Inflammation and heart failure: a two-sample Mendelian randomization study

Causal relationship between chronic obstructive pulmonary disease and heart failure: A Mendelian randomization study

BACKGROUND

Causal association between chronic obstructive pulmonary disease (COPD) and heart failure (HF) has been controversial. This study used Mendelian Randomization (MR) analysis to clarify the potential causal connection between these two conditions.

OBJECTIVES

The purpose of the study was to investigate the causal relationship between COPD and HF based on the hypothesis that the genetic predisposition to COPD could lead to an increased risk of developing HF METHODS: A two-sample MR analysis of genetic data was performed for COPD and HF. This study was based on genome-wide association study (GWAS) data, including 6,915 patients with confirmed COPD and 186,723 controls. The odds ratios (ORs) and their 95 % confidence intervals (95 %CIs) were estimated using a fixed effects inverse variance weighting (IVW) method. Several supplementary statistical methods, including MR-Egger, weighted median, maximum likelihood, penalized weighted median, and random effects IVW, were applied to enhance the robustness of findings. Moreover, MR-PRESSO was employed as an alternative method for statistical detection.

RESULTS

Pooled data for HF were obtained from different GWASs, including 4,7309 confirmed HF patients and 930,014 controls. The MR analysis, based on the IVW model, revealed that COPD was significantly associated with an increased risk of HF. Specifically, the obtained findings showed that COPD patients had a higher risk of developing HF (Model 1: OR = 1.068, 95 %CI: 1.006-1.134, p = 0.031; Model 2: OR = 1.038, 95 %CI: 1.006-1.071, p = 0.020), indicating a causal relationship between COPD and HF. No evidence was found to suggest a reverse causal effect of HF on COPD incidence.

CONCLUSION

The MR analysis substantiates a causal link between COPD and HF, with no evidence supporting a reverse causation from HF to COPD. These findings underscore the importance of proactive COPD management as a potential strategy to prevent the development of HF, highlighting the need for targeted interventions in patients with COPD to mitigate their risk of HF.

Matrix Metalloproteinase and Aortic Aneurysm: A Two-sample Mendelian Randomization Study

BACKGROUND

Studies have linked matrix metalloproteinases (MMPs) to both thoracic aortic aneurysm and abdominal aortic aneurysm (TAA and AAA). The precise MMPs entailed in this procedure, however, were still unknown. This study used a two-sample Mendelian randomization (MR) analysis to look into the causal relationship between MMPs and the risk of TAA and AAA.

METHODS

Eight MMPs, including MMP-1, MMP-2, MMP-3, MMP-8, MMP-9, MMP-10, MMP-12, and MMP-13, were found among people of European ancestry with accessible Genome-Wide Association Studies (GWAS). We employed the findings from Genome-Wide Association Studies (GWAS) for 8 MMPs, and TAA and AAA from the FinnGen consortiums (3,201 cases and 317,899 controls, respectively) were used in a two-sample MR analysis. The primary method of analysis for MR was the inverse variance weighted (IVW) method, along with analyses of heterogeneity and horizontal pleiotropy. 31 single-nucleotide polymorphisms connected to MMP were retrieved.

RESULTS

IVW demonstrated a negative causal association between TAA and AAA and serum MMP-12 levels. The incidence of TAA decreased by 1.031% for every 1 ng/mL increase in serum MMP-12 [odds ratio (OR) = 0.897, 95% confidence interval (CI): 0.831-0.968, P = 0.005]. The incidence of AAA fell by 1.653% (OR = 0.835, 95% CI: 0.752-0.926, P = 0.001) for every 1 ng/mL increase in serum MMP-12. There was no horizontal pleiotropy or heterogeneity in the MR data (P > 0.05).

CONCLUSIONS

The levels of TAA and AAA and serum MMP-12 are causally related. MMP-12 is a factor that reduces the risk of AAA and TTA. Our study suggested that MMP-12 level is causally associated with a decreased risk of TAA and AAA.

