First-trimester proteomic profiling identifies novel predictors of gestational diabetes mellitus

Serum amyloid P component: Structure, biological activity, and application in diagnosis and treatment of immune-associated diseases

Serum amyloid P component (SAP) is a member the innate immune humoral arm and participated in various processes, including the innate immune responses, tissue remodeling, and the pathogenesis of inflammatory diseases. Remarkably, SAP is a highly versatile immunomodulatory factor that can serve as a drug target for treating amyloid diseases and reduce inflammation, fibrosis degree, and respiratory disease. In this review, we focus on the biological activities of SAP and its application in different systemic immune-associated diseases. First, we reviewed the regulatory effects of SAP on innate immune cells and possible mechanisms. Second, we emphasized SAP as a diagnostic marker and therapeutic target for immune-associated diseases, including the neuropsychiatric disorders. Third, we presented several recommendations for regulating SAP in immune cell function and potential areas for future research. Some authorities consider SAP to be a pattern recognition molecule that plays multiple roles in the innate immune system and inflammation. Developing therapeutics that target SAP or its associated signaling pathways may be a promising strategy for treating immune-associated diseases.

Prospecting Specific Protein Patterns for High Body Mass Index (BMI), Metabolic Syndrome and Type 2 Diabetes in Saliva and Blood Plasma From a Brazilian Population

PURPOSE

Obesity and its associated metabolic disorders, such as T2DM and MeS, are a growing public health problem worldwide. Our goal was the identification of protein patterns that are uniquely characteristic of higher BMI, MeS, and T2DM in a Brazilian population.

EXPERIMENTAL DESIGN

Saliva and plasma proteomes, clinical parameters were analyzed in a population from the state of Rio de Janeiro, Brazil, a mixed-race population. Volunteers were sorted by their BMI into normal (n = 29), overweight (n = 25), and obese (n = 15) and were compared with individuals with MeS (n = 23) and T2DM (n = 11).

RESULTS

The Random Forest (RF) predictive model revealed that three clinical variables, BMI, HOMA-IR, and fasting blood glucose, are most important for predicting MeS and T2DM. A total of six plasmatic proteins (ABCD4, LDB1, PDZ, podoplanin, lipirin-alpha-3, and WRS) and six salivary proteins (hemoglobin subunit beta, POTEE, T cell receptor alpha variable 9-2, lactotransferrin, cystatin-S, carbonic anhydrase 6), are enhanced in T2DM and in MeS.

CONCLUSIONS AND CLINICAL RELEVANCE

Our data revealed similar alterations in protein composition across individuals with abnormal weight gain, T2DM, and MeS. This finding confirms the close link between these conditions at the molecular level in the studied population, potentially enhancing our understanding of these diseases and paving the way for the development of novel diagnostic tools.

Serum proteomics of mother-infant dyads carrying HLA-conferred type 1 diabetes risk

In-utero and dietary factors make important contributions toward health and development in early childhood. In this respect, serum proteomics of maturing infants can provide insights into studies of childhood diseases, which together with perinatal proteomes could reveal further biological perspectives. Accordingly, to determine differences between feeding groups and changes in infancy, serum proteomics analyses of mother-infant dyads with HLA-conferred susceptibility to type 1 diabetes (n = 22), weaned to either an extensively hydrolyzed or regular cow's milk formula, were made. The LC-MS/MS analyses included samples from the beginning of third trimester, the time of delivery, 3 months postpartum, cord blood, and samples from the infants at 3, 6, 9, and 12 months. Correlations between ranked protein intensities were detected within the dyads, together with perinatal and age-related changes. Comparison with intestinal permeability data revealed a number of significant correlations, which could merit further consideration in this context.

