Proteomic analysis of cardiorespiratory fitness for prediction of mortality and multisystem disease risks.

Despite the wide effects of cardiorespiratory fitness (CRF) on metabolic, cardiovascular, pulmonary and neurological health, challenges in the feasibility and reproducibility of CRF measurements have impeded its use for clinical decision-making. Here we link proteomic profiles to CRF in 14,145 individuals across four international cohorts with diverse CRF ascertainment methods to establish, validate and characterize a proteomic CRF score. In a cohort of around 22,000 individuals in the UK Biobank, a proteomic CRF score was associated with a reduced risk of all-cause mortality (unadjusted hazard ratio 0.50 (95% confidence interval 0.48-0.52) per 1 s.d. increase). The proteomic CRF score was also associated with multisystem disease risk and provided risk reclassification and discrimination beyond clinical risk factors, as well as modulating high polygenic risk of certain diseases. Finally, we observed dynamicity of the proteomic CRF score in individuals who undertook a 20-week exercise training program and an association of the score with the degree of the effect of training on CRF, suggesting potential use of the score for personalization of exercise recommendations. These results indicate that population-based proteomics provides biologically relevant molecular readouts of CRF that are additive to genetic risk, potentially modifiable and clinically translatable.

Nicotinamide riboside for peripheral artery disease: the NICE randomized clinical trial.

People with lower extremity peripheral artery disease (PAD) have increased oxidative stress, impaired mitochondrial activity, and poor walking performance. NAD+ reduces oxidative stress and is an essential cofactor for mitochondrial respiration. Oral nicotinamide riboside (NR) increases bioavailability of NAD+ in humans. Among 90 people with PAD, this randomized double-blind clinical trial assessed whether 6-months of NR, with and without resveratrol, improves 6-min walk distance, compared to placebo, at 6-month follow-up. At 6-month follow-up, compared to placebo, NR significantly improved 6-min walk (+7.0 vs. -10.6 meters, between group difference: +17.6 (90% CI: + 1.8,+∞). Among participants who took at least 75% of study pills, compared to placebo, NR improved 6-min walk by 31.0 meters and NR + resveratrol improved 6-min walk by 26.9 meters. In this work, NR meaningfully improved 6-min walk, and resveratrol did not add benefit to NR alone in PAD. A larger clinical trial to confirm these findings is needed.

Designing target trials using electronic health records: A case study of second-line disease-modifying anti-rheumatic drugs and cardiovascular disease outcomes in patients with rheumatoid arthritis.

BACKGROUND: Emulation of the "target trial" (TT), a hypothetical pragmatic randomized controlled trial (RCT), using observational data can be used to mitigate issues commonly encountered in comparative effectiveness research (CER) when randomized trials are not logistically, ethically, or financially feasible. However, cardiovascular (CV) health research has been slow to adopt TT emulation. Here, we demonstrate the design and analysis of a TT emulation using electronic health records to study the comparative effectiveness of the addition of a disease-modifying anti-rheumatic drug (DMARD) to a regimen of methotrexate on CV events among rheumatoid arthritis (RA) patients. METHODS: We used data from an electronic medical records-based cohort of RA patients from Northwestern Medicine to emulate the TT. Follow-up began 3 months after initial prescription of MTX (2000-2020) and included all available follow-up through June 30, 2020. Weighted pooled logistic regression was used to estimate differences in CVD risk and survival. Cloning was used to handle immortal time bias and weights to improve baseline and time-varying covariate imbalance. RESULTS: We identified 659 eligible people with RA with average follow-up of 46 months and 31 MACE events. The month 24 adjusted risk difference for MACE comparing initiation vs non-initiation of a DMARD was -1.47% (95% confidence interval [CI]: -4.74, 1.95%), and the marginal hazard ratio (HR) was 0.72 (95% CI: 0.71, 1.23). In analyses subject to immortal time bias, the HR was 0.62 (95% CI: 0.29-1.44). CONCLUSION: In this sample, we did not observe evidence of differences in risk of MACE, a finding that is compatible with previously published meta-analyses of RCTs. Thoughtful application of the TT framework provides opportunities to conduct CER in observational data. Benchmarking results of observational analyses to previously published RCTs can lend credibility to interpretation.

Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1% (SBP) and 4.7 to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

Association of Cardiovascular Health in Young Adulthood with Long-Term Blood Pressure Trajectories.

