Coronary Microvascular Function Following Severe Preeclampsia

BACKGROUND

Preeclampsia is a pregnancy-specific hypertensive disorder associated with an imbalance in circulating proangiogenic and antiangiogenic proteins. Preclinical evidence implicates microvascular dysfunction as a potential mediator of preeclampsia-associated cardiovascular risk.

METHODS

Women with singleton pregnancies complicated by severe antepartum-onset preeclampsia and a comparator group with normotensive deliveries underwent cardiac positron emission tomography within 4 weeks of delivery. A control group of premenopausal, nonpostpartum women was also included. Myocardial flow reserve, myocardial blood flow, and coronary vascular resistance were compared across groups. sFlt-1 (soluble fms-like tyrosine kinase receptor-1) and PlGF (placental growth factor) were measured at imaging.

RESULTS

The primary cohort included 19 women with severe preeclampsia (imaged at a mean of 15.3 days postpartum), 5 with normotensive pregnancy (mean, 14.4 days postpartum), and 13 nonpostpartum female controls. Preeclampsia was associated with lower myocardial flow reserve (β, -0.67 [95% CI, -1.21 to -0.13]; P=0.016), lower stress myocardial blood flow (β, -0.68 [95% CI, -1.07 to -0.29] mL/min per g; P=0.001), and higher stress coronary vascular resistance (β, +12.4 [95% CI, 6.0 to 18.7] mm Hg/mL per min/g; P=0.001) versus nonpostpartum controls. Myocardial flow reserve and coronary vascular resistance after normotensive pregnancy were intermediate between preeclamptic and nonpostpartum groups. Following preeclampsia, myocardial flow reserve was positively associated with time following delivery (P=0.008). The sFlt-1/PlGF ratio strongly correlated with rest myocardial blood flow (r=0.71; P<0.001), independent of hemodynamics.

CONCLUSIONS

In this exploratory cross-sectional study, we observed reduced coronary microvascular function in the early postpartum period following preeclampsia, suggesting that systemic microvascular dysfunction in preeclampsia involves coronary microcirculation. Further research is needed to establish interventions to mitigate the risk of preeclampsia-associated cardiovascular disease.

Similar enzymatic functions in distinct bioluminescence systems: Evolutionary recruitment of sulfotransferases in ostracod light organs

Genes from ancient families are sometimes involved in the convergent evolutionary origins of similar traits, even across vast phylogenetic distances. Sulfotransferases are an ancient family of enzymes that transfer sulfate from a donor to a wide variety of substrates, including probable roles in some bioluminescence systems. Here we demonstrate multiple sulfotransferases, highly expressed in light organs of the bioluminescent ostracod Vargula tsujii , transfer sulfate in vivo to the luciferin substrate, vargulin. We find luciferin sulfotransferases of ostracods are not orthologous to known luciferin sulfotransferases of fireflies or sea pansies; animals with distinct and convergently evolved bioluminescence systems compared to ostracods. Therefore, distantly related sulfotransferases were independently recruited at least three times, leading to parallel evolution of luciferin metabolism in three highly diverged organisms. Re-use of homologous genes is surprising in these bioluminescence systems because the other components, including luciferins and luciferases, are completely distinct. Whether convergently evolved traits incorporate ancient genes with similar functions or instead use distinct, often newer, genes may be constrained by how many genetic solutions exist for a particular function. When fewer solutions exist, as in genetic sulfation of small molecules, evolution may be more constrained to use the same genes time and again.

Coronary Microvascular Function Following Severe Preeclampsia

Background

Preeclampsia is a pregnancy-specific hypertensive disorder associated with an imbalance in circulating pro- and anti-angiogenic proteins. Preclinical evidence implicates microvascular dysfunction as a potential mediator of preeclampsia-associated cardiovascular risk.

Methods

Women with singleton pregnancies complicated by severe antepartum-onset preeclampsia and a comparator group with normotensive deliveries underwent cardiac positron emission tomography (PET) within 4 weeks of delivery. A control group of pre-menopausal, non-postpartum women was also included. Myocardial flow reserve (MFR), myocardial blood flow (MBF), and coronary vascular resistance (CVR) were compared across groups. Soluble fms-like tyrosine kinase receptor-1 (sFlt-1) and placental growth factor (PlGF) were measured at imaging.

Results

The primary cohort included 19 women with severe preeclampsia (imaged at a mean 16.0 days postpartum), 5 with normotensive pregnancy (mean 14.4 days postpartum), and 13 non-postpartum female controls. Preeclampsia was associated with lower MFR (β=-0.67 [95% CI -1.21 to -0.13]; P=0.016), lower stress MBF (β=-0.68 [95% CI, -1.07 to -0.29] mL/min/g; P=0.001), and higher stress CVR (β=+12.4 [95% CI 6.0 to 18.7] mmHg/mL/min/g; P=0.001) vs. non-postpartum controls. MFR and CVR after normotensive pregnancy were intermediate between preeclamptic and non-postpartum groups. Following preeclampsia, MFR was positively associated with time following delivery (P=0.008). The sFlt-1/PlGF ratio strongly correlated with rest MBF (r=0.71; P<0.001), independent of hemodynamics.

Conclusions

In this exploratory study, we observed reduced coronary microvascular function in the early postpartum period following severe preeclampsia, suggesting that systemic microvascular dysfunction in preeclampsia involves the coronary microcirculation. Further research is needed to establish interventions to mitigate risk of preeclampsia-associated cardiovascular disease.

Genetic Associations of Circulating Cardiovascular Proteins With Gestational Hypertension and Preeclampsia

Importance

Hypertensive disorders of pregnancy (HDPs), including gestational hypertension and preeclampsia, are important contributors to maternal morbidity and mortality worldwide. In addition, women with HDPs face an elevated long-term risk of cardiovascular disease.

Objective

To identify proteins in the circulation associated with HDPs.

Design, Setting, and Participants

Two-sample mendelian randomization (MR) tested the associations of genetic instruments for cardiovascular disease-related proteins with gestational hypertension and preeclampsia. In downstream analyses, a systematic review of observational data was conducted to evaluate the identified proteins' dynamics across gestation in hypertensive vs normotensive pregnancies, and phenome-wide MR analyses were performed to identify potential non-HDP-related effects associated with the prioritized proteins. Genetic association data for cardiovascular disease-related proteins were obtained from the Systematic and Combined Analysis of Olink Proteins (SCALLOP) consortium. Genetic association data for the HDPs were obtained from recent European-ancestry genome-wide association study meta-analyses for gestational hypertension and preeclampsia. Study data were analyzed October 2022 to October 2023.

Exposures

Genetic instruments for 90 candidate proteins implicated in cardiovascular diseases, constructed using cis-protein quantitative trait loci (cis-pQTLs).

Main Outcomes and Measures

Gestational hypertension and preeclampsia.

Results

Genetic association data for cardiovascular disease-related proteins were obtained from 21 758 participants from the SCALLOP consortium. Genetic association data for the HDPs were obtained from 393 238 female individuals (8636 cases and 384 602 controls) for gestational hypertension and 606 903 female individuals (16 032 cases and 590 871 controls) for preeclampsia. Seventy-five of 90 proteins (83.3%) had at least 1 valid cis-pQTL. Of those, 10 proteins (13.3%) were significantly associated with HDPs. Four were robust to sensitivity analyses for gestational hypertension (cluster of differentiation 40, eosinophil cationic protein [ECP], galectin 3, N-terminal pro-brain natriuretic peptide [NT-proBNP]), and 2 were robust for preeclampsia (cystatin B, heat shock protein 27 [HSP27]). Consistent with the MR findings, observational data revealed that lower NT-proBNP (0.76- to 0.88-fold difference vs no HDPs) and higher HSP27 (2.40-fold difference vs no HDPs) levels during the first trimester of pregnancy were associated with increased risk of HDPs, as were higher levels of ECP (1.60-fold difference vs no HDPs). Phenome-wide MR analyses identified 37 unique non-HDP-related protein-disease associations, suggesting potential on-target effects associated with interventions lowering HDP risk through the identified proteins.

Conclusions and Relevance

Study findings suggest genetic associations of 4 cardiovascular disease-related proteins with gestational hypertension and 2 associated with preeclampsia. Future studies are required to test the efficacy of targeting the corresponding pathways to reduce HDP risk.

Infertility and Subclinical Antecedents of Heart Failure With Preserved Ejection Fraction in the Framingham Heart Study

BACKGROUND

Infertility has been shown to be associated with a greater risk of incident heart failure with preserved ejection fraction. We studied the association of infertility with subclinical markers of heart failure with preserved ejection fraction, including echocardiographic signs of cardiac remodeling and cardiac biomarkers.

METHODS AND RESULTS

A history of infertility was ascertained in 2002 women enrolled in the Framingham Heart Study. We examined the association of infertility with echocardiographic measures and cardiac biomarkers with multivariable-adjusted linear regression models. Among 2002 women (mean age 40.84 ± 9.71 years), 285 (14%) reported a history of infertility. Infertility was associated with a greater E/e' ratio (β = 0.120, standard error 0.057, P = .04), even after adjustment for common confounders. Infertility was not associated with other echocardiographic measures or cardiac biomarkers.

