Platelet-derived sTLT-1 is associated with platelet-mediated inflammation in coronary artery disease patients.

The development of coronary artery disease (CAD) depends heavily on platelet activation, and inflammation plays a major role in all stages of atherosclerosis. Platelet-specific soluble triggering receptor expressed on myeloid cells like transcript 1 (sTLT-1) facilitate clot formation and have been linked to chronic inflammation. In this study, we explored the role of platelet-derived sTLT-1 in platelet-mediated inflammation in CAD patients. Plasma levels of sTLT-1 were measured using enzyme-linked immunosorbent assay in CAD patients (n = 163) and healthy controls (n = 99). Correlation analysis was performed to determine the circulatory sTLT-1 levels with platelet activation markers, immune cells, and inflammatory cytokines/chemokines. Increased plasma sTLT-1 levels were observed in CAD patients compared with those in healthy controls (p < 0.0001). A positive correlation was observed between sTLT-1 and platelet activation markers (P-selectin, PAC-1), CD14++ CD16- cells (classical monocytes), Natural killer T (NKT) cells, and platelet-immune cell aggregates with monocytes, neutrophils, dendritic cells, CD11c+ cells, and NKT cells. In contrast, a significant negative correlation was observed with CD8 cells. Furthermore, a significant positive correlation was observed between sTLT-1 and inflammatory markers (TNF-α, IL-1ß, IL-2, IL-6, IL-12p70, IL-18, CXCL-12, and CCL-11). Logistic regression analysis identified sTLT-1 and triglycerides as predictors of CAD. Receiver operating characteristic curve (ROC) analysis showed that sTLT-1 had a higher sensitivity and specificity for predicting CAD. Our findings suggest that platelet activation induces the release of sTLT-1 into the circulation in CAD patients, which aggregates with immune cells and enhances inflammatory responses.

Effect of garlic extract on markers of lipid metabolism and inflammation in coronary artery disease (CAD) patients: A systematic review and meta-analysis.

Several preclinical studies have focused on the beneficial effects of garlic on cardiovascular diseases, but the results were inconsistent. We performed a systematic review and meta-analysis on the effect of garlic powder tablets and aged garlic extract (AGE) in CAD patients, mainly focusing on blood pressure, coronary artery calcification, lipid profile, and inflammatory markers. We searched PubMed, Cochrane CENTRAL, and Google Scholar to identify randomized controlled trials which examined garlic's effect on CAD patients. The standardized mean difference with 95% CI was calculated using fixed-effect or random-effect models. Garlic has shown statistically significant changes of HDL (SMD = 0.18; 95% CI = -0.00 to 0.37; p = .05); LDL (SMD = -0.27; 95% CI = -0.46 to -0.08; p = .004), apolipoprotein-A (SMD = 0.68; 95% CI = 0.24 1.13; p = .002), C-RP (SMD = -0.59; 95% CI = -0.92 to -0.25; p = .0007), IL-6 (SMD = -1.08; 95% CI = -2.17 to 0.01; p = .05), homocysteine (SMD = -0.66; 95% CI = -1.04 to -0.28; p = .0007) and CAC score (SMD = -1.61; 95% CI = -2.66 to -0.57; p = .003). In the case of subgroup analysis, the overall effect was significantly effective in reducing TC, LDL levels and improving HDL levels in CV risk patients. Our study findings provide consistent evidence that intake of garlic reduces CVD risk factors. However, garlic could be considered a safe natural medicine to debilitate inflammation in CAD patients.

Transporter-mediated drug-drug interactions: advancement in models, analytical tools, and regulatory perspective.

Drug-drug interactions mediated by transporters are a serious clinical concern hence a tremendous amount of work has been done on the characterization of the transporter-mediated proteins in humans and animals. The underlying mechanism for the transporter-mediated drug-drug interaction is the induction or inhibition of the transporter which is involved in the cellular uptake and efflux of drugs. Transporter of the brain, liver, kidney, and intestine are major determinants that alter the absorption, distribution, metabolism, excretion profile of drugs, and considerably influence the pharmacokinetic profile of drugs. As a consequence, transporter proteins may affect the therapeutic activity and safety of drugs. However, mounting evidence suggests that many drugs change the activity and/or expression of the transporter protein. Accordingly, evaluation of drug interaction during the drug development process is an integral part of risk assessment and regulatory requirements. Therefore, this review will highlight the clinical significance of the transporter, their role in disease, possible cause underlying the drug-drug interactions using analytical tools, and update on the regulatory requirement. The recent in-silico approaches which emphasize the advancement in the discovery of drug-drug interactions are also highlighted in this review. Besides, we discuss several endogenous biomarkers that have shown to act as substrates for many transporters, which could be potent determinants to find the drug-drug interactions mediated by transporters. Transporter-mediated drug-drug interactions are taken into consideration in the drug approval process therefore we also provided the extrapolated decision trees from in-vitro to in-vivo, which may trigger the follow-up to clinical studies.

