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Metabolomic data often present challenges due to high dimensionality, collinearity, and variability in metabolite concentrations. Machine learning (ML) application in metabolomic analyses is enabling the extraction of meaningful information from complex data. Bringing together domain-specific knowledge from metabolomics with explainable ML methods can refine the predictive performance and interpretability of models used in atherosclerosis research. In this work, we aimed to identify the most impactful metabolites associated with the presence of atherosclerotic cardiovascular disease (ASCVD) in cross-sectional case-control studies using explainable ML methods integrated with metabolomics domain knowledge. For this, a subset from the FLEMENGHO cohort with metabolomic data available was used as the training cohort, including 63 patients with a history of ASCVD and 52 non-smoking controls matched by age, sex, and body mass index from the same population. First, Partial Least Squares Discriminant Analysis (PLS-DA) was applied for dimensionality reduction. The selected metabolites' correlations were analyzed by considering their chemical categorization. Then, eXtreme Gradient Boosting (XGBoost) was used to identify metabolites that characterize ASCVD. Next, the selected metabolites were evaluated in an external cohort to determine their effectiveness in distinguishing between cases and controls. A total of 56 metabolites were selected for ASCVD discrimination using PLS-DA. The primary identified metabolites' superclasses included lipids, organic acids, and organic oxygen compounds. Upon integrating these metabolites with the XGBoost model, the classification yielded a test area under the curve (AUC) of 0.75. SHAP analyses ranked cholesterol, 3-methylhistidine, and glucuronic acid among the most impactful features and showed the diversity of metabolites considered for building the ASCVD discriminator. Also using XGBoost, the selected metabolites achieved an AUC of 0.93 in an independent external validation cohort. In conclusion, the combination of different metabolites has the potential to build classifiers for ASCVD. Integrating metabolite categorization within the SHAP analysis further enhanced the interpretability of the model, offering insights into metabolite-specific contributions to ASCVD risk.

Background: Data collected via wearables may complement in-clinic assessments to monitor subclinical heart failure (HF)., Objectives: Evaluate the association of sensor-based digital walking measures with HF stage and characterize their correlation with in-clinic measures of physical performance, cardiac function and participant reported outcomes (PROs) in individuals with early HF., Methods: The analyzable cohort included participants from the Project Baseline Health Study (PBHS) with HF stage 0, A, or B, or adaptive remodeling phenotype (without risk factors but with mild echocardiographic change, termed RF-/ECHO+) (based on available first-visit in-clinic test and echocardiogram results) and with sufficient sensor data. We computed daily values per participant for 18 digital walking measures, comparing HF subgroups vs stage 0 using multinomial logistic regression and characterizing associations with in-clinic measures and PROs with Spearman's correlation coefficients, adjusting all analyses for confounders., Results: In the analyzable cohort (N=1265; 50.6% of the PBHS cohort), one standard deviation decreases in 17/18 walking measures were associated with greater likelihood for stage-B HF (multivariable-adjusted odds ratios [ORs] vs stage 0 ranging from 1.18-2.10), or A (ORs vs stage 0, 1.07-1.45), and lower likelihood for RF-/ECHO+ (ORs vs stage 0, 0.80-0.93). Peak 30-minute pace demonstrated the strongest associations with stage B (OR vs stage 0=2.10; 95% CI:1.74-2.53) and A (OR vs stage 0=1.43; 95% CI:1.23-1.66). Decreases in 13/18 measures were associated with greater likelihood for stage-B HF vs stage A. Strength of correlation with physical performance tests, echocardiographic cardiac-remodeling and dysfunction indices and PROs was greatest in stage B, then A, and lowest for 0., Conclusions: Digital measures of walking captured by wearable sensors could complement clinic-based testing to identify and monitor pre-symptomatic HF., (Copyright © 2024 Verily Life Sciences LLC. Published by Elsevier Inc. All rights reserved.)

Aims: Left ventricular (LV) strain rate (SR) during early relaxation correlates with LV filling pressures and has been assessed as a prognostic biomarker in several cardiac diseases. Conversely, even though LV SR during isovolumic relaxation (SR IVR ) is more strongly related to invasive measurements of LV diastolic function, to date, studies on the role of SR IVR in the long-term prognosis assessment are lacking. Thus, the goal of this study was to assess the potential additive prognostic value of SR IVR on top of conventional cardiovascular risk factors in a general population., Methods: 657 subjects (mean age 51.6y; 47.6% males) were included in this study and, besides clinical and standard echocardiographic assessment, tissue Doppler imaging (TDI)-based SR was measured during IVR (SR IVR ), early diastole (SR e ), and atrial contraction (SR a ) in the mid-segment of the inferior, inferolateral, lateral, and septal wall of the LV., Results: During the follow-up period (median 12.1 years), the total number of major adverse cardiac events was 85 (13.4%). Overall, after adjustment for known cardiovascular risk factors and important echocardiographic indices in a multivariable-adjusted Cox regression model, SR IVR of the inferolateral wall (SR IVRinflat ) remained an independent predictor of fatal and nonfatal cardiac events (HR: 1.49, p = 0.016), along with GLS (HR: 1.35, p = 0.027), age (HR: 1.09, p < 0.001), and male sex (HR: 2.06, p = 0.037). None of SR IVR measured in the other myocardial walls were associated with cardiac outcome., Conclusion: SR IVRinflat predicted adverse outcome in the general population, on top of conventional cardiovascular factors. However, its incremental value as a prognosticator remained limited., (© 2024. Japanese Society of Echocardiography.)