Vitronectin promotes insulin resistance in trophoblast cells by activating JNK in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a common disorder in the clinic, which may lead to severe detrimental outcomes both for mothers and infants. However, the underlying mechanisms for GDM are still not clear. In the present study, we performed label-free proteomics using placentas from GDM patients and normal controls. Vitronectin caused our attention among differentially expressed proteins due to its potential role in the pathological progression of GDM. Vitronectin was increased in the placentas of GDM patients, which was confirmed by Western blot analysis. Vitronectin represses insulin signal transduction in trophoblast cells, whereas the knockdown of vitronectin further potentiates insulin-evoked events. Neutralization of CD51/61 abolishes the repressed insulin signal transduction in vitronectin-treated trophoblast cells. Moreover, vitronectin activates JNK in a CD51/61-depedent manner. Inhibition of JNK rescues impaired insulin signal transduction induced by vitronectin. Overall, our data indicate that vitronectin binds CD51/61 in trophoblast cells to activate JNK, and thus induces insulin resistance. In this regard, increased expression of vitronectin is likely a risk factor for the pathological progression of GDM. Moreover, blockade of vitronectin production or its receptors (CD51/61) may have therapeutic potential for dealing with GDM.

Circulating afamin positively correlated with the miR-122 expression and type 2 diabetes mellitus-related phenotype according to the duration of diabetes

Background

Afamin is a hepatokine that involves in glucose and lipids metabolism. miR-122 is mainly expressed in liver and involves in lipid and carbohydrate metabolism. This study aimed at investigating the circulating afamin, its correlation with type 2 diabetes mellitus (T2DM) and miR-122 gene expression in T2DM patients and healthy control subjects according to the duration of diabetes.

Methods

This case-control study included 220 participants, with 100 individuals serving as controls and 120 individuals diagnosed with type 2 diabetes mellitus (T2DM). The miR-122 gene expression was assessed using real-time PCR. The serum concentration of biochemical parameters such as glucose levels, lipid profile, and small-dense low-density lipoprotein (sdLDL) were measured using colorimetric kits. Circulating afamin and insulin levels were assayed using an ELISA kit. Glycated hemoglobin (HbA1c) was measured using capillary electrophoresis.

Results

Circulating afamin level was significantly higher in T2DM patients compared to the control group, (73.8 ± 10.8 vs. 65.9 ± 8.7, respectively; P < 0.001). Similarly, miR122 expression was significantly increased in T2DM patients compared to healthy control subjects (4.24 ± 2.01 vs. 1.00 ± 0.85, respectively; P < 0.001). Among patients diagnosed with T2DM, those with longstanding diabetes (>5 years) exhibited significantly higher levels of circulating afamin and miR-122 expression compared to individuals with a shorter duration of diabetes (≤5 years) (P < 0.05). Circulating afamin levels were significantly correlated with waist circumference, small-dense low-density lipoprotein (sdLDL), fasting blood sugar (FBS), insulin, resistance to insulin, and miR-122 expression, depending on the duration of the disease (P < 0.05). Furthermore, the performance of afamin as a diagnostic marker for T2DM was confirmed through receiver operating characteristic (ROC) analysis, yielding an area under the curve (AUC) of 0.7 (P < 0.001).

Conclusions

Circulating afamin involved in the T2DM-related complications and its concentration is positively correlated to the miR-122 expression, especially in patient with longstanding diabetes.

Technical report: The clinically useful selection of proteins protocol: An approach to identify clinically useful proteins for validation

Clinical proteomics studies aiming to develop markers of clinical outcome or disease typically involve distinct discovery and validation stages, neither of which focus on the clinical applicability of the candidate markers studied. Our clinically useful selection of proteins (CUSP) protocol proposes a rational approach, with statistical and non-statistical components, to identify proteins for the validation phase of studies that could be most effective markers of disease or clinical outcome. Additionally, this protocol considers commercially available analysis methods for each selected protein to ensure that use of this prospective marker is easily translated into clinical practice. SIGNIFICANCE: When developing proteomic markers of clinical outcomes, there is currently no consideration at the validation stage of how to implement such markers into a clinical setting. This has been identified by several studies as a limitation to the progression of research findings from proteomics studies. When integrated into a proteomic workflow, the CUSP protocol allows for a strategically designed validation study that improves researchers' abilities to translate research findings from discovery-based proteomics into clinical practice.

Molecular epidemiology of pregnancy using omics data: advances, success stories, and challenges

Multi-omics approaches have been successfully applied to investigate pregnancy and health outcomes at a molecular and genetic level in several studies. As omics technologies advance, research areas are open to study further. Here we discuss overall trends and examples of successfully using omics technologies and techniques (e.g., genomics, proteomics, metabolomics, and metagenomics) to investigate the molecular epidemiology of pregnancy. In addition, we outline omics applications and study characteristics of pregnancy for understanding fundamental biology, causal health, and physiological relationships, risk and prediction modeling, diagnostics, and correlations.