BACKGROUND: Cardiovascular health (CVH) in young adulthood (YA) has been associated with cardiovascular outcomes in older age. However, little is known about the relationship between YA CVH and mid-life BP trajectories. METHODS: Baseline CVH (defined by 7 of AHA's Life's Essential 8 [LE8] metrics, excluding BP) was measured in YA with individual metrics scored and averaged as a composite LE8 score. Categorical CVH status was defined as high, moderate, and low. Latent class analysis was used to identify trajectories of mid-BP (mean of SBP and DBP) from average ages 35 to 55 years. Multinomial logistic regression was used to estimate the association of YA CVH status (continuously and categorically) with mid-life BP trajectory group membership. RESULTS: There were 3,688 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study in YA with follow-up data for mid-life BP trajectories. We observed 3 BP trajectory groups, labeled as Persistently-Low, Middle, and High-Increasing. On average, each 10-points higher baseline LE8 score (mean [SD] of 73.5 [13.1]) in YA was associated with adjusted odds ratios of 0.78 (95% CI, 0.72-0.84) for membership in the Middle and 0.65 (0.57-0.73) for membership in the High-Increasing trajectory groups. Compared with categorical low CVH status at baseline, those with high CVH were significantly less likely to be in the Middle and High-Increasing BP trajectory groups. CONCLUSIONS: Moderate or low CVH status in YA is associated with elevated mid-life BP trajectory. These data suggest that young adult CVH promotion may be important for primordial prevention of hypertension.

Association Between Life's Essential 8 Cardiovascular Health Metrics With Cardiovascular Events in the Cardiovascular Disease Lifetime Risk Pooling Project.

BACKGROUND: The American Heart Association recently launched updated cardiovascular health metrics, termed Life's Essential 8 (LE8). Compared with Life's Simple 7 (LS7), the new approach added sleep health as an eighth metric and updated the remaining 7 health factors and behaviors. The association of the updated LE8 score with long-term cardiovascular disease (CVD) outcomes and death is unknown. METHODS: We pooled individual-level data from 6 contemporary US-based cohorts from the Cardiovascular Lifetime Risk Pooling Project. Total LE8 score (0-100 points), LE8 score without sleep (0-100 points), and prior LS7 scores (0-14 points) were calculated separately. We used multivariable-adjusted Cox models to evaluate the association of LE8 with CVD, CVD subtypes, and all-cause mortality among younger, middle, and older adult participants. Net reclassification improvement analysis was used to measure the improvement in CVD risk classification with the addition of LS7 and LE8 recategorization based on score quartile rankings. RESULTS: Our sample consisted of 32 896 US adults (7836 [23.8%] Black; 14 941 [45.4%] men) followed for 642 000 person-years, of whom 9391 developed CVD events. Each 10-point higher overall LE8 score was associated with lower risk by 22% to 40% for CVD, 24% to 43% for congenital heart disease, 17% to 34% for stroke, 23% to 38% for heart failure, and 17% to 21% for all causes of mortality events across age strata. LE8 score provided more granular differentiation of the related CVD risk than LS7. Overall, 19.5% and 15.5% of the study participants were recategorized upward and downward based on LE8 versus LS7 categories, respectively, and the recategorization was significantly associated with CVD risk in addition to LS7 score. The addition of recategorization between LE8 and LS7 categories improved CVD risk reclassification across age groups (clinical net reclassification improvement, 0.06-0.12; P<0.01). CONCLUSIONS: These findings support the improved utility of the LE8 algorithm for assessing overall cardiovascular health and future CVD risk.

Efficacy and safety of a four-drug, quarter-dose treatment for hypertension: the QUARTET USA randomized trial.

