Citations

Introduction: Increasing evidence unravels the role of loneliness and social connection in cardiovascular diseases potentially mediating accelerated biological aging. The present study aims to explore the association between social connection and biological aging as determinate by artificial intelligence-enabled electrocardiography (ECG). Methods: This is an observational retrospective cohort of adults aged ≥18 seen at Mayo Clinic from 2019-2022 who completed the social determinants of health questionnaire and had a 12-lead ECG within one year of completing the questionnaire. Five questions were asked to understand each patient’s social connection . The answers were scored to assess their level of social connection from socially isolated (score of 0) to socially connected (score of 4). The biological age was predicted from ECGs using the previously developed convolutional neural network (AI-ECG age). Delta age (Δage) was defined as AI-ECG age minus chronological age, where positive values reflect an older than expected age. Results: We included 280,323 subjects (chronological age 59.7±16.4 years, 51% female). The average AI-ECG age was 59.5±13.5 year. Better social connection status correlated with lower delta age (β=-0.33 (95%CI, -0.38 and -0.28, p<0.001, adjusted to chronological age and sex). Conversely, individuals reporting the least social connection were an average of 2 years older than expected whereas those with the most social connection were 2 years younger than expected by AI-ECG (Figure 1). Conclusions: Social connection is strongly associated with slower biological aging compared to chronological aging, independent of the conventional cardiovascular risk factors. This observation underscores the need to address social connection as a healthcare determinant.

Introduction: The physiological changes associated with aging have deleterious effects on cardiovascular function. In addition, increasing evidence showed the effect of exercise on improving cardiovascular health and reducing the aging process. The present study sought to demonstrate the association between exercise and biological age, estimated by our previously reported method using artificial intelligence-enabled electrocardiography (ECG). Methods: This retrospective observational study enrolled adults aged ≥18 years who have been evaluated at Mayo Clinic between 2019-2022 and completed the exercise questionnaire. The total time spent in moderate to strenuous exercise was calculated by multiplying the number of days engaging in exercise per week by the average minutes per day. The biological age was determined by applying our previously developed convolutional neural network model on the 12-lead ECG records (AI-ECG). The ECG records were within one year of subjects’ visits (in case of multiple visits, the closest one to the questionnaire was chosen). Positive Age-Gap (AI-ECG minus chronological age) reflects a person identified as being older by AI-ECG compared to his/her chronological age. Results: A total of 268,002 subjects (51% female) were recruited (mean age 59.7±16.4 years). Of those, 25.7% were not engaged in any exercise. The median day of engaging in exercise was 3 (Interquartile range, 2,5) per week, and the average time of exercising was 31.3±30 minutes/day. Age-Gap diminished progressively with increased duration of moderate to strenuous exercise (Figure 1). Linear regression analysis revealed exercise is an independent predictor of Age-Gap, (β= -0.043, 95%CI, -0.045 and -0.041, p<0.001). Conclusions: Engaging in moderate to strenuous exercise is associated with slower biological aging relative to chronological age as determined by AI-enabled ECG.

Introduction: Peripheral microvascular endothelial dysfunction (PMED) is a marker and precursor of atherosclerosis and is associated with an increased risk of cardiovascular events. The present study aims to identify the best cut-off value of PMED, assessed by the reactive hyperemia index, in predicting major adverse cardiovascular events (MACE). Additionally, we investigate whether integrating PMED to CHA2DS2-Vasc score improves the predicting accuracy of cardiovascular disease. Methods: this is a retrospective study of patients who underwent reactive hyperemia peripheral arterial tonometry (PAT). The optimal cut-off value of reactive hyperemia index associated with MACE was calculated using the area under the receiver-operating curve and the maximum Youden index. Traditional cardiovascular risk factors such as age, sex, congestive heart failure, hypertension, diabetes, stroke, vascular disease were determined to calculate the CHA2DS2-VASc score. MACE was defined as myocardial infarction, heart failure hospitalization, and cerebrovascular events. Results: 1,690 patients were enrolled (average age 51.1±13.9, 64.1% female). The optimal cut-off value of the reactive hyperemia index was 2.0 in the overall population and females and 2.17 in males. The risk of MACE during 10 (Interquartile range: 4,16) years of follow-up was 15.3%. Multivariable logistic regression revealed that PMED as an independent predictor of MACE (PMED: OR, 3.6, 95% CI, 2.6-4.9, p<0.001) (Table1). Furthermore, integrating PMED to CHA2DS2-VASc significantly improved the predictive accuracy (area under the curve, 0.747 vs. 0.708, p<0.001). Conclusion: PMED is a strong predictor of cardiovascular events. Non-invasive assessment of peripheral endothelial function may be useful in early detection and improving the stratification of high-risk patients for cardiovascular events.