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.

Proteins and metabolites fingerprints of gestational diabetes mellitus forming protein-metabolite interactomes are its potential biomarkers

Gestational diabetes mellitus (GDM) is a consequence of glucose intolerance with an inadequate production of insulin that happens during pregnancy and leads to adverse health consequences for both mother and fetus. GDM patients are at higher risk for preeclampsia, and developing diabetes mellitus type 2 in later life, while the child born to GDM mothers are more prone to macrosomia, and hypoglycemia. The universally accepted diagnostic criteria for GDM are lacking, therefore there is a need for a diagnosis of GDM that can identify GDM at its early stage (first trimester). We have reviewed the literature on proteins and metabolites fingerprints of GDM. Further, we have performed protein-protein, metabolite-metabolite, and protein-metabolite interaction network studies on GDM proteins and metabolites fingerprints. Notably, some proteins and metabolites fingerprints are forming strong interaction networks at high confidence scores. Therefore, we have suggested that those proteins and metabolites that are forming protein-metabolite interactomes are the potential biomarkers of GDM. The protein-metabolite biomarkers interactome may help in a deep understanding of the prognosis, pathogenesis of GDM, and also detection of GDM. The protein-metabolites interactome may be further applied in planning future therapeutic strategies to promote long-term health benefits in GDM mothers and their children.

Human Milk Oligosaccharides Variation in Gestational Diabetes Mellitus Mothers

Gestational diabetes mellitus (GDM) is a common disease of pregnancy, but with very limited knowledge of its impact on human milk oligosaccharides (HMOs) in breast milk. This study aimed to explore the lactational changes in the concentration of HMOs in exclusively breastfeeding GDM mothers and the differences between GDM and healthy mothers. A total of 22 mothers (11 GDM mothers vs. 11 healthy mothers) and their offspring were enrolled in the study and the levels of 14 HMOs were measured in colostrum, transitional milk, and mature milk. Most of the HMOs showed a significant temporal trend with decreasing levels over lactation; however, there were some exceptions for 2′-Fucosyllactose (2′-FL), 3-Fucosyllactose (3-FL), Lacto-N-fucopentaose II (LNFP-II), and Lacto-N-fucopentaose III (LNFP-III). Lacto-N-neotetraose (LNnT) was significantly higher in GDM mothers in all time points and its concentrations in colostrum and transitional milk were correlated positively with the infant’s weight-for-age Z-score at six months postnatal in the GDM group. Significant group differences were also found in LNFP-II, 3′-Sialyllactose (3′-SL), and Disialyllacto-N-tetraose (DSLNT) but not in all lactational periods. The role of differently expressed HMOs in GDM needs to be further explored by follow-up studies.

Association of obesity and insulin resistance to gestational diabetes mellitus

Gestational diabetes mellitus is most commonly observed in pregnant women and it was significantly linked with dyslipidemia, obesity and insulin resistance. The present study aimed to evaluate the association of obesity, insulin resistance risk of gestational diabetes mellitus. This cross sectional study included total ninety (90) subjects out of this 30 subjects with 1st trimester, another 30 subjects were considered 2nd trimester and remaining 30 were 3rd trimester. The fasting, post parandial blood sugars, glycated haemoglobin, lipid profile and insulin levels were measured and data was recorded. There was a significantly elevated levels of fasting and post parandial blood sugars, glycated haemoglobin, total cholesterol, triacylglycerol, very low density lipoprotein, low density lipoprotein (p = 0.0001**) in all the trimesters of gestational diabetes mellitus subjects. Additionally, we also observed significantly decreased levels of high density lipoprotein, insulin and HOMA-IR (p = 0.0001**) in all the trimesters of gestational diabetes mellitus subjects. The present study IR raises as the pregnancy progresses and it is linked to bad outcomes for both the mother and the fetus. All trimesters of gestational diabetes mellitus should be screened for IR, and early treatment may assist to lessen the resulting difficulties.