The effect of Gymnema sylvestre supplementation on glycemic control in type 2 diabetes patients: A systematic review and meta-analysis.

This systematic review and meta-analysis aims to find the effect of Gymnema sylvestre (GS) supplementation on glycemic control in type-2 diabetes mellitus (T2DM). PubMed, Cochrane library, Google Scholar, and Science Direct were searched from inception to June 2020 to identify the studies that reported GS supplementation on glycemic parameters. Standardized mean difference (SMD) was calculated by comparing the post-intervention data with baseline data. SMDs with 95% confidence intervals (CIs) were pooled using a random-effects model. Our meta-analysis consisting of 10 studies with a total of 419 participants showed that GS supplementation significantly reduces fasting blood glucose (FBG) (SMD 1.57 mg/dl, 95% CI 2.22 to -0.93, p < .0001, I2 90%), postprandial blood glucose (PPBG) (SMD 1.04 mg/dl, 95% CI 1.53 to -0.54, p < .0001, I2 80%), and glycated haemoglobin (HbA1c) (SMD 3.91, 95% CI 7.35 to -0.16%, p < .0001, I2 99%) compared to baseline. Further, our study also found that GS significantly reduces triglycerides (SMD 1.81 mg/dl, 95% CI 2.95 to -0.66, p < .0001, I2 : 96%), and total cholesterol (SMD 4.10 mg/dl, 95% CI 7.21 to -0.99, p < .0001, I2 : 98%) compared to baseline. Our study shows that GS supplementation is effective in improving glycemic control and reducing lipid levels in T2DM patients and suggests that such supplementation might be used as an effective therapy for the management of T2DM and its associated complications to an extent.

Serum protein signature of coronary artery disease in type 2 diabetes mellitus.

BACKGROUND: Coronary artery disease (CAD) is the leading cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). The purpose of the present study was to discriminate the Indian CAD patients with or without T2DM by using multiple pathophysiological biomarkers. METHODS: Using sensitive multiplex protein assays, we assessed 46 protein markers including cytokines/chemokines, metabolic hormones, adipokines and apolipoproteins for evaluating different pathophysiological conditions of control, T2DM, CAD and T2DM with CAD patients (T2DM_CAD). Network analysis was performed to create protein-protein interaction networks by using significantly (p < 0.05) altered protein markers in each disease using STRING 10.5 database. We used two supervised analysis methods i.e., between class analysis (BCA) and principal component analysis (PCA) to reveals distinct biomarkers profiles. Further, random forest classification (RF) was used to classify the diseases by the panel of markers. RESULTS: Our two supervised analysis methods BCA and PCA revealed a distinct biomarker profiles and high degree of variability in the marker profiles for T2DM_CAD and CAD. Thereafter, the present study identified multiple potential biomarkers to differentiate T2DM, CAD, and T2DM_CAD patients based on their relative abundance in serum. RF classified T2DM based on the abundance patterns of nine markers i.e., IL-1ß, GM-CSF, glucagon, PAI-I, rantes, IP-10, resistin, GIP and Apo-B; CAD by 14 markers i.e., resistin, PDGF-BB, PAI-1, lipocalin-2, leptin, IL-13, eotaxin, GM-CSF, Apo-E, ghrelin, adipsin, GIP, Apo-CII and IP-10; and T2DM _CAD by 12 markers i.e., insulin, resistin, PAI-1, adiponectin, lipocalin-2, GM-CSF, adipsin, leptin, Apo-AII, rantes, IL-6 and ghrelin with respect to the control subjects. Using network analysis, we have identified several cellular network proteins like PTPN1, AKT1, INSR, LEPR, IRS1, IRS2, IL1R2, IL6R, PCSK9 and MYD88, which are responsible for regulating inflammation, insulin resistance, and atherosclerosis. CONCLUSION: We have identified three distinct sets of serum markers for diabetes, CAD and diabetes associated with CAD in Indian patients using nonparametric-based machine learning approach. These multiple marker classifiers may be useful for monitoring progression from a healthy person to T2DM and T2DM to T2DM_CAD. However, these findings need to be further confirmed in the future studies with large number of samples.

