Association between inflammatory burden index and all-cause mortality in the general population aged over 45 years: Data from NHANES 2005-2017.

BACKGROUND AND AIM: The objective of this study was to investigate the association between inflammatory burden index (IBI) and all-cause mortality in the general population aged over 45 years. METHODS AND RESULTS: The study included 8827 participants from the National Health and Examination Nutrition Survey (NHANES) who were aged over 45 years. The IBI was calculated using three markers: C-reaction protein × neutrophil/lymphocyte, and all the participants were classified into four groups (Quartile 1: IBI ≤0.178, N = 2206; Quartile 2: 0.178 1.099, 2207). Cox proportional hazards regression models were used to estimate hazard ratios (HR) and 95 % confidence interval (CI) for the association between IBI and all-cause mortality. During a median follow-up of 129 month, 2431 deaths occurred. The all-cause mortality rate in Quartile 1, Quartile 2, Quartile 3 and Quartile 4 was 14.76 %, 17.67 %, 23.18 % and 29.69 %, respectively (p < 0.001). After adjustment for demographic, and potential clinical factors, higher IBI was significantly associated with an increased risk of all-cause mortality (Quartile 3 vs. Quartile 1: HR = 1.26, 95 % CI: 1.08 to 1.46, p = 0.003; Quartile 4 vs. Quartile 1: HR = 1.59, 95 % CI: 1.40 to 1.80, p < 0.001). Furthermore, the results of the restricted cubic spline analysis suggested that the association between IBI and all-cause mortality was nonlinear and positive, without specific threshold value. CONCLUSIONS: This study supports that higher IBI is associated with an increased risk of all-cause mortality in the general population aged over 45 years.

Causal association between serum 25-hydroxyvitamin D levels and right ventricular structure and function: A Mendelian randomization study.

BACKGROUND AND AIM: Deficient concentrations of vitamin D have been linked to several cardiovascular conditions, but the causal relationship between serum 25-hydroxyvitamin D (25(OH)D) levels and right ventricular structure and function remains unclear. Mendelian randomization (MR) was employed to inspect this association. METHODS AND RESULTS: Genetic instrumental variables associated with 25(OH)D levels were acquired from genome-wide association studies (GWAS) analyses. Summary statistics for right ventricular structure and function, including right ventricular end diastolic volume, right ventricular end systolic volume, right ventricular stroke volume, and right ventricular ejection fraction, were acquired from publicly available GWAS datasets. For the primary analysis, the inverse variance weighted (IVW) method was utilized in performing the MR analysis. Additionally, secondly analyses were conducted to estimate the robustness and consistency of the attained conclusions. The MR analysis did not reveal a considerable causal association between serum 25(OH)D levels and right ventricular end diastolic volume (ß: 0.112, 95% confident interval [CI]: -0.006 to 0.230, p = 0.063), right ventricular end systolic volume (ß: 0.102, 95% CI: -0.021 to 0.226, p = 0.105), right ventricular stroke volume (ß: 0.095, 95% CI: -0.018 to 0.207, p = 0.099), or right ventricular ejection fraction (ß: -0.005, 95% CI: -0.123 to 0.112, p = 0.928). CONCLUSIONS: Our findings did not reveal any substantial evidence supporting a causal relationship between serum 25(OH)D levels and the structure and function of the right ventricle. These findings suggest that serum 25(OH)D levels may not directly influence right ventricular parameters assessed.

Association between basal metabolic rate and cardio-metabolic risk factors: Evidence from a Mendelian Randomization study.

