Maternal serum osteocalcin at 11-14 weeks of gestation in gestational diabetes mellitus

The role of bone in energy metabolism: A focus on osteocalcin

Understanding the mechanisms involved in whole body glucose regulation is key for the discovery of new treatments for type 2 diabetes (T2D). Historically, glucose regulation was largely focused on responses to insulin and glucagon. Impacts of incretin-based therapies, and importance of muscle mass, are also highly relevant. Recently, bone was recognized as an endocrine organ, with several bone proteins, known as osteokines, implicated in glucose metabolism through their effects on the liver, skeletal muscle, and adipose tissue. Research efforts mostly focused on osteocalcin (OC) as a leading example. This review will provide an overview on this role of bone by discussing bone turnover markers (BTMs), the receptor activator of nuclear factor kB ligand (RANKL), osteoprotegerin (OPG), sclerostin (SCL) and lipocalin 2 (LCN2), with a focus on OC. Since 2007, some, but not all, research using mostly OC genetically modified animal models suggested undercarboxylated (uc) OC acts as a hormone involved in energy metabolism. Most data generated from in vivo, ex vivo and in vitro models, indicate that exogenous ucOC administration improves whole-body and skeletal muscle glucose metabolism. Although data in humans are generally supportive, findings are often discordant likely due to methodological differences and observational nature of that research. Overall, evidence supports the concept that bone-derived factors are involved in energy metabolism, some having beneficial effects (ucOC, OPG) others negative (RANKL, SCL), with the role of some (LCN2, other BTMs) remaining unclear. Whether the effect of osteokines on glucose regulation is clinically significant and of therapeutic value for people with insulin resistance and T2D remains to be confirmed.

Predictive Utility of Biochemical Markers for the Diagnosis and Prognosis of Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a common complication during pregnancy with an increasing prevalence worldwide. Early prediction of GDM and its associated adverse outcomes is crucial for timely intervention and improved maternal and fetal health. The objective of this review is to provide a comprehensive summary of contemporary evidence on biomarkers, focusing on their potential to predict the development of GDM and serve as predictors of maternal, fetal, and neonatal outcomes in women with GDM. A literature search was conducted in the PubMed database using relevant terms. Original research articles published in English between 1 January 2015, and 30 June 2024, were included. A two-stage screening process was employed to identify studies on biomarkers for GDM diagnosis and prognosis and to evaluate the evidence for each biomarker's diagnostic performance and its potential prognostic correlation with GDM. Various biochemical markers, including adipokines, inflammatory markers, insulin resistance markers, glycemic markers, lipid profile markers, placenta-derived markers, and other related markers, have shown promise in identifying women at risk of developing GDM and predicting adverse pregnancy outcomes. Several promising markers with high predictive performance were identified. However, no single biomarker has demonstrated sufficient accuracy to replace the current diagnostic criteria for GDM. The complexity of multiple pathways in GDM pathogenesis highlights the need for a multi-marker approach to improve risk stratification and guide personalized management strategies. While significant progress has been made in GDM biomarker research, further studies are required to refine and validate these markers for clinical use and to develop a comprehensive, evidence-based approach to GDM prediction and management that can improve maternal and child health outcomes.

Cardiovascular Disease-Associated MicroRNAs as Novel Biomarkers of First-Trimester Screening for Gestational Diabetes Mellitus in the Absence of Other Pregnancy-Related Complications

We assessed the diagnostic potential of cardiovascular disease-associated microRNAs for the early prediction of gestational diabetes mellitus (GDM) in singleton pregnancies of Caucasian descent in the absence of other pregnancy-related complications. Whole peripheral venous blood samples were collected within 10 to 13 weeks of gestation. This retrospective study involved all pregnancies diagnosed with only GDM (n = 121) and 80 normal term pregnancies selected with regard to equality of sample storage time. Gene expression of 29 microRNAs was assessed using real-time RT-PCR. Upregulation of 11 microRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, and miR-574-3p) was observed in pregnancies destinated to develop GDM. Combined screening of all 11 dysregulated microRNAs showed the highest accuracy for the early identification of pregnancies destinated to develop GDM. This screening identified 47.93% of GDM pregnancies at a 10.0% false positive rate (FPR). The predictive model for GDM based on aberrant microRNA expression profile was further improved via the implementation of clinical characteristics (maternal age and BMI at early stages of gestation and an infertility treatment by assisted reproductive technology). Following this, 69.17% of GDM pregnancies were identified at a 10.0% FPR. The effective prediction model specifically for severe GDM requiring administration of therapy involved using a combination of these three clinical characteristics and three microRNA biomarkers (miR-20a-5p, miR-20b-5p, and miR-195-5p). This model identified 78.95% of cases at a 10.0% FPR. The effective prediction model for GDM managed by diet only required the involvement of these three clinical characteristics and eight microRNA biomarkers (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, and miR-574-3p). With this, the model identified 50.50% of GDM pregnancies managed by diet only at a 10.0% FPR. When other clinical variables such as history of miscarriage, the presence of trombophilic gene mutations, positive first-trimester screening for preeclampsia and/or fetal growth restriction by the Fetal Medicine Foundation algorithm, and family history of diabetes mellitus in first-degree relatives were included in the GDM prediction model, the predictive power was further increased at a 10.0% FPR (72.50% GDM in total, 89.47% GDM requiring therapy, and 56.44% GDM managed by diet only). Cardiovascular disease-associated microRNAs represent promising early biomarkers to be implemented into routine first-trimester screening programs with a very good predictive potential for GDM.

