The peripheral blood transcriptome in septic cardiomyopathy: an observational, pilot study.

BACKGROUND:Septic cardiomyopathy (SCM) is common in sepsis and associated with increased morbidity and mortality. Left ventricular global longitudinal strain (LV GLS), measured by speckle tracking echocardiography, allows improved identification of impaired cardiac contractility. The peripheral blood transcriptome may be an important window into SCM pathophysiology. We therefore studied the peripheral blood transcriptome and LV GLS in a prospective cohort of patients with sepsis. RESULTS:In this single-center observational pilot study, we enrolled adult patients (age > 18) with sepsis within 48 h of admission to the ICU. SCM was defined as LV GLS > - 17% based on echocardiograms performed within 72 h of admission. We enrolled 27 patients, 24 of whom had high-quality RNA results; 18 (75%) of 24 had SCM. The group was 50% female and had a median (IQR) age of 59.5 (48.5-67.0) years and admission APACHE II score of 21.0 (16.0-32.3). Forty-six percent had septic shock. After filtering for low-expression and non-coding genes, 15,418 protein coding genes were expressed and 73 had significantly different expression between patients with vs. without SCM. In patients with SCM, 43 genes were upregulated and 30 were downregulated. Pathway analysis identified enrichment in type 1 interferon signaling (adjusted p < 10-5). CONCLUSIONS:In this hypothesis-generating study, SCM was associated with upregulation of genes in the type 1 interferon signaling pathway. Interferons are cytokines that stimulate the innate and adaptive immune response and are implicated in the early proinflammatory and delayed immunosuppression phases of sepsis. While type 1 interferons have not been implicated previously in SCM, interferon therapy (for viral hepatitis and Kaposi sarcoma) has been associated with reversible cardiomyopathy, perhaps suggesting a role for interferon signaling in SCM

Analysis of family histories suggests shared genetic risk for chronic thromboembolic pulmonary hypertension and venous thromboembolism

Abstract Chronic thromboembolic pulmonary hypertension (CTEPH) and acute pulmonary embolism (PE) are related phenotypes, however, previous reports have suggested that genetic risk factors for CTEPH and PE differ. Here we report that a family history of VTE is equally frequent in individuals with CTEPH and PE, suggesting that shared genetic variants may influence risk of both phenotypes. We also provide the first estimate of the frequency of familial CTEPH, which we identified in 2.2% of CTEPH patients in our cohort

At the X-Roads of Sex and Genetics in Pulmonary Arterial Hypertension

Group 1 pulmonary hypertension (pulmonary arterial hypertension; PAH) is a rare disease characterized by remodeling of the small pulmonary arteries leading to progressive elevation of pulmonary vascular resistance, ultimately leading to right ventricular failure and death. Deleterious mutations in the serine-threonine receptor bone morphogenetic protein receptor 2 (BMPR2; a central mediator of bone morphogenetic protein (BMP) signaling) and female sex are known risk factors for the development of PAH in humans. In this narrative review, we explore the complex interplay between the BMP and estrogen signaling pathways, and the potentially synergistic mechanisms by which these signaling cascades increase the risk of developing PAH. A comprehensive understanding of these tangled pathways may reveal therapeutic targets to prevent or slow the progression of PAH

The association between pulmonary artery enlargement and mortality in an Emergency Department population undergoing computed tomography pulmonary angiography

Abstract Findings of an enlarged pulmonary artery diameter (PAd) and increased pulmonary artery to ascending aorta ratio (PA:AA) on contrast‐enhanced computed tomography pulmonary angiography (CTPA) are associated with increased mortality in particular groups of patients with cardiopulmonary disease. However, the frequency and prognostic significance of these incidental findings has not been studied in unselected patients evaluated in the Emergency Department (ED). This study aims to determine the prevalence and associated prognosis of enlarged pulmonary artery measurements in an ED cohort. We measured PA and AA diameters on 990 CTPA studies performed in the ED. An enlarged PA diameter was defined as >27 mm in females and >29 mm in males, while an increased PA:AA was defined as >0.9. Poisson regression was performed to calculate prevalence ratios for relevant comorbidities, and multivariable Cox regression was performed to calculate hazard ratios (HR) for mortality of patients with enlarged pulmonary artery measurements. An enlarged PAd was observed in 27.9% of 990 patients and was more commonly observed in older patients and in patients with obesity or heart failure. Conversely, PA:AA was increased in 34.2% of subjects, and was more common in younger patients and those with peripheral vascular disease or obesity. After controlling for age, sex, and comorbidities, both enlarged PAd (HR 1.29, 95% CI 1.00–1.68, p = 0.05) and PA:AA (HR 1.70, 95% CI 1.31–2.22 p < 0.01) were independently associated with mortality. In sum, enlarged PAd and increased PA:AA are common in patients undergoing CTPAs in the ED setting and both are independently associated with mortality

The peripheral blood transcriptome in septic cardiomyopathy: an observational, pilot study.

BACKGROUND:Septic cardiomyopathy (SCM) is common in sepsis and associated with increased morbidity and mortality. Left ventricular global longitudinal strain (LV GLS), measured by speckle tracking echocardiography, allows improved identification of impaired cardiac contractility. The peripheral blood transcriptome may be an important window into SCM pathophysiology. We therefore studied the peripheral blood transcriptome and LV GLS in a prospective cohort of patients with sepsis. RESULTS:In this single-center observational pilot study, we enrolled adult patients (age &gt; 18) with sepsis within 48 h of admission to the ICU. SCM was defined as LV GLS &gt; - 17% based on echocardiograms performed within 72 h of admission. We enrolled 27 patients, 24 of whom had high-quality RNA results; 18 (75%) of 24 had SCM. The group was 50% female and had a median (IQR) age of 59.5 (48.5-67.0) years and admission APACHE II score of 21.0 (16.0-32.3). Forty-six percent had septic shock. After filtering for low-expression and non-coding genes, 15,418 protein coding genes were expressed and 73 had significantly different expression between patients with vs. without SCM. In patients with SCM, 43 genes were upregulated and 30 were downregulated. Pathway analysis identified enrichment in type 1 interferon signaling (adjusted p &lt; 10-5). CONCLUSIONS:In this hypothesis-generating study, SCM was associated with upregulation of genes in the type 1 interferon signaling pathway. Interferons are cytokines that stimulate the innate and adaptive immune response and are implicated in the early proinflammatory and delayed immunosuppression phases of sepsis. While type 1 interferons have not been implicated previously in SCM, interferon therapy (for viral hepatitis and Kaposi sarcoma) has been associated with reversible cardiomyopathy, perhaps suggesting a role for interferon signaling in SCM

Gram stain results for blood, respiratory, and urine cultures of patients with positive culture results.

Gram stain results for blood, respiratory, and urine cultures of patients with positive culture results.</p

Patient demographics and baseline characteristics.

All data reported as median (interquartile range) or n(%) unless specified otherwise.</p

Adjusted odds ratio (95% confidence interval) for mortality at different time points for septic cardiomyopathy (SCM) and sepsis-related cardiogenic shock (SeRCS) compared to septic shock without SCM.

Adjusted odds ratio (95% confidence interval) for mortality at different time points for septic cardiomyopathy (SCM) and sepsis-related cardiogenic shock (SeRCS) compared to septic shock without SCM.</p

Data analysis pipeline and machine learning algorithms to identify risk factors for development of SCM and SeRCS.

Data analysis pipeline and machine learning algorithms to identify risk factors for development of SCM and SeRCS.</p