CONCLUSIONS

Infertility was associated with a greater E/e' ratio, a marker of diastolic dysfunction that may signal earlier subclinical cardiac remodeling in women with infertility.

Natural Language Processing for Adjudication of Heart Failure in a Multicenter Clinical Trial: A Secondary Analysis of a Randomized Clinical Trial

Importance

The gold standard for outcome adjudication in clinical trials is medical record review by a physician clinical events committee (CEC), which requires substantial time and expertise. Automated adjudication of medical records by natural language processing (NLP) may offer a more resource-efficient alternative but this approach has not been validated in a multicenter setting.

Objective

To externally validate the Community Care Cohort Project (C3PO) NLP model for heart failure (HF) hospitalization adjudication, which was previously developed and tested within one health care system, compared to gold-standard CEC adjudication in a multicenter clinical trial.

Design, Setting, and Participants

This was a retrospective analysis of the Influenza Vaccine to Effectively Stop Cardio Thoracic Events and Decompensated Heart Failure (INVESTED) trial, which compared 2 influenza vaccines in 5260 participants with cardiovascular disease at 157 sites in the US and Canada between September 2016 and January 2019. Analysis was performed from November 2022 to October 2023.

Exposures

Individual sites submitted medical records for each hospitalization. The central INVESTED CEC and the C3PO NLP model independently adjudicated whether the cause of hospitalization was HF using the prepared hospitalization dossier. The C3PO NLP model was fine-tuned (C3PO + INVESTED) and a de novo NLP model was trained using half the INVESTED hospitalizations.

Main Outcomes and Measures

Concordance between the C3PO NLP model HF adjudication and the gold-standard INVESTED CEC adjudication was measured by raw agreement, κ, sensitivity, and specificity. The fine-tuned and de novo INVESTED NLP models were evaluated in an internal validation cohort not used for training.

Results

Among 4060 hospitalizations in 1973 patients (mean [SD] age, 66.4 [13.2] years; 514 [27.4%] female and 1432 [72.6%] male]), 1074 hospitalizations (26%) were adjudicated as HF by the CEC. There was good agreement between the C3PO NLP and CEC HF adjudications (raw agreement, 87% [95% CI, 86-88]; κ, 0.69 [95% CI, 0.66-0.72]). C3PO NLP model sensitivity was 94% (95% CI, 92-95) and specificity was 84% (95% CI, 83-85). The fine-tuned C3PO and de novo NLP models demonstrated agreement of 93% (95% CI, 92-94) and κ of 0.82 (95% CI, 0.77-0.86) and 0.83 (95% CI, 0.79-0.87), respectively, vs the CEC. CEC reviewer interrater reproducibility was 94% (95% CI, 93-95; κ, 0.85 [95% CI, 0.80-0.89]).

Conclusions and Relevance

The C3PO NLP model developed within 1 health care system identified HF events with good agreement relative to the gold-standard CEC in an external multicenter clinical trial. Fine-tuning the model improved agreement and approximated human reproducibility. Further study is needed to determine whether NLP will improve the efficiency of future multicenter clinical trials by identifying clinical events at scale.

A disease of her own? Unique features of heart failure in women

Heart failure (HF) is a significant and growing public health challenge for women. Compared with men, women tend to develop HF later in life and are more likely to experience HF with preserved ejection fraction. There are also significant sex differences in outcomes, with women reporting lower quality of life but overall better survival versus men. In this review, we summarize sex differences in traditional HF risk factors, such as hypertension, diabetes, obesity and coronary artery disease, as well as female-specific HF risk factors including menopause, pregnancy and adverse pregnancy outcomes, and breast cancer therapy. While our understanding of the sex-specific efficacy of HF therapy remains limited by the underrepresentation of women in major clinical trials, there is a suggestion of preferential benefit of specific agents for women. Further work is required to better understand the pathophysiology of HF in women uniquely and to increase representation of women in clinical trials.

Maternal Cardiovascular Health Post-Dobbs

Maternal Cardiovascular Health Post-DobbsPregnancy is associated with increasing morbidity and mortality in the United States. In the post-Dobbs era, many pregnant patients at highest risk no longer have access to abortion, which has been a crucial component of standard medical care.

Circulating extracellular vesicles in human cardiorenal syndrome promote renal injury in a kidney-on-chip system

BACKGROUNDCardiorenal syndrome (CRS) - renal injury during heart failure (HF) - is linked to high morbidity. Whether circulating extracellular vesicles (EVs) and their RNA cargo directly impact its pathogenesis remains unclear.METHODSWe investigated the role of circulating EVs from patients with CRS on renal epithelial/endothelial cells using a microfluidic kidney-on-chip (KOC) model. The small RNA cargo of circulating EVs was regressed against serum creatinine to prioritize subsets of functionally relevant EV-miRNAs and their mRNA targets investigated using in silico pathway analysis, human genetics, and interrogation of expression in the KOC model and in renal tissue. The functional effects of EV-RNAs on kidney epithelial cells were experimentally validated.RESULTSRenal epithelial and endothelial cells in the KOC model exhibited uptake of EVs from patients with HF. HF-CRS EVs led to higher expression of renal injury markers (IL18, LCN2, HAVCR1) relative to non-CRS EVs. A total of 15 EV-miRNAs were associated with creatinine, targeting 1,143 gene targets specifying pathways relevant to renal injury, including TGF-β and AMPK signaling. We observed directionally consistent changes in the expression of TGF-β pathway members (BMP6, FST, TIMP3) in the KOC model exposed to CRS EVs, which were validated in epithelial cells treated with corresponding inhibitors and mimics of miRNAs. A similar trend was observed in renal tissue with kidney injury. Mendelian randomization suggested a role for FST in renal function.CONCLUSIONPlasma EVs in patients with CRS elicit adverse transcriptional and phenotypic responses in a KOC model by regulating biologically relevant pathways, suggesting a role for EVs in CRS.TRIAL REGISTRATIONClinicalTrials.gov NCT03345446.FUNDINGAmerican Heart Association (AHA) (SFRN16SFRN31280008); National Heart, Lung, and Blood Institute (1R35HL150807-01); National Center for Advancing Translational Sciences (UH3 TR002878); and AHA (23CDA1045944).

Eicosanoid and eicosanoid-related inflammatory mediators and exercise intolerance in heart failure with preserved ejection fraction

Systemic inflammation has been implicated in the pathobiology of heart failure with preserved ejection fraction (HFpEF). Here, we examine the association of upstream mediators of inflammation as ascertained by fatty-acid derived eicosanoid and eicosanoid-related metabolites with HFpEF status and exercise manifestations of HFpEF. Among 510 participants with chronic dyspnea and preserved LVEF who underwent invasive cardiopulmonary exercise testing, we find that 70 of 890 eicosanoid and related metabolites are associated with HFpEF status, including 17 named and 53 putative eicosanoids (FDR q-value < 0.1). Prostaglandin (15R-PGF2α, 11ß-dhk-PGF2α) and linoleic acid derivatives (12,13 EpOME) are associated with greater odds of HFpEF, while epoxides (8(9)-EpETE), docosanoids (13,14-DiHDPA), and oxylipins (12-OPDA) are associated with lower odds of HFpEF. Among 70 metabolites, 18 are associated with future development of heart failure in the community. Pro- and anti-inflammatory eicosanoid and related metabolites may contribute to the pathogenesis of HFpEF and serve as potential targets for intervention.

Deep Learning-Enabled Assessment of Left Heart Structure and Function Predicts Cardiovascular Outcomes

BACKGROUND

Deep learning interpretation of echocardiographic images may facilitate automated assessment of cardiac structure and function.

OBJECTIVES

We developed a deep learning model to interpret echocardiograms and examined the association of deep learning-derived echocardiographic measures with incident outcomes.

METHODS

We trained and validated a 3-dimensional convolutional neural network model for echocardiographic view classification and quantification of left atrial dimension, left ventricular wall thickness, chamber diameter, and ejection fraction. The training sample comprised 64,028 echocardiograms (n = 27,135) from a retrospective multi-institutional ambulatory cardiology electronic health record sample. Validation was performed in a separate longitudinal primary care sample and an external health care system data set. Cox models evaluated the association of model-derived left heart measures with incident outcomes.

RESULTS

Deep learning discriminated echocardiographic views (area under the receiver operating curve >0.97 for parasternal long axis, apical 4-chamber, and apical 2-chamber views vs human expert annotation) and quantified standard left heart measures (R2 range = 0.53 to 0.91 vs study report values). Model performance was similar in 2 external validation samples. Model-derived left heart measures predicted incident heart failure, atrial fibrillation, myocardial infarction, and death. A 1-SD lower model-left ventricular ejection fraction was associated with 43% greater risk of heart failure (HR: 1.43; 95% CI: 1.23-1.66) and 17% greater risk of death (HR: 1.17; 95% CI: 1.06-1.30). Similar results were observed for other model-derived left heart measures.

CONCLUSIONS

Deep learning echocardiographic interpretation accurately quantified standard measures of left heart structure and function, which in turn were associated with future clinical outcomes. Deep learning may enable automated echocardiogram interpretation and disease prediction at scale.