The Search for Associations of Serum Proteins with the Presence of Unstable Atherosclerotic Plaque in Coronary Atherosclerosis

To study the associations of blood proteins with the presence of unstable atherosclerotic plaques in the arteries of patients with coronary atherosclerosis using quantitative proteomics. The studies involved two groups of men with coronary atherosclerosis (group 1 (St) had only stable atherosclerotic plaques; group 2 (Ns) had only unstable atherosclerotic plaques, according to histological analysis of tissue samples); the average age of patients was 57.95 ± 7.22. Protein concentrations in serum samples were determined using the PeptiQuant Plus Proteomics Kit. The identification of protein fractions was carried out by monitoring multiple reactions on a Q-TRAP 6500 mass spectrometer combined with a liquid chromatograph. Mass spectrometric identification revealed in serum samples from patients with unstable atherosclerotic plaques a reduced concentration of proteins in the blood: α-1-acid glycoprotein, α-1-antichymotrypsin, α-1-antitrypsin, ceruloplasmin, hemopexin, haptoglobin, apolipoprotein B-100, apolipoprotein L1, afamin and complement component (C3, C7, C9). Moreover, at the same time a high concentration complements factor H and attractin. The differences were considered significant at p < 0.05. It was found that the instability of atherosclerotic plaques is associated with the concentration of proteins: afamin, attractin, components of the complement system, hemopexin and haptoglobin. The data of our study showed the association of some blood proteins with the instability of atherosclerotic plaques in coronary atherosclerosis. Their potential role in the development of this disease and the possibility of using the studied proteins as biomarkers requires further research.

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.

Developmental Effects of (Pre-)Gestational Diabetes on Offspring: Systematic Screening Using Omics Approaches

Worldwide, gestational diabetes affects 2-25% of pregnancies. Due to related disturbances of the maternal metabolism during the periconceptional period and pregnancy, children bear an increased risk for future diseases. It is well known that an aberrant intrauterine environment caused by elevated maternal glucose levels is related to elevated risks for increased birth weights and metabolic disorders in later life, such as obesity or type 2 diabetes. The complexity of disturbances induced by maternal diabetes, with multiple underlying mechanisms, makes early diagnosis or prevention a challenging task. Omics technologies allowing holistic quantification of several classes of molecules from biological fluids, cells, or tissues are powerful tools to systematically investigate the effects of maternal diabetes on the offspring in an unbiased manner. Differentially abundant molecules or distinct molecular profiles may serve as diagnostic biomarkers, which may also support the development of preventive and therapeutic strategies. In this review, we summarize key findings from state-of-the-art Omics studies addressing the impact of maternal diabetes on offspring health.

Discovery of metabolic biomarkers for gestational diabetes mellitus in a Chinese population

Background

Gestational diabetes mellitus (GDM), one of the most common pregnancy complications, can lead to morbidity and mortality in both the mother and the infant. Metabolomics has provided new insights into the pathology of GDM and systemic analysis of GDM with metabolites is required for providing more clues for GDM diagnosis and mechanism research. This study aims to reveal metabolic differences between normal pregnant women and GDM patients in the second- and third-trimester stages and to confirm the clinical relevance of these new findings.

Methods

Metabolites were quantitated with the serum samples of 200 healthy pregnant women and 200 GDM women in the second trimester, 199 normal controls, and 199 GDM patients in the third trimester. Both function and pathway analyses were applied to explore biological roles involved in the two sets of metabolites. Then the trimester stage-specific GDM metabolite biomarkers were identified by combining machine learning approaches, and the logistic regression models were constructed to evaluate predictive efficiency. Finally, the weighted gene co-expression network analysis method was used to further capture the associations between metabolite modules with biomarkers and clinical indices.

Results

This study revealed that 57 differentially expressed metabolites (DEMs) were discovered in the second-trimester group, among which the most significant one was 3-methyl-2-oxovaleric acid. Similarly, 72 DEMs were found in the third-trimester group, and the most significant metabolites were ketoleucine and alpha-ketoisovaleric acid. These DEMs were mainly involved in the metabolism pathway of amino acids, fatty acids and bile acids. The logistic regression models for selected metabolite biomarkers achieved the area under the curve values of 0.807 and 0.81 for the second- and third-trimester groups. Furthermore, significant associations were found between DEMs/biomarkers and GDM-related indices.