Integrative Placental Multi-Omics Analysis Reveals Perturbed Pathways and Potential Prognostic Biomarkers in Gestational Hypertension.

BACKGROUND: Gestational hypertension (GH) is a severe complication that occurs after 20 weeks of pregnancy; however, its molecular mechanisms are not yet fully understood. OBJECTIVE: Through this case-control discovery phase study, we aimed to find disease-specific candidate placental microRNAs (miRNAs) and metabolite markers for differentiating GH by integrating next-generation sequencing and metabolomics multi-omics analysis of placenta. Using small RNA sequencing and metabolomics of placental tissues of healthy pregnant (HP, n = 24) and GH subjects (n = 20), the transcriptome and metabolome were characterized in both groups. RESULTS: The study identified a total of 44 downregulated placental miRNAs which includes three novel, three mature and 38 precursor miRNAs. Six miRNAs including three mature (hsa-miR-181a-5p, hsa-miR-498-5p, and hsa-miR-26b-5p) and three novel (NC_000016.10_1061, NC_000005.10_475, and NC_000001.11_53) were considered for final target prediction and functional annotation. Integrative analysis of differentially expressed miRNAs and metabolites yielded five pathways such as purine, glutathione, glycerophospholipid, inositol phosphate and ß-alanine to be significantly perturbed in GH. We present fourteen genes (LPCAT1, LPCAT2, DGKH, PISD, GPAT2, PTEN, SACM1L, PGM2, AMPD3, AK7, AK3, CNDP1, IDH2, and ODC1) and eight metabolites (xanthosine, xanthine, spermine, glycine, CDP-Choline, glyceraldehyde 3-phosphate, ß-alanine, and histidine) with potential to distinguish GH and HP. CONCLUSION: The differential expression of miRNAs, their target genes, altered metabolites and metabolic pathways in GH patients were identified for the first time in our study. Further, the altered miRNAs and metabolites were integrated to build their inter-connectivity network. The findings obtained from our study may be used as a valuable source to further unravel the molecular pathways associated with GH and also for the evaluation of prognostic markers.

Inflammatory Protein Signatures as Predictive Disease-Specific Markers for Non-Alcoholic Steatohepatitis (NASH).

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic disease worldwide, consisting of a broad spectrum of diseases such as simple steatosis (NAFL), non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and hepatocellular carcinoma. Hepatic inflammation plays a key role in the pathophysiology of NAFLD. Inflammatory mediators such as cytokines and chemokines are considered as contributing factors to NAFLD development and progression. In the present study, we aimed to investigate the inflammatory protein signatures as predictive disease-specific markers for non-alcoholic fatty liver disease (NAFLD). This cross-sectional study included healthy control (n = 64), NAFL (n = 109), and NASH (n = 60) human subjects. Serum concentrations of various cytokines and chemokines were evaluated using sensitive multiplex assays. We used principal component analysis (PCoA) to reveal distinct differences in the levels of cytokines and chemokines between each of the study groups. Further, a random forest classification model was developed to identify the panel of markers that could predict diseases. The protein-protein network analysis was performed to determine the various signaling pathways associated with the disease-specific panel of markers. Serum concentrations of TNF-α, IL-1ß, IL-1ra, G-CSF, PDGF-BB, MCP-1, MIP-1a, MIP-1b, RANTES, eotaxin, IL-8 and IP-10 were significantly increased in NASH group as compared to control group. Furthermore, serum concentrations of IL-9 and IL-13 were significantly lower in the NASH group, whereas IL-2 levels were significantly decreased in the NAFL group when compared to the control group. PCoA results demonstrated statistically significant differences in cytokines and chemokines between each of the study groups (PERMANOVA p = 0.001; R2 = 0.102). RANTES, IL-1ra, MIP-1b, IL-2, and G-CSF could differentiate the NAFL group from the controls; G-CSF, IL-1ra, TNF-α, RANTES, and IL-9 could differentiate the NASH group from the controls; and G-CSF, IL-9, IL-13, eotaxin, and TNF- α could differentiate the NASH group from the NAFL group. Our protein-protein network revealed that these markers are involved in cytokine-cytokine receptor interaction, Th1 and Th2 cell differentiation, TNF, chemokine, JAK/STAT, P13K/Akt, TLR, NOD-like receptor, NF-kB, and adipocytokine signaling pathways which might be responsible for disease pathogenesis. Our study findings revealed a set of distinct cytokine and chemokine markers and they might be considered as biomarkers in distinguishing NASH from NAFL. Future multicentre studies with larger sample size are recommended to determine the potential utility of these panels of markers.

