The long non-coding RNA MALAT1 is increased in renal ischemia-reperfusion injury and inhibits hypoxia-induced inflammation

Background: To investigate the expression of long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in renal ischemia-reperfusion injury and explore its role in acute kidney injury. Methods: 18 mice were randomly divided into a sham operation group (Sham) and an ischemia-reperfusion group (IR) in which animals were sacrificed at 6 h or 12 h after surgery. The kidneys were harvested to measure the expression of MALAT1 mRNA. HK2 cells were treated with cobalt chloride (CoCl2) to mimic hypoxia or transfected with siRNA to knockdown MALAT1 before CoCl2 treatment. After that, MALAT1 was analyzed by RT-PCR (reverse transcription-polymerase chain reaction). HIF-1ɑ (hypoxia-inducible factor-1 alpha) and NF-κB (nuclear factor-kappa B) was measured by Western blot. The concentrations of IL-6 (interleukin-6) and TNF-ɑ (tumor necrosis factor-alpha) in the media were detected by ELISA (enzyme-linked immunosorbent assay). Results: The expression of MALAT1 in the IR (6 h/12 h) group was significantly higher than that in the sham group. In HK2 cells, MALAT1 was significantly increased at 1 h, 3 h, and 6 h after CoCl2 treatment but had reduced to the basal level at 12 h and 24 h. Knockdown of MALAT1 by siRNA significantly up-regulated the expression of HIF-1ɑ and NF-κB proteins in CoCl2-treated HK2 cells. In addition, the concentrations of IL-6 and TNF-ɑ were increased by MALAT1 siRNA transfection in CoCl2-treated HK2 cells. Conclusion: The expression of MALAT1 is increased in renal ischemia-reperfusion injury. It is likely that MALAT1 inhibits the hypoxia-induced inflammatory response through the NF-κB pathway

Cross-Sectional Association of Blood Selenium with Glycemic Biomarkers among U.S. Adults with Normoglycemia in the National Health and Nutrition Examination Survey 2013–2016

Selenium (Se) remains to have an inconsistent relationship with glycemic biomarkers and the risk of developing type 2 diabetes (T2D). Few studies have investigated the relationship between blood Se and glycemic biomarkers among people with normoglycemia. We conducted a cross-sectional analysis using the U.S. National Health and Nutrition Examination Survey 2013–2016. Multivariable linear regression models were developed to examine the associations of blood Se with glycemic biomarkers, namely, fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), insulin, and the oral glucose tolerance test (OGTT). Blood Se was treated as continuous (per log-10 increment) and categorical exposure (in quartiles) in separate regression models. We assessed the dose–response relationships by restricted cubic spline analysis. After excluding the participants with T2D or incomplete data, 2706 participants were analyzed. The highest quartile of blood Se was associated with increased FPG [adjusted β = 0.12, 95% Confidence Intervals (CI) = 0.04, 0.20], OGTT (adjusted β = 0.29, 95% CI = 0.02, 0.56), HbA1c (adjusted β = 0.04, 95% CI = 0.00, 0.07), and insulin (adjusted β = 2.50, 95% CI = 1.05, 3.95) compared with the lowest quartile. Positive associations were also observed between every log-10 increment of blood Se level and glycemic biomarkers, except for OGTT. A positive linear dose–response relationship existed between blood Se and FPG (Poverall = 0.003, Pnonlinear = 0.073) and insulin (Poverall = 0.004, Pnonlinear =0.060). BMI, age, and smoking status modified the associations of the highest quartile of Se (compared with the lowest quartile) with glycemic biomarkers. Overall, positive associations of blood Se with glycemic biomarkers were observed among U.S. adults with normoglycemia. These findings implied that people with normoglycemia need to be aware of the level of Se and other mineral intakes from diet and supplements. Further research is required to identify the mechanisms of excess Se in the progression of diabetes

Angiopoietin-2 promotes osteogenic differentiation of thoracic ligamentum flavum cells via modulating the Notch signaling pathway.

Thoracic ossification of the ligamentum flavum (TOLF) is heterotopic ossification of spinal ligaments, which may cause serious thoracic spinal canal stenosis and myelopathy. However, the underlying etiology remains inadequately understood. In this study, the ossification patterns of TOLF were analyzed by micro-computer tomography (micro-CT). The expression profile of genes associated with angiogenesis was analyzed in thoracic ligamentum flavum cells at sites of different patterns of ossification using RNA sequencing. Significant differences in the expression profile of several genes were identified from Gene Ontology (GO) analysis. Angiopoietin-2 (ANGPT2) was significantly up-regulated in primary thoracic ligamentum flavum cells during osteogenic differentiation. To address the effect of ANGPT2 on Notch signaling and osteogenesis, ANGPT2 stimulation increased the expression of Notch2 and osteogenic markers of primary thoracic ligamentum flavum cells of immature ossification, while inhibition of ANGPT2 exhibited opposite effect on Notch pathway and osteogenesis of cells of mature ossification. These findings provide the first evidence for positive regulation of ANGPT2 on osteogenic differentiation in human thoracic ligamentum flavum cells via modulating the Notch signaling pathway

Additional file 1 of Evaluating the impact of glucokinase activation on risk of cardiovascular disease: a Mendelian randomisation analysis

Additional file 1. Table S1. Information of included summary-level statistics. Table S2. Associations of instrumental variables for GK activation in main analyses with exposure and outcomes. Table S3. Colocalization analysis of genetically proxied GK activation and outcomes. Table S4. Associations of instrumental variables for GK activation in sensitivity analyses with exposure and outcomes. Table S5. Instrumental variables for GK activation in East Asian population and their associations with HbA1c. Table S6. Associations of genetically proxied GK activation with risks of cardiovascular outcomes in East Asian population. Table S7. Instrumental variables for non-targeted HbA1c lowering and their associations with HbA1c. Table S8. Associations of genetically predicted lower HbA1c with outcomes after removing GCK variants. Figure S1. Conceptual framework of study design. Supplementary Method. Brief summary of outcome definition

Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes : A Systematic Review and Meta-analysis

BACKGROUND: Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D).METHODS: We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that could improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies.Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination on internal validation, with lower performance on external validation.CONCLUSIONS: Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.PLAIN LANGUAGE SUMMARY: Patients with T2D are at high risk for CVD but predicting who will experience a cardiac event is challenging. Current risk tools and prognostic factors, such as laboratory tests, may not accurately predict risk in different patient populations. There is a need for personalized risk prediction tools to identify patients more accurately so that CVD prevention can be targeted to those who need it most. This study examined novel biomarkers, genetic markers, and risk scores on the prediction of CVD in individuals with T2D. We found that four laboratory markers and a genetic risk score for CHD had high predictive utility beyond traditional CVD risk factors and that risk scores had modest predictive utility when tested in diverse populations, but more studies are needed to determine their usefulness in clinical practice. The highest strength of evidence was observed for NT-proBNP, a laboratory test currently used to monitor patients with heart failure but not currently used in clinical practice for the purpose of CVD prediction in T2D

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis

Abstract Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D