Conclusions

Metabolic differences between healthy pregnant women and GDM patients were found. Associations between biomarkers and clinical indices were also investigated, which may provide insights into pathology of GDM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12986-021-00606-8.

Basement membrane collagen IV deficiency promotes abdominal aortic aneurysm formation

Abdominal aortic aneurysm (AAA) is a complex disease which is incompletely accounted for. Basement membrane (BM) Collagen IV (COL4A1/A2) is abundant in the artery wall, and several lines of evidence indicate a protective role of baseline COL4A1/A2 in AAA development. Using Col4a1/a2 hemizygous knockout mice (Col4a1/a2^+/-, 129Svj background) we show that partial Col4a1/a2 deficiency augmented AAA formation. Although unchallenged aortas were morphometrically and biomechanically unaffected by genotype, explorative proteomic analyses of aortas revealed a clear reduction in BM components and contractile vascular smooth muscle cell (VSMC) proteins, suggesting a central effect of the BM in maintaining VSMCs in the contractile phenotype. These findings were translated to human arteries by showing that COL4A1/A2 correlated to BM proteins and VSMC markers in non-lesioned internal mammary arteries obtained from coronary artery bypass procedures. Moreover, in human AAA tissue, MYH11 (VSMC marker) was depleted in areas of reduced COL4 as assessed by immunohistochemistry. Finally, circulating COL4A1 degradation fragments correlated with AAA progression in the largest Danish AAA cohort, suggesting COL4A1/A2 proteolysis to be an important feature of AAA formation. In sum, we identify COL4A1/A2 as a critical regulator of VSMC phenotype and a protective factor in AAA formation.

Hepatokine levels during the first or early second trimester of pregnancy and the subsequent risk of gestational diabetes mellitus: a systematic review and meta-analysis

PURPOSE

The relationship between hepatokine levels during the first or early second trimester of pregnancy and the subsequent risk of gestational diabetes mellitus (GDM) have been studied extensively. However, conclusions remain debateable whether hepatokines are potential markers of GDM. We conducted a meta-analysis of published articles to understand the association between circulating levels of selected hepatokines (including FGF21, fetuin-A, afamin, adropin, ficolin-3, selenoprotein P, ANGPTL4 and AGF) and the risk of GDM.

MATERIALS AND METHODS

We searched the PubMed, Embase, Cochrane Library and Web of Science databases for studies published before January 2021 that examined the association between hepatokines and GDM (Prospero Registration# CRD42020191408). The quality was assessed by the Newcastle-Ottawa Scale (NOS). Pooled standard mean differences (SMDs) and weighted mean differences (WMDs) with 95% confidence intervals (CIs) were used to compare the levels of hepatokines in different groups using fixed effects or random effects models. Meta-regression analysis and publication bias were conducted in accordance with standard methods. The trim-fill adjustment method was used to further assess the possible effect of publication bias. Sensitivity analysis was performed by omitting each study one at a time.

RESULTS

The meta-analysis included 31 observational studies relating hepatokine levels to GDM in 4729 participants (1908 GDM, 2821 non-GDM). Serum FGF21 levels in patients with GDM were higher than those in healthy pregnant women during the second trimester and after delivery (SMD 0.89, [95% CI] 0.01-1.78 for the second trimester; SMD 1.42, [95% CI] 0.86-1.98 for after delivery). The serum levels of afamin in patients with GDM were significantly higher than those in healthy pregnant women during the first trimester and before pregnancy (SMD 0.51, [95% CI] 0.15-0.86 for first trimester; SMD 0.97, [95% CI] 0.45-1.50 for before pregnancy). Serum adropin levels in patients with GDM were higher than those in healthy pregnant women during the first and third trimesters of pregnancy (SMD 4.26, [95% CI] 3.30-5.23 for the first trimester; SMD 4.02, [95% CI] 3.09-4.94 for the third trimester). The serum levels of ficolin-3 in GDM patients were higher than those in healthy pregnant women during the second and third trimesters of pregnancy (WMD 1.43, [95% CI] 0.91-1.96 for the second trimester; SMD 1.28, [95% CI] 0.72-1.84 for the third trimester). The serum AGF level of patients with GDM was higher than that of healthy pregnant women in the control group in the third trimester (WMD 61 [95% CI] 37.04-81.96). The serum levels of selenoprotein P in patients with GDM were higher than those in healthy pregnant women in the control group during the first trimester (WMD 7.09 [95% CI] 4.6-9.57).

