Multi-Ethnic Study of Atherosclerosis Early Heart Failure Study: Rationale, Design, and Baseline Characteristics.

BACKGROUND: Current prevalence estimates of heart failure (HF) are primarily based on self-report or HF hospitalizations. There is an unmet need to define the prevalence and pathogenesis of early symptomatic HF, which may be undiagnosed and precedes HF hospitalization. METHODS: The MESA (Multi-Ethnic Study of Atherosclerosis) Early HF study was conducted during MESA exam 6 to determine the prevalence of early HF and investigate the transition from risk factors to early HF in a diverse population-based cohort of older adults. Between 2016 and 2018, 3285 MESA participants from 6 field centers underwent comprehensive speckle-tracking echocardiography with passive leg raise maneuver, Kansas City Cardiomyopathy Questionnaire, 6-minute walk test, arterial stiffness assessment, and proteomics (including NT-proBNP [N-terminal pro-B-type natriuretic peptide]). RESULTS: Median age was 73 (25th-75th percentile 67-81) years, 53.2% were female, 25.6% were Black, 12.8% were Chinese, and 40.0% were White. The prevalence of HF risk factors was high: hypertension, 61.9%; former or current smoking, 53.7%; obesity 34.8%; diabetes; 24.7%; and chronic kidney disease; 22%. Overt cardiovascular disease, which ranged from 2.1% (HF) to 13.6% (atrial fibrillation), was less common. Of the 3285 participants, 96% underwent proteomics, 94% Kansas City Cardiomyopathy Questionnaire, 93% speckle-tracking echocardiography with passive leg raise, 82% arterial stiffness exam, and 77% 6-minute walk test. Feasibility of resting speckle-tracking echocardiography (87%-99% across cardiac chambers) and passive leg raise Doppler/speckle-tracking echocardiography (>84%) measurements was high. A total of 120 unique echocardiographic indices were measured. CONCLUSIONS: The MESA Early HF study is a key resource for cardiovascular researchers who are interested in improving the epidemiological and phenotypic characterization of early HF. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005487.

Sex differences in proteomic correlates of coronary microvascular dysfunction among patients with heart failure and preserved ejection fraction.

AIMS: Little information is available on sex differences in coronary microvascular dysfunction (CMD) in heart failure with preserved ejection fraction (HFpEF). We investigated sex-specific proteomic profiles associated with CMD in patients with HFpEF. METHODS AND RESULTS: Using the prospective multinational PROMIS-HFpEF study (Prevalence of Microvascular Dysfunction in HFpEF; n = 182; 54.6% women), we compared clinical and biomarker correlates of CMD (defined as coronary flow reserve [CFR] <2.5) between men and women with HFpEF. We used lasso penalized regression to analyse 242 biomarkers from high-throughput proximity extension assays, adjusting for age, body mass index, creatinine, smoking and study site. The prevalence of CMD was similarly high in men and women with HFpEF (77% vs. 70%; p = 0.27). Proteomic correlates of CFR differed by sex, with 10 versus 16 non-overlapping biomarkers independently associated with CFR in men versus women, respectively. In men, proteomic correlates of CFR included chemokine ligand 20, brain natriuretic peptide, proteinase 3, transglutaminase 2, pregnancy-associated plasma protein A and tumour necrosis factor receptor superfamily member 14. Among women, the strongest proteomic correlates with CFR were insulin-like growth factor-binding protein 1, phage shock protein D, CUB domain-containing protein 1, prostasin, decorin, FMS-like tyrosine kinase 3, ligand growth differentiation factor 15, spondin-1, delta/notch-like epidermal growth factor-related receptor and tumour necrosis factor receptor superfamily member 13B. Pathway analyses suggested that CMD was related to the inflammation-mediated chemokine and cytokine signalling pathway among men with HFpEF, and the P13-kinase and transforming growth factor-beta signalling pathway among women with HFpEF. CONCLUSION: While the prevalence of CMD among men and women with HFpEF is similar, the drivers of microvascular dysfunction may differ by sex. The current inflammatory paradigm of CMD in HFpEF potentially predominates in men, while derangement in ventricular remodelling and fibrosis may play a more important role in women.

Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms.

Patients with rare conditions such as cardiac amyloidosis (CA) are difficult to identify, given the similarity of disease manifestations to more prevalent disorders. The deployment of approved therapies for CA has been limited by delayed diagnosis of this disease. Artificial intelligence (AI) could enable detection of rare diseases. Here we present a pipeline for CA detection using AI models with electrocardiograms (ECG) or echocardiograms as inputs. These models, trained and validated on 3 and 5 academic medical centers (AMC) respectively, detect CA with C-statistics of 0.85-0.91 for ECG and 0.89-1.00 for echocardiography. Simulating deployment on 2 AMCs indicated a positive predictive value (PPV) for the ECG model of 3-4% at 52-71% recall. Pre-screening with ECG enhance the echocardiography model performance at 67% recall from PPV of 33% to PPV of 74-77%. In conclusion, we developed an automated strategy to augment CA detection, which should be generalizable to other rare cardiac diseases.

Proteomic Evaluation of the Comorbidity-Inflammation Paradigm in Heart Failure With Preserved Ejection Fraction: Results From the PROMIS-HFpEF Study.

BACKGROUND: A systemic proinflammatory state has been hypothesized to mediate the association between comorbidities and abnormal cardiac structure/function in heart failure with preserved ejection fraction (HFpEF). We conducted a proteomic analysis to investigate this paradigm. METHODS: In 228 patients with HFpEF from the multicenter PROMIS-HFpEF study (Prevalence of Microvascular Dysfunction in Heart Failure With Preserved Ejection Fraction), 248 unique circulating proteins were quantified by a multiplex immunoassay (Olink) and used to recapitulate systemic inflammation. In a deductive approach, we performed principal component analysis to summarize 47 proteins known a priori to be involved in inflammation. In an inductive approach, we performed unbiased weighted coexpression network analyses of all 248 proteins to identify clusters of proteins that overrepresented inflammatory pathways. We defined comorbidity burden as the sum of 8 common HFpEF comorbidities. We used multivariable linear regression and statistical mediation analyses to determine whether and to what extent inflammation mediates the association of comorbidity burden with abnormal cardiac structure/function in HFpEF. We also externally validated our findings in an independent cohort of 117 HFpEF cases and 30 comorbidity controls without heart failure. RESULTS: Comorbidity burden was associated with abnormal cardiac structure/function and with principal components/clusters of inflammation proteins. Systemic inflammation was also associated with increased mitral E velocity, E/e' ratio, and tricuspid regurgitation velocity; and worse right ventricular function (tricuspid annular plane systolic excursion and right ventricular free wall strain). Inflammation mediated the association between comorbidity burden and mitral E velocity (proportion mediated 19%-35%), E/e' ratio (18%-29%), tricuspid regurgitation velocity (27%-41%), and tricuspid annular plane systolic excursion (13%) (P<0.05 for all), but not right ventricular free wall strain. TNFR1 (tumor necrosis factor receptor 1), UPAR (urokinase plasminogen activator receptor), IGFBP7 (insulin-like growth factor binding protein 7), and GDF-15 (growth differentiation factor-15) were the top individual proteins that mediated the relationship between comorbidity burden and echocardiographic parameters. In the validation cohort, inflammation was upregulated in HFpEF cases versus controls, and the most prominent inflammation protein cluster identified in PROMIS-HFpEF was also present in HFpEF cases (but not controls) in the validation cohort. CONCLUSIONS: Proteins involved in inflammation form a conserved network in HFpEF across 2 independent cohorts and may mediate the association between comorbidity burden and echocardiographic indicators of worse hemodynamics and right ventricular dysfunction. These findings support the comorbidity-inflammation paradigm in HFpEF.

Fully Automated Echocardiogram Interpretation in Clinical Practice.

