) and 478 metabolites were identified as differential metabolites in the plasma of GDM pregnant women at 12-16 weeks and 24-28 weeks of pregnancy, respectively. Among these, 40 metabolites were overlapped. Most of them are associated with the mechanism of diabetes, and related to short-term and long-term complications in the perinatal period. Among them, 7 and 10 differential metabolites may serve as potential biomarkers at the 12-16 weeks and 24-28 weeks of pregnancy, respectively. By MRM analysis, compared with controls, increased levels of 17(S)-HDoHE and sebacic acid may serve as early prediction biomarkers of GDM. At 24-28 weeks of pregnancy, elevated levels of 17(S)-HDoHE and L-Serine may be used as auxiliary diagnostic markers for GDM CONCLUSION: Abnormal amino acid metabolism and lipid metabolism in patients with GDM may be related to GDM pathogenesis. Several differential metabolites identified in this study may serve as potential biomarkers for GDM prediction and diagnosis.

Theranostic Advances of Bionanomaterials against Gestational Diabetes Mellitus: A Preliminary Review

Gestational diabetes mellitus (GDM) is the most frequent complication during pregnancy. This complex disease is characterized by glucose intolerance and consequent hyperglycemia that begins or is first diagnosed in pregnancy, and affects almost 7% of pregnant women. Previous reports have shown that GDM is associated with increased pregnancy complications and might cause abnormal fetal development. At present, treatments are not suitable for the prevention and management of these patients. As an alternative therapeutic opportunity and a leading scientific technique, nanotechnology has helped enlighten the health of these affected women. Theranostic nanomaterials with unique properties and small sizes (at least <100 nm in one of their dimensions) have been recently engineered for clinics and pharmaceutics. Reducing materials to the nanoscale has successfully changed their properties and enabled them to uniquely interact with cell biomolecules. Several biosensing methods have been developed to monitor glucose levels in GDM patients. Moreover, cerium oxide nanoparticles (NPs), selenium NPs, polymeric NPs, and drug-loaded NPs loaded with therapeutic agents have been used for GDM treatment. Still, there are some challenges associated with the detection limits and toxicity of such nanomaterials. This preliminary review covers the aspects from a fast-developing field to generating nanomaterials and their applications in GDM diagnosis and treatment.

Techniques, perspectives, and challenges of bioactive peptide generation: A comprehensive systematic review

Due to the digestible refractory and absorbable structures of bioactive peptides (BPs), they could induce notable biological impacts on the living organism. In this regard, the current study was devoted to providing an overview regarding the available methods for BPs generation by the aid of a systematic review conducted on the published articles up to April 2019. In this context, the PubMed and Scopus databases were screened to retrieve the related publications. According to the results, although the characterization of BPs mainly has been performed using enzymatic and microbial in-vitro methods, they cannot be considered as suitable techniques for further stimulation of digestion in the gastrointestinal tract. Therefore, new approaches for both in-vivo and in-silico methods for BPs identification should be developed to overcome the obstacles that belonged to the current methods. The purpose of this review was to compile the recent analytical methods applied for studying various aspects of food-derived biopeptides, and emphasizing generation at in vitro, in vivo, and in silico.

A Critical Review of Proteomic Studies in Gestational Diabetes Mellitus

Gestational diabetes mellitus is a progressive and complex pregnancy complication, which threatens both maternal and fetal health. It is urgent to screen for specific biomarkers for early diagnosis and precise treatment, as well as to identify key moleculars to better understand the pathogenic mechanisms. In the present review, we comprehensively summarized recent studies of gestational diabetes using mass spectrometry-based proteomic technologies. Focused on the entire experimental design and proteomic results, we showed that these studies have covered a broad range of research contents in terms of sampling time, sample types, and outcome associations. Although most of the studies only stayed in the stage of initial discovery, several proteins were further verified to be efficient for disease diagnosis. Functional analysis of all the combined significant proteins also showed that a small number of proteins are known to be involved in the regulation of insulin or indirect signaling pathways. However, many factors such as diagnostic criteria, sample processing, proteomic method, and statistical method can greatly affect the identification of reproducible and reliable protein candidates. Thus, we further provided constructive suggestions and recommendations for carrying out proteomic or follow-up studies of gestational diabetes or other pregnancy complications in the future.

