Genetic Architecture and Clinical Outcomes of Combined Lipid Disturbances.

BACKGROUND: Dyslipoproteinemia often involves simultaneous derangements of multiple lipid traits. We aimed to evaluate the phenotypic and genetic characteristics of combined lipid disturbances in a general population-based cohort. METHODS: Among UK Biobank participants without prevalent coronary artery disease, we used blood lipid and apolipoprotein B concentrations to ascribe individuals into 1 of 6 reproducible and mutually exclusive dyslipoproteinemia subtypes. Incident coronary artery disease risk was estimated for each subtype using Cox proportional hazards models. Phenome-wide analyses and genome-wide association studies were performed for each subtype, followed by in silico causal gene prioritization and heritability analyses. Additionally, the prevalence of disruptive variants in causal genes for Mendelian lipid disorders was assessed using whole-exome sequence data. RESULTS: Among 450 636 UK Biobank participants: 63 (0.01%) had chylomicronemia; 40 005 (8.9%) had hypercholesterolemia; 94 785 (21.0%) had combined hyperlipidemia; 13 998 (3.1%) had remnant hypercholesterolemia; 110 389 (24.5%) had hypertriglyceridemia; and 49 (0.01%) had mixed hypertriglyceridemia and hypercholesterolemia. Over a median (interquartile range) follow-up of 11.1 (10.4-11.8) years, incident coronary artery disease risk varied across subtypes, with combined hyperlipidemia exhibiting the largest hazard (hazard ratio, 1.92 [95% CI, 1.84-2.01]; P=2×10-16), even when accounting for non-HDL-C (hazard ratio, 1.45 [95% CI, 1.30-1.60]; P=2.6×10-12). Genome-wide association studies revealed 250 loci significantly associated with dyslipoproteinemia subtypes, of which 72 (28.8%) were not detected in prior single lipid trait genome-wide association studies. Mendelian lipid variant carriers were rare (2.0%) among individuals with dyslipoproteinemia, but polygenic heritability was high, ranging from 23% for remnant hypercholesterolemia to 54% for combined hyperlipidemia. CONCLUSIONS: Simultaneous assessment of multiple lipid derangements revealed nuanced differences in coronary artery disease risk and genetic architectures across dyslipoproteinemia subtypes. These findings highlight the importance of looking beyond single lipid traits to better understand combined lipid and lipoprotein phenotypes and implications for disease risk.

A multivariate genome-wide association study of psycho-cardiometabolic multimorbidity.

Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D (rg = 0.39, P = 2e-34) and weakly correlated with depression (rg = 0.13, P = 3e-6). Depression was weakly correlated with T2D (rg = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank (N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74-2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways.

Nonischemic or Dual Cardiomyopathy in Patients With Coronary Artery Disease.

BACKGROUND: Randomized trials in obstructive coronary artery disease (CAD) have largely shown no prognostic benefit from coronary revascularization. Although there are several potential reasons for the lack of benefit, an underexplored possible reason is the presence of coincidental nonischemic cardiomyopathy (NICM). We investigated the prevalence and prognostic significance of NICM in patients with CAD (CAD-NICM). METHODS: We conducted a registry study of consecutive patients with obstructive CAD on coronary angiography who underwent contrast-enhanced cardiovascular magnetic resonance imaging for the assessment of ventricular function and scar at 4 hospitals from 2004 to 2020. We identified the presence and cause of cardiomyopathy using cardiovascular magnetic resonance imaging and coronary angiography data, blinded to clinical outcomes. The primary outcome was a composite of all-cause death or heart failure hospitalization, and secondary outcomes were all-cause death, heart failure hospitalization, and cardiovascular death. RESULTS: Among 3023 patients (median age, 66 years; 76% men), 18.2% had no cardiomyopathy, 64.8% had ischemic cardiomyopathy (CAD+ICM), 9.3% had CAD+NICM, and 7.7% had dual cardiomyopathy (CAD+dualCM), defined as both ICM and NICM. Thus, 16.9% had CAD+NICM or dualCM. During a median follow-up of 4.8 years (interquartile range, 2.9, 7.6), 1116 patients experienced the primary outcome. In Cox multivariable analysis, CAD+NICM or dualCM was independently associated with a higher risk of the primary outcome compared with CAD+ICM (adjusted hazard ratio, 1.23 [95% CI, 1.06-1.43]; P=0.007) after adjustment for potential confounders. The risks of the secondary outcomes of all-cause death and heart failure hospitalization were also higher with CAD+NICM or dualCM (hazard ratio, 1.21 [95% CI, 1.02-1.43]; P=0.032; and hazard ratio, 1.37 [95% CI, 1.11-1.69]; P=0.003, respectively), whereas the risk of cardiovascular death did not differ from that of CAD+ICM (hazard ratio, 1.15 [95% CI, 0.89-1.48]; P=0.28). CONCLUSIONS: In patients with CAD referred for clinical cardiovascular magnetic resonance imaging, NICM or dualCM was identified in 1 of every 6 patients and was associated with worse long-term outcomes compared with ICM. In patients with obstructive CAD, coincidental NICM or dualCM may contribute to the lack of prognostic benefit from coronary revascularization.

