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.

Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes.

BACKGROUND: This work is aimed at improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis by generating a multi-omic disease signature. METHODS/RESULTS: We combined classic plasma biochemistry and plasma biomarkers with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (morbidly obese and lipodystrophy) and lean individuals to identify the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells. Our analyses showed that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, 6 months after bariatric surgery, revealed the loss of the abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurred via the establishment of novel gene expression landscapes. NETosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. CONCLUSIONS: We showed that the morbidly obese and lipodystrophy groups, despite some differences, shared a common cardiometabolic syndrome signature. We also showed that this could be used to discriminate, amongst the normal population, those individuals with a higher likelihood of presenting with the disease, even when not displaying the classic features.

Proenkephalin in Heart Failure.

The opioid system is activated in heart failure, which may be cardioprotective but may also be counter-regulatory. Recently, systemic proenkephalin activation has been investigated in various conditions predicting mortality and kidney injury. In acute heart failure, proenkephalin independently predicts mortality and heart failure rehospitalization in addition to traditional risk markers. It also predicts worsening renal function, increasingly recognized as an important risk predictor for poor outcome in heart failure. This article explores the role of enkephalins and delta-opioid receptors in the heart, then reviews studies measuring proenkephalin levels in the circulation and their associations with prognosis.

Identification of novel biomarkers in plasma for prediction of treatment response in patients with heart failure.

BACKGROUND: Heart failure is a complex clinical syndrome that occurs at the end stage of heart disease. Despite advances in therapy for heart failure, improvement of clinical outcomes remains a challenge for physicians. The identification of treatment response early in the course of disease would be useful to improve management of these patients. The aim of this study was to identify novel biomarkers in plasma that could predict treatment response in patients with heart failure. METHODS: Patients with heart failure who met inclusion and exclusion criteria according to the guidelines of the European Society of Cardiology were recruited. Uptitration of angiotensin-converting enzyme inhibitors and ß blockers was performed over 6 months. Patients were followed up for clinical events within the next 24 months. Plasma proteins in patients who responded to standard treatment (responders) were compared with patients who died or were re-admitted for heart failure (non-responders). Plasma samples were depleted of 14 high abundance proteins with a multiple affinity removal system column (MARS). Then plasma samples were analysed on two-dimensional liquid chromatography coupled to a tandem mass spectrometry (2D LC-ESI-MS/MS) in high definition mode (HDMS(E)) to identify and quantify the different expression of proteins in plasma. Finally, ELISA was used to verify candidate biomarkers. FINDINGS: Participants were 100 patients with heart failure matched for sex and age (50 responders [25 women], 50 non-responders [25 women], mean age 76·6 years [SD 8·1]). Of the non-responders, 18 died and 32 were re-admitted to hospital. 2D LC-ESI-MS/MS showed that the expression of neurotrimin (NTM) was highly upregulated, by 26·5 times (p<0·0001), in the responder group compared with the non-responder group. ELISA in the verification phase showed that the concentrations of NTM in plasma were significantly higher in the responders and lower in the non-responders (mean 4·73 log10 relative light units [SD 0·07] vs 4·70 [0·08], p=0·036). When ANOVA with Bonferroni post-hoc comparisons was used in three outcome subgroups (responders, patients re-admitted to hospital, and deaths), NTM concentrations were significantly different between death and the other groups (higher in responder vs death group, p<0·0001; higher in re-admission vs death group, p=0·001). INTERPRETATION: Our findings suggest that NTM as a novel biomarker in heart failure will not only add information to understand the pathophysiological mechanisms of heart failure better, but also might provide a more accurate prediction of treatment response to guide medical therapy. In addition, a novel therapeutic target could be identified for design of drugs to improve outcomes. Futher work is required in larger populations to confirm this biomarker. FUNDING: European Union's Seventh Framework Programme (BIOSTAT-CHF), John and Lucille van Geest Foundation.