Background: Cardio-metabolic risk factors play a crucial role in the development of cardiovascular and metabolic diseases. Basal metabolic rate (BMR) is a fundamental physiological parameter that affects energy expenditure and might contribute to variations in these risk factors. However, the exact relationship between BMR and cardio-metabolic risk factors has remained unclear. Methods: We employed Mendelian Randomization (MR) analysis to explore the association between BMR (N: 534,045) and various cardio-metabolic risk factors, including body mass index (BMI, N: 681,275), fasting glucose (N: 200,622), high-density lipoprotein (HDL) cholesterol (N = 403,943), low-density lipoprotein (LDL) cholesterol (N = 431,167), total cholesterol (N: 344,278), and triglycerides (N: 441,016), C-reactive protein (N: 436,939), waist circumference (N: 232,101), systolic blood pressure (N: 810,865), diastolic blood pressure (N: 810,865), glycated haemoglobin (N: 389,889), and N-terminal prohormone brain natriuretic peptide (N: 21,758). We leveraged genetic variants strongly associated with BMR as instrumental variables to investigate potential causal relationships, with the primary analysis using the Inverse Variance Weighted (IVW) method. Results: Our MR analysis revealed compelling evidence of a causal link between BMR and specific cardio-metabolic risk factors. Specifically, genetically determined higher BMR was associated with an increased BMI (ß = 0.7538, 95% confidence interval [CI]: 0.6418 to 0.8659, p < 0.001), lower levels of HDL cholesterol (ß = -0.3293, 95% CI: 0.4474 to -0.2111, p < 0.001), higher levels of triglycerides (ß = 0.1472, 95% CI: 0.0370 to 0.2574, p = 0.0088), waist circumference (ß = 0.4416, 95% CI: 0.2949 to 0.5883, p < 0.001), and glycated haemoglobin (ß = 0.1037, 95% CI: 0.0080 to 0.1995, p = 0.0377). However, we did not observe any significant association between BMR and fasting glucose, LDL cholesterol, total cholesterol, C-reactive protein, systolic blood pressure, diastolic blood pressure, or N-terminal prohormone brain natriuretic peptide (all p-values>0.05). Conclusion: This MR study provides valuable insights into the relationship between BMR and cardio-metabolic risk factors. Understanding the causal links between BMR and these factors could have important implications for the development of targeted interventions and therapies.

Erratum to comprehensive bioinformatics analysis of the TP53 signaling pathway in Wilms' tumor.

[This corrects the article DOI: 10.21037/atm-20-6047.].

Comprehensive bioinformatics analysis of the TP53 signaling pathway in Wilms' tumor.

BACKGROUND: Differential expression of tumor protein 53 (TP53, or p53) has been observed in multiple cancers. However, the expression levels and prognostic role of TP53 signaling pathway genes in Wilms' tumor (WT) have yet to be fully explored. METHODS: The expression levels of TP53 signaling pathway genes including TP53, mouse double minute 2 (MDM2), mouse double minute 4 (MDM4), cyclin-dependent kinase 2A (CDKN2A), cyclin-dependent kinase 2B (CDKN2B), and tumor suppressor p53-binding protein 1 (TP53BP1) in WT were analyzed using the Oncomine database. Aberration types, co-mutations, mutation locations, signaling pathways, and the prognostic role of TP53 in WT were investigated using cBioPortal. MicroRNA (miRNA) and transcription factor (TF) targets were identified with miRTarBase, miWalk, and ChIP-X Enrichment Analysis 3 (CheA3), respectively. A protein-protein network was constructed using GeneMANIA. The expression of TP53 signaling genes were confirmed in WT samples and normal kidney tissues using the Human Protein Atlas (HPA). Cancer Therapeutics Response Portal (CTRP) was used to analyze the small molecules potentially targeting TP53. RESULTS: TP53 was significantly expressed in the Cutcliffe Renal (P=0.010), but not in the Yusenko Renal (P=0.094). Meanwhile, MDM2 was significantly overexpressed in the Yusenko Renal (P=0.058), but not in the Cutcliffe Renal (P=0.058). The expression levels of MDM4 no significant difference between the tumor and normal tissue samples. The most common TP53 alteration was missense and the proportion of TP53 pathway-related mutations was 2.3%. Co-expressed genes included ZNF609 (zinc finger protein 609), WRAP53 (WD40-encoding RNA antisense to p53), CNOT2 (CC chemokine receptor 4-negative regulator of transcription 2), and CDH13 (cadherin 13). TP53 alterations indicated poor prognosis of WT (P=1.051e-4). The regulators of the TP53 pathway included miR-485-5p and TFs NR2F2 and KDM5B. The functions of TP53 signaling pathway were signal transduction in response to DNA damage and regulate the cell cycle. The small molecules targeting TP53 included PRIMA-1, RITA, SJ-172550, and SCH-529074. CONCLUSIONS: TP53 was found to be differentially expressed in WT tissues. TP53 mutations indicated poor outcomes of WT. Therefore, pifithrin-mu, PRIMA-1, RITA, SJ-172550, and SCH-529074 could be used in combination with traditional chemotherapy to treat WT.