Associations of Urban Blue and Green Spaces With Coronary Artery Calcification in Black Individuals and Disadvantaged Neighborhoods.

BACKGROUND: Proximity to urban blue and green spaces has been associated with improved cardiovascular health; however, few studies have examined the role of race and socioeconomic status in these associations. METHODS: Data were from the CARDIA study (Coronary Artery Risk Development in Young Adults). We included longitudinal measurements (1985-1986 to 2010-2011) of blue and green spaces, including percentage of blue space cover, distance to the nearest river, green space cover, and distance to the nearest major park. Presence of coronary artery calcification (CAC) was measured with noncontrast cardiac computed tomography in 2010 to 2011. The associations of blue and green spaces with CAC were assessed with generalized estimating equation regression with adjustment for demographics, individual and neighborhood socioeconomic status, health-related behaviors, and other health conditions. We conducted stratified analyses by race and neighborhood deprivation score to investigate whether the association varied according to social determinants of health. RESULTS: The analytic sample included 1365 Black and 1555 White participants with a mean±SD age of 50.1±3.6 years. Among Black participants, shorter distance to a river and greater green space cover were associated with lower odds of CAC (per interquartile range decrease [1.45 km] to the river: odds ratio [OR], 0.90 [95% CI, 0.84-0.96]; per 10 percentage-point increase of green space cover: OR, 0.85 [95% CI, 0.75-0.95]). Among participants in deprived neighborhoods, greater green space cover was associated with lower odds of CAC (per a 10 percentage-point increase: OR, 0.89 [95% CI, 0.80-0.99]), whereas shorter distance to the park was associated with higher odds of CAC (per an interquartile range decrease [5.3 km]: OR, 1.07 [95% CI, 1.00-1.15]). Black participants in deprived neighborhoods had lower odds of CAC with shorter distance to a river (per an interquartile range decrease: OR, 0.90 [95% CI, 0.82-0.98]) and greater green space cover (per a 10 percentage-point increase: OR, 0.85 [95% CI, 0.75-0.97]). There was no statistical interaction between the blue and green spaces and race or neighborhood characteristics in association with CAC. CONCLUSIONS: Longitudinally, shorter distance to a river and greater green space cover were associated with less CAC among Black participants and those in deprived neighborhoods. Shorter distance to a park was associated with increased odds of CAC among participants in deprived neighborhoods. Black participants residing in more deprived neighborhoods showed lower odds of CAC in association with greater exposure to river and green space cover.

Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study.

BACKGROUND: Coronary computed tomography angiography (CCTA) is the first line investigation for chest pain, and it is used to guide revascularisation. However, the widespread adoption of CCTA has revealed a large group of individuals without obstructive coronary artery disease (CAD), with unclear prognosis and management. Measurement of coronary inflammation from CCTA using the perivascular fat attenuation index (FAI) Score could enable cardiovascular risk prediction and guide the management of individuals without obstructive CAD. The Oxford Risk Factors And Non-invasive imaging (ORFAN) study aimed to evaluate the risk profile and event rates among patients undergoing CCTA as part of routine clinical care in the UK National Health Service (NHS); to test the hypothesis that coronary arterial inflammation drives cardiac mortality or major adverse cardiac events (MACE) in patients with or without CAD; and to externally validate the performance of the previously trained artificial intelligence (AI)-Risk prognostic algorithm and the related AI-Risk classification system in a UK population. METHODS: This multicentre, longitudinal cohort study included 40 091 consecutive patients undergoing clinically indicated CCTA in eight UK hospitals, who were followed up for MACE (ie, myocardial infarction, new onset heart failure, or cardiac death) for a median of 2·7 years (IQR 1·4-5·3). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3393 consecutive patients from the two hospitals with the longest follow-up (7·7 years [6·4-9·1]). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was then evaluated in this population. FINDINGS: In the 2·7 year median follow-up period, patients without obstructive CAD (32 533 [81·1%] of 40 091) accounted for 2857 (66·3%) of the 4307 total MACE and 1118 (63·7%) of the 1754 total cardiac deaths in the whole of Cohort A. Increased FAI Score in all the three coronary arteries had an additive impact on the risk for cardiac mortality (hazard ratio [HR] 29·8 [95% CI 13·9-63·9], p<0·001) or MACE (12·6 [8·5-18·6], p<0·001) comparing three vessels with an FAI Score in the top versus bottom quartile for each artery. FAI Score in any coronary artery predicted cardiac mortality and MACE independently from cardiovascular risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (6·75 [5·17-8·82], p<0·001, for very high risk vs low or medium risk) and MACE (4·68 [3·93-5·57], p<0·001 for very high risk vs low or medium risk). Finally, the AI-Risk model was well calibrated against true events. INTERPRETATION: The FAI Score captures inflammatory risk beyond the current clinical risk stratification and CCTA interpretation, particularly among patients without obstructive CAD. The AI-Risk integrates this information in a prognostic algorithm, which could be used as an alternative to traditional risk factor-based risk calculators. FUNDING: British Heart Foundation, NHS-AI award, Innovate UK, National Institute for Health and Care Research, and the Oxford Biomedical Research Centre.

