Different Metabolic Phenotypes of Obesity and Risk of Coronary Artery Calcium Progression and Incident Cardiovascular Disease Events: The CARDIA Study

Association of Anthropometric Indices With Midlife Cardiovascular Risk in Young Individuals Without Obesity and Traditional Risk Factors

BACKGROUND

The aim of this study was to assess how early-adulthood body mass index (BMI) and waist circumference (WC) relate to long-term cardiovascular structure, function, and prognosis in individuals without obesity and with low cardiovascular risk factor (CVRF) burden.

METHODS AND RESULTS

A total of 2024 participants aged 18 to 30 from the CARDIA (Coronary Artery Risk Development in Young Adults) study, without obesity and with low CVRFs defined as the absence of cardiovascular disease (CVD), diabetes, hypertension, current smoking, and dyslipidemia were included. A CVRF-optimal subgroup was also defined, with blood pressure<120/80 mm Hg, fasting glucose <100 mg/dL, total cholesterol <200, low-density lipoprotein cholesterol <130, and women with high-density lipoprotein cholesterol ≥50 mg/dL. Coronary artery calcification, carotid intima-media thickness, left ventricular mass, left ventricular ejection fraction, longitudinal peak systolic strain, and diastolic function were assessed in midlife. Cox regression was used to calculate hazard ratios of BMI and WC for all-cause death and CVD events. Logistic regression was used to estimate odds ratios for subclinical CVD. Over 33.9 years (median follow-up), 5.2% (n=105) died, and 2.6% (n=52) had CVD events. Each 1-SD BMI increase was associated with 27% (95% CI, 1.10-1.47), 24% (1.08-1.43), 42% (1.20-1.68), 28% (1.05-1.57), 51% (1.20-1.90), and 49% (1.10-2.02) higher odds of coronary artery calcification presence, increased carotid intima-media thickness, left ventricular hypertrophy, reduced left ventricular ejection fraction, low longitudinal peak systolic strain, and diastolic dysfunction, respectively, in the CVRF-low group. Generally, similar associations were found for WC and in the CVRF-optimal subgroup. No significant associations between BMI and WC with CVD and death were found.

CONCLUSIONS

Elevations in BMI and WC among young low-risk individuals, even within the nonobesity range, are associated with midlife cardiovascular health.

Association of metabolic health and obesity with coronary heart disease in adult cancer survivors

BACKGROUND

The metabolically healthy obese (MHO) phenotype is associated with an increased risk of coronary heart disease (CHD) in the general population. However, association of metabolic health and obesity phenotypes with CHD risk in adult cancer survivors remains unclear. We aimed to investigate the associations between different metabolic health and obesity phenotypes with incident CHD in adult cancer survivors.

METHODS

We used National Health Insurance Service (NHIS) to identify a cohort of 173,951 adult cancer survivors aged more than 20 years free of cardiovascular complications. Metabolically healthy nonobese (MHN), MHO, metabolically unhealthy nonobese (MUN), metabolically unhealthy obese (MUO) phenotypes were created using as at least three out of five metabolic health criteria along with obesity (body mass index ≥ 25.0 kg/m2). We used Cox proportional hazards model to assess CHD risk in each metabolic health and obesity phenotypes.

RESULTS

During 1,376,050 person-years of follow-up, adult cancer survivors with MHO phenotype had a significantly higher risk of CHD (hazard ratio [HR] = 1.52; 95% confidence intervals [CI]: 1.41 to 1.65) as compared to those without obesity and metabolic abnormalities. MUN (HR = 1.81; 95% CI: 1.59 to 2.06) and MUO (HR = 1.92; 95% CI: 1.72 to 2.15) phenotypes were also associated with an increased risk of CHD among adult cancer survivors.

CONCLUSIONS

Adult cancer survivors with MHO phenotype had a higher risk of CHD than those who are MHN. Metabolic health status and obesity were jointly associated with CHD risk in adult cancer survivors.

Impact of coronary artery calcium on mortality and cardiovascular events in metabolic syndrome and diabetes among younger adults

AIMS

Whether coronary artery calcium (CAC) testing in younger individuals with metabolic syndrome (MetS) and diabetes mellitus (DM) helps predict cardiovascular disease (CVD) and death independent of traditional risk factors (RFs) remains less clear.

METHODS AND RESULTS

We pooled data obtained from 5174 individuals aged 38-55 years from the CARDIA (Coronary Artery Risk Development in Young Adults; n = 3047, year 20) and MESA (Multi-Ethnic Study of Atherosclerosis; n = 2127, Visit 1) studies who completed computed tomography of CAC. The mean age (SD) of participants (44.7% men) was 47.3 (4.2) years. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HRs) of CVD, coronary heart disease (CHD), and all-cause death. There were 1085 participants (21.0%) with prevalent CAC at baseline. A total of 461 (8.9%) had DM, 1025 (19.8%) had MetS without DM, and 3688 (71.3%) had neither condition. Over a median follow-up of 14.2 years, 256 (5.0%) participants died, and 304 (5.9%) CVD and 188 (3.6%) CHD events occurred. The CAC score was independently associated with incident CVD in those with DM (HR: 95% CI; 1.22: 1.08-1.38), MetS (1.18: 1.08-1.31), and neither condition (1.36: 1.26-1.46). The corresponding HRs for CAC ≥ 100 were 2.70 (1.25-5.83), 3.29 (1.87-5.79), and 6.30 (4.02-9.86), respectively. Similar associations for CHD and death were found. The impact of CAC ≥ 100 on CVD and CHD was lower in the presence of DM (P interaction < 0.05). The association of CAC with all outcomes in individuals with DM remained significant after adjusting with haemoglobin A1c levels.