Novel Biomolecules in the Pathogenesis of Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is one of the most common metabolic diseases in pregnant women. Its early diagnosis seems to have a significant impact on the developing fetus, the course of delivery, and the neonatal period. It may also affect the later stages of child development and subsequent complications in the mother. Therefore, the crux of the matter is to find a biopredictor capable of singling out women at risk of developing GDM as early as the very start of pregnancy. Apart from the well-known molecules with a proven and clear-cut role in the pathogenesis of GDM, e.g., adiponectin and leptin, a potential role of newer biomolecules is also emphasized. Less popular and less known factors with different mechanisms of action include: galectins, growth differentiation factor-15, chemerin, omentin-1, osteocalcin, resistin, visfatin, vaspin, irisin, apelin, fatty acid-binding protein 4 (FABP4), fibroblast growth factor 21, and lipocalin-2. The aim of this review is to present the potential and significance of these 13 less known biomolecules in the pathogenesis of GDM. It seems that high levels of FABP4, low levels of irisin, and high levels of under-carboxylated osteocalcin in the serum of pregnant women can be used as predictive markers in the diagnosis of GDM. Hopefully, future clinical trials will be able to determine which biomolecules have the most potential to predict GDM.

High maternal osteocalcin levels during pregnancy is associated with low birth weight infants: A nested case-control study in China

BACKGROUND

Low birth weight infants (LBW) are at risk of chronic diseases in later life due to the disorder of energy metabolism during pregnancy. Osteocalcin (OC) has been identified as a hormone that regulate energy metabolism. However, few studies have researched on the associations between maternal serum OC levels and low birth weight infants.

OBJECTIONS

To examine the associations between maternal serum OC concentrations and LBW.

METHODS

This was a nested case-control study involving a total of 230 pregnant women delivering LBW and 382 control pregnant women (matched for infant gender, gestational age at blood draw, region of Maternity and Child Healthcare Hospital and maternal age in 1: (1-2) ratio). One serum sample was collected from each pregnant woman at 5-35 weeks' gestation. Pregnant women were divided into 3 groups (1st, 2nd and 3rd trimester group). There were 60 and 142 and 28 pregnant women delivering LBW in the first, second and third trimester, respectively. Similarly, there were 101 and 233 and 48 controls in the first, second and third trimester, respectively. Maternal serum OC and 25(OH)D concentrations were categorized into low and high levels, the low level used as reference in analyses. Binary logistic regression model was used to compute odd radio (ORs) for LBW according to levels of maternal serum OC and 25(OH)D.

RESULTS

Compared with the subjects in low level in first trimester, LBW was two times as likely to occur among pregnancy women with high serum OC concentrations (OR = 2.04, 95%CI:1.05-3.96). After adjusted for confounding factors, a significant positive relationship still existed (adjusted ORs = 2.29, 95%CI: 1.11-4.72). In second trimester, women in high level of serum OC had nearly 1.6 times the risk of delivering LBW infants as those in the low level (OR = 1.55, 95%CI: 1.01-2.37). After adjusted for confounding factors, the ORs increased (ORs = 1.59, 95%CI:1.03-2.45). No significant associations were found between maternal serum OC levels and LBW in third trimester. In addition, there were no associations between maternal 25(OH)D concentrations and LBW during pregnancy.

CONCLUSION

High maternal serum OC levels in the first or the second trimester during pregnancy may be associated with the risk of LBW.

Osteocalcin Serum Levels in Gestational Diabetes Mellitus and Their Intrinsic and Extrinsic Determinants: Systematic Review and Meta-Analysis

BACKGROUND

Undercarboxylated osteocalcin (ucOC) increases insulin release and insulin resistance in mice. In humans, evidence is scarce but a correlation of ucOC and total osteocalcin (tOC) with glycemic status markers has been demonstrated. The relationship of ucOC and tOC with gestational diabetes mellitus (GDM) has been even less characterized.

OBJECTIVE

To assess the mean difference of tOC and ucOC serum concentrations among nondiabetic pregnant women and women diagnosed as GDM in the second trimester of pregnancy and to determine the possible intrinsic and extrinsic contributors to this difference.

METHODS

A systematic search was performed to identify relevant studies published in English and Spanish using PubMed, SCOPUS, ISI Web of Knowledge, and PROSPERO database for meta-analysis. Observational studies measuring mean serum levels of osteocalcin among GDM, with at least 10 subjects analyzed in each group were selected. Mean difference (MD) by random effects model was used. Heterogeneity between studies was assessed using Cochran's Q, H, and I ² statistics.

RESULTS

From 38 selected studies, 5 were retained for analysis for a total of 1119 pregnant women. Serum concentrations of tOC were not significantly different among women with GDM and nondiabetic pregnant controls (MD: 1.56; 95% CI: -0.70 to 3.82; p = 0.175). Meanwhile, ucOC serum levels were significantly higher among women with GDM (MD: 1.17; 95% CI: 0.24 to 2.11; p = 0.013). The only factor influencing tOC was the UV index, showing a reduction in mean difference between GDM and controls when exposed to higher concentrations of UV rays.

CONCLUSIONS

This meta-analysis provides evidence to support the use of ucOC as a potential marker for GDM rather than tOC, yielding very little variability among studies and no difference among methods or brands used for its analysis.