Age at Menopause, Leukocyte Telomere Length, and Coronary Artery Disease in Postmenopausal Women.

BACKGROUND: Premature menopause is a risk factor for accelerated cardiovascular aging, but underlying mechanisms remain incompletely understood. This study investigated the role of leukocyte telomere length (LTL), a marker of cellular aging and genomic instability, in the association of premature menopause with cardiovascular disease. METHODS: Participants from the UK Biobank and Women's Health Initiative with complete reproductive history and LTL measurements were included. Primary analyses tested the association between age at menopause and LTL using multivariable-adjusted linear regression. Secondary analyses stratified women by history of gynecologic surgery. Mendelian randomization was used to infer causal relationships between LTL and age at natural menopause. Multivariable-adjusted Cox regression and mediation analyses tested the joint associations of premature menopause and LTL with incident coronary artery disease. RESULTS: This study included 130 254 postmenopausal women (UK Biobank: n=122 224; Women's Health Initiative: n=8030), of whom 4809 (3.7%) had experienced menopause before age 40. Earlier menopause was associated with shorter LTL (meta-analyzed ß=-0.02 SD/5 years of earlier menopause [95% CI, -0.02 to -0.01]; P=7.2×10-12). This association was stronger and significant in both cohorts for women with natural/spontaneous menopause (meta-analyzed ß=-0.04 SD/5 years of earlier menopause [95% CI, -0.04 to -0.03]; P<2.2×10-16) and was independent of hormone therapy use. Mendelian randomization supported a causal association of shorter genetically predicted LTL with earlier age at natural menopause. LTL and age at menopause were independently associated with incident coronary artery disease, and mediation analyses indicated small but significant mediation effects of LTL in the association of menopausal age with coronary artery disease. CONCLUSIONS: Earlier age at menopause is associated with shorter LTL, especially among women with natural menopause. Accelerated telomere shortening may contribute to the heightened cardiovascular risk associated with premature menopause.

The Cardio-Kidney Patient: Epidemiology, Clinical Characteristics and Therapy.

Patients with chronic kidney disease (CKD) are at high risk to develop cardiovascular disease with its manifestations coronary artery disease, heart failure, arrhythmias, and sudden cardiac death. In addition, the presence of CKD has a major impact on the prognosis of patients with cardiovascular disease, leading to an increased morbidity and mortality if both comorbidities are present. Therapeutic options including medical therapy and interventional treatment are often limited in patients with advanced CKD, and in most cardiovascular outcome trials, patients with advanced CKD have been excluded. Thus, in many patients, treatment strategies for cardiovascular disease need to be extrapolated from trials conducted in patients without CKD. The current article summarizes the epidemiology, clinical presentation, and treatment options for the most prevalent manifestations of cardiovascular disease in CKD and discusses the currently available treatment options to reduce morbidity and mortality in this high-risk population.

Influence of Polygenic Background on the Clinical Presentation of Familial Hypercholesterolemia.

BACKGROUND: Heterozygous familial hypercholesterolemia (FH) is among the most common genetic conditions worldwide that affects ≈ 1 in 300 individuals. FH is characterized by increased levels of low-density lipoprotein cholesterol (LDL-C) and increased risk of coronary artery disease (CAD), but there is a wide spectrum of severity within the FH population. This variability in expression is incompletely explained by known risk factors. We hypothesized that genome-wide genetic influences, as represented by polygenic risk scores (PRSs) for cardiometabolic traits, would influence the phenotypic severity of FH. METHODS: We studied individuals with clinically diagnosed FH (n=1123) from the FH Canada National Registry, as well as individuals with genetically identified FH from the UK Biobank (n=723). For all individuals, we used genome-wide gene array data to calculate PRSs for CAD, LDL-C, lipoprotein(a), and other cardiometabolic traits. We compared the distribution of PRSs in individuals with clinically diagnosed FH, genetically diagnosed FH, and non-FH controls and examined the association of the PRSs with the risk of atherosclerotic cardiovascular disease. RESULTS: Individuals with clinically diagnosed FH had higher levels of LDL-C, and the incidence of atherosclerotic cardiovascular disease was higher in individuals with clinically diagnosed compared with genetically identified FH. Individuals with clinically diagnosed FH displayed enrichment for higher PRSs for CAD, LDL-C, and lipoprotein(a) but not for other cardiometabolic risk factors. The CAD PRS was associated with a risk of atherosclerotic cardiovascular disease among individuals with an FH-causing genetic variant. CONCLUSIONS: Genetic background, as expressed by genome-wide PRSs for CAD, LDL-C, and lipoprotein(a), influences the phenotypic severity of FH, expanding our understanding of the determinants that contribute to the variable expressivity of FH. A PRS for CAD may aid in risk prediction among individuals with FH.

Artificial intelligence-based assessment of built environment from Google Street View and coronary artery disease prevalence.