Garlic and cardioprotection: insights into the molecular mechanisms.

Garlic is widely recognized for its immense therapeutic potential. Garlic has been shown to exert its beneficial effects against a wide spectrum of diseases, including cancer, diabetes, and microbial infections, as well as immunological and cardiovascular disorders. Most of the research on garlic has indicated that garlic and its active compounds are effective in reducing cardiovascular and metabolic risk by normalizing abnormal plasma lipids, oxidized low density lipoproteins, abnormal platelet aggregation, high blood pressure, and cardiac injury. Some of the beneficial effects of dietary garlic against cardiovascular disorders are mediated via the generation of hydrogen sulfide and nitric oxide in cardiomyocytes and endothelial cells. Garlic has the potential to protect the heart against myocardial infarction, doxorubicin-induced cardiotoxicity, arrhythmia, hypertrophy, and ischemia-reperfusion injury. The induction of cardiac endogenous antioxidants and the reduction of lipid peroxidation by garlic has been reported by several different groups. Other mechanisms, such as regulating ion channels, modulating Akt signaling pathways, histone deacetylase inhibition, and cytochrome P450 inhibition, could be responsible for the cardioprotective effect of garlic. Although several mechanisms have been identified for the cardioprotective effect of garlic, there is a need for further research to identify the specific molecular mechanism of cardioprotection in different cardiac diseases.

Exposure to endocrine-disrupting chemicals and risk of gestational hypertension and preeclampsia: A systematic review and meta-analysis.

Prenatal exposure to endocrine-disrupting chemicals has been linked to gestational hypertension (GH) and preeclampsia (PE). However, the results were conflicting and inconclusive. We conducted a systematic review and meta-analysis for an overview of these relationships. We searched PubMed, and Google Scholar for studies investigating bisphenol A, phthalates, and per or poly-fluoroalkyl substances and GH or PE. Pooled odds ratio (OR) with a 95% confidence interval (CI) were calculated for risk estimate using the generic inverse variance method. A total of 14 studies were included in the present analysis. The pooled results demonstrated that perfluorooctanoic acid (PFOA, OR:1.20, 95% CI: 1.04, 1.39), perfluoro octane sulfonic acid (PFOS, (OR:1.23, 95% CI: 1.10, 1.38), and perfluononanoic acid (PFNA, OR:1.20, 95% CI: 1.03, 1.40) were significantly associated with an increased risk of PE. There was no significant association observed with perfluoro hexane sulfonic acid (PFHxS), perfluoro decanoic acid (PFDA), perfluoro heptanoic acid (PFHpA), and perfluoro undecanoic acid (PFUnDA) and PE. For GH, a statistically significant positive association was found with PFOA (OR:1.18, 95% CI: 1.01, 1.39) and PFHxS (OR:1.15, 95% CI: 1.02, 1.29). Among various phthalates analysed only mono-ethyl phthalate (MEP, OR:1.37, 95% CI: 1.11, 1.70) showed an association with GH. From our analysis, bisphenol A exposure during pregnancy did not show a significant association with the risk of PE. Our findings indicated that exposure to PFASs such as PFOA, PFOS, and PFNA during pregnancy is associated with an increased risk of PE and PFOA and PFHxS with GH. We also found that MEP was associated with GH. Most of the results were unstable in sensitivity analysis. Since most of these associations have limited evidence, more research is needed to confirm these findings.

Disrupted placental vitamin D metabolism and calcium signaling in gestational diabetes and pre-eclampsia patients.

INTRODUCTION: Gestational diabetes (GDM) and pre-eclampsia (PE) represents the unrecognized risk factors for reduced bone content in neonates. The present study is planned to explore the components of vitamin D metabolism and calcium transport in placenta of GDM and PE cases and its effect on the neonatal bone mass determination using bone densitometry system. METHODS: We have collected serum and placenta tissues from GDM (n = 20), PE (n = 20), and healthy pregnancies (n = 20). In the present study, we found mRNA expression of oxidative stress markers, vitamin D metabolic components and calcium channels, calcium channel binding proteins, plasma membrane calcium ATPase, ATP synthase and Ca2+ release genes; Ryanodine receptors genes were assessed by quantitative real-time PCR (qRT-PCR) in placental tissue of GDM, PE, and healthy pregnancies. RESULTS: We observed high level of oxidative stress in both GDM and PE placenta compared to normal pregnancies. CYP2R1 and VDR mRNA expression was significantly downregulated and upregulation of CYP27B1 and CYP24A1 in GDM and PE compared with healthy cases. Similarly, calcium transporters were downregulated in GDM and PE placental tissues. In addition, CYP24A1, VDR, CaBP28K, TRPV5 and PMCA3 mRNA expression were correlated with BMC of neonates. DISCUSSION: Oxidative stress is probably relevant to disrupted vitamin D homeostasis and calcium transport in the placenta of GDM and PE cases. The altered regulatory mechanism of CYP24A1 and VDR could indicates more pronounced serum 25(OH)D reduction. Additionally, reduced BMC in the neonates of these cases might be as consequences of modified CYP24A1, VDR, CaBP28K, TRPV5 and PMCA3 mRNA expression.

