KLF2 regulates neutrophil activation and thrombosis in cardiac hypertrophy and heart failure progression

Tang, Xinmiao; Wang, Peiwei; Zhang, Rongli; Watanabe, I.; Chang, Eugene; Vinayachandran, Vinesh; Nayak, Lalitha; Lapping, Stephanie; Liao, Sarah; Madera, Annmarie; Sweet, David R; Luo, Jiemeng; Fei, Jinsong; Jeong, Hyun‐Woo; Adams, Ralf H.; Zhang, Teng; Liao, Xudong; Jain, Mukesh K.

doi:10.1172/jci147191

Cited by 45 publications

(50 citation statements)

References 74 publications

(91 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are, for example, no specific and effective treatments for heart failure with preserved ejection fraction, a condition commonly characterized by left ventricular hypertrophy ( 2 , 4 ). In this issue of the JCI , Tang et al provide a translationally provocative contribution to the understanding of nonischemic cardiac hypertrophy and failure ( 6 ).…”

Section: Neutrophils In Cardiac Hypertrophymentioning

confidence: 99%

“…One recent study showed that neutrophil depletion reduces cardiac hypertrophy and dysfunction induced by pressure overload (i.e., transverse aortic constriction) in mice ( 7 ). Tang et al provide evidence that neutrophils contribute to cardiac hypertrophy and dysfunction induced by angiotensin II ( 6 ).…”

Section: Neutrophils In Cardiac Hypertrophymentioning

confidence: 99%

Section: Neutrophils In Cardiac Hypertrophymentioning

confidence: 99%

“…Using a loss-of-function strategy, Tang et al show that depletion of neutrophils with anti-Ly6G antibody reduces cardiac hypertrophy and dysfunction induced by angiotensin II infusion in mice ( 6 ). Conversely, acute neutrophilia achieved by neutrophil transfusion aggravates cardiac hypertrophy and dysfunction ( 6 ). Moreover, genetic deletion in the myeloid compartment (including monocytes/macrophages and neutrophils) of Krüppel-like factor 2 (KLF2), a transcription factor that has been shown to oppose inflammation ( 8 ), increases neutrophil accumulation in the myocardium and enhances cardiac hypertrophy, fibrosis, and dysfunction upon angiotensin II infusion; notably, this cardiac phenotype was also suppressed by depleting neutrophils with anti-Ly6G antibody ( 6 ).…”

Section: Neutrophils In Cardiac Hypertrophymentioning

confidence: 99%

“…Conversely, acute neutrophilia achieved by neutrophil transfusion aggravates cardiac hypertrophy and dysfunction ( 6 ). Moreover, genetic deletion in the myeloid compartment (including monocytes/macrophages and neutrophils) of Krüppel-like factor 2 (KLF2), a transcription factor that has been shown to oppose inflammation ( 8 ), increases neutrophil accumulation in the myocardium and enhances cardiac hypertrophy, fibrosis, and dysfunction upon angiotensin II infusion; notably, this cardiac phenotype was also suppressed by depleting neutrophils with anti-Ly6G antibody ( 6 ). Finally, deletion of KLF2 only in monocytes/macrophages did not increase angiotensin II–induced cardiac hypertrophy and dysfunction ( 6 ).…”

Section: Neutrophils In Cardiac Hypertrophymentioning

confidence: 99%

See 4 more Smart Citations

Neutrophil extracellular traps in cardiac hypertrophy: a KLF2 perspective

Riascos-Bernal¹,

Sibinga²

2022

Journal of Clinical Investigation

View full text Add to dashboard Cite

About 6 million adults in the United States have heart failure, and the mortality five years after diagnosis remains high at approximately 50%. Incomplete understanding of disease pathogenesis limits therapeutics, especially in the case of heart failure with preserved ejection fraction, a condition commonly associated with cardiac hypertrophy. Neutrophils, the most abundant leukocyte in blood, have functions beyond antimicrobial activity and participate in both sterile inflammation and disease; however, their role in nonischemic cardiac hypertrophy and heart failure is underexplored. In this issue of the JCI , Tang et al. show that neutrophil extracellular trap (NET) formation contributes to cardiac hypertrophy and dysfunction in a mouse model of angiotensin II–induced cardiomyopathy, and that Krüppel-like factor 2 (KLF2) functions in neutrophils to oppose this process. Whether a neutrophil-centered strategy may benefit patients with cardiac hypertrophy and failure deserves further investigation.