BACKGROUND AND AIMS: Built environment plays an important role in the development of cardiovascular disease. Tools to evaluate the built environment using machine vision and informatic approaches have been limited. This study aimed to investigate the association between machine vision-based built environment and prevalence of cardiometabolic disease in US cities. METHODS: This cross-sectional study used features extracted from Google Street View (GSV) images to measure the built environment and link them with prevalence of coronary heart disease (CHD). Convolutional neural networks, linear mixed-effects models, and activation maps were utilized to predict health outcomes and identify feature associations with CHD at the census tract level. The study obtained 0.53 million GSV images covering 789 census tracts in seven US cities (Cleveland, OH; Fremont, CA; Kansas City, MO; Detroit, MI; Bellevue, WA; Brownsville, TX; and Denver, CO). RESULTS: Built environment features extracted from GSV using deep learning predicted 63% of the census tract variation in CHD prevalence. The addition of GSV features improved a model that only included census tract-level age, sex, race, income, and education or composite indices of social determinant of health. Activation maps from the features revealed a set of neighbourhood features represented by buildings and roads associated with CHD prevalence. CONCLUSIONS: In this cross-sectional study, the prevalence of CHD was associated with built environment factors derived from GSV through deep learning analysis, independent of census tract demographics. Machine vision-enabled assessment of the built environment could potentially offer a more precise approach to identify at-risk neighbourhoods, thereby providing an efficient avenue to address and reduce cardiovascular health disparities in urban environments.

Integration of a polygenic score into guideline-recommended prediction of cardiovascular disease.

BACKGROUND AND AIMS: It is not clear how a polygenic risk score (PRS) can be best combined with guideline-recommended tools for cardiovascular disease (CVD) risk prediction, e.g. SCORE2. METHODS: A PRS for coronary artery disease (CAD) was calculated in participants of UK Biobank (n = 432 981). Within each tenth of the PRS distribution, the odds ratios (ORs)-referred to as PRS-factor-for CVD (i.e. CAD or stroke) were compared between the entire population and subgroups representing the spectrum of clinical risk. Replication was performed in the combined Framingham/Atherosclerosis Risk in Communities (ARIC) populations (n = 10 757). The clinical suitability of a multiplicative model 'SCORE2 × PRS-factor' was tested by risk reclassification. RESULTS: In subgroups with highly different clinical risks, CVD ORs were stable within each PRS tenth. SCORE2 and PRS showed no significant interactive effects on CVD risk, which qualified them as multiplicative factors: SCORE2 × PRS-factor = total risk. In UK Biobank, the multiplicative model moved 9.55% of the intermediate (n = 145 337) to high-risk group increasing the individuals in this category by 56.6%. Incident CVD occurred in 8.08% of individuals reclassified by the PRS-factor from intermediate to high risk, which was about two-fold of those remained at intermediate risk (4.08%). Likewise, the PRS-factor shifted 8.29% of individuals from moderate to high risk in Framingham/ARIC. CONCLUSIONS: This study demonstrates that absolute CVD risk, determined by a clinical risk score, and relative genetic risk, determined by a PRS, provide independent information. The two components may form a simple multiplicative model improving precision of guideline-recommended tools in predicting incident CVD.

Streptococcus Species Abundance in the Gut Is Linked to Subclinical Coronary Atherosclerosis in 8973 Participants From the SCAPIS Cohort.

BACKGROUND: Gut microbiota have been implicated in atherosclerotic disease, but their relation with subclinical coronary atherosclerosis is unclear. This study aimed to identify associations between the gut microbiome and computed tomography-based measures of coronary atherosclerosis and to explore relevant clinical correlates. METHODS: We conducted a cross-sectional study of 8973 participants (50 to 65 years of age) without overt atherosclerotic disease from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study). Coronary atherosclerosis was measured using coronary artery calcium score and coronary computed tomography angiography. Gut microbiota species abundance and functional potential were assessed with shotgun metagenomics sequencing of fecal samples, and associations with coronary atherosclerosis were evaluated with multivariable regression models adjusted for cardiovascular risk factors. Associated species were evaluated for association with inflammatory markers, metabolites, and corresponding species in saliva. RESULTS: The mean age of the study sample was 57.4 years, and 53.7% were female. Coronary artery calcification was detected in 40.3%, and 5.4% had at least 1 stenosis with >50% occlusion. Sixty-four species were associated with coronary artery calcium score independent of cardiovascular risk factors, with the strongest associations observed for Streptococcus anginosus and Streptococcus oralis subsp oralis (P<1×10-5). Associations were largely similar across coronary computed tomography angiography-based measurements. Out of the 64 species, 19 species, including streptococci and other species commonly found in the oral cavity, were associated with high-sensitivity C-reactive protein plasma concentrations, and 16 with neutrophil counts. Gut microbial species that are commonly found in the oral cavity were negatively associated with plasma indole propionate and positively associated with plasma secondary bile acids and imidazole propionate. Five species, including 3 streptococci, correlated with the same species in saliva and were associated with worse dental health in the Malmö Offspring Dental Study. Microbial functional potential of dissimilatory nitrate reduction, anaerobic fatty acid ß-oxidation, and amino acid degradation were associated with coronary artery calcium score. CONCLUSIONS: This study provides evidence of an association of a gut microbiota composition characterized by increased abundance of Streptococcus spp and other species commonly found in the oral cavity with coronary atherosclerosis and systemic inflammation markers. Further longitudinal and experimental studies are warranted to explore the potential implications of a bacterial component in atherogenesis.