CONCLUSIONS

Measurement of circulating hepatokines in the first or second trimester of pregnancy may improve the identification of women at risk of developing GDM later. Prospective evaluation of the combination of hepatokines and maternal characteristics for early identification of those who do and do not require OGTT is warranted. Additional well-designed prospective studies with longitudinal assessment of hepatokines during pregnancy are needed to understand the trajectories and dynamic associations of hepatokines with GDM risk.

Emerging Protein Biomarkers for the Diagnosis or Prediction of Gestational Diabetes-A Scoping Review

Introduction: Gestational diabetes (GDM), defined as hyperglycemia with onset or initial recognition during pregnancy, has a rising prevalence paralleling the rise in type 2 diabetes (T2DM) and obesity. GDM is associated with short-term and long-term consequences for both mother and child. Therefore, it is crucial we efficiently identify all cases and initiate early treatment, reducing fetal exposure to hyperglycemia and reducing GDM-related adverse pregnancy outcomes. For this reason, GDM screening is recommended as part of routine pregnancy care. The current screening method, the oral glucose tolerance test (OGTT), is a lengthy, cumbersome and inconvenient test with poor reproducibility. Newer biomarkers that do not necessitate a fasting sample are needed for the prompt diagnosis of GDM. The aim of this scoping review is to highlight and describe emerging protein biomarkers that fulfill these requirements for the diagnosis of GDM. Materials and Methods: This scoping review was conducted according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for scoping reviews using Cochrane Central Register of Controlled Trials (CENTRAL), the Cumulative Index to Nursing & Allied Health Literature (CINAHL), PubMed, Embase and Web of Science with a double screening and extraction process. The search included all articles published in the literature to July 2020. Results: Of the 3519 original database citations identified, 385 were eligible for full-text review. Of these, 332 (86.2%) were included in the scoping review providing a total of 589 biomarkers studied in relation to GDM diagnosis. Given the high number of biomarkers identified, three post hoc criteria were introduced to reduce the items set for discussion: we chose only protein biomarkers with at least five citations in the articles identified by our search and published in the years 2017-2020. When applied, these criteria identified a total of 15 biomarkers, which went forward for review and discussion. Conclusions: This review details protein biomarkers that have been studied to find a suitable test for GDM diagnosis with the potential to replace the OGTT used in current GDM screening protocols. Ongoing research efforts will continue to identify more accurate and practical biomarkers to take GDM screening and diagnosis into the 21st century.

Serum Afamin a Novel Marker of Increased Hepatic Lipid Content

AIM

Afamin is a liver-produced glycoprotein, a potential early marker of metabolic syndrome. Here we investigated regulation of afamin in a course of the metabolic disease development and in response to 3-month exercise intervention.

METHODS

We measured whole-body insulin sensitivity (euglycemic hyperinsulinemic clamp), glucose tolerance, abdominal adiposity, hepatic lipid content (magnetic resonance imaging/spectroscopy), habitual physical activity (accelerometers) and serum afamin (enzyme-linked immunosorbent assay) in 71 middle-aged men with obesity, prediabetes and newly diagnosed type 2 diabetes. Effects of 3-month exercise were investigated in 22 overweight-to-obese middle-aged individuals (16M/6F).

RESULTS

Prediabetes and type 2 diabetes, but not obesity, were associated with increased serum afamin (p<0.001). Afamin correlated positively with hepatic lipids, fatty liver index and liver damage markers; with parameters of adiposity (waist circumference, %body fat, adipocyte diameter) and insulin resistance (fasting insulin, C-peptide, HOMA-IR; p<0.001 all). Moreover, afamin negatively correlated with whole-body insulin sensitivity (M-value/Insulin, p<0.001). Hepatic lipids and fasting insulinemia were the most important predictors of serum afamin, explaining >63% of its variability. Exercise-related changes in afamin were paralleled by reciprocal changes in insulinemia, insulin resistance and visceral adiposity. No significant change in hepatic lipid content was observed.