Identification of Co-diagnostic Genes for Heart Failure and Hepatocellular Carcinoma Through WGCNA and Machine Learning Algorithms

This research delves into the intricate relationship between hepatocellular carcinoma (HCC) and heart failure (HF) by exploring shared genetic characteristics and molecular processes. Employing advanced methodologies such as differential analysis, weighted correlation network analysis (WGCNA), and algorithms like Random Forest (RF), Least Absolute Shrinkage Selection (LASSO), and XGBoost, we meticulously identified modular differential genes (DEGs) associated with both HF and HCC. Gene Set Variation Analysis (GSVA) and single sample gene set enrichment analysis (ssGSEA) were employed to unveil underlying biological mechanisms. The study revealed 88 core genes shared between HF and HCC, indicating a common mechanism. Enrichment analysis emphasized the roles of immune responses and inflammation in both diseases. Leveraging XGBoost, we crafted a robust multigene diagnostic model (including FCN3, MAP2K1, AP3M2, CDH19) with an area under the curve (AUC) > 0.9, showcasing exceptional predictive accuracy. GSVA and ssGSEA analyses unveiled the involvement of immune cells and metabolic pathways in the pathogenesis of HF and HCC. This research uncovers a pivotal interplay between HF and HCC, highlighting shared pathways and key genes, offering promising insights for future clinical treatments and experimental research endeavors.

Sodium-glucose cotransporter 2 inhibitors, inflammation, and heart failure: a two-sample Mendelian randomization study

BACKGROUND

Sodium-glucose cotransporter 2 (SGLT-2) inhibitors are increasingly recognized for their role in reducing the risk and improving the prognosis of heart failure (HF). However, the precise mechanisms involved remain to be fully delineated. Evidence points to their potential anti-inflammatory pathway in mitigating the risk of HF.

METHODS

A two-sample, two-step Mendelian Randomization (MR) approach was employed to assess the correlation between SGLT-2 inhibition and HF, along with the mediating effects of inflammatory biomarkers in this relationship. MR is an analytical methodology that leverages single nucleotide polymorphisms as instrumental variables to infer potential causal inferences between exposures and outcomes within observational data frameworks. Genetic variants correlated with the expression of the SLC5A2 gene and glycated hemoglobin levels (HbA1c) were selected using datasets from the Genotype-Tissue Expression project and the eQTLGen consortium. The Genome-wide association study (GWAS) data for 92 inflammatory biomarkers were obtained from two datasets, which included 14,824 and 575,531 individuals of European ancestry, respectively. GWAS data for HF was derived from a meta-analysis that combined 26 cohorts, including 47,309 HF cases and 930,014 controls. Odds ratios (ORs) and 95% confidence interval (CI) for HF were calculated per 1 unit change of HbA1c.

RESULTS

Genetically predicted SGLT-2 inhibition was associated with a reduced risk of HF (OR 0.42 [95% CI 0.30-0.59], P < 0.0001). Of the 92 inflammatory biomarkers studied, two inflammatory biomarkers (C-X-C motif chemokine ligand 10 [CXCL10] and leukemia inhibitory factor) were associated with both SGLT-2 inhibition and HF. Multivariable MR analysis revealed that CXCL10 was the primary inflammatory cytokine related to HF (MIP = 0.861, MACE = 0.224, FDR-adjusted P = 0.0844). The effect of SGLT-2 inhibition on HF was mediated by CXCL10 by 17.85% of the total effect (95% CI [3.03%-32.68%], P = 0.0183).

CONCLUSIONS

This study provides genetic evidence supporting the anti-inflammatory effects of SGLT-2 inhibitors and their beneficial impact in reducing the risk of HF. CXCL10 emerged as a potential mediator, offering a novel intervention pathway for HF treatment.

Type 1 diabetes, its complications, and non-ischemic cardiomyopathy: a mendelian randomization study of European ancestry

BACKGROUND

Type 1 diabetes (T1D) is a significant risk factor for a range of cardiovascular diseases. Nonetheless, the causal relationship between T1D and non-ischemic cardiomyopathy (NICM) remains to be elucidated. Furthermore, the mechanisms responsible for the progression from T1D to NICM have not been definitively characterized.

OBJECTIVE

The aim of this study was to conduct a Mendelian randomization (MR) study to investigate the causal effects of T1D and its complications on the development of NICM. Additionally, this study aimed to conduct a mediation analysis to identify potential mediators within this correlation.

METHODS

Genetic variants were used as instrumental variables for T1D. The summary data for T1D were obtained from two genome-wide association study datasets. The summary data for T1D with complications and NICM were obtained from the Finnish database. Two-sample MR, multivariable MR and mediation MR were conducted in this study.

