Association between transthyretin concentrations and gestational diabetes mellitus in Chinese women

Associations of maternal serum transthyretin concentration with pregnancy and birth outcomes

OBJECTIVE

This study aims to explore the association of maternal serum transthyretin (TTR) concentrations with adverse pregnancy and birth outcomes, as well as the variations in TTR concentrations across different gestational weeks in relation to these outcomes.

METHODS

This retrospective cohort study included 6,584 women who delivered at The Second Affiliated Hospital of Wenzhou Medical University between January 1, 2022 and January 30, 2024. Logistic regression and Restricted cubic spline (RCS) models were applied to evaluate the association between TTR levels and the risk of complications, based on TTR quartile analyses. Locally estimated scatter plot smoothing (LOESS) curves were performed to provide a graphical representation of the relationship between TTR levels and gestational weeks.

RESULTS

Significant negative correlations were observed between maternal TTR levels and the risk of gestational diabetes mellitus (GDM), preeclampsia (PE), liver disease, anemia during pregnancy, and preterm delivery (all P < 0.001). The RCS models revealed a non-linear relationship between TTR levels and maternal comorbidities, including anemia (adjusted OR 0.992 [95% CI 0.990-0.994]; P = 0.017), liver disease (adjusted OR 0.991 [95% CI 0.988-0.994]; P < 0.001), hypothyroidism (adjusted OR 0.999 [95% CI 0.996-1.001]; P = 0.023) and preterm delivery (adjusted OR 0.986 [95% CI 0.983-0.989]; P < 0.001). The LOESS curves indicated a declining trend in TTR concentrations during the third trimester of pregnancy.

CONCLUSION

Maternal TTR concentrations showed an inverse linear association with the incidence of GDM and PE. Moreover, complex non-linear relationships were identified with TTR levels and comorbidities such as liver disease, anemia, hypothyroidism during pregnancy, and preterm delivery.

Transthyretin mutagenesis: impact on amyloidogenesis and disease

Transthyretin (TTR), a homotetrameric protein found in plasma, cerebrospinal fluid, and the eye, plays a pivotal role in the onset of several amyloid diseases with high morbidity and mortality. Protein aggregation and fibril formation by wild-type TTR and its natural more amyloidogenic variants are hallmarks of ATTRwt and ATTRv amyloidosis, respectively. The formation of soluble amyloid aggregates and the accumulation of insoluble amyloid fibrils and deposits in multiple tissues can lead to organ dysfunction and cell death. The most frequent manifestations of ATTR are polyneuropathies and cardiomyopathies. However, clinical manifestations such as carpal tunnel syndrome, leptomeningeal, and ocular amyloidosis, among several others may also occur. This review provides an up-to-date listing of all single amino-acid mutations in TTR known to date. Of approximately 220 single-point mutations, 93% are considered pathogenic. Aspartic acid is the residue mutated with the highest frequency, whereas tryptophan is highly conserved. "Hot spot" mutation regions are mainly assigned to β-strands B, C, and D. This manuscript also reviews the protein aggregation models that have been proposed for TTR amyloid fibril formation and the transient conformational states that convert native TTR into aggregation-prone molecular species. Finally, it compiles the various in vitro TTR aggregation protocols currently in use for research and drug development purposes. In short, this article reviews and discusses TTR mutagenesis and amyloidogenesis, and their implications in disease onset.

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.

Novel insights into the genetic architecture of pregnancy glycemic traits from 14,744 Chinese maternities

Glycemic traits are critical indicators of maternal and fetal health during pregnancy. We performed genetic analysis for five glycemic traits in 14,744 Chinese pregnant women. Our genome-wide association study identified 25 locus-trait associations, including established links between gestational diabetes mellitus (GDM) and the genes CDKAL1 and MTNR1B. Notably, we discovered a novel association between fasting glucose during pregnancy and the ESR1 gene (estrogen receptor), which was validated by an independent study in pregnant women. The ESR1-GDM link was recently reported by the FinnGen project. Our work enhances the findings in East Asian populations and highlights the need for independent studies. Further analyses, including genetic correlation, Mendelian randomization, and transcriptome-wide association studies, provided genetic insights into the relationship between pregnancy glycemic traits and hypertension. Overall, our findings advance the understanding of genetic architecture of pregnancy glycemic traits, especially in East Asian populations.

Diagnostic and prognostic value of triglyceride glucose index: a comprehensive evaluation of meta-analysis

OBJECTIVE

The present umbrella review aims to collate and summarize the findings from previous meta-analyses on the Triglyceride and Glucose (TyG) Index, providing insights to clinicians, researchers, and policymakers regarding the usefulness of this biomarker in various clinical settings.