Obesity-Related Biomarkers Are Associated With Exercise Intolerance and HFpEF

BACKGROUND

Obesity and adiposity are associated with an increased risk of heart failure with preserved ejection fraction (HFpEF); yet, specific underlying mechanisms remain unclear. We sought to examine the association of obesity-related biomarkers including adipokines (leptin, resistin, adiponectin), inflammatory markers (CRP [C-reactive protein], IL-6 [interleukin-6]), and insulin resistance (HOMA-IR) with HFpEF status, exercise capacity, and cardiovascular outcomes.

METHODS

We studied 509 consecutive patients with left ventricular ejection fraction ≥50% and chronic dyspnea, who underwent clinically indicated cardiopulmonary exercise test with invasive hemodynamic monitoring between 2006 and 2017. We defined HFpEF based on the presence of elevated left ventricular filling pressures at rest or during exercise. Fasting blood samples collected at the time of the cardiopulmonary exercise test were used to assay obesity-related biomarkers. We examined the association of log-transformed biomarkers with HFpEF status and exercise traits using multivariable-adjusted logistic regression models.

RESULTS

We observed associations of obesity-related biomarkers with measures of impaired exercise capacity including peak VO2 (P≤0.002 for all biomarkers). The largest effect size was seen with leptin, where a 1-SD higher leptin was associated with a 2.35 mL/kg per min lower peak VO2 (β, -2.35±0.19; P<0.001). In addition, specific biomarkers were associated with distinct measures of exercise reserve including blood pressure (homeostatic model assessment of insulin resistance, leptin, adiponectin; P≤0.002 for all), and chronotropic response (CRP, IL-6, homeostatic model assessment of insulin resistance, leptin, and resistin; P<0.05 for all). Our findings suggest that among the obesity-related biomarkers studied, higher levels of leptin and CRP are independently associated with increased odds of HFpEF, with odds ratios of 1.36 (95% CI, 1.09-1.70) and 1.25 (95% CI, 1.03-1.52), respectively.

CONCLUSIONS

Specific obesity-related pathways including inflammation, adipokine signaling, and insulin resistance may underlie the association of obesity with HFpEF and exercise intolerance.

The association of eicosanoids and eicosanoid-related metabolites with pulmonary hypertension

BACKGROUND

Eicosanoids are bioactive lipids that regulate systemic inflammation and exert vasoactive effects. Specific eicosanoid metabolites have previously been associated with pulmonary hypertension (PH), yet their role remains incompletely understood.

METHODS

We studied 482 participants with chronic dyspnoea who underwent clinically indicated cardiopulmonary exercise testing (CPET) with invasive haemodynamic monitoring. We performed comprehensive profiling of 888 eicosanoids and eicosanoid-related metabolites using directed non-targeted mass spectrometry, and examined associations with PH (mean pulmonary arterial pressure (mPAP) >20 mmHg), PH subtypes and physiological correlates, including transpulmonary metabolite gradients.

RESULTS

Among 482 participants (mean±sd age 56±16 years, 62% women), 200 had rest PH. We found 48 eicosanoids and eicosanoid-related metabolites that were associated with PH. Specifically, prostaglandin (11β-dhk-PGF2α), linoleic acid (12,13-EpOME) and arachidonic acid derivatives (11,12-DiHETrE) were associated with higher odds of PH (false discovery rate q<0.05 for all). By contrast, epoxide (8(9)-EpETE), α-linolenic acid (13(S)-HOTrE(γ)) and lipokine derivatives (12,13-DiHOME) were associated with lower odds. Among PH-related eicosanoids, 14 showed differential transpulmonary metabolite gradients, with directionality suggesting that metabolites associated with lower odds of PH also displayed pulmonary artery uptake. In individuals with exercise PH, eicosanoid profiles were intermediate between no PH and rest PH, with six metabolites that differed between rest and exercise PH.

CONCLUSIONS

Our findings highlight the role of specific eicosanoids, including linoleic acid and epoxide derivatives, as potential regulators of inflammation in PH. Of note, physiological correlates, including transpulmonary metabolite gradients, may prioritise future studies focused on eicosanoid-related pathways as important contributors to PH pathogenesis.

Aging and Vascular Disease: A Multidisciplinary Overview

Vascular aging, i.e., the deterioration of the structure and function of the arteries over the life course, predicts cardiovascular events and mortality. Vascular degeneration can be recognized before becoming clinically symptomatic; therefore, its assessment allows the early identification of individuals at risk. This opens the possibility of minimizing disease progression. To review these issues, a search was completed using PubMed, MEDLINE, and Google Scholar from 2000 to date. As a network of clinicians and scientists involved in vascular medicine, we here describe the structural and functional age-dependent alterations of the arteries, the clinical tools for an early diagnosis of vascular aging, and the cellular and molecular events implicated. It emerges that more studies are necessary to identify the best strategy to quantify vascular aging, and to design proper physical activity programs, nutritional and pharmacological strategies, as well as social interventions to prevent, delay, and eventually revert the disease.

Natural Language Processing for Adjudication of Heart Failure Hospitalizations in a Multi-Center Clinical Trial

Background

The gold standard for outcome adjudication in clinical trials is chart review by a physician clinical events committee (CEC), which requires substantial time and expertise. Automated adjudication by natural language processing (NLP) may offer a more resource-efficient alternative. We previously showed that the Community Care Cohort Project (C3PO) NLP model adjudicates heart failure (HF) hospitalizations accurately within one healthcare system.

Methods

This study externally validated the C3PO NLP model against CEC adjudication in the INVESTED trial. INVESTED compared influenza vaccination formulations in 5260 patients with cardiovascular disease at 157 North American sites. A central CEC adjudicated the cause of hospitalizations from medical records. We applied the C3PO NLP model to medical records from 4060 INVESTED hospitalizations and evaluated agreement between the NLP and final consensus CEC HF adjudications. We then fine-tuned the C3PO NLP model (C3PO+INVESTED) and trained a de novo model using half the INVESTED hospitalizations, and evaluated these models in the other half. NLP performance was benchmarked to CEC reviewer inter-rater reproducibility.

Results

1074 hospitalizations (26%) were adjudicated as HF by the CEC. There was high agreement between the C3PO NLP and CEC HF adjudications (agreement 87%, kappa statistic 0.69). C3PO NLP model sensitivity was 94% and specificity was 84%. The fine-tuned C3PO and de novo NLP models demonstrated agreement of 93% and kappa of 0.82 and 0.83, respectively. CEC reviewer inter-rater reproducibility was 94% (kappa 0.85).

Conclusion

Our NLP model developed within a single healthcare system accurately identified HF events relative to the gold-standard CEC in an external multi-center clinical trial. Fine-tuning the model improved agreement and approximated human reproducibility. NLP may improve the efficiency of future multi-center clinical trials by accurately identifying clinical events at scale.

Protein Biomarkers of Early Menopause and Incident Cardiovascular Disease

Background Premature and early menopause are independently associated with greater risk of cardiovascular disease (CVD). However, mechanisms linking age of menopause with CVD remain poorly characterized. Methods and Results We measured 71 circulating CVD protein biomarkers in 1565 postmenopausal women enrolled in the FHS (Framingham Heart Study). We examined the association of early menopause with biomarkers and tested whether early menopause modified the association of biomarkers with incident cardiovascular outcomes (heart failure, major CVD, and all-cause death) using multivariable-adjusted linear regression and Cox models, respectively. Among 1565 postmenopausal women included (mean age 62 years), 395 (25%) had a history of early menopause. Of 71 biomarkers examined, we identified 7 biomarkers that were significantly associated with early menopause, of which 5 were higher in women with early menopause including adrenomedullin and resistin, and 2 were higher in women without early menopause including insulin growth factor-1 and CNTN1 (contactin-1) (Benjamini-Hochberg adjusted P<0.1 for all). Early menopause also modified the association of specific biomarkers with incident cardiovascular outcomes including adrenomedullin (Pint<0.05). Conclusions Early menopause is associated with circulating levels of CVD protein biomarkers and appears to modify the association between select biomarkers with incident cardiovascular outcomes. Identified biomarkers reflect several distinct biological pathways, including inflammation, adiposity, and neurohormonal regulation. Further investigation of these pathways may provide mechanistic insights into the pathogenesis, prevention, and treatment of early menopause-associated CVD.

Genetic Susceptibility to Atrial Fibrillation Identified via Deep Learning of 12-Lead Electrocardiograms

BACKGROUND

Artificial intelligence (AI) models applied to 12-lead ECG waveforms can predict atrial fibrillation (AF), a heritable and morbid arrhythmia. However, the factors forming the basis of risk predictions from AI models are usually not well understood. We hypothesized that there might be a genetic basis for an AI algorithm for predicting the 5-year risk of new-onset AF using 12-lead ECGs (ECG-AI)-based risk estimates.

METHODS

We applied a validated ECG-AI model for predicting incident AF to ECGs from 39 986 UK Biobank participants without AF. We then performed a genome-wide association study (GWAS) of the predicted AF risk and compared it with an AF GWAS and a GWAS of risk estimates from a clinical variable model.