CONCLUSION

Coronary artery calcium score is independently associated with cardiovascular events and death over nearly 15 years after screening at ages 38-55 years, with a less pronounced impact on CVD and CHD events in the presence of DM.

Metabolic Obesity Phenotypes and Incident Cardiovascular Outcomes in Middle-Aged and Older Korean Adults: A Longitudinal 10-Year Analysis of the Korean Genome and Epidemiology Study

Background: This study investigated the association of four metabolic obesity phenotypes with incident coronary artery disease and stroke in a large-scale, community population-based, prospective Korean cohort observed for over 10 years. Methods: The study participants included 7374 adults aged 40-69 years, drawn from the Korean Genome and Epidemiology Study. Participants with different metabolic obesity phenotypes were categorized according to body weight and metabolic health status into four groups: metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy nonobese (MUHNO), and metabolically unhealthy obese (MUHO). Combined cardiovascular events were defined as coronary artery disease and stroke. We used multivariate Cox proportional hazards regression models to prospectively assess hazard ratios (HRs) with 95% confidence intervals (CIs) for incident coronary artery disease or stroke over 10 years after the baseline survey. Results: During the follow-up period, newly developed coronary artery disease, stroke, and combined cardiovascular events were diagnosed in 151 (2.0%), 137 (1.9%), and 283 (3.8%) participants, respectively. After adjusting for confounding variables, the HRs (95% CIs) for incident combined cardiovascular events were 1.81 (1.34-2.46) in the MUHO group, 1.29 (0.92-1.81) in the MUHNO group, and 1.21 (0.81-1.79) in the MHO group compared with those in the MHNO group. Conclusions: This study revealed distinct risks associated with four metabolic obesity phenotypes concerning incident coronary artery disease and stroke. After adjusting for potential confounding variables, the results indicated that MUHO, but not MUHNO or MHO, showed a higher risk of developing coronary artery disease and stroke than MHNO.

Using a machine learning-based risk prediction model to analyze the coronary artery calcification score and predict coronary heart disease and risk assessment

OBJECTIVES

To calculate the coronary artery calcification score (CACS) obtained from coronary artery computed tomography angiography (CCTA) examination and combine it with the influencing factors of coronary artery calcification (CAC), which is then analyzed by machine learning (ML) to predict the probability of coronary heart disease(CHD).

METHODS

All patients who were admitted to the Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University from January 2019 to March 2022, suspected of CHD, and underwent CCTA inspection were retrospectively selected. The degree of CAC was quantified based on the Agatston score. To compare the correlation between the CACS and clinical-related factors, we collected 31 variables, including hypertension, diabetes, smoking, hyperlipidemia, among others. ML models containing the random forest (RF), radial basis function neural network (RBFNN),support vector machine (SVM),K-Nearest Neighbor algorithm (KNN) and kernel ridge regression (KRR) were used to assess the risk of CHD based on CACS and clinical-related factors.

RESULTS

Among the five ML models, RF achieves the best performance about accuracy (ACC) (78.96%), sensitivity (SN) (93.86%), specificity(Spe) (51.13%), and Matthew's correlation coefficient (MCC) (0.5192).It also has the best area under the receiver operator characteristic curve (ROC) (0.8375), which is far superior to the other four ML models.

CONCLUSION

Computer ML model analysis confirmed the importance of CACS in predicting the occurrence of CHD, especially the outstanding RF model, making it another advancement of the ML model in the field of medical analysis.

Diabesity in Elderly Cardiovascular Disease Patients: Mechanisms and Regulators

Cardiovascular disease (CVD) is the leading cause of death in the world. In 2019, 550 million people were suffering from CVD and 18 million of them died as a result. Most of them had associated risk factors such as high fasting glucose, which caused 134 million deaths, and obesity, which accounted for 5.02 million deaths. Diabesity, a combination of type 2 diabetes and obesity, contributes to cardiac, metabolic, inflammation and neurohumoral changes that determine cardiac dysfunction (diabesity-related cardiomyopathy). Epicardial adipose tissue (EAT) is distributed around the myocardium, promoting myocardial inflammation and fibrosis, and is associated with an increased risk of heart failure, particularly with preserved systolic function, atrial fibrillation and coronary atherosclerosis. In fact, several hypoglycaemic drugs have demonstrated a volume reduction of EAT and effects on its metabolic and inflammation profile. However, it is necessary to improve knowledge of the diabesity pathophysiologic mechanisms involved in the development and progression of cardiovascular diseases for comprehensive patient management including drugs to optimize glucometabolic control. This review presents the mechanisms of diabesity associated with cardiovascular disease and their therapeutic implications.