Hypertensive disorders of pregnancy: Strategy to develop clinical peptide biomarkers for more accurate evaluation of the pathophysiological status of this syndrome

Hypertensive disorders of pregnancy (HDP) is the most common and widely known as serious complication of pregnancy. As this syndrome is a major leading cause of maternal, fetal, and neonatal morbidity/mortality worldwide, many studies have sought to identify candidate molecules as potential disease biomarkers (DBMs) for use in clinical examinations. Accumulating evidence over the past 2 decades that the many proteolytic peptides appear in human humoral fluids, including peripheral blood, in association with an individual's health condition. This review provides the potential utility of peptidomic analysis for monitoring for pathophysiological status in HDP, and presents an overview of current status of peptide quantification technology. Especially, the technical limitations of the methods used for DBM discovery in the blood are discussed.

Gestational diabetes from A to Z

Gestational diabetes mellitus (GDM) is defined as any degree of hyperglycaemia that is recognized for the first time during pregnancy. This definition includes cases of undiagnosed type 2 diabetes mellitus (T2DM) identified early in pregnancy and true GDM which develops later. GDM constitutes a greater impact on diabetes epidemic as it carries a major risk of developing T2DM to the mother and foetus later in life. In addition, GDM has also been linked with cardiometabolic risk factors such as lipid abnormalities, hypertensive disorders and hyperinsulinemia. These might result in later development of cardiovascular disease and metabolic syndrome. The understanding of the different risk factors, the pathophysiological mechanisms and the genetic factors of GDM, will help us to identify the women at risk, to develop effective preventive measures and to provide adequate management of the disease. Clinical trials have shown that T2DM can be prevented in women with prior GDM, by intensive lifestyle modification and by using pioglitazone and metformin. However, a matter of controversy surrounding both screening and management of GDM continues to emerge, despite several recent well-designed clinical trials tackling these issues. The aim of this manuscript is to critically review GDM in a detailed and comprehensive manner, in order to provide a scientific analysis and updated write-up of different related aspects.

Multiplexed Temporal Quantification of the Exercise-regulated Plasma Peptidome

Exercise is extremely beneficial to whole body health reducing the risk of a number of chronic human diseases. Some of these physiological benefits appear to be mediated via the secretion of peptide/protein hormones into the blood stream. The plasma peptidome contains the entire complement of low molecular weight endogenous peptides derived from secretion, protease activity and PTMs, and is a rich source of hormones. In the current study we have quantified the effects of intense exercise on the plasma peptidome to identify novel exercise regulated secretory factors in humans. We developed an optimized 2D-LC-MS/MS method and used multiple fragmentation methods including HCD and EThcD to analyze endogenous peptides. This resulted in quantification of 5,548 unique peptides during a time course of exercise and recovery. The plasma peptidome underwent dynamic and large changes during exercise on a time-scale of minutes with many rapidly reversible following exercise cessation. Among acutely regulated peptides, many were known hormones including insulin, glucagon, ghrelin, bradykinin, cholecystokinin and secretogranins validating the method. Prediction of bioactive peptides regulated with exercise identified C-terminal peptides from Transgelins, which were increased in plasma during exercise. In vitro experiments using synthetic peptides identified a role for transgelin peptides on the regulation of cell-cycle, extracellular matrix remodeling and cell migration. We investigated the effects of exercise on the regulation of PTMs and proteolytic processing by building a site-specific network of protease/substrate activity. Collectively, our deep peptidomic analysis of plasma revealed that exercise rapidly modulates the circulation of hundreds of bioactive peptides through a network of proteases and PTMs. These findings illustrate that peptidomics is an ideal method for quantifying changes in circulating factors on a global scale in response to physiological perturbations such as exercise. This will likely be a key method for pinpointing exercise regulated factors that generate health benefits.

Comparative study of saliva peptide signatures between gastric carcinoma and chronic gastritis

AIM: To screen differential protein expression profiles in saliva between gastric carcinoma and chronic gastritis, and to establish a model for differentiating these groups.

METHODS: Saliva samples from 57 patients with gastric carcinoma and 28 patients with gastritis were purified with weak cationic-exchange magnetic beads (MB-WCX) and then analyzed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Subsequently, we compared the saliva peptide signatures of the two groups and obtained differently expressed peptides by using Biomarker Wizard. Then, we established two diagnostic models to distinguish the gastric carcinoma group from the gastritis group and normal control group by using Biomarker Patterns 5.0.2.