Circulatory bone morphogenetic protein (BMP) 8B is a non-invasive predictive biomarker for the diagnosis of non-alcoholic steatohepatitis (NASH).

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is a complex disease which is characterized by the deposition of fats in the hepatocytes. Further, it progresses to nonalcoholic steatohepatitis (NASH), fibrosis, and hepatocellular carcinoma. The increasing prevalence of NAFLD urges to find the non-invasive predictive biomarkers. In this study, we sought to determine increased BMP8B levels as predictors for the progression of NAFLD. METHODS: In the present cross-sectional study, circulatory BMP8B levels were measured in healthy controls (n = 56), NAFL patients (n = 72) and NASH patients (n = 77) by using an ELISA kit. Human hepatic BMP8B mRNA expression was measured in the liver tissue of control and NASH patients. In addition, BMP8B expression was confirmed by immunohistochemistry analysis. Furthermore, hepatic BMP8B mRNA expression was measured in wild type (WT) mice, WT mice fed with choline deficient high fat diet (WT+CDHF), iNOS (inducible nitric oxide synthase) knockout (iNOS-/-) mice, iNOS-/- fed with CDHF diet (iNOS-/-+CDHF). RESULTS: Increased circulatory BMP8B levels and BMP8B mRNA expression in hepatic tissue were significantly higher in NASH patients as compared with the control subjects. BMP8B expression was increased parallel to the fibrosis score in the hepatic tissues of NASH patients. It was observed that increased BMP8B levels have shown a significant positive correlation between aspartate aminotransferase (r = 0.31, p = 0.005), alanine aminotransferase (r = 0.23, p = 0.045), APRI (r = 0.30, p = 0.009), and Fib-4 score (r = 0.25, p = 0.036) in NASH patients. BMP8B has maintained a significant association with NASH and shown high sensitivity (92.91%) and specificity (92.73%) in NASH patients. Furthermore, increased BMP8B mRNA expression levels were observed in iNOS-/-+CDHF mice. CONCLUSION: Our study findings confirmed that BMP8B increases with the severity of the disease and BMP8B shows potential as a non-invasive predictive biomarker to identify NAFLD progression. However, future studies should investigate circulatory BMP8B levels in a large number of patients and also its impact on liver during NAFLD progression.

Untargeted metabolomics reveals altered branch chain amino acids, glucose and fat metabolism contributing to coronary artery disease among Indian diabetic patients.

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterised by increased blood glucose levels. Patients with T2DM have a high risk of developing atherosclerotic coronary artery disease (CAD). CAD with T2DM has a complex etiology and the understanding of the pathophysiology of coronary artery disease (CAD) in the presence of diabetes is poor. Here, we have used LC-MS/MS-based untargeted metabolomics to unveil the alterations of metabolites in the serum of South-Indian patients diagnosed with T2DM, CAD and T2DM along with CAD (T2DM-CAD) compared with the healthy subjects (CT). Using untargeted metabolomics and network-based approaches, a set of metabolites highly co-expressed with T2DM-CAD pathogenesis were identified. Our results revealed that these metabolites belong to essential pathways such as amino acid metabolism, fatty acid metabolism and carbohydrate metabolism. The candidate metabolites identified by metabolomics study are branch chain amino acids, L-arginine, linoleic acid, L-serine, L-cysteine, fructose-6-phosphate, glycerol, creatine and 3-phosphoglyceric acid, and explain the pathogenesis of T2DM-assisted CAD. The identified metabolites could be used as potential prognostic markers to predict CAD in patients diagnosed with T2DM.

Integrated metabolomics and machine learning approach to predict hypertensive disorders of pregnancy.