RESULTS

In the ECG-AI GWAS, we identified 3 signals (P<5×10-8) at established AF susceptibility loci marked by the sarcomeric gene TTN and sodium channel genes SCN5A and SCN10A. We also identified 2 novel loci near the genes VGLL2 and EXT1. In contrast, the clinical variable model prediction GWAS indicated a different genetic profile. In genetic correlation analysis, the prediction from the ECG-AI model was estimated to have a higher correlation with AF than that from the clinical variable model.

CONCLUSIONS

Predicted AF risk from an ECG-AI model is influenced by genetic variation implicating sarcomeric, ion channel and body height pathways. ECG-AI models may identify individuals at risk for disease via specific biological pathways.

Multiple Prior Live Births Are Associated With Cardiac Remodeling and Heart Failure Risk in Women

OBJECTIVE

Greater parity has been associated with cardiovascular disease risk. We sought to find whether the effects on cardiac remodeling and heart failure risk are clear.

METHODS

We examined the association of number of live births with echocardiographic measures of cardiac structure and function in participants of the Framingham Heart Study (FHS) using multivariable linear regression. We next examined the association of parity with incident heart failure with preserved (HFpEF) or reduced (HFrEF) ejection fraction using a Fine-Gray subdistribution hazards model in a pooled analysis of n = 12,635 participants in the FHS, the Cardiovascular Health Study, the Multi-Ethnic Study of Atherosclerosis, and Prevention of Renal and Vascular Endstage Disease. Secondary analyses included major cardiovascular disease, myocardia infarction and stroke.

RESULTS

Among n = 3931 FHS participants (mean age 48 ± 13 years), higher numbers of live births were associated with worse left ventricular fractional shortening (multivariable β -1.11 (0.31); P = 0.0005 in ≥ 5 live births vs nulliparous women) and worse cardiac mechanics, including global circumferential strain and longitudinal and radial dyssynchrony (P < 0.01 for all comparing ≥ 5 live births vs nulliparity). When examining HF subtypes, women with ≥ 5 live births were at higher risk of developing future HFrEF compared with nulliparous women (HR 1.93, 95% CI 1.19-3.12; P = 0.008); by contrast, a lower risk of HFpEF was observed (HR 0.58, 95% CI 0.37-0.91; P = 0.02).

CONCLUSIONS

Greater numbers of live births are associated with worse cardiac structure and function. There was no association with overall HF, but a higher number of live births was associated with greater risk for incident HFrEF.

Effect of 2022 ACC/AHA/HFSA Criteria on Stages of Heart Failure in a Pooled Community Cohort

BACKGROUND

The 2022 American College of Cardiology (ACC)/American Heart Association (AHA)/Heart Failure Society of America (HFSA) clinical practice guideline proposed an updated definition for heart failure (HF) stages.

OBJECTIVES

This study aimed to compare prevalence and prognosis of HF stages according to classification/definition originally described in 2013 and 2022 ACC/AHA/HFSA definitions.

METHODS

Study participants from 3 longitudinal cohorts (the MESA [Multi-Ethnic Study of Atherosclerosis], CHS [Cardiovascular Health Study], and the FHS [Framingham Heart Study]), were categorized into 4 HF stages according to the 2013 and 2022 criteria. Cox proportional hazards regression was used to assess predictors of progression to symptomatic HF and adverse clinical outcomes associated with each HF stage.

RESULTS

Among 11,618 study participants, according to the 2022 staging, 1,943 (16.7%) were healthy, 4,348 (37.4%) were in stage A (at risk), 5,019 (43.2%) were in stage B (pre-HF), and 308 (2.7%) were in stage C/D (symptomatic HF). Compared to the classification/definition originally described in 2013, the 2022 ACC/AHA/HFSA approach resulted in a higher proportion of individuals with stage B HF (increase from 15.9% to 43.2%); this shift disproportionately involved women as well as Hispanic and Black individuals. Despite the 2022 criteria designating a greater proportion of individuals as stage B, the relative risk of progression to symptomatic HF remained similar (HR: 10.61; 95% CI: 9.00-12.51; P < 0.001).

CONCLUSIONS

New standards for HF staging resulted in a substantial shift of community-based individuals from stage A to stage B. Those with stage B HF in the new system were at high risk for progression to symptomatic HF.

Assessment of valvular function in over 47,000 people using deep learning-based flow measurements

Valvular heart disease is associated with a high global burden of disease. Even mild aortic stenosis confers increased morbidity and mortality, prompting interest in understanding normal variation in valvular function at scale. We developed a deep learning model to study velocity-encoded magnetic resonance imaging in 47,223 UK Biobank participants. We calculated eight traits, including peak velocity, mean gradient, aortic valve area, forward stroke volume, mitral and aortic regurgitant volume, greatest average velocity, and ascending aortic diameter. We then computed sex-stratified reference ranges for these phenotypes in up to 31,909 healthy individuals. In healthy individuals, we found an annual decrement of 0.03cm ² in the aortic valve area. Participants with mitral valve prolapse had a 1 standard deviation [SD] higher mitral regurgitant volume (P=9.6 × 10 ^-12 ), and those with aortic stenosis had a 4.5 SD-higher mean gradient (P=1.5 × 10 ^-431 ), validating the derived phenotypes' associations with clinical disease. Greater levels of ApoB, triglycerides, and Lp(a) assayed nearly 10 years prior to imaging were associated with higher gradients across the aortic valve. Metabolomic profiles revealed that increased glycoprotein acetyls were also associated with an increased aortic valve mean gradient (0.92 SD, P=2.1 x 10 ^-22 ). Finally, velocity-derived phenotypes were risk markers for aortic and mitral valve surgery even at thresholds below what is considered relevant disease currently. Using machine learning to quantify the rich phenotypic data of the UK Biobank, we report the largest assessment of valvular function and cardiovascular disease in the general population.

Sex Differences in Extensive Mitral Annular Calcification With Associated Mitral Valve Dysfunction

Mitral annular calcification (MAC)-related mitral valve (MV) dysfunction is an increasingly recognized entity, which confers a high burden of morbidity and mortality. Although more common among women, there is a paucity of data regarding how the phenotype of MAC and the associated adverse clinical implications may differ between women and men. A total of 3,524 patients with extensive MAC and significant MAC-related MV dysfunction (i.e., transmitral gradient ≥3 mm Hg) were retrospectively analyzed from a large institutional database, with the goal of defining gender differences in clinical and echocardiographic characteristics and the prognostic importance of MAC-related MV dysfunction. We stratified patients into low- (3 to 5 mm Hg), moderate- (5 to 10 mm Hg), and high- (≥10 mm Hg) gradient groups and analyzed the gender differences in phenotype and outcome. The primary outcome was all-cause mortality, assessed using adjusted Cox regression models. Women represented the majority (67%) of subjects, were older (79.3 ± 10.4 vs 75.5 ± 10.9 years, p <0.001) and had a lower burden of cardiovascular co-morbidities than men. Women had higher transmitral gradients (5.7 ± 2.7 vs 5.3 ± 2.6 mm Hg, p <0.001), more concentric hypertrophy (49% vs 33%), and more mitral regurgitation. The median survival was 3.4 years (95% confidence interval 3.0 to 3.6) among women and 3.0 years (95% confidence interval 2.6 to 4.5) among men. The adjusted survival was worse among men, and the prognostic impact of the transmitral gradient did not differ overall by gender. In conclusion, we describe important gender differences among patients with MAC-related MV dysfunction and show worse adjusted survival among men; although, the adverse prognostic impact of the transmitral gradient was similar between men and women.

Association of Initial and Longitudinal Changes in C-reactive Protein With the Risk of Cardiovascular Disease, Cancer, and Mortality

OBJECTIVE

To evaluate the value of serial C-reactive protein (CRP) measurements in predicting the risk of cardiovascular disease (CVD), cancer, and mortality.

METHODS

The analysis was performed using data from two prospective, population-based observational cohorts: the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study and the Framingham Heart Study (FHS). A total of 9253 participants had CRP measurements available at two examinations (PREVEND: 1997-1998 and 2001-2002; FHS Offspring cohort: 1995-1998 and 1998-2001). All CRP measurements were natural log-transformed before analyses. Cardiovascular disease included fatal and nonfatal cardiovascular, cerebrovascular and peripheral vascular events, and heart failure. Cancer included all malignancies except nonmelanoma skin cancers.

RESULTS

The mean age of the study population at baseline was 52.4±12.1 years and 51.2% (n=4733) were women. Advanced age, female sex, smoking, body mass index, and total cholesterol were associated with greater increases in CRP levels over time (Pall<.001 in the multivariable model). Baseline CRP, as well as increase in CRP over time (ΔCRP), were associated with incident CVD (hazard ratio [HR]: 1.29 per 1-SD increase; 95% confidence interval [CI]: 1.29 to 1.47, and HR per 1-SD increase: 1.19; 95% CI: 1.09 to 1.29 respectively). Similar findings were observed for incident cancer (baseline CRP, HR: 1.17; 95% CI: 1.09 to 1.26; ΔCRP, HR: 1.08; 95% CI: 1.01 to 1.15) and mortality (baseline CRP, HR: 1.29; 95% CI: 1.21 to 1.37; ΔCRP, HR: 1.10; 95% CI: 1.05 to 1.16).