Low-Density Lipoprotein Cholesterol Is Predominantly Associated With Atherosclerotic Cardiovascular Disease Events in Patients With Evidence of Coronary Atherosclerosis: The Western Denmark Heart Registry.

BACKGROUND: Low-density lipoprotein cholesterol (LDL-C) is an important causal risk factor for atherosclerotic cardiovascular disease (ASCVD). However, a sizable proportion of middle-aged individuals with elevated LDL-C level have not developed coronary atherosclerosis as assessed by coronary artery calcification (CAC). Whether presence of CAC modifies the association of LDL-C with ASCVD risk is unknown. We evaluated the association of LDL-C with future ASCVD events in patients with and without CAC. METHODS: The study included 23 132 consecutive symptomatic patients evaluated for coronary artery disease using coronary computed tomography angiography (CTA) from the Western Denmark Heart Registry, a seminational, multicenter-based registry with longitudinal registration of patient and procedure data. We assessed the association of LDL-C level obtained before CTA with ASCVD (myocardial infarction and ischemic stroke) events occurring during follow-up stratified by CAC>0 versus CAC=0 using Cox regression models adjusted for baseline characteristics. Outcomes were identified through linkage among national registries covering all hospitals in Denmark. We replicated our results in the National Heart, Lung, and Blood Institute-funded Multi-Ethnic Study of Atherosclerosis. RESULTS: During a median follow-up of 4.3 years, 552 patients experienced a first ASCVD event. In the overall population, LDL-C (per 38.7 mg/dL increase) was associated with ASCVD events occurring during follow-up (adjusted hazard ratio [aHR], 1.14 [95% CI, 1.04-1.24]). When stratified by the presence or absence of baseline CAC, LDL-C was only associated with ASCVD in the 10 792/23 132 patients (47%) with CAC>0 (aHR, 1.18 [95% CI, 1.06-1.31]); no association was observed among the 12 340/23 132 patients (53%) with CAC=0 (aHR, 1.02 [95% CI, 0.87-1.18]). Similarly, a very high LDL-C level (>193 mg/dL) versus LDL-C <116 mg/dL was associated with ASCVD in patients with CAC>0 (aHR, 2.42 [95% CI, 1.59-3.67]) but not in those without CAC (aHR, 0.92 [0.48-1.79]). In patients with CAC=0, diabetes, current smoking, and low high-density lipoprotein cholesterol levels were associated with future ASCVD events. The principal findings were replicated in the Multi-Ethnic Study of Atherosclerosis. CONCLUSIONS: LDL-C appears to be almost exclusively associated with ASCVD events over ≈5 years of follow-up in middle-aged individuals with versus without evidence of coronary atherosclerosis. This information is valuable for individualized risk assessment among middle-aged people with or without coronary atherosclerosis.

Exercise Volume Versus Intensity and the Progression of Coronary Atherosclerosis in Middle-Aged and Older Athletes: Findings From the MARC-2 Study.

BACKGROUND: Physical activity and exercise training are associated with a lower risk for coronary events. However, cross-sectional studies in middle-aged and older male athletes revealed increased coronary artery calcification (CAC) and atherosclerotic plaques, which were related to the amount and intensity of lifelong exercise. We examined the longitudinal relationship between exercise training characteristics and coronary atherosclerosis. METHODS: Middle-aged and older men from the MARC-1 (Measuring Athlete's Risk of Cardiovascular Events 1) study were invited for follow-up in MARC-2 (Measuring Athlete's Risk of Cardiovascular Events 2) study. The prevalence and severity of CAC and plaques were determined by coronary computed tomography angiography. The volume (metabolic equivalent of task [MET] hours/week) and intensity (moderate [3 to 6 MET hours/week]; vigorous [6 to 9 MET hours/week]; and very vigorous [≥9 MET hours/week]) of exercise training were quantified during follow-up. Linear and logistic regression analyses were performed to determine the association between exercise volume/intensity and markers of coronary atherosclerosis. RESULTS: We included 289 (age, 54 [50 to 60] years [median (Q1 to Q3)]) of the original 318 MARC-1 participants with a follow-up of 6.3±0.5 years (mean±SD). Participants exercised for 41 (25 to 57) MET hours/week during follow-up, of which 0% (0 to 19%) was at moderate intensity, 44% (0 to 84%) was at vigorous intensity, and 34% (0 to 80%) was at very vigorous intensity. Prevalence of CAC and the median CAC score increased from 52% to 71% and 1 (0 to 32) to 31 (0 to 132), respectively. Exercise volume during follow-up was not associated with changes in CAC or plaque. Vigorous intensity exercise (per 10% increase) was associated with a lesser increase in CAC score (ß, -0.05 [-0.09 to -0.01]; P=0.02), whereas very vigorous intensity exercise was associated with a greater increase in CAC score (ß, 0.05 [0.01 to 0.09] per 10%; P=0.01). Very vigorous exercise was also associated with increased odds of dichotomized plaque progression (adjusted odds ratio [aOR], 1.09 [1.01 to 1.18] per 10%; aOR, 2.04 [0.93 to 4.15] for highest versus lowest very vigorous intensity tertiles, respectively), and specifically with increased calcified plaques (aOR, 1.07 [1.00 to 1.15] per 10%; aOR, 2.09 [1.09 to 4.00] for highest versus lowest tertile, respectively). CONCLUSIONS: Exercise intensity but not volume was associated with progression of coronary atherosclerosis during 6-year follow-up. It is intriguing that very vigorous intensity exercise was associated with greater CAC and calcified plaque progression, whereas vigorous intensity exercise was associated with less CAC progression.