CONCLUSIONS

Subjects with prediabetes and type 2 diabetes had the highest serum afamin levels. Afamin was more tightly related to hepatic lipid accumulation, liver damage and insulin resistance than to obesity.

FGF21 Serum Levels in the Early Second Trimester Are Positively Correlated With the Risk of Subsequent Gestational Diabetes Mellitus: A Propensity-Matched Nested Case-Control Study

BACKGROUND

As an important endocrine hormone regulating glucose metabolism, fibroblast growth factor 21 (FGF21) is increased in individuals with gestational diabetes mellitus (GDM) after 24 gestational weeks. However, it is unknown whether the increase in FGF21 precedes the diagnosis of GDM.

METHODS

In this nested case-control study, 133 pregnant women with GDM and 133 pregnant women with normal glucose tolerance (NGT) were identified through propensity score matching, and serum FGF21 levels were measured at 14 to 21 gestational weeks, before GDM is routinely identified. The differences in FGF21 levels were compared. The association between FGF21 and the occurrence of GDM was evaluated using logistic regression models with adjustment for confounders.

RESULTS

The serum FGF21 levels of the GDM group at 14 to 21 gestational weeks were significantly higher than those of the NGT group overall (P < 0.001), with similar results observed between the corresponding BMI subgroups (P < 0.05). The 2nd (OR 1.224, 95% CI 0.603-2.485), 3rd (OR 2.478, 1.229-5.000), and 4th (OR 3.419, 95% CI 1.626-7.188) FGF21 quartiles were associated with greater odds of GDM occurrence than the 1st quartile after multivariable adjustments.

CONCLUSIONS

The serum FGF21 levels in GDM groups increased in the early second trimester, regardless of whether participants were stratified according to BMI. After adjusting for confounding factors, the FGF21 levels in the highest quartile were associated with more than three times higher probability of the diagnosis of GDM in the pregnancy as compared to levels in the first quartile.

Gestational Diabetes Mellitus-Innovative Approach to Prediction, Diagnosis, Management, and Prevention of Future NCD-Mother and Offspring

Gestational diabetes mellitus (GDM) is the commonest medical complication of pregnancy. The association of GDM with immediate pregnancy complications including excess fetal growth and adiposity with subsequent risk of birth trauma and with hypertensive disorders of pregnancy is well recognized. However, the associations with wide ranges of longer-term health outcomes for mother and baby, including the lifetime risks of obesity, pre-diabetes, and diabetes and cardiovascular disease have received less attention and few health systems address these important issues in a systematic way. This article reviews historical and recent data regarding prediction of GDM using demographic, clinical, and biochemical parameters. We evaluate current and potential future diagnostic approaches designed to most effectively identify GDM and extend this analysis into a critical evaluation of lifestyle and nutritional/pharmacologic interventions designed to prevent the development of GDM. The general approach to management of GDM during pregnancy is then discussed and the major final focus of the article revolves around the importance of a GDM diagnosis as a future marker of the risk of non-communicable disease (NCD), in particular pre-diabetes, diabetes, and cardiovascular disease, both in mother and offspring.

Quantitative Comparative Proteomics Reveals Candidate Biomarkers for the Early Prediction of Gestational Diabetes Mellitus: A Preliminary Study

AIM

To identify differentially expressed proteins (DEPs) in 1^st trimester maternal plasma between pregnant women at risk for gestational diabetes mellitus (GDM) and uncomplicated controls.

MATERIALS AND METHODS

First-trimester plasma from five women who developed GDM and five from non-diabetic ones were analyzed using isobaric tag for relative and absolute quantitation - labeled proteomics. Enzyme-linked immunosorbent assay was further applied in an independent cohort of 25 GDM cases and 25 controls for verification.

RESULTS

Prenylcysteine oxidase 1 (PCYOX1), beta-ala-his dipeptidase (CNDP1), extracellular matrix protein 1 (ECM1), basement membrane-specific heparan sulfate proteoglycan core protein (HSPG2), thrombospondin-4 (TSP-4) demonstrated significant differences in expression between the two groups (p<0.05). DEPs are mainly associated with complement and coagulation cascades.