Introduction: Newly developed Systematic Coronary Risk Evaluation-2 (SCORE-2) and the version for older people [(SCORE2-OP) ≥70 years] algorithms for 10-yr incident cardiovascular disease (CVD) have been derived incorporating European and US populations. Its performance has not been externally validated in community-based populations representative of real-world clinical practice. Hypothesis: We tested the hypothesis that the SCORE-2 and SCORE2-OP algorithms will accurately estimate 10-yr risk of first-onset CVD in this population. Methods: Consecutive patients who, between 1998-2000, sought primary care in Olmsted county, MN, and were followed-up using the Rochester Epidemiology Project. Inclusion criteria were set as those used in the derivation of the original algorithm. The composite outcome of CVD was defined as first myocardial infarction, ischemic stroke, or cardiovascular mortality. We compared predicted and observed events and generated C-statistics across predefined risk subgroups. Results: We included 22,858 adults, mean age of 55.11±11.58 (13.50% >70 yr) 54% females. After a mean follow-up of 9.55±1.5 yr, 2,145 events were observed. 6.39% of subjects for SCORE-2 and 59.88% using SCORE2-OP were considered at high risk. Overall, the SCORE-2 had better discrimination than the SCORE2-OP (C-statistic: 0.72 and 0.64, respectively) (Fig B-D). The algorithms performed better in individuals 50-69 yr while underpredicting in younger individuals and overpredicting CVD in ages above 70 (in the low and moderate risk group) (Fig A-C). Prediction was mostly similar between men, women and middle-aged individuals but demonstrated pronounced underprediction in older men (Fig B-D). Conclusions: The SCORE-2 Risk prediction tool performed with marginal results whereas the SCORE2-OP had poor performance when predicting CVD events in a community cohort representing real-world clinical practice in a non-European population.

Introduction: Chronic coronary disease (CCD) is a leading cause of death worldwide. Whole blood (WB) transcriptomic (RNA-seq) and methylation ‘omics’ data can discern molecular underpinnings of CCD and create molecular subtypes to aid risk prediction. Methods: Of 1,064 participants with moderate-severe ischemia (Age: 67.1±6.2, 19.4% Female, 17% non-White) from the ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) biorepository, 646 participants had available WB RNA-seq and 737 had WB methylation data ( Fig 1A ). Unsupervised clustering and differential analyses identified omics-derived molecular subtypes. We identified co-regulated gene modules of each subtype, performed subtype-level enrichment of clinical variables, and performed Kaplan-Meier analyses for time to cardiovascular (CV) death or myocardial infarction (MI). Results: Multi-omic analysis revealed 4 RNA-seq-derived subtypes (RS) and 3 methylation-derived subtypes (MS). RNA-seq Subtype 1 (RS1) was enriched for molecular drivers indicative of an adaptive immune response, had clinical enrichment of female sex, statin use, and greater ischemia, and had decreased risk of CV death or MI ( Fig 1B ). RNA-seq Subtype 2 (RS2) was enriched for innate immune response pathway, and patients who were older and White, and was associated with increased risk of CV death or MI. Similarly, methylation subtypes also yielded a high-risk subtype (MS3) and a low-risk subtype (MS2) ( Fig 1C ). Integration of transcriptomic and methylomic subtypes led to further distinction of resilient and vulnerable subgroups. Conclusions: WB RNA-seq and methylation data identified molecularly-defined subtypes that informed the underlying disease pathology of CCD patients in ISCHEMIA. These subgroups were differentially enriched for clinical characteristics and event outcomes, demonstrating the potential use for blood-based omics tests to aid in the prognosis of CCD.