CONCLUSION

Initial as well as subsequent increases in CRP levels predict future CVD, cancer, and mortality in the general population.

Family History of Modifiable Risk Factors and Association With Future Cardiovascular Disease

Background A parental history of cardiovascular disease (CVD) confers greater risk of future CVD among offspring. Whether the presence of parental modifiable risk factors contribute to or modify CVD risk in offspring is unclear. Methods and Results We studied 6278 parent-child trios in the multigenerational longitudinal Framingham Heart Study. We assessed parental history of CVD and modifiable risk factors (smoking, hypertension, diabetes, obesity, and hyperlipidemia). Multivariable Cox models were used to evaluate the association of parental history and future CVD among offspring. Among 6278 individuals (mean age 45±11 years), 44% had at least 1 parent with history of CVD. Over a median follow-up of 15 years, 353 major CVD events occurred among offspring. Parental history of CVD conferred 1.7-fold increased hazard of future CVD (hazard ratio [HR], 1.71 [95% CI, 1.33-2.21]). Parental obesity and smoking status were associated with higher hazard of future CVD (obesity: HR, 1.32 [95% CI, 1.06-1.64]; smoking: HR, 1.34 [95% CI, 1.07-1.68], attenuated after adjusting for offspring smoking status). By contrast, parental history of hypertension, diabetes, and hypercholesterolemia were not associated with future CVD in offspring (P>0.05 for all). Furthermore, parental risk factors did not modify the association of parental CVD history on future offspring CVD risk. Conclusions Parental history of obesity and smoking were associated with a higher hazard of future CVD in offspring. By contrast, other parental modifiable risk factors did not alter offspring CVD risk. In addition to parental CVD, the presence of parental obesity should prompt a focus on disease prevention.

A Women in Medicine Trainees' Council: a model for women trainee professional development

Women physicians are promoted less often, more likely to experience harassment and bias, and paid less than their male peers. Although many institutions have developed initiatives to help women physicians overcome these professional hurdles, few are specifically geared toward physicians-in-training. The Women in Medicine Trainees' Council (WIMTC) was created in 2015 to support the professional advancement of women physicians-in-training in the Massachusetts General Hospital Department of Medicine (MGH-DOM). In a 2021 survey, the majority of respondents agreed that the WIMTC ameliorated the challenges of being a woman physician-in-training and contributed positively to overall wellness. Nearly all agreed that they would advise other training programs to implement a similar program. We present our model for women-trainee support to further the collective advancement of women physicians.

Rethinking Menopausal Hormone Therapy: For Whom, What, When, and How Long?

Menopausal hormone therapy (HT) was widely used in the past, but with the publication of seminal primary and secondary prevention trials that reported an excess cardiovascular risk with combined estrogen-progestin, HT use declined significantly. However, over the past 20 years, much has been learned about the relationship between the timing of HT use with respect to age and time since menopause, HT route of administration, and cardiovascular disease risk. Four leading medical societies recommend HT for the treatment of menopausal women with bothersome menopausal symptoms. In this context, this review, led by the American College of Cardiology Cardiolovascular Disease in Women Committee, along with leading gynecologists, women's health internists, and endocrinologists, aims to provide guidance on HT use, including the selection of patients and HT formulation with a focus on caring for symptomatic women with cardiovascular disease risk.

Aspirin for primary prevention of cardiovascular disease in women

Aspirin use for primary prevention of cardiovascular disease is controversial. Low-dose aspirin may be considered for primary prevention in women on an individualized basis for those aged 40 to 59 years with a 10-year cardiovascular risk of 10% or more and without increased bleeding risk. Low-dose aspirin for primary prevention is not advised for low-risk women or women aged 60 years or older.

Prolactin Inhibition in Peripartum Cardiomyopathy: Systematic Review and Meta-analysis

Heart failure (HF) is one of the leading causes of maternal mortality and morbidity in the United States. Peripartum cardiomyopathy (PPCM) constitutes up to 70% of all HF in pregnancy. Cardiac angiogenic imbalance caused by cleaved 16kDa prolactin has been hypothesized to contribute to the development of PPCM, fueling investigation of prolactin inhibitors for the management of PPCM. We conducted a systematic review and meta-analysis to assess the impact of prolactin inhibition on left ventricular (LV) function and mortality in patients with PPCM. We included English language articles from PubMed and EMBASE published upto March 2022. We pooled the mean difference (MD) for left ventricular ejection fraction (LVEF) at follow-up, odds ratio (OR) for LV recovery and risk ratio (RR) for all-cause mortality using random-effects meta-analysis. Among 548 studies screened, 10 studies (3 randomized control trials (RCTs), 2 retrospective and 5 prospective cohorts) were included in the systematic review. Patients in the Bromocriptine + standard guideline directed medical therapy (GDMT) group had higher LVEF% (pMD 12.56 (95% CI 5.84-19.28, I2=0%) from two cohorts and pMD 14.25 (95% CI 0.61-27.89, I2=88%) from two RCTs) at follow-up compared to standard GDMT alone group. Bromocriptine group also had higher odds of LV recovery (pOR 3.55 (95% CI 1.39-9.1, I2=62)). We did not find any difference in all-cause mortality between the groups. Our analysis demonstrates that the addition of Bromocriptine to standard GDMT was associated with a significant improvement in LVEF% and greater odds of LV recovery, without significant reduction in all-cause mortality.

One Clinician Is All You Need-Cardiac Magnetic Resonance Imaging Measurement Extraction: Deep Learning Algorithm Development

BACKGROUND

Cardiac magnetic resonance imaging (CMR) is a powerful diagnostic modality that provides detailed quantitative assessment of cardiac anatomy and function. Automated extraction of CMR measurements from clinical reports that are typically stored as unstructured text in electronic health record systems would facilitate their use in research. Existing machine learning approaches either rely on large quantities of expert annotation or require the development of engineered rules that are time-consuming and are specific to the setting in which they were developed.

OBJECTIVE

We hypothesize that the use of pretrained transformer-based language models may enable label-efficient numerical extraction from clinical text without the need for heuristics or large quantities of expert annotations. Here, we fine-tuned pretrained transformer-based language models on a small quantity of CMR annotations to extract 21 CMR measurements. We assessed the effect of clinical pretraining to reduce labeling needs and explored alternative representations of numerical inputs to improve performance.

METHODS

Our study sample comprised 99,252 patients that received longitudinal cardiology care in a multi-institutional health care system. There were 12,720 available CMR reports from 9280 patients. We adapted PRAnCER (Platform Enabling Rapid Annotation for Clinical Entity Recognition), an annotation tool for clinical text, to collect annotations from a study clinician on 370 reports. We experimented with 5 different representations of numerical quantities and several model weight initializations. We evaluated extraction performance using macroaveraged F1-scores across the measurements of interest. We applied the best-performing model to extract measurements from the remaining CMR reports in the study sample and evaluated established associations between selected extracted measures with clinical outcomes to demonstrate validity.

RESULTS

All combinations of weight initializations and numerical representations obtained excellent performance on the gold-standard test set, suggesting that transformer models fine-tuned on a small set of annotations can effectively extract numerical quantities. Our results further indicate that custom numerical representations did not appear to have a significant impact on extraction performance. The best-performing model achieved a macroaveraged F1-score of 0.957 across the evaluated CMR measurements (range 0.92 for the lowest-performing measure of left atrial anterior-posterior dimension to 1.0 for the highest-performing measures of left ventricular end systolic volume index and left ventricular end systolic diameter). Application of the best-performing model to the study cohort yielded 136,407 measurements from all available reports in the study sample. We observed expected associations between extracted left ventricular mass index, left ventricular ejection fraction, and right ventricular ejection fraction with clinical outcomes like atrial fibrillation, heart failure, and mortality.

CONCLUSIONS

This study demonstrated that a domain-agnostic pretrained transformer model is able to effectively extract quantitative clinical measurements from diagnostic reports with a relatively small number of gold-standard annotations. The proposed workflow may serve as a roadmap for other quantitative entity extraction.

Deep learning on resting electrocardiogram to identify impaired heart rate recovery

Background and Objective

Postexercise heart rate recovery (HRR) is an important indicator of cardiac autonomic function and abnormal HRR is associated with adverse outcomes. We hypothesized that deep learning on resting electrocardiogram (ECG) tracings may identify individuals with impaired HRR.

Methods

We trained a deep learning model (convolutional neural network) to infer HRR based on resting ECG waveforms (HRR_pred) among UK Biobank participants who had undergone exercise testing. We examined the association of HRR_pred with incident cardiovascular disease using Cox models, and investigated the genetic architecture of HRR_pred in genome-wide association analysis.

Results

Among 56,793 individuals (mean age 57 years, 51% women), the HRR_pred model was moderately correlated with actual HRR (r = 0.48, 95% confidence interval [CI] 0.47-0.48). Over a median follow-up of 10 years, we observed 2060 incident diabetes mellitus (DM) events, 862 heart failure events, and 2065 deaths. Higher HRR_pred was associated with lower risk of DM (hazard ratio [HR] 0.79 per 1 standard deviation change, 95% CI 0.76-0.83), heart failure (HR 0.89, 95% CI 0.83-0.95), and death (HR 0.83, 95% CI 0.79-0.86). After accounting for resting heart rate, the association of HRR_pred with incident DM and all-cause mortality were similar. Genetic determinants of HRR_pred included known heart rate, cardiac conduction system, cardiomyopathy, and metabolic trait loci.

