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Abstract The genetic contributions to early onset heart failure (HF) are incompletely understood. Genetic testing in advanced HF patients undergoing heart transplantation (HTx) may yield clinical benefits, but data is limited. We performed deep-coverage whole genome sequencing (WGS) in 102 Swedish HTx recipients. Gene lists were compiled through a systematic literature review. Variants were prioritized for pathogenicity and classified manually. We also compared polygenic HF risk scores to a population-based cohort. We found a pathogenic (LP/P) variant in 34 individuals (34%). Testing yield was highest in hypertrophic (63% LP/P carriers), dilated (40%) and arrhythmogenic right ventricular (33%) cardiomyopathy and lower in ischemic cardiomyopathy (10%). A family history was more common in LP/P variant carriers than in non-carriers but was present in less than half of carriers (44% vs 13%, P

Abstract Plasma metabolomics holds potential for precision medicine, but limited information is available to compare the performance of such methods across multiple cohorts. We compared plasma metabolite profiles after an overnight fast in 11,309 participants of five population-based Swedish cohorts (50–80 years, 52% women). Metabolite profiles were uniformly generated at a core laboratory (Metabolon Inc.) with untargeted liquid chromatography mass spectrometry and a comprehensive reference library. Analysis of a second sample obtained one year later was conducted in a subset. Of 1629 detected metabolites, 1074 (66%) were detected in all cohorts while only 10% were unique to one cohort, most of which were xenobiotics or uncharacterized. The major classes were lipids (28%), xenobiotics (22%), amino acids (14%), and uncharacterized (19%). The most abundant plasma metabolome components were the major dietary fatty acids and amino acids, glucose, lactate and creatinine. Most metabolites displayed a log-normal distribution. Temporal variability was generally similar to clinical chemistry analytes but more pronounced for xenobiotics. Extensive metabolite-metabolite correlations were observed but mainly restricted to within each class. Metabolites were broadly associated with clinical factors, particularly body mass index, sex and renal function. Collectively, our findings inform the conduct and interpretation of metabolite association and precision medicine studies.

Abstract Whereas autonomic dysfunction and the metabolic syndrome are clinically associated, the relationships with the plasma metabolome is unknown. We explored the association between orthostatic blood pressure responses and 818 plasma metabolites in middle-aged subjects from the general population. We included 3803 out of 6251 subjects (mean age, 57 years; 52% women) from the Malmö sub-cohort of The Swedish CardioPulmonary bioImage Study with information on smoking habits, diabetes, antihypertensive drug treatment, anthropometrics, hemodynamic measurements and 818 plasma metabolites (mass-spectrometry). The associations between each metabolite and orthostatic systolic blood pressure responses were determined using multivariable linear regression analysis and p values were corrected using the Bonferroni method. Six amino acids, five vitamins, co-factors and carbohydrates, nine lipids and two xenobiotics were associated with orthostatic blood pressure after adjusting for age, gender and systolic blood pressure. After additional adjustments for BMI, diabetes, smoking and antihypertensive treatment, the association remained significant for six lipids, four amino acids and one xenobiotic. Twenty-two out of 818 plasma metabolites were associated with orthostatic blood pressure responses. Eleven metabolites, including lipids in the dihydrosphingomyelin and sphingosine pathways, were independently associated with orthostatic systolic blood pressure responses after additional adjustment for markers of cardio-metabolic disease.

Abstract Hemodynamic force analysis has been proposed as a novel tool for early detection of subclinical systolic dysfunction in heart failure with preserved ejection fraction (HFpEF). Here we investigated the ability of hemodynamic forces to discriminate between healthy subjects and heart failure patients with varying degrees of systolic dysfunction. We studied 34 controls, 16 HFpEF patients, and 25 heart failure patients with mid-range (HFmrEF) or reduced ejection fraction (HFrEF) using cardiac magnetic resonance with acquisition of cine images and 4D flow at 1.5 T. The Navier–Stokes equation was used to compute global left ventricular hemodynamic forces over the entire cardiac cycle. Forces were analyzed for systole, diastole, and the entire heartbeat, with and without normalization to left ventricular volume. Volume-normalized hemodynamic forces demonstrated significant positive correlation with EF (r2 = 0.47, p 0.34). Non-normalized forces displayed no differences between controls and HFpEF (p > 0.24 for all analyses) and did not correlate with EF (p = 0.36). Left ventricular hemodynamic force analysis, whether indexed to LV volumes or not, is not ready for clinical trials on HFpEF assessment.

The genetic contributions to early onset heart failure (HF) are incompletely understood. Genetic testing in advanced HF patients undergoing heart transplantation (HTx) may yield clinical benefits, but data is limited. We performed deep-coverage whole genome sequencing (WGS) in 102 Swedish HTx recipients. Gene lists were compiled through a systematic literature review. Variants were prioritized for pathogenicity and classified manually. We also compared polygenic HF risk scores to a population-based cohort. We found a pathogenic (LP/P) variant in 34 individuals (34%). Testing yield was highest in hypertrophic (63% LP/P carriers), dilated (40%) and arrhythmogenic right ventricular (33%) cardiomyopathy and lower in ischemic cardiomyopathy (10%). A family history was more common in LP/P variant carriers than in non-carriers but was present in less than half of carriers (44% vs 13%, P < 0.001), whereas age was similar. Polygenic risk scores were similar in HTx recipients and the population cohort. In conclusion, we observed a high prevalence of pathogenic cardiomyopathy gene variants in individuals with early-onset advanced HF, which could not accurately be ruled out by family history and age. In contrast, we did not observe higher polygenic risk scores in early onset advanced HF cases than in the general population. [ABSTRACT FROM AUTHOR]