Heterogeneity in the Association Between the Presence of Coronary Artery Calcium and Cardiovascular Events: A Machine-Learning Approach in the MESA Study.

BACKGROUND: Coronary artery calcium (CAC) has been widely recognized as an important predictor of cardiovascular disease (CVD). Given the finite resources, it is important to identify individuals who would receive the most benefit from detecting positive CAC by screening. However, the evidence is limited as to whether the burden of positive CAC on CVD differs by multidimensional individual characteristics. We sought to investigate the heterogeneity in the association between positive CAC and incident CVD. METHODS: This cohort study included adults from MESA (Multi-Ethnic Study of Atherosclerosis) ages ≥45 years and free of cardiovascular disease. After propensity score matching in a 1:1 ratio, we applied a machine learning causal forest model to (1) evaluate the heterogeneity in the association between positive CAC and incident CVD, and (2) predict the increase in CVD risk at 10-years when CAC>0 (versus CAC=0) at the individual level. We then compared the estimated increase in CVD risk when CAC>0 to the absolute 10-year atherosclerotic CVD (ASCVD) risk calculated by the 2013 American College of Cardiology/American Heart Association pooled cohort equations. RESULTS: Across 3328 adults in our propensity score-matched analysis, our causal forest model showed the heterogeneity in the association between CAC>0 and incident CVD. We found a dose-response relationship of the estimated increase in CVD risk when CAC>0 with higher 10-year ASCVD risk. Almost all individuals (2293 of 2428 [94.4%]) with borderline risk of ASCVD or higher showed ≥2.5% increase in CVD risk when CAC>0. Even among 900 adults with low ASCVD risk, 689 (69.2%) showed ≥2.5% increase in CVD risk when CAC>0; these individuals were more likely to be male, Hispanic, and have unfavorable CVD risk factors than others. CONCLUSIONS: The expected increases in CVD risk when CAC>0 were heterogeneous across individuals. Moreover, nearly 70% of people with low ASCVD risk showed a large increase in CVD risk when CAC>0, highlighting the need for CAC screening among such low-risk individuals. Future studies are needed to assess whether targeting individuals for CAC measurements based on not only the absolute ASCVD risk but also the expected increase in CVD risk when CAC>0 improves cardiovascular outcomes.

Twenty Years of Cardiovascular Complications and Risk Factors in Patients With Type 2 Diabetes: A Nationwide Swedish Cohort Study.

BACKGROUND: The goal of this work was to investigate trends (2001-2019) for cardiovascular events and cardiometabolic risk factor levels in individuals with type 2 diabetes (T2D) and matched control subjects. METHODS: This study included 679 072 individuals with T2D from the Swedish National Diabetes Register and 2 643 800 matched control subjects. Incident outcomes comprised coronary artery disease, acute myocardial infarction, cerebrovascular disease, and heart failure (HF). Trends in time to first event for each outcome were analyzed with Cox regression and standardized incidence rates. In the group with T2D, Cox regression was also used to assess risk factor levels beyond target and outcomes, as well as the relative importance of each risk factor to each model. RESULTS: Among individuals with T2D, incidence rates per 10 000 person-years in 2001 and 2019 were as follows: acute myocardial infarction, 73.9 (95% CI, 65.4-86.8) and 41.0 (95% CI, 39.5-42.6); coronary artery disease, 205.1 (95% CI, 186.8-227.5) and 80.2 (95% CI, 78.2-82.3); cerebrovascular disease, 83.9 (95% CI, 73.6-98.5) and 46.2 (95% CI, 44.9-47.6); and HF, 98.3 (95% CI, 89.4-112.0) and 75.9 (95% CI, 74.4-77.5). The incidence for HF plateaued around 2013, a trend that then persisted. In individuals with T2D, glycated hemoglobin, systolic blood pressure, estimated glomerular filtration rate, and lipids were independently associated with outcomes. Body mass index alone potentially explained >30% of HF risk in T2D. For those with T2D with no risk factor beyond target, there was no excess cardiovascular risk compared with control subjects except for HF, with increased hazard with T2D even when no risk factor was above target (hazard ratio, 1.50 [95% CI, 1.35-1.67]). Risk for coronary artery disease and cerebrovascular disease increased in a stepwise fashion for each risk factor not within target. Glycated hemoglobin was most prognostically important for incident atherosclerotic events, as was body mass index for incident of HF. CONCLUSIONS: Risk and rates for atherosclerotic complications and HF are generally decreasing among individuals with T2D, although HF incidence has notably plateaued in recent years. Modifiable risk factors within target levels were associated with lower risks for outcomes. This was particularly notable for systolic blood pressure and glycated hemoglobin for atherosclerotic outcomes and body mass index for heart failure.