BACKGROUND: Hypertensive disorders of pregnancy account for 3% to 10% of maternal-fetal morbidity and mortality worldwide. This condition has been considered one of the leading causes of maternal deaths in developing countries, such as India. OBJECTIVE: This study aimed to discover hypertensive disorders of pregnancy-specific candidate urine metabolites as markers for hypertensive disorders of pregnancy by applying integrated metabolomics and machine learning approaches. STUDY DESIGN: The targeted urinary metabolomics study was conducted in 70 healthy pregnant controls and 133 pregnant patients having hypertension as cases. Hypertensive disorders of pregnancy-specific metabolites for disease prediction were further extracted using univariate and multivariate statistical analyses. For machine learning analysis, 80% of the data were used for training (79 for hypertensive disorders of pregnancy and 42 for healthy pregnancy) and validation (27 for hypertensive disorders of pregnancy and 14 for healthy pregnancy), and 20% of the data were used for test sets (27 for hypertensive disorders of pregnancy and 14 for healthy pregnancy). RESULTS: The statistical analysis using an unpaired t test revealed 44 differential metabolites. Pathway analysis showed mainly that purine and thiamine metabolism were altered in the group with hypertensive disorders of pregnancy compared with the healthy pregnancy group. The area under the receiver operating characteristic curves of the 5 most predominant metabolites were 0.98 (adenosine), 0.92 (adenosine monophosphate), 0.89 (deoxyadenosine), 0.81 (thiamine), and 0.81 (thiamine monophosphate). The best prediction accuracies were obtained using 2 machine learning models (95% for the gradient boost model and 98% for the decision tree) among the 5 used models. The machine learning models showed higher predictive performance for 3 metabolites (ie, thiamine monophosphate, adenosine monophosphate, and thiamine) among 5 metabolites. The combined accuracies of adenosine from all models were 98.6 in the training set and 95.6 in the test set. Moreover, the predictive performance of adenosine was higher than other metabolites. The relative feature importance of adenosine was also observed in the decision tree and the gradient boost model. CONCLUSION: Among other metabolites, adenosine and thiamine metabolites were found to differentiate participants with hypertensive disorders of pregnancy from participants with healthy pregnancies; hence, these metabolites can serve as a promising noninvasive marker for the detection of hypertensive disorders of pregnancy.

Machine learning-based protein signatures for differentiating hypertensive disorders of pregnancy.

Hypertensive disorders of pregnancy (HDP) result in major maternal and fetal complications. Our study aimed to find a panel of protein markers to identify HDP by applying machine-learning models. The study was conducted on a total of 133 samples, divided into four groups, healthy pregnancy (HP, n = 42), gestational hypertension (GH, n = 67), preeclampsia (PE, n = 9), and ante-partum eclampsia (APE, n = 15). Thirty circulatory protein markers were measured using Luminex multiplex immunoassay and ELISA. Significant markers were screened for potential predictive markers by both statistical and machine-learning approaches. Statistical analysis found seven markers such as sFlt-1, PlGF, endothelin-1(ET-1), basic-FGF, IL-4, eotaxin and RANTES to be altered significantly in disease groups compared to healthy pregnant. Support vector machine (SVM) learning model classified GH and HP with 11 markers (eotaxin, GM-CSF, IL-4, IL-6, IL-13, MCP-1, MIP-1α, MIP-1ß, RANTES, ET-1, sFlt-1) and HDP with 13 markers (eotaxin, G-CSF, GM-CSF, IFN-gamma, IL-4, IL-5, IL-6, IL-13, MCP-1, MIP-1ß, RANTES, ET-1, sFlt-1). While logistic regression (LR) model classified PE with 13 markers (basic FGF, IL-1ß, IL-1ra, IL-7, IL-9, MIP-1ß, RANTES, TNF-alpha, nitric oxide, superoxide dismutase, ET-1, PlGF, sFlt-1) and APE by 12 markers (eotaxin, basic-FGF, G-CSF, GM-CSF, IL-1ß, IL-5, IL-8, IL-13, IL-17, PDGF-BB, RANTES, PlGF). These markers may be used to diagnose the progression of healthy pregnant to a hypertensive state. Future longitudinal studies with large number of samples are needed to validate these findings.