METHODS

A comprehensive search was conducted in PubMed, Scopus, and Web of Science up to April 14, 2024, without language restrictions. The AMSTAR2 checklist assessed the methodological quality of the included meta-analyses. Statistical analyses were performed using Comprehensive Meta-Analysis (CMA) software.

RESULTS

A total of 32 studies were finally included. The results revealed significant associations between the TyG index and various health outcomes. For kidney outcomes, a high TyG index was significantly associated with an increased risk of contrast-induced nephropathy (CIN) (OR = 2.24, 95% CI: 1.82-2.77) and chronic kidney disease (CKD) (RR = 1.46, 95% CI: 1.32-1.63). High TyG index was significantly associated with an increased risk of type 2 diabetes mellitus (T2DM) (RR = 3.53, 95% CI: 2.74-4.54), gestational diabetes mellitus (GDM) (OR = 2.41, 95% CI: 1.48-3.91), and diabetic retinopathy (DR) (OR = 2.34, 95% CI: 1.31-4.19). Regarding metabolic diseases, the TyG index was significantly higher in patients with obstructive sleep apnea (OSA) (SMD = 0.86, 95% CI: 0.57-1.15), metabolic syndrome (MD = 0.83, 95% CI: 0.74-0.93), and non-alcoholic fatty liver disease (NAFLD) (OR = 2.36, 95% CI: 1.88-2.97) compared to those without these conditions. In cerebrovascular diseases, a higher TyG index was significantly associated with an increased risk of dementia (OR = 1.14, 95% CI: 1.12-1.16), cognitive impairment (OR = 2.31, 95% CI: 1.38-3.86), and ischemic stroke (OR = 1.37, 95% CI: 1.22-1.54). For cardiovascular outcomes, the TyG index showed significant associations with an increased risk of heart failure (HF) (HR = 1.21, 95% CI: 1.12-1.30), atrial fibrillation (AF) (SMD = 1.22, 95% CI: 0.57-1.87), and hypertension (HTN) (RR = 1.52, 95% CI: 1.25-1.85).

CONCLUSION

The TyG index is a promising biomarker for screening and predicting various medical conditions, particularly those related to insulin resistance and metabolic disorders. However, the heterogeneity and methodological quality of the included studies suggest the need for further high-quality research to confirm these findings and refine the clinical utility of the TyG index.

Retinol-binding protein 4 (RBP4) circulating levels and gestational diabetes mellitus: a systematic review and meta-analysis

Background

Gestational diabetes mellitus (GDM) is a prevalent condition where diabetes is diagnosed during pregnancy, affecting both maternal and fetal outcomes. Retinol-binding protein 4 (RBP4) is a circulating adipokine which belongs to the lipocalin family and acts as a specific carrier protein that delivers retinol (vitamin A) from the liver to the peripheral tissues. Growing data indicate that circulating RBP4 levels may positively correlate with GDM. Thus, this systematic review and meta-analysis aimed to investigate the potential relationship between circulating RBP4 levels and GDM when measured at various stages of pregnancy.

Methods

MEDLINE, CINAHL, EMCARE, EMBASE, Scopus, and Web of Science databases were searched to identify studies comparing pregnant women with and without GDM, whose circulating RBP4 levels were measured in at least one pregnancy trimester. Findings were reported using standardized mean difference (SMD) and random-effects models were used to account for variability among studies. Furthermore, the risk of bias was assessed using the RoBANS tool.

Results

Out of the 34 studies identified, 32 were included in the meta-analysis (seven with circulating RBP4 levels measured in the first trimester, 19 at 24-28 weeks, and 14 at >28 weeks of pregnancy). RBP4 levels were statistically higher in the GDM group than in controls when measured during all these pregnancy stages, with the noted RBP4 SMD being 0.322 in the first trimester (95% CI: 0.126-0.517; p < 0.001; 946 GDM cases vs. 1701 non-GDM controls); 0.628 at 24-28 weeks of gestation (95% CI: 0.290-0.966; p < 0.001; 1776 GDM cases vs. 1942 controls); and 0.875 at >28 weeks of gestation (95% CI: 0.252-1.498; p = 0.006; 870 GDM cases vs. 1942 non-GDM controls). Significant study heterogeneity was noted for all three pregnancy timepoints.

Conclusion

The present findings indicate consistently higher circulating RBP4 levels in GDM cases compared to non-GDM controls, suggesting the potential relevance of RBP4 as a biomarker for GDM. However, the documented substantial study heterogeneity, alongside imprecision in effect estimates, underscores the need for further research and standardization of measurement methods to elucidate whether RBP4 can be utilized in clinical practice as a potential GDM biomarker.

Systematic review registration

PROSPERO (CRD42022340097: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022340097).