Coronary artery calcium and cardiovascular outcomes in patients with lymphoma undergoing autologous hematopoietic cell transplantation.

BACKGROUND: Patients undergoing autologous hematopoietic cell transplantation (HCT) have a >2-fold risk of developing cardiovascular disease (CVD; heart failure, myocardial infarction, and stroke), compared to the general population. Coronary artery calcium (CAC) is predictive of CVD in nononcology patients but is not as well studied in patients who underwent HCT and survivors of HCT.The objective of this study was to examine the association between CAC and CVD risk and outcomes after HCT in patients with lymphoma. METHODS: This was a retrospective cohort study of 243 consecutive patients who underwent a first autologous HCT for lymphoma between 2009 and 2014. CAC (Agatston score) was determined from chest computed tomography obtained <60 days from HCT. Multivariable Cox regression analysis was used to calculate hazard ratio (HR) estimates and 95% confidence intervals (CIs), adjusted for covariates (age, conventional risk factors [e.g., hypertension and dyslipidemia], and cancer treatment). RESULTS: The median age at HCT was 55.7 years (range, 18.5-75.1 years), 59% were male, and 60% were non-Hispanic White. The prevalence of CAC was 37%. The 5-year CVD incidence for the cohort was 12%, and there was an incremental increase in the incidence according to CAC score: 0 (6%), 1-100 (20%), and >100 (32%) (p = .001). CAC was significantly associated with CVD risk (HR, 3.0; 95% CI, 1.2-7.5) and worse 5-year survival (77% vs. 50%; p < .001; HR, 2.0; 95% CI, 1.1-3.4), compared to those without CAC. CONCLUSIONS: CAC is independently associated with CVD and survival after HCT. This highlights the importance of integrating readily available imaging information in risk stratification and decision-making in patients undergoing HCT, which sets the stage for strategies to optimize outcomes after HCT.

Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts.

BACKGROUND: Binary diagnosis of coronary artery disease does not preserve the complexity of disease or quantify its severity or its associated risk with death; hence, a quantitative marker of coronary artery disease is warranted. We evaluated a quantitative marker of coronary artery disease derived from probabilities of a machine learning model. METHODS: In this cohort study, we developed and validated a coronary artery disease-predictive machine learning model using 95 935 electronic health records and assessed its probabilities as in-silico scores for coronary artery disease (ISCAD; range 0 [lowest probability] to 1 [highest probability]) in participants in two longitudinal biobank cohorts. We measured the association of ISCAD with clinical outcomes-namely, coronary artery stenosis, obstructive coronary artery disease, multivessel coronary artery disease, all-cause death, and coronary artery disease sequelae. FINDINGS: Among 95 935 participants, 35 749 were from the BioMe Biobank (median age 61 years [IQR 18]; 14 599 [41%] were male and 21 150 [59%] were female; 5130 [14%] were with diagnosed coronary artery disease) and 60 186 were from the UK Biobank (median age 62 [15] years; 25 031 [42%] male and 35 155 [58%] female; 8128 [14%] with diagnosed coronary artery disease). The model predicted coronary artery disease with an area under the receiver operating characteristic curve of 0·95 (95% CI 0·94-0·95; sensitivity of 0·94 [0·94-0·95] and specificity of 0·82 [0·81-0·83]) and 0·93 (0·92-0·93; sensitivity of 0·90 [0·89-0·90] and specificity of 0·88 [0·87-0·88]) in the BioMe validation and holdout sets, respectively, and 0·91 (0·91-0·91; sensitivity of 0·84 [0·83-0·84] and specificity of 0·83 [0·82-0·83]) in the UK Biobank external test set. ISCAD captured coronary artery disease risk from known risk factors, pooled cohort equations, and polygenic risk scores. Coronary artery stenosis increased quantitatively with ascending ISCAD quartiles (increase per quartile of 12 percentage points), including risk of obstructive coronary artery disease, multivessel coronary artery disease, and stenosis of major coronary arteries. Hazard ratios (HRs) and prevalence of all-cause death increased stepwise over ISCAD deciles (decile 1: HR 1·0 [95% CI 1·0-1·0], 0·2% prevalence; decile 6: 11 [3·9-31], 3·1% prevalence; and decile 10: 56 [20-158], 11% prevalence). A similar trend was observed for recurrent myocardial infarction. 12 (46%) undiagnosed individuals with high ISCAD (≥0·9) had clinical evidence of coronary artery disease according to the 2014 American College of Cardiology/American Heart Association Task Force guidelines. INTERPRETATION: Electronic health record-based machine learning was used to generate an in-silico marker for coronary artery disease that can non-invasively quantify atherosclerosis and risk of death on a continuous spectrum, and identify underdiagnosed individuals. FUNDING: National Institutes of Health.