Introduction: Mechanisms underlying bioprosthetic valve deterioration (BVD) are multifactorial and incompletely elucidated. Reparative circulating progenitor cells (CPCs), and conversely calcification-associated osteocalcin expressing CPCs (CPC-OCN), have been linked to native aortic valve deterioration. However, their role in BVD remains elusive. This study sought to evaluate the contribution of different subpopulations of CPCs in BVD. Methods: This prospective study enrolled 121 patients who had peripheral blood mononuclear cells (PBMC) isolated prior to bioprosthetic aortic valve replacement (surgical 104, transcatheter 17) and had an echocardiographic follow-up ≥2 years after the procedure. Using flow cytometry, fresh PBMC were analyzed for the surface markers CD34, CD133, and osteocalcin (OCN). BVD was evaluated by hemodynamic valve deterioration (HVD) using echocardiography, which was defined as an elevated mean transprosthetic gradient ≥30mmHg and/or at least moderate intraprosthetic regurgitation. Multivariable models were constructed to evaluate the association of each subpopulation of CPCs and other clinical characteristics with HVD. Results: Sixteen patients (13.2%) developed HVD during follow-up for a median of 5.9 years. Patients with HVD showed significantly lower levels of reparative CD34 + CD133 + cells and higher levels of OCN + cells than those without HVD (CD34 + CD133 + cells: 125 [80, 210] vs 270 [130, 420], P=0.002; OCN + cells: 3060 [523, 5528] vs 670 [180, 1930], P=0.005 respectively). Decreased level of CD34 + CD133 + cells was a significant predictor of HVD. Conclusions: Circulating levels of CD34 + CD133 + cells and OCN + cells were significantly associated with the subsequent occurrence of HVD in patients undergoing bioprosthetic aortic valve replacement. CPCs might play a vital role in the mechanism, risk stratification and a potential therapeutic target for patients with bioprosthetic valve deterioration.

Introduction: Cardiac rehabilitation (CR) is a comprehensive secondary cardiovascular disease (CVD) program which integrates structured lifestyle interventions to reduce morbidity and mortality. The Life’s Simple 7 (LS7) is an objective measure of cardiovascular health (CVH) which incorporates health-promoting behaviors and clinical factors however, it has not been rigorously evaluated in the CR setting. Methods: Retrospective cohort study of 937 patients who attended center-based CR at Mayo Clinic from Jan 2018 -Sept 2020. Patient characteristics and LS7 component metrics at baseline (pre-CR) and completion (post-CR) were collected: 3 clinical factors (blood pressure [BP], cholesterol, and hemoglobin A1c [HbA1c]), and 4 health behaviors (smoking, body mass index [BMI], physical activity [PA] and diet). LS7 score was computed as a composite of each LS7 component by assigning 2-points for ideal, 1-point for intermediate, or 0-points for poor CVH ranging from 0-14 points. LS7 score was further categorized as poor 0-6, intermediate 7-8 and ideal 9 -14. Results: Patients were 64±13 years old, 34% were female, and attended a mean of 11±12 CR sessions, Table 1. At baseline, the LS7 components with the highest proportion within the poor category were HbA1c (201/495, 41%) and BMI (465/936, 50%), Table 2. From pre to post-CR, there was a reduction in proportion of patients classified within the poor category for each LS7 component except HbA1c ( Figure 1 ), and the proportion of patients with LS7 scores in the ideal range increased from 6.4% to 19% (P<0.001). There was a statistically significant improvement in LS7 score from 5.5±1.8 to 6.7± 2.4 (+Δ1.6±2.4, P<.0001), Table 2 . Conclusions: Patients attending CR demonstrated an improvement in LS7 score and almost all LS7 components suggesting an overall positive impact of CR on CVH. Further research is needed to better understand the impact of the individual LS7 components on CV outcomes in diverse populations participating in CR.