New approaches are needed to lower blood pressure (BP) given persistently low control rates. QUARTET USA sought to evaluate the effect of four-drug, quarter-dose BP lowering combination in patients with hypertension. QUARTET USA was a randomized (1:1), double-blinded trial conducted in federally qualified health centers among adults with hypertension. Participants received either a quadpill of candesartan 2 mg, amlodipine 1.25 mg, indapamide 0.625 mg, and bisoprolol 2.5 mg or candesartan 8 mg for 12 weeks. If BP was >130/>80 mm Hg at 6 weeks in either arm, then participants received open label add-on amlodipine 5 mg. The primary outcome was mean change in systolic blood pressure (SBP) at 12 weeks, controlling for baseline BP. Secondary outcomes included mean change in diastolic blood pressure (DBP), and safety included serious adverse events, relevant adverse drug effects, and electrolyte abnormalities. Among 62 participants randomized between August 2019-May 2022 (n = 32 intervention, n = 30 control), mean (SD) age was 52 (11.5) years, 45% were female, 73% identified as Hispanic, and 18% identified as Black. Baseline mean (SD) SBP was 138.1 (11.2) mmHg, and baseline mean (SD) DBP was 84.3 (10.5) mmHg. In a modified intention-to-treat analysis, there was no significant difference in SBP (-4.8 mm Hg [95% CI: -10.8, 1.3, p = 0.123] and a -4.9 mmHg (95% CI: -8.6, -1.3, p = 0.009) greater mean DBP change in the intervention arm compared with the control arm at 12 weeks. Adverse events did not differ significantly between arms. The quadpill had a similar SBP and greater DBP lowering effect compared with candesartan 8 mg. Trial registration number: NCT03640312.

Association of epicardial adipose tissue with early structural and functional cardiac changes in Type 2 diabetes.

BACKGROUND: Dysregulated epicardial adipose tissue (EAT) may contribute to the development of heart failure in Type 2 diabetes (T2D). This study aimed to evaluate the associations between EAT volume and composition with imaging markers of subclinical cardiac dysfunction in people with T2D and no prevalent cardiovascular disease. METHODS: Prospective case-control study enrolling participants with and without T2D and no known cardiovascular disease. Two hundred and fifteen people with T2D (median age 63 years, 60 % male) and thirty-nine non-diabetics (median age 59 years, 62 % male) were included. Using computed tomography (CT), total EAT volume and mean CT attenuation, as well as, low attenuation (Hounsfield unit range -190 to -90) EAT volume were quantified by a deep learning method and volumes indexed to body surface area. Associations with cardiac magnetic resonance-derived left ventricular (LV) volumes and strain indices were assessed using linear regression. RESULTS: T2D participants had higher LV mass/volume ratio (median 0.89 g/mL [0.82-0.99] vs 0.79 g/mL [0.75-0.89]) and lower global longitudinal strain (GLS; 16.1 ± 2.3 % vs 17.2 ± 2.2 %). Total indexed EAT volume correlated inversely with mean CT attenuation. Low attenuation indexed EAT volume was 2-fold higher (18.8 cm3/m2 vs. 9.4 cm3/m2, p < 0.001) in T2D and independently associated with LV mass/volume ratio (ß = 0.002, p = 0.01) and GLS (ß = -0.03, p = 0.03). CONCLUSIONS: Higher EAT volumes seen in T2D are associated with a lower mean CT attenuation. Low attenuation indexed EAT volume is independently, but only weakly, associated with markers of subclinical cardiac dysfunction in T2D.

Use of Nonhuman Sera as a Highly Cost-Effective Internal Standard for Quantitation of Multiple Human Proteins Using Species-Specific Tryptic Peptides: Applicability in Clinical LC-MS Analyses.

Quantitation of proteins using liquid chromatography-tandem mass spectrometry (LC-MS/MS) is complex, with a multiplicity of options ranging from label-free techniques to chemically and metabolically labeling proteins. Increasingly, for clinically relevant analyses, stable isotope-labeled (SIL) internal standards (ISs) represent the "gold standard" for quantitation due to their similar physiochemical properties to the analyte, wide availability, and ability to multiplex to several peptides. However, the purchase of SIL-ISs is a resource-intensive step in terms of cost and time, particularly for screening putative biomarker panels of hundreds of proteins. We demonstrate an alternative strategy utilizing nonhuman sera as the IS for quantitation of multiple human proteins. We demonstrate the effectiveness of this strategy using two high abundance clinically relevant analytes, vitamin D binding protein [Gc globulin] (DBP) and albumin (ALB). We extend this to three putative risk markers for cardiovascular disease: plasma protease C1 inhibitor (SERPING1), annexin A1 (ANXA1), and protein kinase, DNA-activated catalytic subunit (PRKDC). The results show highly specific, reproducible, and linear measurement of the proteins of interest with comparable precision and accuracy to the gold standard SIL-IS technique. This approach may not be applicable to every protein, but for many proteins it can offer a cost-effective solution to LC-MS/MS protein quantitation.

Social and psychosocial determinants of racial and ethnic differences in cardiovascular health: The MASALA and MESA studies.