Immune checkpoint inhibitors in cancer: the increased risk of atherosclerotic cardiovascular disease events and progression of coronary artery calcium.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have contributed to a significant advancement in the treatment of cancer, leading to improved clinical outcomes in many individuals with advanced disease. Both preclinical and clinical investigations have shown that ICIs are associated with atherosclerosis and other cardiovascular events; however, the exact mechanism underlying this relationship has not been clarified. METHODS: Patients diagnosed with stages III or IV non-small cell lung cancer (NSCLC) at the Wuhan Union Hospital from March 1, 2020, to April 30, 2022, were included in this retrospective study. Coronary artery calcium (CAC) volume and score were assessed in a subset of patients during non-ECG-gated chest CT scans at baseline and 3, 6, and 12 months after treatment. Propensity score matching (PSM) was performed in a 1:1 ratio to balance the baseline characteristics between the two groups. RESULTS: Overall, 1458 patients (487 with ICI therapy and 971 without ICI therapy) were enrolled in this cardiovascular cohort study. After PSM, 446 patients were included in each group. During the entire period of follow-up (median follow-up 23.1 months), 24 atherosclerotic cardiovascular disease (ASCVD) events (4.9%) occurred in the ICI group, and 14 ASCVD events (1.4%) in the non-ICI group, before PSM; 24 ASCVD events (5.4%) occurred in the ICI group and 5 ASCVD events (1.1%) in the non-ICI group after PSM. The CAC imaging study group comprised 113 patients with ICI therapy and 133 patients without ICI therapy. After PSM, each group consisted of 75 patients. In the ICI group, the CAC volume/score increased from 93.4 mm3/96.9 (baseline) to 125.1 mm3/132.8 (at 12 months). In the non-ICI group, the CAC volume/score was increased from 70.1 mm3/68.8 (baseline) to 84.4 mm3/87.9 (at 12 months). After PSM, the CAC volume/score was increased from 85.1 mm3/76.4 (baseline) to 111.8 mm3/121.1 (12 months) in the ICI group and was increased from 74.9 mm3/76.8 (baseline) to 109.3 mm3/98.7 (12 months) in the non-ICI group. Both cardiovascular events and CAC progression were increased after the initiation of ICIs. CONCLUSIONS: Treatment with ICIs was associated with a higher rate of ASCVD events and a noticeable increase in CAC progression.

The gut microbiota and coronary artery calcification in Japanese men.

BACKGROUND: The gut microbiota differs between patients with coronary artery disease (CAD) and healthy controls; however, it currently remains unclear whether these differences exist prior to the onset of CAD. We herein investigated the gut microbiota associated with subclinical coronary artery calcification (CAC) in a Japanese population. METHODS: A total of 663 Japanese men were enrolled in this cross-sectional study. Computed tomography and gut microbiology tests were performed, and CAC scores were calculated using the Agatston method. Participants were categorized into 4 groups based on their CAC scores: CAC = 0, 0

Identifying the highest risk vascular patients: Insights from the XATOA registry.

BACKGROUND: Patients with coronary and peripheral artery disease (PAD) have a residual risk of major adverse cardiovascular and limb events despite standards of care. Among patients with coronary artery disease (CAD) and/or PAD selected for low dose rivaroxaban (2.5 mg BID) and aspirin, we sought to determine the highest risk vascular patients. METHODS: Xarelto pluc Acetylsalicylic acid: Treatment patterns and Outcomes in patients with Atherosclerosis (XATOA) is a single-arm registry of CAD and/or PAD patients. All participants were initiated on low dose rivaroxaban (2.5 mg BID) and aspirin. We report the incidence risk of major adverse cardiovascular events (MACE) or major adverse limb events (MALE) and major bleeding. A classification and regression tree analysis determined independent subgroups. RESULTS: Between November 2018 and May 2020, 5,808 participants were enrolled in XATOA; 5,532 were included in the full analysis. The median follow-up (interquartile range) was 462 (371-577) days. The incidence risk per 100 patient-years of MACE or MALE was highest among participants with polyvascular disease (2 or more vascular beds affected, n = 2,889). The incidence risk was 9.16 versus 2.48 per 100 patient-years in polyvascular and nonpolyvascular patients respectively. Other subgroups of high-risk patients included participants 75 years or older, with a history of diabetes, heart failure, or chronic renal insufficiency (CRI). Rates of major bleeding were low overall. A classification and regression tree analysis showed that polyvascular disease was the most dominant factor separating higher from lower risk participants, and this was heightened with CRI or diabetes. CONCLUSION: Patients with polyvascular disease represent a substantial subset of patients in clinical practice and should be prioritized to receive maximal medical therapy including low dose rivaroxaban (2.5 mg BID) and aspirin.