RESULTS

The study revealed a causal association between T1D, T1D with complications, and NICM (with odds ratios of 1.02, 95% CI 1.01-1.04, p = 1.17e-04 and 1.03, 95% CI 1.01-1.05, p = 3.15e-3). Even after adjusting for confounding factors such as body mass index and hypertension, T1D remained statistically significant (with odds ratio of 1.02, 95% CI 1.01-1.04, p = 1.35e-4). Mediation analysis indicated that monokine induced by gamma interferon may play a mediating role in the pathogenesis of T1D-NICM (mediation effect indicated by odds ratio of 1.005, 95% CI 1.001-1.01, p = 4.9e-2).

CONCLUSION

The study demonstrates a causal relationship between T1D, its complications, and NICM. Additionally, monokine induced by gamma interferon may act as a potential mediator in the pathogenesis of T1D-NICM.

Clonal hematopoiesis of indeterminate potential: implications for the cardiologists

Myeloproliferative neoplasms, including polycythemia vera, essential thrombocythemia, and myelofibrosis, are characterized by somatic gene mutations in bone marrow stem cells, which trigger an inflammatory response influencing the development of associated cardiovascular complications. In recent years, the same mutations were found in individuals with cardiovascular diseases even in the absence of hematological alterations. These genetic events allow the identification of a new entity called 'clonal hematopoiesis of indeterminate potential' (CHIP), as it was uncertain whether it could evolve toward hematological malignancies. CHIP is age-related and, remarkably, myocardial infarction, stroke, and heart failure were frequently reported in these individuals and attributed to systemic chronic inflammation driven by the genetic mutation. We reviewed the connection between clonal hematopoiesis, inflammation, and cardiovascular diseases, with a practical approach to improve clinical practice and highlight the current unmet needs in this area of knowledge.

Inflammation in acute heart failure

Acute heart failure (AHF) represents a common clinical scenario that requires prompt evaluation and therapy and that is characterized by a high risk of mortality or subsequent rehospitalizations. The pathophysiology leading to AHF decompensation is still not fully understood. Significant activation of inflammatory pathways has been identified in patients with AHF, particularly in its most severe forms, and it has been hypothesized that systemic inflammation has a role in AHF pathogenesis. Several inflammatory mediators and cytokines, such as high sensitivity C-reactive protein, tumor necrosis factor-α, interleukin-6, interleukin-1, soluble suppression of tumorigenicity 2 and galectin-3, have been shown to play a role in the pathogenesis, development and worsening of this condition with an independent prediction of adverse outcomes. This manuscript reviews the prevalence and prognostic value of systemic inflammation in AHF, as well as the potential role of anti-inflammatory therapies, focusing on available evidence from clinical trials and ongoing studies.

Effect of C-reactive protein on the risk of Heart failure: a mendelian randomization study

BACKGROUND

Traditional observational studies have shown positive associations between c-reactive protein (CRP) and heart failure (HF) risk. However, this association has not been fully elucidated. Therefore, Mendelian randomization was used to examine CRP's possible etiological roles with HF.

METHODS

We implemented a two-sample Mendelian randomization framework to examine the causality of the association between CRP and HF based on summary statistics by large-scale genome-wide association studies (GWAS) datasets of European ancestry through inverse-variance weighted, weighted median, MREgger regression, and MR-PRESSO methods. The summary statistics dataset on the association of genetic variants with CRP was used from the published GWAS of European descent in UK Biobank participants (N = 427,367) and the CHARGE consortium (N = 575,531). The GWAS dataset used to identify genetic variants underlying HF from the HERMES consortium includes 977,323 participants (47,309 cases and 930,014 controls). The odds ratio (OR) with 95% confidence intervals (CIs) was employed to examine this association.

RESULTS

The results of our IVW indicated that CRP was strongly associated with HF (OR = 4.18, 95% CI = 3.40-5.13, p < 0.001). The Cochran heterogeneity test showed significant heterogeneity among SNPs of CRP (Q = 317.55, p < 0.001; I² = 37.6%), and no considerable pleiotropy was detected for the association of CRP with HF [intercept = 0.003; p = 0.234]. This finding remained consistent using different Mendelian randomization methods and sensitivity analyses.

CONCLUSION

Our MR study did identify convincing evidence to support CRP associated with HF risk. Human genetic data suggest that CRP is a causative factor in HF. Hence, CRP assessment may offer additional prognostic information as an adjuvant to overall risk assessment in HF patients. These findings prompt significant questions about the function of inflammation in the progression of HF. More research into the role of inflammation in HF is needed to guide trials of anti-inflammation management.