Conclusion

Deep learning-derived estimates of HRR using resting ECG independently associated with future clinical outcomes, including new-onset DM and all-cause mortality. Inferring postexercise heart rate response from a resting ECG may have potential clinical implications and impact on preventive strategies warrants future study.

Infertility and Risk of Heart Failure in the Women's Health Initiative

BACKGROUND

There is growing recognition that reproductive factors are associated with increased risk of future cardiovascular disease. Infertility has been less well studied, although emerging data support its association with increased risk of cardiovascular disease. Whether infertility is associated with future risk of heart failure (HF) is not known.

OBJECTIVES

This study sought to examine the development of HF and HF subtypes in women with and without history of infertility.

METHODS

We followed postmenopausal women from the Women's Health Initiative prospectively for the development of HF. Infertility was self-reported at study baseline. Multivariable cause-specific Cox models were used to evaluate the association of infertility with incident overall HF and HF subtypes (heart failure with preserved ejection fraction [HFpEF]: left ventricular ejection fraction of ≥50% vs heart failure with reduced ejection fraction [HFrEF]: left ventricular ejection fraction of <50%]).

RESULTS

Among 38,528 postmenopausal women (mean age: 63 ± 7 years), 5,399 (14%) participants reported a history of infertility. Over a median follow-up of 15 years, 2,373 developed incident HF, including 807 with HFrEF and 1,133 with HFpEF. Infertility was independently associated with future risk of overall HF (HR: 1.16; 95% CI: 1.04-1.30; P = 0.006). Notably, when examining HF subtypes, infertility was associated with future risk of HFpEF (HR: 1.27; 95% CI: 1.09-1.48; P = 0.002) but not HFrEF (HR: 0.97; 95% CI: 0.80-1.18).

CONCLUSIONS

Infertility was significantly associated with incident HF. This was driven by increased risk of HFpEF, but not HFrEF, and appeared independent of traditional cardiovascular risk factors and other infertility-related conditions. Future research should investigate mechanisms that underlie the link between infertility and HFpEF.

Cohort design and natural language processing to reduce bias in electronic health records research

Electronic health record (EHR) datasets are statistically powerful but are subject to ascertainment bias and missingness. Using the Mass General Brigham multi-institutional EHR, we approximated a community-based cohort by sampling patients receiving longitudinal primary care between 2001-2018 (Community Care Cohort Project [C3PO], n = 520,868). We utilized natural language processing (NLP) to recover vital signs from unstructured notes. We assessed the validity of C3PO by deploying established risk models for myocardial infarction/stroke and atrial fibrillation. We then compared C3PO to Convenience Samples including all individuals from the same EHR with complete data, but without a longitudinal primary care requirement. NLP reduced the missingness of vital signs by 31%. NLP-recovered vital signs were highly correlated with values derived from structured fields (Pearson r range 0.95-0.99). Atrial fibrillation and myocardial infarction/stroke incidence were lower and risk models were better calibrated in C3PO as opposed to the Convenience Samples (calibration error range for myocardial infarction/stroke: 0.012-0.030 in C3PO vs. 0.028-0.046 in Convenience Samples; calibration error for atrial fibrillation 0.028 in C3PO vs. 0.036 in Convenience Samples). Sampling patients receiving regular primary care and using NLP to recover missing data may reduce bias and maximize generalizability of EHR research.

Exercise Blood Pressure in Heart Failure With Preserved and Reduced Ejection Fraction

OBJECTIVES

This study aimed to evaluate hemodynamic correlates of inducible blood pressure (BP) pulsatility with exercise in heart failure with preserved ejection fraction (HFpEF), to identify relationships to outcomes, and to compare this with heart failure with reduced ejection fraction (HFrEF).

BACKGROUND

In HFpEF, determinants and consequences of exercise BP pulsatility are not well understood.

METHODS

We measured exercise BP in 146 patients with HFpEF who underwent invasive cardiopulmonary exercise testing. Pulsatile BP was evaluated as proportionate pulse pressure (PrPP), the ratio of pulse pressure to systolic pressure. We measured pulmonary arterial catheter pressures, Fick cardiac output, respiratory gas exchange, and arterial stiffness. We correlated BP changes to central hemodynamics and cardiovascular outcome (nonelective cardiovascular hospitalization) and compared findings with 57 patients with HFrEF from the same referral population.

RESULTS

In HFpEF, only age (standardized beta = 0.593; P < 0.001), exercise stroke volume (standardized beta = 0.349; P < 0.001), and baseline arterial stiffness (standardized beta = 0.182; P = 0.02) were significant predictors of peak exercise PrPP in multivariable analysis (R = 0.661). In HFpEF, lower PrPP was associated with lower risk of cardiovascular events, despite adjustment for confounders (HR:0.53 for PrPP below median; 95% CI: 0.28-0.98; P = 0.043). In HFrEF, lower exercise PrPP was not associated with arterial stiffness but was associated with lower peak exercise stroke volume (P = 0.013) and higher risk of adverse cardiovascular outcomes (P = 0.004).

CONCLUSIONS

In HFpEF, greater inducible BP pulsatility measured using exercise PrPP reflects greater arterial stiffness and higher risk of adverse cardiovascular outcomes, in contrast to HFrEF where inducible exercise BP pulsatility relates to stroke volume reserve and favorable outcome.

Association of infertility with atherosclerotic cardiovascular disease among postmenopausal participants in the Women’s Health Initiative

OBJECTIVE

To investigate the association of infertility with atherosclerotic cardiovascular disease (ASCVD) among postmenopausal participants in the Women's Health Initiative (WHI). We hypothesized that nulliparity and pregnancy loss may reveal more extreme phenotypes of infertility, enabling further understanding of the association of infertility with ASCVD.

DESIGN

Prospective cohort study.

SETTING

Forty clinical centers in the United States.

PATIENT(S)

A total of 158,787 postmenopausal participants in the Women's Health Initiative cohort.

INTERVENTION(S)

Infertility, parity, and pregnancy loss.

MAIN OUTCOME MEASURE(S)

The primary outcome was risk of ASCVD among women with and without a history of infertility, stratified by history of live birth and pregnancy loss. Cox proportional-hazards models were adjusted for demographics and risk factors for ASCVD.

RESULT(S)

Among 158,787 women, 25,933 (16.3%) reported a history of infertility; 20,427 (80%) had at least 1 live birth; and 9,062 (35%) had at least 1 pregnancy loss. There was a moderate overall association between infertility and ASCVD (adjusted hazard ratio, 1.02; 95% confidence interval [CI], 0.99-1.06) over 19 years of follow-up. Among nulliparous women, infertility was associated with a 13% higher risk of ASCVD (95% CI, 1.04-1.23). Among nulliparous women who had a pregnancy loss, infertility was associated with a 36% higher risk of ASCVD (95% CI, 1.09-1.71).

CONCLUSION(S)

Women with a history of infertility overall had a moderately higher risk of ASCVD compared with women without a history of infertility. Atherosclerotic cardiovascular disease risk was much higher among nulliparous infertile women and among nulliparous infertile women who also had a pregnancy loss, suggesting that in these more extreme phenotypes, infertility may be associated with ASCVD risk.

Association of Cardiometabolic Disease With Cancer in the Community

Background

Obesity and cardiometabolic dysfunction have been associated with cancer risk and severity. Underlying mechanisms remain unclear.

Objectives

The aim of this study was to examine associations of obesity and related cardiometabolic traits with incident cancer.

Methods

FHS (Framingham Heart Study) and PREVEND (Prevention of Renal and Vascular End-Stage Disease) study participants without prevalent cancer were studied, examining associations of obesity, body mass index (BMI), waist circumference, visceral adipose tissue (VAT) and subcutaneous adipose tissue depots, and C-reactive protein (CRP) with future cancer in Cox models.

Results

Among 20,667 participants (mean age 50 years, 53% women), 2,619 cancer events were observed over a median follow-up duration of 15 years. Obesity was associated with increased risk for future gastrointestinal (HR: 1.30; 95% CI: 1.05-1.60), gynecologic (HR: 1.62; 95% CI: 1.08-2.45), and breast (HR: 1.32; 95% CI: 1.05-1.66) cancer and lower risk for lung cancer (HR: 0.62; 95% CI: 0.44-0.87). Similarly, waist circumference was associated with increased risk for overall, gastrointestinal, and gynecologic but not lung cancer. VAT but not subcutaneous adipose tissue was associated with risk for overall cancer (HR: 1.22; 95% CI: 1.05-1.43), lung cancer (HR: 1.92; 95% CI: 1.01-3.66), and melanoma (HR: 1.56; 95% CI: 1.02-2.38) independent of BMI. Last, higher CRP levels were associated with higher risk for overall, colorectal, and lung cancer (P < 0.05 for all).