Efficacy and Safety of Saroglitazar in Patients with Cardiometabolic Diseases: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND AND OBJECTIVE: The incidence of cardiometabolic diseases is increasing because of an increase in the standard of living. Currently, clinical treatment strategies for cardiometabolic diseases mainly focus on maintaining glycemic and lipid profiles. The objective of this systematic review and meta-analysis was to evaluate the efficacy and safety of saroglitazar in patients with metabolic disease and provide evidence for clinical decision making. METHODS: We searched electronic databases (PubMed, Cochrane Central Register of Controlled Trials [CENTRAL], and Google Scholar) for randomized controlled trials that examined saroglitazar for the treatment of patients with cardiometabolic disease. A total of seven randomized controlled trials were included for the qualitative and quantitative synthesis. Mean difference (MD) and risk ratio with a 95% confidence interval (CI) were applied for continuous and dichotomous data, respectively. RESULTS: The overall effect of saroglitazar showed significant changes in triglycerides, total cholesterol, low-density lipoprotein, non-high-density lipoprotein, high-density lipoprotein, very low-density lipoprotein, alkaline phosphatase, and gamma-glutamyl transferase levels [MD: - 40.50; 95% CI - 58.09 to - 22.92; p < 0.00001; I2 = 78%], [MD: - 7.49; 95% CI - 11.33 to - 3.65; p = 0.0001; I2 = 41%], [MD: - 3.53; 95% CI - 6.91 to - 0.15; p = 0.04; I2 = 19%], [MD: - 8.08; 95% CI - 15.63 to - 0.54; p = 0.04; I2 = 58%], [MD: 2.04; 95% CI 0.17 to 3.92; p = 0.03; I2 = 69%], [MD: - 6.10; 95% CI - 9.40 to - 2.80; p = 0.0003; I2 = 65%], [MD: - 5.89; 95% CI - 7.50 to - 4.28; p < 0.00001; I2 = 98%], and [MD: - 1.64; 95% CI - 2.83 to - 0.45; p = 0.007; I2 = 95%], respectively. A subgroup analysis showed favorable outcomes with sarogiltazar 4 mg. There was a statistically non-significant reduced risk of adverse event occurrence in the saroglitazar treatment group. CONCLUSIONS: Our study results conclude that the overall effect of saroglitazar was beneficial only in terms of lipid profiles and liver function parameters, whereas saroglitazar 4 mg showed a better therapeutic role in maintaining lipid and glycemic parameters in patients with cardiometabolic disease.

Levels of parabens and bisphenols in personal care products and urinary concentrations in Indian young adult women: Implications for human exposure and health risk assessment.

Limited information is available about the levels of exposure of paraben and bisphenols emerging from personal care products (PCPs) use in Indian women and the risk associated with it. In this study, liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to determine the concentrations of six parabens (methyl-, ethyl-, propyl-, butyl, benzyl-, and heptyl-parabens) and 8 bisphenols (Bisphenol A, B, F, P, S, Z, AP, and AF) in PCPs samples (n = 114) obtained from Indian market and in the urine samples of young adult females (n = 52). The concentrations measured in PCPs and urine samples were used to determine the estimated daily intake. The mean concentrations of 6 parabens and 8 bisphenols in PCPs ranged from 38.3 to 2.38 × 105 ng/g and 2.71-148 ng/g, respectively. In urine samples analysed, the mean concentrations of 6 parabens and 8 bisphenols ranged from 0.007 to 293 ng/mL and 0.10-10.8 ng/mL, respectively. There was no significant correlation of EDCs with age, BMI and waist-to-hip ratio (WHR), but significant correlations (p < 0.05) were observed between urinary paraben and bisphenol concentrations. A statistically significant difference (p < 0.05) exists between the BMI and WHR groups by bisphenol concentrations. Estimated daily intake and exposure risks for parabens and bisphenols revealed no possible concerns for Indian young adult females. Hitherto, this is the first study to show that Indian young adult females were exposed to parabens and bisphenols. This study provides evidence on PCPs usage contribute to the urinary concentrations of EDCs.

Estimation of parabens and bisphenols in maternal products and urinary concentrations in Indian pregnant women: daily intake and health risk assessment.

The presence of parabens and bisphenols in maternal products and usage during pregnancy have raised serious concern about their possible harm to pregnant women. The concentrations of six parabens and eight bisphenols were quantified by high-performance liquid chromatography-tandem mass spectrometry in the samples of commercially available herbal-based ayurvedic maternal products and urine of healthy pregnant women from Assam, India. Methyl paraben (MP) and bisphenol AF (BPAF) were found to be more dominant in the maternal products, whereas MP, bisphenol A (BPA), and BPAF were dominant in urine samples of healthy pregnant women. The sum of the mean concentrations of all forms of parabens and bisphenols in maternal products were 48,308.50 ng/g and 542.42 ng/g, respectively, and urine 101.33 ng/mL and 23.42 ng/mL, respectively. The estimated daily intake (EDI) of total parabens and bisphenols in maternal products were 7378.02 and 19.78 ng/kg body weight/day, respectively. EDI of total parabens and bisphenols from urinary concentrations were 690.12 and 111.33 µg/kg body weight/day, respectively. The concentrations of butyl (BP) and heptyl (HP) parabens have a significant positive correlation with birth weight. The hazard quotient (HQ) value of MP, EP, and BPA was less than 1, and margin of exposure (MOE) identified potential risk associated with propyl paraben. Results from Monte-Carlo risk assessment analysis did not exceed the acceptable daily intake (ADI). Our results showed that higher concentrations of parabens and bisphenols are present in maternal products and the urine of healthy pregnant women. Hence maternal products containing bisphenols and parabens should be used cautiously during pregnancy to avoid maternal and fetal complications.