Introduction: Doxorubicin (DOX) is widely used for chemotherapy, but cardiotoxicity and cardiomyopathy are major adverse effects. The canonical transient receptor potential 6 gene ( TRPC6) is a putative risk gene for cardiomyopathy. Recently, a TRPC6 N338S mutation was found in a patient with DOX-induced heart failure. However, the TRPC6 N338S mutant has not been characterized, and how it affects cardiac function is unknown. Hypothesis: We hypothesized that TRPC6 N338S is a gain-of-function mutation producing intracellular Ca 2+ overload in cardiomyocytes. Methods: Using patch clamp recording, molecular biological and molecular docking analyses, we assessed the function of TRPC6 N338S heterologously expressed in HL-1 cardiac cells. Results: TRPC6 N338S significantly increased the current densities of TRPC6 (defined as 1 μM BI-749327 sensitive components, a highly selective TRPC6 inhibitor) in HL-1 cells at baseline and after exposure to 50 μM 1-oleoyl 2-acetyl-sn-glycerol (OAG, an activator of TRPC6), compared to cells expressing TRPC6 WT. Moreover, a 24-h pretreatment with 0.5 μM DOX further potentiated the OAG effects on TRPC6 WT currents with a significantly greater response in the N338S currents. Ca 2+ imaging also showed enhanced intracellular Ca 2+ levels in cells expressing the N338S mutant with OAG and DOX treatment. Biological studies found that the cytoplasmic and surface expression of TRPC6 WT and N338S mutant were identical in HL-1 cells, but those of TRPC6 N338S were markedly upregulated after treatment with 0.5 μM DOX, compared to TRPC6 WT. Molecular docking and dynamics simulation analysis unraveled that OAG binds to a pocket constituted by the pore-helix, S5 and S6 domains of TRPC6 through polar interactions. OAG binds to the same site in TRPC6 N338S with shortened interfacial distances due to additional polar and hydrogen bonding between OAG and the N338S mutant. Conclusions: TRPC6 N338S mutation strengthens the interaction with OAG, stabilizes the OAG-TRPC6 N338S complex, and enhances the OAG effects. Treatment with DOX significantly increases the expression and function of TRPC6 N338S in HL-1 cells. Hence, the TRPC6 N338S is a gain-of-function mutation and may contribute to cardiotoxicity in patients with anthracycline treatment.

Introduction: Aortic valve calcification (AVC) is the key pathophysiology underlying aortic stenosis (AS). We aimed to assess computed tomography AVC in AS by valve morphology (bicuspid [BAV] vs. tricuspid aortic valve[TAV]) and sex. Methods: Retrospective study of patients with echocardiographic AS severity and AVC assessments within six months. Patients with > moderate aortic regurgitation, prosthetic aortic valve, or indeterminate aortic valve morphology were excluded. Severe AS with high mean gradient (MG) was defined as aortic valve area (AVA)≤1cm2 or indexed AVA≤0.6 cm2/m2 + MG≥40 mmHg. Results: Of 2647 patients, 361(65% men) had BAV and 2286(59% men) had TAV, age 65±11 vs. 80±9 years(p<0.001), AVA 1.07±0.42 vs. 0.90±0.25 cm2(p<0.001), MG 41±16 vs.42±14 mmHg(p=0.4) for BAV and TAV, respectively. For both BAV and TAV groups, age, MG, and severe AS frequency were similar between women and men(all p≥0.06). BAV morphology affected AVC-AS severity and AVC-sex associations (p for interactions <0.001): as AS severity increased, mean AVC difference became larger between BAV-men and TAV-men, but smaller between BAV-women and TAV-women. Similar patterns were observed in AVC density (AVCd, AVC divided by left ventricular outflow tract diameter)-AS severity and AVCd-sex associations (p for interactions < 0.001). In patients with concordant AS severity and MG levels, the best BAV AVC-cutoff for detecting severe AS + high MG by area-under-the-curve analysis was 924 AU for BAV-women and 2851 AU for BAV-men, different from guideline-recommended AVC-thresholds (1200 for women and 2000 for men). The best BAV AVCd cutoff was 289 for BAV-women and 476 for BAV-men, similar to the cutoffs for patients predominantly with TAV (292 for women and 476 for men from Clavel MA JACC 2013). The BAV-AVC threshold identified more patients with severe AS than guideline-recommended threshold in BAV-women (84% vs 74%, p<0.001), but not in BAV-men. Conclusions: Valvular calcium accretion in AS was different by valve morphology and sex. As compared to TAV, BAV-women exhibited the least calcification while BAV-men exhibited the highest. Such patterns may impact the sensitivity of guideline-recommended AVC thresholds for detecting severe AS in BAV patients.

Introduction: Hypertrophic cardiomyopathy (HCM) is characterized by left ventricular hypertrophy. Approximately 40-50% of HCM is caused by pathogenic variants in genes encoding proteins of the cardiac sarcomere. Patients with sarcomeric HCM have earlier expression and more severe disease progression. Herein, we evaluated the proteomic differences between patients with sarcomeric HCM and genotype negative HCM. Methods: Mass-spectrometry was performed on cardiac tissue from genotyped patients with HCM obtained after surgical myectomy, followed by differential proteomics (log2fc ≥