show abstract

Section: Neutrophils In Cardiac Hypertrophymentioning

confidence: 99%

Section: Neutrophils In Cardiac Hypertrophymentioning

confidence: 99%

Section: Neutrophils In Cardiac Hypertrophymentioning

confidence: 99%

Section: Neutrophils In Cardiac Hypertrophymentioning

confidence: 99%

Section: Neutrophils In Cardiac Hypertrophymentioning

confidence: 99%

See 3 more Smart Citations

Neutrophil extracellular traps in cardiac hypertrophy: a KLF2 perspective

Riascos-Bernal¹,

Sibinga²

2022

Journal of Clinical Investigation

View full text Add to dashboard Cite

show abstract

Increased transferrin protects from thrombosis in Chuvash erythrocytosis

et al. 2023

View full text Add to dashboard Cite

Von Hippel–Lindau protein (VHL) is essential to hypoxic regulation of cellular processes. VHL promotes proteolytic clearance of hypoxia‐inducible transcription factors (HIFs) that have been modified by oxygen‐dependent HIF‐prolyl hydroxylases. A homozygous loss‐of‐function VHLR200W mutation causes Chuvash erythrocytosis, a congenital disorder caused by augmented hypoxia‐sensing. Homozygous VHLR200W results in accumulation of HIFs that increase transcription of the erythropoietin gene and raise hematocrit. Phlebotomies reduce hematocrit and hyperviscosity symptoms. However, the major cause of morbidity and mortality in Chuvash erythrocytosis is thrombosis. Phlebotomies cause iron deficiency, which may further elevate HIF activity and transferrin, the HIF‐regulated plasma iron transporter recently implicated in thrombogenesis. We hypothesized that transferrin is elevated in Chuvash erythrocytosis, and that iron deficiency contributes to its elevation and to thrombosis. We studied 155 patients and 154 matched controls at steady state and followed them for development of thrombosis. Baseline transferrin was elevated, and ferritin reduced in patients. VHLR200W homozygosity and lower ferritin correlated with higher erythropoietin and transferrin. During 11 years of follow‐up, risk of thrombosis increased 8.9‐fold in patients versus controls. Erythropoietin elevation, but not hematocrit or ferritin, correlated with thrombosis risk. Unexpectedly, transferrin elevation associated with reduced rather than increased thrombosis risk. The A allele of the promoter EPO single nucleotide polymorphisms (SNP), rs1617640, associated with elevated erythropoietin and increased thrombosis risk, whereas the A allele of the intronic TF SNP, rs3811647, associated with higher transferrin and protection from thrombosis in patients. Our findings suggest an unexpected causal relationship between increased transferrin and protection from thrombosis in Chuvash erythrocytosis.

show abstract

Identification of common mechanisms and biomarkers of atrial fibrillation and heart failure based on machine learning

Zhang,

Ding,

et al. 2024

ESC Heart Failure

View full text Add to dashboard Cite

AimsAtrial fibrillation (AF) is the most common arrhythmia. Heart failure (HF) is a disease caused by heart dysfunction. The prevalence of AF and HF were progressively increasing over time. The co‐existence of AF and HF presents a significant therapeutic challenge. In order to provide new ideas for the diagnosis of AF and HF, it is necessary to carry out biomarker related studies.Methods and resultsThe training set and validation set data of AF and HF patient samples were downloaded from the GEO database, ‘limma’ was used to compare the differences in gene expression levels between the disease group and the normal group to screen for differentially expressed genes (DEGs). Weighted correlation network analysis (WGCNA) identified the modules with the highest positive correlation with AF and HF. Functional enrichment and PPI network construction of key genes were carried out. Biomarkers were screened by machine learning. The infiltration of immune cells in AF and HF groups was evaluated by R‐packet ‘CIBERSORT’. The miRNA network was constructed and potential therapeutic agents for biomarker genes were predicted through the drugbank database. Through WGCNA analysis, it was found that the modules most positively correlated with AF and HF were MEturquoise (r = 0.21, P value = 0.09) and MEbrown (r = 0.62, P value = 8e‐12), respectively. We screened 25 genes that were highly correlated with both AF and HF. Lasso regression analysis results showed 7 and 20 core genes in AF and HF groups, respectively. The top 20 important genes in AF and HF groups were obtained as core genes by RF model analysis. Four biomarkers were obtained after the intersection of core genes in four groups, namely, GLUL, NCF2, S100A12, and SRGN. The diagnostic efficacy of four genes in AF validation sets was good (AUC: GLUL 0.76, NCF2 0.64, S100A12 0.68, and SRGN 0.76), as well as in the HF validation set (AUC: GLUL 0.76, NCF2 0.84, S100A12 0.92, and SRGN 0.68). The highest correlation with neutrophils was observed for GLUL, NCF2, and S100A12, while SRGN exhibited the strongest correlation with T cells CD4 memory resting in the AF group. GLUL, NCF2, S100A12, and SRGN were most associated with neutrophils in the HF group. A total of 101 miRNAs were predicted by four genes, and GLUL, NCF2, and S100A12 predicted a total of 10 potential therapeutic agents.ConclusionsWe identified four biological markers that are highly correlated with AF and HF, namely, GLUL, NCF2, S100A12, and SRGN. Our findings provide theoretical basis for the clinical diagnosis and treatment of AF and HF.

show abstract

KLF2 regulates neutrophil activation and thrombosis in cardiac hypertrophy and heart failure progression

Cited by 45 publications

References 74 publications

Neutrophil extracellular traps in cardiac hypertrophy: a KLF2 perspective

Neutrophil extracellular traps in cardiac hypertrophy: a KLF2 perspective

Increased transferrin protects from thrombosis in Chuvash erythrocytosis

Identification of common mechanisms and biomarkers of atrial fibrillation and heart failure based on machine learning

Contact Info

Product

Resources

About