Nowadays cardiorespiratory fitness (CRF) is assessed using summary indexes of cardiopulmonary exercise tests (CPETs). Yet, raw time-series CPET recordings may hold additional information with clinical relevance. Therefore, we investigated whether analysis of raw CPET data using dynamic time warping combined with k-medoids could identify distinct CRF phenogroups and improve cardiovascular (CV) risk stratification. CPET recordings from 1,399 participants (mean age, 56.4 years; 37.7% women) were separated into 5 groups with distinct patterns. Cluster 5 was associated with the worst CV profile with higher use of antihypertensive medication and a history of CV disease, while cluster 1 represented the most favorable CV profile. Clusters 4 (hazard ratio: 1.30; p  = 0.033) and 5 (hazard ratio: 1.36; p  = 0.0088) had a significantly higher risk of incident adverse events compared to clusters 1 and 2. The model evaluation in the external validation cohort revealed similar patterns. Therefore, an integrative CRF profiling might facilitate CV risk stratification and management., Competing Interests: The authors declare no competing interests., (© 2024 The Author(s).)

The goal of this study is to quantify the assumptions associated with the Wasserman-Hansen (WH) and Fitness Registry and the Importance of Exercise: A National Database (FRIEND) predictive peak oxygen consumption (pVO 2 ) equations across body mass index (BMI). Assumptions in pVO 2 for both equations were first determined using a simulation and then evaluated using exercise data from the Stanford Exercise Testing registry. We calculated percent-predicted VO 2 (ppVO 2 ) values for both equations and compared them using the Bland-Altman method. Assumptions associated with pVO 2 across BMI categories were quantified by comparing the slopes of age-adjusted VO 2 ratios (pVO 2 /pre-exercise VO 2 ) and ppVO 2 values for different BMI categories. The simulation revealed lower predicted fitness among adults with obesity using the FRIEND equation compared to the WH equations. In the clinical cohort, we evaluated 2471 patients (56.9% male, 22% with BMI >30 kg/m 2 , pVO 2 26.8 mlO 2 /kg/min). The Bland-Altman plot revealed an average relative difference of -1.7% (95% CI: -2.1 to -1.2%) between WH and FRIEND ppVO 2 values with greater differences among those with obesity. Analysis of the VO 2 ratio to ppVO 2 slopes across the BMI spectrum confirmed the assumption of lower fitness in those with obesity, and this trend was more pronounced using the FRIEND equation. Peak VO 2 estimations between the WH and FRIEND equations differed significantly among individuals with obesity. The FRIEND equation resulted in a greater attributable reduction in pVO 2 associated with obesity relative to the WH equations. The outlined relationships between BMI and predicted VO 2 may better inform the clinical interpretation of ppVO 2 values during cardiopulmonary exercise test evaluations., (© 2024 World Obesity Federation.)