Conclusions

Obesity and abdominal adiposity are associated with future risk for specific cancers (eg, gastrointestinal, gynecologic). Although obesity was associated with lower risk for lung cancer, greater VAT and CRP were associated with higher lung cancer risk after adjusting for BMI.

Sexual Dimorphism in Cardiovascular Biomarkers: Clinical and Research Implications

Sex-based differences in cardiovascular disease presentation, diagnosis, and response to therapies are well established, but mechanistic understanding and translation to clinical applications are limited. Blood-based biomarkers have become an important tool for interrogating biologic pathways. Understanding sexual dimorphism in the relationship between biomarkers and cardiovascular disease will enhance our insights into cardiovascular disease pathogenesis in women, with potential to translate to improved individualized care for men and women with or at risk for cardiovascular disease. In this review, we examine how biologic sex associates with differential levels of blood-based biomarkers and influences the effect of biomarkers on disease outcomes. We further summarize key differences in blood-based cardiovascular biomarkers along central biologic pathways, including myocardial stretch/injury, inflammation, adipose tissue metabolism, and fibrosis pathways in men versus women. Finally, we present recommendations for leveraging our current knowledge of sex differences in blood-based biomarkers for future research and clinical innovation.

Arterial Stiffness and Vascular Load in HFpEF: Differences Among Women and Men

BACKGROUND

Mechanisms underlying sex differences in heart failure with preserved ejection fraction (HFpEF) are poorly understood. We sought to examine sex differences in measures of arterial stiffness and the association of arterial stiffness measures with left ventricular hemodynamic responses to exercise in men and women.

METHODS

We studied 83 men (mean age 62 years) and 107 women (mean age 59 years) with HFpEF who underwent cardiopulmonary exercise testing with invasive hemodynamic monitoring and arterial stiffness measurement (augmentation pressure [AP], augmentation index [AIx], and aortic pulse pressure [AoPP]). Sex differences were compared using multivariable linear regression. We examined the association of arterial stiffness with abnormal left ventricular diastolic response to exercise, defined as a rise in pulmonary capillary wedge pressure relative to cardiac output (∆PCWP/∆CO) ≥ 2 mmHg/L/min by using logistic regression models.

RESULTS

Women with HFpEF had increased arterial stiffness compared with men. AP was nearly 10 mmHg higher, and AIx was more than 10% higher in women compared with men (P < 0.0001 for both). Arterial stiffness measures were associated with a greater pulmonary capillary wedge pressure response to exercise, particularly among women. A 1-standard deviation higher AP was associated with > 3-fold increased odds of abnormal diastolic exercise response (AP: OR 3.16, 95% CI 1.34-7.42; P = 0.008 [women] vs OR 2.07, 95% CI 0.95-5.49; P = 0.15 [men]) with similar findings for AIx and AoPP.

CONCLUSIONS

Arterial stiffness measures are significantly higher in women with HFpEF than in men and are associated with abnormally steep increases in pulmonary capillary wedge pressure with exercise, particularly in women. Arterial stiffness may preferentially contribute to abnormal diastolic function during exercise in women with HFpEF compared with men.

Cardiovascular disease related circulating biomarkers and cancer incidence and mortality: is there an association?

AIMS

Recent studies suggest an association between cardiovascular disease (CVD) and cancer incidence/mortality, but the pathophysiological mechanisms underlying these associations are unclear. We aimed to examine biomarkers previously associated with CVD and study their association with incident cancer and cancer-related death in a prospective cohort study.

METHODS AND RESULTS

We used a proteomic platform to measure 71 cardiovascular biomarkers among 5,032 participants in the Framingham Heart Study who were free of cancer at baseline. We used multivariable-adjusted Cox models to examine the association of circulating protein biomarkers with risk of cancer incidence and mortality. To account for multiple testing, we set a 2-sided false discovery rate (FDR Q-value) <0.05.Growth differentiation factor-15 (GDF15; also known as macrophage inhibitory cytokine-1 [MIC1])) was associated with increased risk of incident cancer (hazards ratio [HR] per 1 standard deviation increment 1.31, 95% CI 1.17-1.47), incident gastrointestinal cancer (HR 1.85, 95% CI 1.37-2.50), incident colorectal cancer (HR 1.94, 95% CI 1.29-2.91) and cancer-related death (HR 2.15, 95% CI 1.72-2.70). Stromal cell-derived factor-1 (SFD1) showed an inverse association with cancer-related death (HR 0.75, 95% CI 0.65-0.86). Fibroblast growth factor-23 (FGF23) showed an association with colorectal cancer (HR 1.55, 95% CI 1.20-2.00), and granulin (GRN) was associated with hematologic cancer (HR 1.61, 95% CI 1.30-1.99). Other circulating biomarkers of inflammation, immune activation, metabolism, and fibrosis showed suggestive associations with future cancer diagnosis.

CONCLUSION

We observed several significant associations between circulating CVD biomarkers and cancer, supporting the idea that shared biological pathways underlie both diseases. Further investigations of specific mechanisms that lead to both CVD and cancer are warranted.

TRANSLATIONAL PERSPECTIVE

In our prospective cohort study, baseline levels of biomarkers previously associated with CVD were found to be associated with future development of cancer. In particular, GDF15 was associated with increased risk of cancer incidence and mortality, including gastrointestinal and colorectal cancers; SDF1 was inversely associated with cancer-related death, and FGF23 and GRN were associated with increased risk of colorectal and hematologic cancers, respectively. Other biomarkers of inflammation, immune activation, metabolism, and fibrosis showed suggestive associations. These results suggest potential shared biological pathways that underlie both development of cancer and CVD.

Increasing Participation of Women in Cardiovascular Trials: JACC Council Perspectives

Although some progress has been made in the last 3 decades to increase the number of women in clinical cardiology trials, review of recent cardiovascular literature demonstrates that women and underrepresented minority women are still underrepresented in most clinical cardiology trials. This is especially notable in trials of patients with coronary artery disease, heart failure with reduced ejection fraction, and arrhythmia studies, especially those involving devices and procedures. Despite the call from National Institutes of Health, Food and Drug Administration, Institute of Medicine, and various professional societies, the gap remains. This paper seeks to identify the barriers for low enrollment and retention from patient, clinician, research team, study design, and system perspectives, and offers recommendations to improve recruitment and retention in the current era.

Cardiovascular Biomarkers of Obesity and Overlap With Cardiometabolic Dysfunction

Background Obesity may be associated with a range of cardiometabolic manifestations. We hypothesized that proteomic profiling may provide insights into the biological pathways that contribute to various obesity-associated cardiometabolic traits. We sought to identify proteomic signatures of obesity and examine overlap with related cardiometabolic traits, including abdominal adiposity, insulin resistance, and adipose depots. Methods and Results We measured 71 circulating cardiovascular disease protein biomarkers in 6981 participants (54% women; mean age, 49 years). We examined the associations of obesity, computed tomography measures of adiposity, cardiometabolic traits, and incident metabolic syndrome with biomarkers using multivariable regression models. Of the 71 biomarkers examined, 45 were significantly associated with obesity, of which 32 were positively associated and 13 were negatively associated with obesity (false discovery rate q<0.05 for all). There was significant overlap of biomarker profiles of obesity and cardiometabolic traits, but 23 biomarkers, including melanoma cell adhesion molecule (MCAM), growth differentiation factor-15 (GDF15), and lipoprotein(a) (LPA) were unique to metabolic traits only. Using hierarchical clustering, we found that the protein biomarkers clustered along 3 main trait axes: adipose, metabolic, and lipid traits. In longitudinal analyses, 6 biomarkers were significantly associated with incident metabolic syndrome: apolipoprotein B (apoB), insulin-like growth factor-binding protein 2 (IGFBP2), plasma kallikrein (KLKB1), complement C2 (C2), fibrinogen (FBN), and N-terminal pro-B-type natriuretic peptide (NT-proBNP); false discovery rate q<0.05 for all. Conclusions We found that the proteomic architecture of obesity overlaps considerably with associated cardiometabolic traits, implying shared pathways. Despite overlap, hierarchical clustering of proteomic profiles identified 3 distinct clusters of cardiometabolic traits: adipose, metabolic, and lipid. Further exploration of these novel protein targets and associated pathways may provide insight into the mechanisms responsible for the progression from obesity to cardiometabolic disease.

Exercise Intolerance in Heart Failure With Preserved Ejection Fraction: Arterial Stiffness and Aabnormal Left Ventricular Hemodynamic Responses During Exercise

BACKGROUND

Arterial stiffness is thought to contribute to the pathophysiology of heart failure with preserved ejection fraction (HFpEF). We sought to examine arterial stiffness in HFpEF and hypertension and investigate associations of arterial and left ventricular hemodynamic responses to exercise.