CONCLUSION

The reported plasma proteomic changes represent potential biomarkers for the early identification of women at risk for GDM. Future studies using larger and more diverse cohorts are necessary to assess the clinical utility of these findings.

Vitamin D Correction Down-Regulates Serum Amyloid P Component Levels in Vitamin D Deficient Arab Adults: A Single-Arm Trial

Vitamin D (VD) has been observed to have anti-inflammatory properties. However, the effects of VD supplementation on the serum amyloid P component (SAP) has not been established. This study aimed to investigate the effect of VD supplementation on serum SAP levels in Arab adults. A total of 155 VD-deficient adult Saudis (56 males and 99 females) were recruited in this non-randomized, 6-month, single-arm trial. The intervention was as follows; cholecalciferol 50,000 international units (IU) every week for the first 2 months, followed by 50,000 twice a month for the next two months, and for the last two months, 1000 IU daily. Serum 25(OH)D, SAP, C-reactive protein (CRP), lipid profile, and glucose were assessed at baseline and post-intervention. At post-intervention, VD levels were significantly increased, while SAP levels significantly decreased in all study participants. Remarkably, this reduction in SAP was more significant in males than females after stratification. SAP was inversely correlated with VD overall (r = −0.17, p < 0.05), and only in males (r = −0.27, p < 0.05) after stratification according to sex after 6 months of VD supplementation. Such a relationship was not observed at baseline. VD supplementation can favorably modulate serum SAP concentrations in Arab adults, particularly in males.

Proteome profiling of gestational diabetes mellitus at 16-18 weeks revealed by LC-MS/MS

BACKGROUND

The practices used to diagnose gestational diabetes mellitus (GDM) could only be carried out around the time of detectable symptoms, and predictive capacity is little.

METHODS

LC-MS/MS was conducted to explore overview proteomics for GDM complicated pregnant woman at 16-18 gestation weeks, while normal pregnant for control. Enzyme-linked immunosorbent assay was further applied in an independent cohort of 15 GDM cases and 15 controls for verification.

RESULTS

The results indicated that 24 protein expression levels were significantly changed in GDM group samples, and inflammation, oxidative stress, insulin resistance, blood coagulation, and lipid homeostasis were associated with GDM. The abnormal expression of CRP and IGFBP2 was verified in the first-trimester maternal plasma in women who subsequently developed GDM.

CONCLUSIONS

This study not only identified 24 potential predictive biomarkers for GDM also provided a global overview of protein rearrangements induced by GDM.

Association of Proteins Modulating Immune Response and Insulin Clearance During Gestation with Antenatal Complications in Patients with Gestational or Type 2 Diabetes Mellitus

Background: The purpose of the study is to establish and quantitatively assess protein markers and their combination in association with insulin uptake that may be have value for early prospective recognition of diabetic fetopathy (DF) as a complication in patients with diabetes mellitus during gestation. Methods: Proteomic surveying and accurate quantitative measurement of selected proteins from plasma samples collected from the patients with gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM) who gave birth of either healthy or affected by maternal diabetes newborns was performed using mass spectrometry. Results: We determined and quantitatively measured several proteins, including CRP, CEACAM1, CNDP1 and Ig-family that were significantly differed in patients that gave birth of newborns with signs of DF. We found that patients with newborns associated with DF are characterized by significantly decreased CEACAM1 (113.18 ± 16.23 ng/mL and 81.09 ± 10.54 ng/mL in GDM and T2DM, p < 0.005) in contrast to control group (515.6 ± 72.14 ng/mL, p < 0.005). On the contrary, the concentration of CNDP1 was increased in DF-associated groups and attained 49.3 ± 5.18 ng/mL and 37.7 ± 3.34 ng/mL (p < 0.005) in GDM and T2DM groups, respectively. Among other proteins, dramatically decreased concentration of IgG4 and IgA2 subclasses of immunoglobulins were noticed. Conclusion: The combination of the measured markers may assist (AUC = 0.893 (CI 95%, 0.785–0.980) in establishing the clinical finding of the developing DF especially in patients with GDM who are at the highest risk of chronic insulin resistance.

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.