Shared peripheral blood biomarkers for Alzheimer’s disease, major depressive disorder, and type 2 diabetes and cognitive risk factor analysis

Background

Alzheimer's disease (AD), type 2 diabetes mellitus (T2DM), and Major Depressive Disorder (MDD) have a higher incidence rate in modern society. Although increasing evidence supports close associations between the three, the mechanisms underlying their interrelationships remain elucidated.

Objective

The primary purpose is to explore the shared pathogenesis and the potential peripheral blood biomarkers for AD, MDD, and T2DM.

Methods

We downloaded the microarray data of AD, MDD, and T2DM from the Gene Expression Omnibus database and constructed co-expression networks by Weighted Gene Co-Expression Network Analysis to identify differentially expressed genes. We took the intersection of differentially expressed genes to obtain co-DEGs. Then, we performed GO and KEGG enrichment analysis on the common genes in the AD, MDD, and T2DM-related modules. Next, we utilized the STRING database to find the hub genes in the protein-protein interaction network. ROC curves were constructed for co-DEGs to obtain the most diagnostic valuable genes and to make drug predictions against the target genes. Finally, we conducted a present condition survey to verify the correlation between T2DM, MDD and AD.

Results

Our findings indicated 127 diff co-DEGs, 19 upregulated co-DEGs, and 25 down-regulated co-DEGs. Functional enrichment analysis showed co-DEGs were mainly enriched in signaling pathways such as metabolic diseases and some neurodegeneration. Protein-protein interaction network construction identified hub genes in AD, MDD and T2DM shared genes. We identified seven hub genes of co-DEGs, namely, SMC4, CDC27, HNF1A, RHOD, CUX1, PDLIM5, and TTR. The current survey results suggest a correlation between T2DM, MDD and dementia. Moreover, logistic regression analysis showed that T2DM and depression increased the risk of dementia.

Conclusion

Our work identified common pathogenesis of AD, T2DM, and MDD. These shared pathways might provide novel ideas for further mechanistic studies and hub genes that may serve as novel therapeutic targets for diagnosing and treating.

Triglyceride glycemic index as a biomarker for gestational diabetes mellitus: a systemic review and meta-analysis

BACKGROUND

Triglyceride glycemic (TyG) index is a novel tool for assessing insulin resistance (IR). Recently, TyG index as a potential biomarker for gestational diabetes mellitus (GDM) has been studied, but its performance is yet inconclusive. Thus, we performed this systemic review and meta-analysis to evaluate the performance of TyG index in predicting GDM.

METHODS

Studies published before March 1, 2021, with comparison of TyG index between GDM patients and healthy controls were retrieved from multiple databases (PubMed, Web of Science, The Cochrane Library, and Embase). The mean difference (MD) of TyG index in GDM patients and healthy controls was pooled using random-effect models.

RESULTS

Differentiation of TyG index between patients with GDM and controls showed significant results. Overall, there is a four-fold increase in TyG index in GDM patients compared with controls (MD: 0.22, 95% CI: 0.07-0.36, P = 0.003; I2 = 71%, P = 0.009). In subgroup analyses according to gestational time, TyG index in the second trimester predicted GDM with low heterogeneity (MD: 0.26, 95% CI: 0.15-0.37, P < 0.001; I2 = 0%, P = 0.54), while no such correlation was found in the first trimester.

CONCLUSION

TyG index, especially in the second trimester, could be a promising biomarker for predicting GDM.

Exploring the Physiological Role of Transthyretin in Glucose Metabolism in the Liver

Transthyretin (TTR), a 55 kDa evolutionarily conserved protein, presents altered levels in several conditions, including malnutrition, inflammation, diabetes, and Alzheimer’s Disease. It has been shown that TTR is involved in several functions, such as insulin release from pancreatic β-cells, recovery of blood glucose and glucagon levels of the islets of Langerhans, food intake, and body weight. Here, the role of TTR in hepatic glucose metabolism was explored by studying the levels of glucose in mice with different TTR genetic backgrounds, namely with two copies of the TTR gene, TTR+/+; with only one copy, TTR+/−; and without TTR, TTR−/−. Results showed that TTR haploinsufficiency (TTR+/−) leads to higher glucose in both plasma and in primary hepatocyte culture media and lower expression of the influx glucose transporters, GLUT1, GLUT3, and GLUT4. Further, we showed that TTR haploinsufficiency decreases pyruvate kinase M type (PKM) levels in mice livers, by qRT-PCR, but it does not affect the hepatic production of the studied metabolites, as determined by 1H NMR. Finally, we demonstrated that TTR increases mitochondrial density in HepG2 cells and that TTR insufficiency triggers a higher degree of oxidative phosphorylation in the liver. Altogether, these results indicate that TTR contributes to the homeostasis of glucose by regulating the levels of glucose transporters and PKM enzyme and by protecting against mitochondrial oxidative stress.

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.