Background: Social and psychosocial determinants are associated with cardiovascular health (CVH). Objectives: To quantify the contributions of social and psychosocial factors to racial/ethnic differences in CVH. Methods: In the Multi-Ethnic Study of Atherosclerosis and Mediators of Atherosclerosis in South Asians Living in America cohorts, Kitagawa-Blinder-Oaxaca decomposition quantified the contributions of social and psychosocial factors to differences in mean CVH score (range 0-14) in Black, Chinese, Hispanic, or South Asian compared with White participants. Results: Among 7,978 adults (mean age 61 [SD 10] years, 52 % female), there were 1,892 Black (mean CVH score for decomposition analysis 7.96 [SD 2.1]), 804 Chinese (CVH 9.69 [1.8]), 1,496 Hispanic (CVH 8.00 [2.1]), 1,164 South Asian (CVH 9.16 [2.0]), and 2,622 White (CVH 8.91 [2.1]) participants. The factors that were associated with the largest magnitude of explained differences in mean CVH score were income for Black participants (if mean income in Black participants were equal to White participants, Black participants' mean CVH score would be 0.14 [SE 0.05] points higher); place of birth for Chinese participants (if proportion of US-born and foreign-born individuals among Chinese adults were equivalent to White participants, Chinese participants' mean CVH score would be 0.22 [0.10] points lower); and education for Hispanic and South Asian participants (if educational attainment were equivalent to White participants, Hispanic and South Asian participants' mean CVH score would be 0.55 [0.11] points higher and 0.37 [0.11] points lower, respectively). Conclusions: In these multiethnic US cohorts, social and psychosocial factors were associated with racial/ethnic differences in CVH.

A high throughput immuno-affinity mass spectrometry method for detection and quantitation of SARS-CoV-2 nucleoprotein in human saliva and its comparison with RT-PCR, RT-LAMP, and lateral flow rapid antigen test.

OBJECTIVES: Many reverse transcription polymerase chain reaction (RT-PCR) methods exist that can detect SARS-CoV-2 RNA in different matrices. RT-PCR is highly sensitive, although viral RNA may be detected long after active infection has taken place. SARS-CoV-2 proteins have shorter detection windows hence their detection might be more meaningful. Given salivary droplets represent a main source of transmission, we explored the detection of viral RNA and protein using four different detection platforms including SISCAPA peptide immunoaffinity liquid chromatography-mass spectrometry (SISCAPA-LC-MS) using polyclonal capture antibodies. METHODS: The SISCAPA-LC MS method was compared to RT-PCR, RT-loop-mediated isothermal amplification (RT-LAMP), and a lateral flow rapid antigen test (RAT) for the detection of virus material in the drool saliva of 102 patients hospitalised after infection with SARS-CoV-2. Cycle thresholds (Ct) of RT-PCR (E gene) were compared to RT-LAMP time-to-positive (TTP) (NE and Orf1a genes), RAT optical densitometry measurements (test line/control line ratio) and to SISCAPA-LC-MS for measurements of viral protein. RESULTS: SISCAPA-LC-MS showed low sensitivity (37.7 %) but high specificity (89.8 %). RAT showed lower sensitivity (24.5 %) and high specificity (100 %). RT-LAMP had high sensitivity (83.0 %) and specificity (100.0 %). At high initial viral RNA loads (<20 Ct), results obtained using SISCAPA-LC-MS correlated with RT-PCR (R2 0.57, p-value 0.002). CONCLUSIONS: Detection of SARS-CoV-2 nucleoprotein in saliva was less frequent than the detection of viral RNA. The SISCAPA-LC-MS method allowed processing of multiple samples in <150 min and was scalable, enabling high throughput.

Association between secondhand smoke exposure and incident heart failure: The Multi-Ethnic Study of Atherosclerosis (MESA).