BACKGROUND: Automated cardiac image interpretation has the potential to transform clinical practice in multiple ways, including enabling serial assessment of cardiac function by nonexperts in primary care and rural settings. We hypothesized that advances in computer vision could enable building a fully automated, scalable analysis pipeline for echocardiogram interpretation, including (1) view identification, (2) image segmentation, (3) quantification of structure and function, and (4) disease detection. METHODS: Using 14 035 echocardiograms spanning a 10-year period, we trained and evaluated convolutional neural network models for multiple tasks, including automated identification of 23 viewpoints and segmentation of cardiac chambers across 5 common views. The segmentation output was used to quantify chamber volumes and left ventricular mass, determine ejection fraction, and facilitate automated determination of longitudinal strain through speckle tracking. Results were evaluated through comparison to manual segmentation and measurements from 8666 echocardiograms obtained during the routine clinical workflow. Finally, we developed models to detect 3 diseases: hypertrophic cardiomyopathy, cardiac amyloid, and pulmonary arterial hypertension. RESULTS: Convolutional neural networks accurately identified views (eg, 96% for parasternal long axis), including flagging partially obscured cardiac chambers, and enabled the segmentation of individual cardiac chambers. The resulting cardiac structure measurements agreed with study report values (eg, median absolute deviations of 15% to 17% of observed values for left ventricular mass, left ventricular diastolic volume, and left atrial volume). In terms of function, we computed automated ejection fraction and longitudinal strain measurements (within 2 cohorts), which agreed with commercial software-derived values (for ejection fraction, median absolute deviation=9.7% of observed, N=6407 studies; for strain, median absolute deviation=7.5%, n=419, and 9.0%, n=110) and demonstrated applicability to serial monitoring of patients with breast cancer for trastuzumab cardiotoxicity. Overall, we found automated measurements to be comparable or superior to manual measurements across 11 internal consistency metrics (eg, the correlation of left atrial and ventricular volumes). Finally, we trained convolutional neural networks to detect hypertrophic cardiomyopathy, cardiac amyloidosis, and pulmonary arterial hypertension with C statistics of 0.93, 0.87, and 0.85, respectively. CONCLUSIONS: Our pipeline lays the groundwork for using automated interpretation to support serial patient tracking and scalable analysis of millions of echocardiograms archived within healthcare systems.

Prevalence and correlates of coronary microvascular dysfunction in heart failure with preserved ejection fraction: PROMIS-HFpEF.

Aims: To date, clinical evidence of microvascular dysfunction in patients with heart failure (HF) with preserved ejection fraction (HFpEF) has been limited. We aimed to investigate the prevalence of coronary microvascular dysfunction (CMD) and its association with systemic endothelial dysfunction, HF severity, and myocardial dysfunction in a well defined, multi-centre HFpEF population. Methods and results: This prospective multinational multi-centre observational study enrolled patients fulfilling strict criteria for HFpEF according to current guidelines. Those with known unrevascularized macrovascular coronary artery disease (CAD) were excluded. Coronary flow reserve (CFR) was measured with adenosine stress transthoracic Doppler echocardiography. Systemic endothelial function [reactive hyperaemia index (RHI)] was measured by peripheral arterial tonometry. Among 202 patients with HFpEF, 151 [75% (95% confidence interval 69-81%)] had CMD (defined as CFR <2.5). Patients with CMD had a higher prevalence of current or prior smoking (70% vs. 43%; P = 0.0006) and atrial fibrillation (58% vs. 25%; P = 0.004) compared with those without CMD. Worse CFR was associated with higher urinary albumin-to-creatinine ratio (UACR) and NTproBNP, and lower RHI, tricuspid annular plane systolic excursion, and right ventricular (RV) free wall strain after adjustment for age, sex, body mass index, atrial fibrillation, diabetes, revascularized CAD, smoking, left ventricular mass, and study site (P < 0.05 for all associations). Conclusions: PROMIS-HFpEF is the first prospective multi-centre, multinational study to demonstrate a high prevalence of CMD in HFpEF in the absence of unrevascularized macrovascular CAD, and to show its association with systemic endothelial dysfunction (RHI, UACR) as well as markers of HF severity (NTproBNP and RV dysfunction). Microvascular dysfunction may be a promising therapeutic target in HFpEF.