Implications of endocrine-disrupting chemicals on polycystic ovarian syndrome: A comprehensive review.

Polycystic ovarian syndrome (PCOS) is a complex multifactorial disorder of unknown pathogenesis in which genetic and environmental factors contribute synergistically to its phenotypic expressions. Endocrine-disrupting chemicals (EDCs), a group of widespread pollutants freely available in the environment and consumer products, can interfere with normal endocrine signals. Extensive evidence has shown that EDCs, environmental contributors to PCOS, can frequently induce ovarian and metabolic abnormalities at low doses. The current research on environmental EDCs suggests that there may be link between EDC exposure and PCOS, which calls for more human bio-monitoring of EDCs using highly sophisticated analytical techniques for the identification and quantification and to discover the underlying pathophysiology of the disease. This review briefly elaborated on the general etiology of PCOS and listed various epidemiological and experimental data from human and animal studies correlating EDCs and PCOS. This review also provides insights into various analytical tools and sample preparation techniques for biomonitoring studies for PCOS risk assessment. Furthermore, we highlight the role of metabolomics in disease-specific biomarker discovery and its use in clinical practice. It also suggests the way forward to integrate biomonitoring studies and metabolomics to underpin the role of EDCs in PCOS pathophysiology.

Circulatory hepcidin levels association with gestational diabetes mellitus: a meta-analysis of observational studies.

OBJECTIVES: Hepcidin is linked to glucose metabolism in women with gestational diabetes mellitus (GDM). This systematic review and meta-analysis was conducted to determine the association between hepcidin levels and GDM. A literature search was performed using different databases to identify potential studies investigating hepcidin association in GDM patients. The effect sizes were calculated based on the standardized mean difference (SMD) and Fisher's Z value with a 95% confidence interval (CI). KEY FINDINGS: Out of 827 articles, only 7 case-control studies satisfied the inclusion and exclusion criteria. The pooled SMD of circulatory hepcidin levels in GDM patients was considerably higher than normal pregnant women (SMD = 1.69; 95% CI, 0.86 to 2.53; P < 0.0001). This study also observed that hepcidin levels were positively correlated with ferritin levels (r = 0.264; Z = 0.27; P < 0.0001). Furthermore, a subgroup analysis of serum and plasma groups revealed significantly higher hepcidin levels in serum (SMD = 2.12; 95% CI, 0.44 to3.79; P = 0.001) than in the plasma group (SMD = 1.28; 95% CI, 0.32 to 2.2; I2 = 96%). SUMMARY: Our findings suggest that hepcidin levels may be elevated in GDM patients, making it a viable marker for GDM diagnosis, and regular monitoring of its levels could be helpful in aiding clinical decisions.

Comparative efficacy and safety of oral nifedipine with other antihypertensive medications in the management of hypertensive disorders of pregnancy: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Hypertensive disorders of pregnancy are the most frequently occurring medical condition during pregnancy, resulting in fetal and/or maternal morbidity and mortality. This meta-analysis compared the efficacy and safety of nifedipine with other antihypertensive medications used in hypertensive disorders of pregnancy. METHODOLOGY: A comprehensive search was performed using PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), and Google Scholar. The meta-analysis was carried out using Review Manager Software, and the pooled effect estimate was generated as standardized mean difference and odds ratio with 95% confidence interval and two-sided P -value. RESULTS: The meta-analysis was comprised of 22 randomized control trials with 2595 participants. It was found that meantime and number of doses required to achieve target blood pressure were lower in the nifedipine group ( P  < 0.05). Even though it is statistically insignificant, fetal APGAR (Appearance, Pulse, Grimace, Activity, and Respiration) scores less than seven favors nifedipine intervention. Furthermore, none of the fetal or maternal secondary outcomes were found significant. CONCLUSION: Nifedipine was found to be more effective than other antihypertensive medications to reduce blood pressure, particularly in patients with severe hypertension. However, future clinical studies, including real-world data are necessary to establish the safety profile of nifedipine concerning the fetal outcomes in hypertensive pregnant women.