AIMS: There are no studies on the association between secondhand smoke (SHS) exposure and incident heart failure (HF). This cohort study aimed to examine the associations of self-reported and urinary cotinine-assessed SHS exposure with incident HF. METHODS AND RESULTS: This study included 5548 non-active smoking participants aged 45-84 years and free of known cardiovascular diseases and HF at baseline who self-reported SHS exposure time in the Multi-Ethnic Study of Atherosclerosis (MESA) at baseline (2000-2002). A cohort subset of 3376 non-active smoking participants underwent urinary cotinine measurements. HF events were verified by medical records or death certificates and ascertained from baseline through 2019. Multivariable Cox proportional hazards regression analysis was used with adjustment for demographic variables, traditional cardiovascular risk factors, physical activity, tobacco pack-years and medications. During a median follow-up of 17.7 years, 353 and 196 HF events were identified in the self-report cohort and cohort subset, respectively. In the self-report cohort, compared with the SHS unexposed group (0 h/week), the highest tertile of the SHS exposed group (7-168 h/week) was not associated with incident HF (hazard ratio [HR] 0.70, 95% confidence interval [CI] 0.49-1.00; p = 0.052). In contrast, in the cohort subset, participants with detectable urinary cotinine >7.07 ng/ml had a higher risk of incident HF than those with undetectable urinary cotinine ≤7.07 ng/ml (HR 1.45, 95% CI 1.03-2.06; p = 0.034). There were no significant heterogeneities in HF risk by age, sex, race/ethnicity, or past smoking status. CONCLUSION: Secondhand smoke exposure reflected by modestly increased urinary cotinine (>7.07 ng/ml) rather than self-report in non-active smokers was associated with a 40-50% higher risk of any HF event.

Association of 20-Year Longitudinal Depressive Symptoms With Left Ventricular Geometry Outcomes in the Coronary Artery Risk Development in Young Adults Study: A Role for Androgens?

OBJECTIVE: Depression is a risk factor for coronary heart disease and left ventricular hypertrophy (LVH) is a potent predictor of coronary heart disease events. Whether depression is associated with LVH has received limited investigation. This study assessed cross-sectional and 20-year longitudinal associations of depressive symptoms with LVH outcomes after accounting for important known confounders. METHODS: From 5115 participants enrolled in 1985-1986 in the Coronary Artery Risk Development in Young Adults Study, 2533 had serial measures of depressive symptoms and subsequent echocardiography to measure normal LV geometry, concentric remodeling, and LVH. The primary exposure variable was trajectories of the Center for Epidemiologic Studies Depression (CES-D) scale score from 1990-1991 to 2010-2011. Multivariable polytomous logistic regression was used to assess associations of trajectories with a composite LV geometry outcome created using echocardiogram data measured in 2010-2011 and 2015-2016. Sex-specific conflicting results led to exploratory models that examined potential importance of testosterone and sex hormone-binding globulin. RESULTS: Overall CES-D and Somatic subscale trajectories had significant associations with LVH for female participants only. Odds ratios for the subthreshold (mean CES-D ≈ 14) and stable (mean CES-D ≈ 19) groups were 1.49 (95% confidence interval = 1.05-2.13) and 1.88 (95% confidence interval = 1.16-3.04), respectively. For female participants, sex hormone-binding globulin was inversely associated with LVH, and for male participants, bioavailable testosterone was positively associated with concentric geometry. CONCLUSIONS: Findings from cross-sectional and longitudinal regression models for female participants, but not male ones, and particularly for Somatic subscale trajectories suggested a plausible link among depression, androgens, and LVH. The role of androgens to the depression-LVH relation requires additional investigation in future studies.

Familial Hypercholesterolemia Variant and Cardiovascular Risk in Individuals With Elevated Cholesterol.

Importance: Familial hypercholesterolemia (FH) is a genetic disorder that often results in severely high low-density lipoprotein cholesterol (LDL-C) and high risk of premature coronary heart disease (CHD). However, the impact of FH variants on CHD risk among individuals with moderately elevated LDL-C is not well quantified. Objective: To assess CHD risk associated with FH variants among individuals with moderately (130-189 mg/dL) and severely (≥190 mg/dL) elevated LDL-C and to quantify excess CHD deaths attributable to FH variants in US adults. Design, Setting, and Participants: A total of 21 426 individuals without preexisting CHD from 6 US cohort studies (Atherosclerosis Risk in Communities study, Coronary Artery Risk Development in Young Adults study, Cardiovascular Health Study, Framingham Heart Study Offspring cohort, Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis) were included, 63 of whom had an FH variant. Data were collected from 1971 to 2018, and the median (IQR) follow-up was 18 (13-28) years. Data were analyzed from March to May 2023. Exposures: LDL-C, cumulative past LDL-C, FH variant status. Main Outcomes and Measures: Cox proportional hazards models estimated associations between FH variants and incident CHD. The Cardiovascular Disease Policy Model projected excess CHD deaths associated with FH variants in US adults. Results: Of the 21 426 individuals without preexisting CHD (mean [SD] age 52.1 [15.5] years; 12 041 [56.2%] female), an FH variant was found in 22 individuals with moderately elevated LDL-C (0.3%) and in 33 individuals with severely elevated LDL-C (2.5%). The adjusted hazard ratios for incident CHD comparing those with and without FH variants were 2.9 (95% CI, 1.4-6.0) and 2.6 (95% CI, 1.4-4.9) among individuals with moderately and severely elevated LDL-C, respectively. The association between FH variants and CHD was slightly attenuated when further adjusting for baseline LDL-C level, whereas the association was no longer statistically significant after adjusting for cumulative past LDL-C exposure. Among US adults 20 years and older with no history of CHD and LDL-C 130 mg/dL or higher, more than 417 000 carry an FH variant and were projected to experience more than 12 000 excess CHD deaths in those with moderately elevated LDL-C and 15 000 in those with severely elevated LDL-C compared with individuals without an FH variant. Conclusions and Relevance: In this pooled cohort study, the presence of FH variants was associated with a 2-fold higher CHD risk, even when LDL-C was only moderately elevated. The increased CHD risk appeared to be largely explained by the higher cumulative LDL-C exposure in individuals with an FH variant compared to those without. Further research is needed to assess the value of adding genetic testing to traditional phenotypic FH screening.