RESULTS: A diagnostic pattern for discriminating between the gastric carcinoma group and gastritis group using three peptides (m/z 4267.09, 6564.85, 2138.14) was established with a 96% (55/57) sensitivity and an 86% (24/28) specificity. A sensitivity of 89%(51/57) and a specificity of 75% (21/28) were obtained in cross validation.

CONCLUSION: The novel molecular diagnostic model obtained by saliva protein fingerprinting for distinguishing gastric carcinoma from chronic gastritis is sensitive and noninvasive.

Peptidome profiling of umbilical cord plasma associated with gestational diabetes-induced fetal macrosomia

Fetal macrosomia, defined as a birth weight ≥4000g, may affect 15-45% of newborns of women with gestational diabetes mellitus (GDM). The associations between endogenous peptides and gestational diabetes-induced macrosomia have not been investigated extensively by peptidome analysis. Here, we analyzed the umbilical cord plasma by combining ultrafiltration using molecular weight cut-off filters and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to investigate potential associations of GDM with macrosomia. As macrosomic babies have increased susceptibility to obesity, diabetes and cardiovascular diseases in later life, we also aimed to identify specific biomarkers to detect these future diseases. Thirty pairs of GDM mothers and controls were randomly divided into three subgroups. We identified 235 peptides of around 1000-3000Da, originating from 115 proteins. Analyzing the cleavage sites revealed that these peptides were cleaved in regulation, which may reflect the protease activity and distribution in umbilical cord plasma. Four identified peptides, of 2471.7, 1077.2, 1446.5 and 2372.7Da, were significantly differentially expressed in the GDM macrosomia groups compared with controls, whose precursors may play a critical role in developing GDM macrosomia. We provide for the first time a validated GDM macrosomia peptidome profile and identify potential biomarkers linking the effects of macrosomia to later-life diseases.

BIOLOGICAL SIGNIFICANCE

Fetal macrosomia is the predominant adverse outcome of gestational diabetes mellitus (GDM), which is a frequent medical condition during pregnancy. Till now, the detailed molecular mechanisms underlying gestational diabetes-induced macrosomia are still not elucidated. With high detection sensitivity and high throughput of peptidome technology, it is now possible to systemically identify peptides possibly involved in the umbilical cord plasma of GDM induced macrosomia cases. With LC-MS/MS based quantification, totally, we identified 235 peptides originated from 115 precursor proteins. And four peptides of 2471.7, 1077.2, 1446.5 and 2372.7Da differentially expressed between GDM cases and compared controls. A precursor protein of 1077.2Da was fibrinogen alpha chain (FGA), which was also identified in the Ai et al. [29] study with a downregulated manner in the serum samples of GDM cases. And further analysis the cleavage pattern of the identified peptides revealed that the enzymes in tissues cleaved the protein according to their rules. Thus, this quantitative peptidome approach can identify related peptides that may play a role in the gestational diabetes-induced macrosomia, and give candidate biomarkers contributing to the development of later-life diseases in macrosomic babies.

Proteomic-driven biomarker discovery in gestational diabetes mellitus: a review

Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with onset or first recognition during pregnancy and it affects 18% of pregnant women worldwide. GDM is considered a high-risk state which may lead to type II diabetes which is associated with an increase in a number of interrelated adverse perinatal outcomes. Given the fact that the progress of a successful pregnancy is dependent on the intricate communication between several biological molecules, identification of the proteomic profile perturbations in women with GDM is expected to help in understanding the disease pathogenesis and also discovery of clinical biomarker(s). In recent years, both gel-free and gel-based proteomics have been extensively investigated for improving maternal and child health. Although there are several reports integrating various aspects of proteomics in pregnancy related diseases such as preeclampsia, extensive Pubmed search shows no review so far on the application of proteomics in gestational diabetes. In this review, we focus on various high-throughput proteomic technologies for the identification of unique biosignatures and biomarkers responsible for the early prediction of GDM. Further, different analytical strategies and biological samples involved in proteomic analysis of this pregnancy-related disease are discussed.This article is part of a Special Issue entitled: Proteomics in India.