Targeted and untargeted metabolomic approach for GDM diagnosis

Biomarkers of heart failure: advances in omics studies

Heart failure is a complex syndrome characterized by progressive circulatory dysfunction, manifesting clinically as pulmonary and systemic venous congestion, alongside inadequate tissue perfusion. The early identification of HF, particularly at the mild and moderate stages (stages B and C), presents a clinical challenge due to the overlap of signs, symptoms, and natriuretic peptide levels with other cardiorespiratory pathologies. Nonetheless, early detection coupled with timely pharmacological intervention is imperative for enhancing patient outcomes. Advances in high-throughput omics technologies have enabled researchers to analyze patient-derived biofluids and tissues, discovering biomarkers that are sensitive and specific for HF diagnosis. Due to the diversity of HF etiology, it is insufficient to study the diagnostic data of early HF using a single omics technology. This study reviewed the latest progress in genomics, transcriptomics, proteomics, and metabolomics for the identification of HF biomarkers, offering novel insights into the early clinical diagnosis of HF. However, the validity of biomarkers depends on the disease status, intervention time, genetic diversity and comorbidities of the subjects. Moreover, biomarkers lack generalizability in different clinical settings. Hence, it is imperative to conduct multi-center, large-scale and standardized clinical trials to enhance the diagnostic accuracy and utility of HF biomarkers.

Fatty acids and their metabolites (resolvins) are altered in women with gestational diabetes mellitus (GDM)

The maternal fatty acid status plays a key role in influencing pregnancy outcomes. Omega-3 fatty acids are the precursors for E-series (RvE) and D-series resolvins (RvD) and possess anti-inflammatory properties. Pregnancy complications like gestational diabetes mellitus (GDM) are associated with excess maternal inflammation. This study reports the levels of maternal fatty acids across gestation in GDM and non-GDM women, placental fatty acids, resolvins and their association with the maternal fatty acid status. Pregnant women were recruited at 11-14 (V1) weeks and followed at 18-22 (V2) and 26-28 (V3) weeks and at delivery (V4). A total of 209 women who were diagnosed as GDM and 207 non-GDM women were included in this study. Fatty acids were estimated using gas chromatography. The protein levels of resolvins (RvE1, RvE2, RvD1 and RvD2) were measured using ELISA kits. Total PUFAs, eicosapentaenoic acid (EPA), omega-6 fatty acids, linoleic acid (LA) and arachidonic acid (AA) were lower, while saturated fatty acid (SFA) and alpha-linolenic acid (ALA) levels were higher in GDM women at 18-22 weeks. Placental AA was lower (p < 0.05) in women with GDM. Placental protein levels of RvE1, RvD1 and RvD2 were lower (p < 0.001 for all) in the GDM group. The maternal delta 5 desaturase index was positively associated, while erythrocyte omega-3 and omega-6 fatty acids were negatively associated with RvE2 at 11-14 weeks. Placental LA and ALA were positively associated with RvD1 and RvD2 (p < 0.05, for both), respectively. Our findings suggest that the maternal fatty acid status influences pro-resolving mediators which may lead to increased inflammation in GDM.

The role of lipid dysregulation in gestational diabetes mellitus: Early prediction and postpartum prognosis

Gestational diabetes mellitus (GDM) is a pathological condition during pregnancy characterized by impaired glucose tolerance, and the failure of pancreatic beta-cells to respond appropriately to an increased insulin demand. However, while the majority of women with GDM will return to normoglycemia after delivery, they have up to a seven times higher risk of developing type 2 diabetes during midlife, compared with those with no history of GDM. Gestational diabetes mellitus also increases the risk of multiple metabolic disorders, including non-alcoholic fatty liver disease, obesity, and cardiovascular diseases. Lipid metabolism undergoes significant changes throughout the gestational period, and lipid dysregulation is strongly associated with GDM and the progression to future type 2 diabetes. In addition to common lipid variables, discovery-based omics techniques, such as metabolomics and lipidomics, have identified lipid biomarkers that correlate with GDM. These lipid species also show considerable potential in predicting the onset of GDM and subsequent type 2 diabetes post-delivery. This review aims to update the current knowledge of the role that lipids play in the onset of GDM, with a focus on potential lipid biomarkers or metabolic pathways. These biomarkers may be useful in establishing predictive models to accurately predict the future onset of GDM and type 2 diabetes, and early intervention may help to reduce the complications associated with GDM.