Circulating sphingolipids and relationship to cardiac remodelling before and following a low-energy diet in asymptomatic Type 2 Diabetes.

BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is a heterogenous multi-system syndrome with limited efficacious treatment options. The prevalence of Type 2 diabetes (T2D) continues to rise and predisposes patients to HFpEF, and HFpEF remains one of the biggest challenges in cardiovascular medicine today. Novel therapeutic targets are required to meet this important clinical need. Deep phenotyping studies including -OMIC analyses can provide important pathogenic information to aid the identification of such targets. The aims of this study were to determine; 1) the impact of a low-energy diet on plasma sphingolipid/ceramide profiles in people with T2D compared to healthy controls and, 2) if the change in sphingolipid/ceramide profile is associated with reverse cardiovascular remodelling. METHODS: Post-hoc analysis of a randomised controlled trial (NCT02590822) including adults with T2D with no cardiovascular disease who completed a 12-week low-energy (∼810 kcal/day) meal-replacement plan (MRP) and matched healthy controls (HC). Echocardiography, cardiac MRI and a fasting blood for lipidomics were undertaken pre/post-intervention. Candidate biomarkers were identified from case-control comparison (fold change > 1.5 and statistical significance p < 0.05) and their response to the MRP reported. Association between change in biomarkers and change indices of cardiac remodelling were explored. RESULTS: Twenty-four people with T2D (15 males, age 51.1 ± 5.7 years), and 25 HC (15 male, 48.3 ± 6.6 years) were included. Subjects with T2D had increased left ventricular (LV) mass:volume ratio (0.84 ± 0.13 vs. 0.70 ± 0.08, p < 0.001), increased systolic function but impaired diastolic function compared to HC. Twelve long-chain polyunsaturated sphingolipids, including four ceramides, were downregulated in subjects with T2D at baseline. Three sphingomyelin species and all ceramides were inversely associated with LV mass:volume. There was a significant increase in all species and shift towards HC following the MRP, however, none of these changes were associated with reverse cardiac remodelling. CONCLUSION: The lack of association between change in sphingolipids/ceramides and reverse cardiac remodelling following the MRP casts doubt on a causative role of sphingolipids/ceramides in the progression of heart failure in T2D. TRIAL REGISTRATION: NCT02590822.

Incorporating longitudinal history of risk factors into atherosclerotic cardiovascular disease risk prediction using deep learning.

It is increasingly clear that longitudinal risk factor levels and trajectories are related to risk for atherosclerotic cardiovascular disease (ASCVD) above and beyond single measures. Currently used in clinical care, the Pooled Cohort Equations (PCE) are based on regression methods that predict ASCVD risk based on cross-sectional risk factor levels. Deep learning (DL) models have been developed to incorporate longitudinal data for risk prediction but its benefit for ASCVD risk prediction relative to the traditional Pooled Cohort Equations (PCE) remain unknown. Our study included 15,565 participants from four cardiovascular disease cohorts free of baseline ASCVD who were followed for adjudicated ASCVD. Ten-year ASCVD risk was calculated in the training set using our benchmark, the PCE, and a longitudinal DL model, Dynamic-DeepHit. Predictors included those incorporated in the PCE: sex, race, age, total cholesterol, high density lipid cholesterol, systolic and diastolic blood pressure, diabetes, hypertension treatment and smoking. The discrimination and calibration performance of the two models were evaluated in an overall hold-out testing dataset. Of the 15,565 participants in our dataset, 2170 (13.9%) developed ASCVD. The performance of the longitudinal DL model that incorporated 8 years of longitudinal risk factor data improved upon that of the PCE [AUROC: 0.815 (CI 0.782-0.844) vs 0.792 (CI 0.760-0.825)] and the net reclassification index was 0.385. The brier score for the DL model was 0.0514 compared with 0.0542 in the PCE. Incorporating longitudinal risk factors in ASCVD risk prediction using DL can improve model discrimination and calibration.