METHODS AND RESULTS

A total of 385 symptomatic individuals with an EF of ≥50% underwent upright cardiopulmonary exercise testing with invasive hemodynamic assessment of arterial stiffness and load (aortic augmentation pressure, augmentation index, systemic vascular resistance index, total arterial compliance index, effective arterial elastance index, and pulse pressure amplification) at rest and during incremental exercise. An abnormal hemodynamic response to exercise was defined as a steep increase in pulmonary capillary wedge pressure relative to cardiac output (∆PCWP/∆CO > 2 mm Hg/L/min). We compared rest and exercise measures between HFpEF and hypertension in multivariable analyses. Among 188 participants with HFpEF (mean age 61 ± 13 years, 56% women), resting arterial stiffness parameters were worse compared with 94 hypertensive participants (mean age 55 ± 15 years, 52% women); these differences were accentuated during exercise in HFpEF (all P ≤ .0001). Among all participants, exercise measures of arterial stiffness correlated with worse ∆PCWP/∆CO. Specifically, a 1 standard deviation higher exercise augmentation pressure was associated with 2.15-fold greater odds of abnormal LV hemodynamic response (95% confidence interval 1.52-3.05; P < .001). Further, exercise measures of systemic vascular resistance index, elastance index, and pulse pressure amplification correlated with a lower peak oxygen consumption.

CONCLUSIONS

Exercise accentuates the increased arterial stiffness found in HFpEF, which in turn correlates with left ventricular hemodynamic responses. Unfavorable ventricular-vascular interactions during exercise in HFpEF may contribute to exertional intolerance and inform future therapeutic interventions.

Association of obesity-related inflammatory pathways with lung function and exercise capacity

BACKGROUND

Obesity has multifactorial effects on lung function and exercise capacity. The contributions of obesity-related inflammatory pathways to alterations in lung function remain unclear.

RESEARCH QUESTION

To examine the association of obesity-related inflammatory pathways with pulmonary function, exercise capacity, and pulmonary-specific contributors to exercise intolerance.

METHOD

We examined 695 patients who underwent cardiopulmonary exercise testing (CPET) with invasive hemodynamic monitoring at Massachusetts General Hospital between December 2006-June 2017. We investigated the association of adiponectin, leptin, resistin, IL-6, CRP, and insulin resistance (HOMA-IR) with pulmonary function and exercise parameters using multivariable linear regression.

RESULTS

Obesity-related inflammatory pathways were associated with worse lung function. Specifically, higher CRP, IL-6, and HOMA-IR were associated with lower percent predicted FEV₁ and FVC with a preserved FEV₁/FVC ratio suggesting a restrictive physiology pattern (P ≤ 0.001 for all). For example, a 1-SD higher natural-logged CRP level was associated with a nearly 5% lower percent predicted FEV₁ and FVC (beta -4.8, s.e. 0.9 for FEV1; beta -4.9, s.e. 0.8 for FVC; P < 0.0001 for both). Obesity-related inflammatory pathways were associated with worse pulmonary vascular distensibility (adiponectin, IL-6, and CRP, P < 0.05 for all), as well as lower pulmonary artery compliance (IL-6 and CRP, P ≤ 0.01 for both).

INTERPRETATION

Our findings highlight the importance of obesity-related inflammatory pathways including inflammation and insulin resistance on pulmonary spirometry and pulmonary vascular function. Specifically, systemic inflammation as ascertained by CRP, IL-6 and insulin resistance are associated with restrictive pulmonary physiology independent of BMI. In addition, inflammatory markers were associated with lower exercise capacity and pulmonary vascular dysfunction.

Sex differences in inflammatory markers in patients hospitalized with COVID-19 infection: Insights from the MGH COVID-19 patient registry

Background

Men are at higher risk for serious complications related to COVID-19 infection than women. More robust immune activation in women has been proposed to contribute to decreased disease severity, although systemic inflammation has been associated with worse outcomes in COVID-19 infection. Whether systemic inflammation contributes to sex differences in COVID-19 infection is not known.

Study design and methods

We examined sex differences in inflammatory markers among 453 men (mean age 61) and 328 women (mean age 62) hospitalized with COVID-19 infection at the Massachusetts General Hospital from March 8 to April 27, 2020. Multivariable linear regression models were used to examine the association of sex with initial and peak inflammatory markers. Exploratory analyses examined the association of sex and inflammatory markers with 28-day clinical outcomes using multivariable logistic regression.

Results

Initial and peak CRP were higher in men compared with women after adjustment for baseline differences (initial CRP: ß 0.29, SE 0.07, p = 0.0001; peak CRP: ß 0.31, SE 0.07, p<0.0001) with similar findings for IL-6, PCT, and ferritin (p<0.05 for all). Men had greater than 1.5-greater odds of dying compared with women (OR 1.71, 95% CI 1.04–2.80, p = 0.03). Sex modified the association of peak CRP with both death and ICU admission, with stronger associations observed in men compared with women (death: OR 9.19, 95% CI 4.29–19.7, p <0.0001 in men vs OR 2.81, 95% CI 1.52–5.18, p = 0.009 in women, P_interaction = 0.02).

Conclusions

In a sample of 781 men and women hospitalized with COVID-19 infection, men exhibited more robust inflammatory activation as evidenced by higher initial and peak inflammatory markers, as well as worse clinical outcomes. Better understanding of sex differences in immune responses to COVID-19 infection may shed light on the pathophysiology of COVID-19 infection.

Age dependent associations of risk factors with heart failure: pooled population based cohort study

OBJECTIVE

To assess age differences in risk factors for incident heart failure in the general population.

DESIGN

Pooled population based cohort study.

SETTING

Framingham Heart Study, Prevention of Renal and Vascular End-stage Disease Study, and Multi-Ethnic Study of Atherosclerosis.

PARTICIPANTS

24 675 participants without a history of heart failure stratified by age into young (<55 years; n=11 599), middle aged (55-64 years; n=5587), old (65-74 years; n=5190), and elderly (≥75 years; n=2299) individuals.

MAIN OUTCOME MEASURE

Incident heart failure.

RESULTS

Over a median follow-up of 12.7 years, 138/11 599 (1%), 293/5587 (5%), 538/5190 (10%), and 412/2299 (18%) of young, middle aged, old, and elderly participants, respectively, developed heart failure. In young participants, 32% (n=44) of heart failure cases were classified as heart failure with preserved ejection fraction compared with 43% (n=179) in elderly participants. Risk factors including hypertension, diabetes, current smoking history, and previous myocardial infarction conferred greater relative risk in younger compared with older participants (P for interaction <0.05 for all). For example, hypertension was associated with a threefold increase in risk of future heart failure in young participants (hazard ratio 3.02, 95% confidence interval 2.10 to 4.34; P<0.001) compared with a 1.4-fold risk in elderly participants (1.43, 1.13 to 1.81; P=0.003). The absolute risk for developing heart failure was lower in younger than in older participants with and without risk factors. Importantly, known risk factors explained a greater proportion of overall population attributable risk for heart failure in young participants (75% v 53% in elderly participants), with better model performance (C index 0.79 v 0.64). Similarly, the population attributable risks of obesity (21% v 13%), hypertension (35% v 23%), diabetes (14% v 7%), and current smoking (32% v 1%) were higher in young compared with elderly participants.

CONCLUSIONS

Despite a lower incidence and absolute risk of heart failure among younger compared with older people, the stronger association and greater attributable risk of modifiable risk factors among young participants highlight the importance of preventive efforts across the adult life course.

Cardiovascular Risk Factors are Associated with Future Cancer

Background

The extent to which co-occurrence of cardiovascular disease (CVD) and cancer is due to shared risk factors or other mechanisms is unknown.

Objectives

This study investigated the association of standard CVD risk factors, CVD biomarkers, pre-existing CVD, and ideal cardiovascular (CV) health metrics with the development of future cancer.

Methods

This study prospectively followed Framingham Heart Study and PREVEND (Prevention of Renal and Vascular End-Stage Disease) study participants free of cancer at baseline and ascertained histology-proven cancer. This study assessed the association of baseline CV risk factors, 10-year atherosclerotic (ASCVD) risk score, established CVD biomarkers, prevalent CVD, and the American Heart Association (AHA) Life’s Simple 7 CV health score with incident cancer using multivariable Cox models. Analyses of interim CVD events with incident cancer used time-dependent covariates.

Results

Among 20,305 participants (mean age 50 ± 14 years; 54% women), 2,548 incident cancer cases occurred over a median follow-up of 15.0 years (quartile 1 to 3: 13.3 to 15.0 years). Traditional CVD risk factors, including age, sex, and smoking status, were independently associated with cancer (p < 0.001 for all). Estimated 10-year ASCVD risk was also associated with future cancer (hazard ratio [HR]: 1.16 per 5% increase in risk; 95% confidence interval [CI] 1.14 to 1.17; p < 0.001). The study found that natriuretic peptides (tertile 3 vs. tertile 1; HR: 1.40; 95% CI: 1.03 to 1.91; p = 0.035) were associated with incident cancer but not high-sensitivity troponin (p = 0.47). Prevalent CVD and the development of interim CV events were not associated with higher risk of subsequent cancer. However, ideal CV health was associated with lower future cancer risk (HR: 0.95 per 1-point increase in the AHA health score; 95% CI: 0.92 to 0.99; p = 0.009).

Conclusions

CVD risk, as captured by traditional CVD risk factors, 10-year ASCVD risk score, and natriuretic peptide concentrations are associated with increased risk of future cancer. Conversely, a heart healthy lifestyle is associated with a lower risk of future cancer. These data suggest that the association between CVD and future cancer is attributable to shared risk factors.