Aims: We aimed to investigate the association between the exercise systolic blood pressure (SBP) response and future hypertension (HTN) in normotensive individuals referred for cycle ergometry, with special regard to reference exercise SBP values and exercise capacity., Methods and Results: In this longitudinal cohort study, data from 14 428 exercise tests were cross-linked with Swedish national registries on diagnoses and medications. We excluded individuals with a baseline diagnosis of cardiovascular disease or HTN. The peak exercise SBP (SBPpeak) was recorded and compared with the upper limit of normal (ULN) derived from SBPpeak reference equations incorporating age, sex, resting SBP, and exercise capacity. To evaluate the impact of exercise capacity, three SBP to work rate slopes (SBP/W-slopes) were calculated, relative to either supine or seated SBP at rest or to the first exercise SBP. Adjusted hazard ratios [HRadjusted (95% confidence interval, CI)] for incident HTN during follow-up, in relation to SBP response metrics, were calculated. We included 3895 normotensive individuals (49 ± 14 years, 45% females) with maximal cycle ergometer tests. During follow-up (median 7.5 years), 22% developed HTN. Higher SBPpeak and SBPpeak > ULN were associated with incident HTN [HRadjusted 1.19 (1.14-1.23) per 10 mmHg, and 1.95 (1.54-2.47), respectively]. All three SBP/W-slopes were positively associated with incident HTN, particularly the SBP/W-slope calculated as supine-to-peak SBP [HRadjusted 1.25 (1.19-1.31) per 1 mmHg/10 W]., Conclusion: Both SBPpeak > ULN based on reference values and high SBP/W-slopes were associated with incident HTN in normotensive individuals and should be considered in the evaluation of the cycle ergometry SBP response., Competing Interests: Conflict of interest: none declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Objectives: Physical performance tests are predictive of mortality and may screen for certain health conditions (e.g., sarcopenia); however, their diagnostic and/or prognostic value has primarily been studied in age-limited or disease-specific cohorts. Our objective was to identify the most salient characteristics associated with three lower quarter balance and strength tests in a cohort of community-dwelling adults., Methods: We applied a stacked elastic net approach on detailed data on sociodemographic, health and health-related behaviors, and biomarker data from the first visit of the Project Baseline Health Study ( N  = 2,502) to determine which variables were most associated with three physical performance measures: single-legged balance test (SLBT), sitting-rising test (SRT), and 30-second chair-stand test (30CST). Analyses were stratified by age (<65 and ≥65)., Results: Female sex, Black or African American race, lower educational attainment, and health conditions such as non-alcoholic fatty liver disease and cardiovascular conditions (e.g., hypertension) were consistently associated with worse performance across all three tests. Several other health conditions were associated with either better or worse test performance, depending on age group and test. C-reactive protein was the only laboratory value associated with performance across age and test groups with some consistency., Conclusions: Our results highlighted previously identified and several novel salient factors associated with performance on the SLBT, SRT, and 30CST. These tests could represent affordable, noninvasive biomarkers of prevalent and/or future disease in adult individuals; future research should validate these findings., Clinical Trial Registration: ClinicalTrials.gov, identifier NCT03154346, registered on May 15, 2017., Competing Interests: MC and SS are employees of Verily Life Sciences. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Taylor, Carroll, Short, Celestin, Gilbertson, Olivier, Haddad and Cauwenberghs.)

Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Exercise capacity (EC) is an important predictor of survival in the general population and in subjects with cardiopulmonary disease. Despite its relevance, considering the percent-predicted workload (%pWL) given by current equations may overestimate EC in older adults. Therefore, to improve the reporting of EC in clinical practice, our main objective was to develop workload reference equations (pWL) that better reflect the relation between workload and age. Using the Fitness Registry and the Importance of Exercise National Database (FRIEND), we analyzed a reference group of 6,966 apparently healthy participants and 1,060 participants with heart failure who underwent graded treadmill cardiopulmonary exercise testing. For the first group, the mean age was 44 years (18 to 79); 56.5% of participants were males and 15.4% had obesity. Peak oxygen consumption was 11.6 ± 3.0 METs in males and 8.5 ± 2.4 METs in females. After partition analysis, we first developed sex-specific pWL equations to allow comparisons to a healthy weight reference. For males, pWL (METs) = 14.1-0.9×10 -3 ×age 2 and 11.5-0.87×10 -3 ×age 2 for females. We used those equations as denominators of %pWL, and based on their distribution, we determined thresholds for EC classification, with average EC defined by the range corresponding to 85% to 115%pWL. Compared with %pWL using current equations, the new equations yielded better-calibrated %pWL across different age ranges. We also derived body mass index-adjusted pWL equations that better assessed EC in subjects with heart failure. In conclusion, the novel pWL equations have the potential to impact the report of EC in practice., Competing Interests: Declaration of competing interest The authors have no competing interests to declare., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: There is a need for better understanding the factors that modulate left atrial (LA) dysfunction. Therefore, we determined associations of clinical and biochemical biomarkers with serial changes in echocardiographic indexes of LA function in the general population., Methods: We measured LA maximal and minimal volume indexes (LAVImax and LAVImin) by echocardiography and LA reservoir strain (LARS) by two-dimensional speckle-tracking in 627 participants (mean age 50.8 years, 51.2% women) at baseline and after 4.8 years., Results: During follow-up, LARS decreased significantly in men (-.90%, P = .033) but not in women (-.23%, P = .60). In stepwise regression analysis, stronger decrease in LARS over time was associated with male sex, a higher age, body mass index (BMI), mean arterial pressure (MAP) and serum insulin at baseline and with a greater increase in BMI and MAP over time (P ≤ .018). Similarly, an increased risk of developing or retaining abnormal LARS was observed in older participants, in subjects with a higher baseline BMI, MAP, heart rate (HR), troponin T and ΔMAP, and in those who used β-blockers at baseline. Both LAVImax and LAVImin increased significantly over time (P ≤ .0007). This increase was associated with a higher baseline age, pulse pressure and a lower HR at baseline and a greater increase in pulse pressure over time (P ≤ .029). Higher serum insulin and D-dimer were independently associated with a stronger increase in LAVImin (P ≤ .0034)., Conclusion: Subclinical worsening in LA dysfunction was associated with older age, hypertension, obesity, insulin resistance and troponin T levels. Cardiovascular risk management strategies may delay LA deterioration., (© 2024 Wiley Periodicals LLC.)