Longitudinal clustering of Life's Essential 8 health metrics: application of a novel unsupervised learning method in the CARDIA study.

OBJECTIVE: Changes in cardiovascular health (CVH) during the life course are associated with future cardiovascular disease (CVD). Longitudinal clustering analysis using subgraph augmented non-negative matrix factorization (SANMF) could create phenotypic risk profiles of clustered CVH metrics. MATERIALS AND METHODS: Life's Essential 8 (LE8) variables, demographics, and CVD events were queried over 15 ears in 5060 CARDIA participants with 18 years of subsequent follow-up. LE8 subgraphs were mined and a SANMF algorithm was applied to cluster frequently occurring subgraphs. K-fold cross-validation and diagnostics were performed to determine cluster assignment. Cox proportional hazard models were fit for future CV event risk and logistic regression was performed for cluster phenotyping. RESULTS: The cohort (54.6% female, 48.7% White) produced 3 clusters of CVH metrics: Healthy & Late Obesity (HLO) (29.0%), Healthy & Intermediate Sleep (HIS) (43.2%), and Unhealthy (27.8%). HLO had 5 ideal LE8 metrics between ages 18 and 39 years, until BMI increased at 40. HIS had 7 ideal LE8 metrics, except sleep. Unhealthy had poor levels of sleep, smoking, and diet but ideal glucose. Race and employment were significantly different by cluster (P < .001) but not sex (P = .734). For 301 incident CV events, multivariable hazard ratios (HRs) for HIS and Unhealthy were 0.73 (0.53-1.00, P = .052) and 2.00 (1.50-2.68, P < .001), respectively versus HLO. A 15-year event survival was 97.0% (HIS), 96.3% (HLO), and 90.4% (Unhealthy, P < .001). DISCUSSION AND CONCLUSION: SANMF of LE8 metrics identified 3 unique clusters of CVH behavior patterns. Clustering of longitudinal LE8 variables via SANMF is a robust tool for phenotypic risk assessment for future adverse cardiovascular events.

Epigenetic Aging Is Associated With Measures of Midlife Muscle Volume and Attenuation in CARDIA Study.

BACKGROUND: GrimAge acceleration (GAA), an epigenetic marker that represents physiologic aging, is associated with age-related diseases including cancer and cardiovascular diseases. However, the associations between GAA and muscle mass and function are unknown. METHODS: We estimated measures of GAA in 1 118 Black and White participants from the Coronary Artery Risk Development in Young Adults (CARDIA) Study at exam years (Y) 15 (2000-2001) and 20 (2005-2006). Abdominal muscle composition was measured using CT scans at the Y25 (2010-2011) visit. We used multivariate regression models to examine associations of GAA estimates with muscle imaging measurements. RESULTS: In the CARDIA study, each 1-year higher GAA was associated with an average 1.1% (95% confidence interval [CI]: 0.6%, 1.5%) higher intermuscular adipose tissue (IMAT) volume for abdominal muscles. Each 1-year higher GAA was associated with an average -0.089 Hounsfield unit (HU; 95% CI: -0.146, -0.032) lower lean muscle attenuation and an average -0.049 HU (95% CI: -0.092, -0.007) lower IMAT attenuation for abdominal muscles. Stratified analyses showed that GAA was more strongly associated with higher abdominal muscle IMAT volume in females and significantly associated with lower lean muscle attenuation for White participants only. CONCLUSIONS: Higher GAA is associated with higher abdominal muscle IMAT volume and lower lean muscle attenuation in a midlife population.

Development and Validation of the American Heart Association's PREVENT Equations.

BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD. METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets. RESULTS: Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P=0.01). CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.