Plasma metabolomics holds potential for precision medicine, but limited information is available to compare the performance of such methods across multiple cohorts. We compared plasma metabolite profiles after an overnight fast in 11,309 participants of five population-based Swedish cohorts (50–80 years, 52% women). Metabolite profiles were uniformly generated at a core laboratory (Metabolon Inc.) with untargeted liquid chromatography mass spectrometry and a comprehensive reference library. Analysis of a second sample obtained one year later was conducted in a subset. Of 1629 detected metabolites, 1074 (66%) were detected in all cohorts while only 10% were unique to one cohort, most of which were xenobiotics or uncharacterized. The major classes were lipids (28%), xenobiotics (22%), amino acids (14%), and uncharacterized (19%). The most abundant plasma metabolome components were the major dietary fatty acids and amino acids, glucose, lactate and creatinine. Most metabolites displayed a log-normal distribution. Temporal variability was generally similar to clinical chemistry analytes but more pronounced for xenobiotics. Extensive metabolite-metabolite correlations were observed but mainly restricted to within each class. Metabolites were broadly associated with clinical factors, particularly body mass index, sex and renal function. Collectively, our findings inform the conduct and interpretation of metabolite association and precision medicine studies. [ABSTRACT FROM AUTHOR]

Whereas autonomic dysfunction and the metabolic syndrome are clinically associated, the relationships with the plasma metabolome is unknown. We explored the association between orthostatic blood pressure responses and 818 plasma metabolites in middle-aged subjects from the general population. We included 3803 out of 6251 subjects (mean age, 57 years; 52% women) from the Malmö sub-cohort of The Swedish CardioPulmonary bioImage Study with information on smoking habits, diabetes, antihypertensive drug treatment, anthropometrics, hemodynamic measurements and 818 plasma metabolites (mass-spectrometry). The associations between each metabolite and orthostatic systolic blood pressure responses were determined using multivariable linear regression analysis and p values were corrected using the Bonferroni method. Six amino acids, five vitamins, co-factors and carbohydrates, nine lipids and two xenobiotics were associated with orthostatic blood pressure after adjusting for age, gender and systolic blood pressure. After additional adjustments for BMI, diabetes, smoking and antihypertensive treatment, the association remained significant for six lipids, four amino acids and one xenobiotic. Twenty-two out of 818 plasma metabolites were associated with orthostatic blood pressure responses. Eleven metabolites, including lipids in the dihydrosphingomyelin and sphingosine pathways, were independently associated with orthostatic systolic blood pressure responses after additional adjustment for markers of cardio-metabolic disease. [ABSTRACT FROM AUTHOR]

Hemodynamic force analysis has been proposed as a novel tool for early detection of subclinical systolic dysfunction in heart failure with preserved ejection fraction (HFpEF). Here we investigated the ability of hemodynamic forces to discriminate between healthy subjects and heart failure patients with varying degrees of systolic dysfunction. We studied 34 controls, 16 HFpEF patients, and 25 heart failure patients with mid-range (HFmrEF) or reduced ejection fraction (HFrEF) using cardiac magnetic resonance with acquisition of cine images and 4D flow at 1.5 T. The Navier–Stokes equation was used to compute global left ventricular hemodynamic forces over the entire cardiac cycle. Forces were analyzed for systole, diastole, and the entire heartbeat, with and without normalization to left ventricular volume. Volume-normalized hemodynamic forces demonstrated significant positive correlation with EF (r2 = 0.47, p < 0.0001) and were found significantly lower in heart failure with reduced ejection fraction compared to controls (p < 0.0001 for systole and diastole). No difference was seen between controls and HFpEF (p > 0.34). Non-normalized forces displayed no differences between controls and HFpEF (p > 0.24 for all analyses) and did not correlate with EF (p = 0.36). Left ventricular hemodynamic force analysis, whether indexed to LV volumes or not, is not ready for clinical trials on HFpEF assessment. [ABSTRACT FROM AUTHOR]

Plasma concentrations of many cardiovascular and inflammatory proteins are altered after ST-elevation myocardial infarction (STEMI) and may provide prognostic information. We conducted a large-scale proteomic analysis in patients with STEMI, correlating protein levels to infarct size and left ventricular ejection fraction (LVEF) determined with cardiac magnetic resonance imaging. We analysed 131 cardiovascular and inflammatory proteins using a multiplex proximity extension assay and blood samples obtained at baseline, 6, 24, and 96 h from the randomised clinical trial CHILL-MI. Cardiac magnetic resonance imaging data at 4 ± 2 days and 6 months were available as per trial protocol. Using a linear regression model with bootstrap resampling and false discovery rate adjustment we identified five proteins (ST2, interleukin-6, pentraxin-3, interleukin-10, renin, and myoglobin) with elevated values corresponding to larger infarct size or worse LVEF and four proteins (TNF-related apoptosis-inducing ligand, TNF-related activation induced cytokine, interleukin-16, and cystatin B) with values inversely related to LVEF and infarct size, concluding that among 131 circulating inflammatory and cardiovascular proteins in the acute and sub-acute phase of STEMI, nine showed a relationship with infarct size and LVEF post-STEMI, with IL-6 and ST2 exhibiting the strongest association. [ABSTRACT FROM AUTHOR]