Associations Between Cardiovascular Risk Factors, Inflammation, and Progression of Carotid Atherosclerosis Among Smokers

Biological and Functional Changes in Healthy Adult Smokers Who Are Continuously Abstinent From Smoking for One Year: Protocol for a Prospective, Observational, Multicenter Cohort Study

Background

The harm of smoking results mainly from long-term exposure to harmful and potentially harmful constituents (HPHCs) generated by tobacco combustion. Smoking cessation (SC) engenders favorable changes of clinical signs, pathomechanisms, and metabolic processes that together could reduce the harm of smoking-related diseases to a relative risk level approximating that of never-smokers over time. In most SC studies, the main focus is on the quitting rate of the SC program being tested. As there is limited information in the literature on short to multiple long-term functional or biological changes following SC, more data on short to mid-term favorable impacts of SC are needed.

Objective

The overall aim of the study was to assess the reversibility of the harm related to smoking over 1 year of continuous smoking abstinence (SA). This has been verified by assessing a set of biomarkers of exposure to HPHCs and a set of biomarkers of effect indicative of multiple pathophysiological pathways underlying the development of smoking-related diseases.

Methods

This multiregional (United States, Japan, and Europe), multicenter (42 sites) cohort study consisting of a 1-year SA period in an ambulatory setting was conducted from May 2015 to May 2017. A total of 1184 male and female adult healthy smokers, willing to quit smoking, were enrolled in the study. Nicotine replacement therapy (NRT) was provided for up to 3 months upon the subject’s request. SC counseling and behavioral support were continuously provided. Biomarkers of exposure to HPHCs and biomarkers of effect were assessed in urine and blood at baseline, Month 3, Month 6, and Month 12. Cardiovascular biomarkers of effect included parameters reflecting inflammation (white blood cell), lipid metabolism (high-density lipoprotein cholesterol), endothelial function (soluble intercellular adhesion molecule-1), platelet function (11-dehydrothromboxane B2), oxidative stress (8-epi-prostaglandin F2 alpha), and carbon monoxide exposure (carboxyhemoglobin). Respiratory biomarkers of effect included lung function parameters and cough symptoms. The biomarkers of effect to evaluate genotoxicity (total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol) and xenobiotic metabolism (cytochrome P450 2A6 activity) were also assessed. Continuous SA was verified at each visit following the actual quit date using self-reporting and chemical verification. Safety assessments included adverse events and serious adverse events, body weight, vital signs, spirometry, electrocardiogram, clinical chemistry, hematology and urine analysis safety panel, physical examination, and concomitant medications.

Results

In total, 1184 subjects (50.1% male) were enrolled; 30% of them quit smoking successfully for 1 year. Data analyses of the study results are ongoing and will be published after study completion.

Conclusions

This study provides insights into biological and functional changes and health effects, after continuous SA over 1 year. Study results will be instrumental in assessing novel alternative products to cigarettes considered for tobacco harm reduction strategies.

Trial Registration

ClinicalTrials.gov NCT02432729; http://clinicaltrials.gov/ct2/show/NCT02432729 (Archived by WebCite at http://www.webcitation.org/78QxovZrr)

International Registered Report Identifier (IRRID)

DERR1-10.2196/12138

Effect of carotid image-based phenotypes on cardiovascular risk calculator: AECRS1.0

Today, the 10-year cardiovascular risk largely relies on conventional cardiovascular risk factors (CCVRFs) and suffers from the effect of atherosclerotic wall changes. In this study, we present a novel risk calculator AtheroEdge Composite Risk Score (AECRS1.0), designed by fusing CCVRF with ultrasound image-based phenotypes. Ten-year risk was computed using the Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score. AECRS1.0 was computed by measuring the 10-year five carotid phenotypes such as IMT (ave., max., min.), IMT variability, and total plaque area (TPA) by fusing eight CCVRFs and then compositing them. AECRS1.0 was then benchmarked against the five conventional cardiovascular risk calculators by computing the receiver operating characteristics (ROC) and area under curve (AUC) values with a 95% CI. Two hundred four IRB-approved Japanese patients' left/right common carotid arteries (407 ultrasound scans) were collected with a mean age of 69 ± 11 years. The calculators gave the following AUC: FRS, 0.615; UKPDS56, 0.576; UKPDS60, 0.580; RRS, 0.590; PCRS, 0.613; and AECRS1.0, 0.990. When fusing CCVRF, TPA reported the highest AUC of 0.81. The patients were risk-stratified into low, moderate, and high risk using the standardized thresholds. The AECRS1.0 demonstrated the best performance on a Japanese diabetes cohort when compared with five conventional calculators. Graphical abstract AECRS1.0: Carotid ultrasound image phenotype-based 10-year cardiovascular risk calculator. The figure provides brief overview of the proposed carotid image phenotype-based 10-year cardiovascular risk calculator called AECRS1.0. AECRS1.0 was also benchmarked against five conventional cardiovascular risk calculators (Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score).

Carotid intima-media thickness in chronic obstructive pulmonary disease and survival: A multicenter prospective study

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) is associated with increased cardiovascular morbidity and mortality. Carotid intima-media thickness (CIMT) is a noninvasive method assessing atherosclerosis.

OBJECTIVE

It was aimed to determine relationship and survival between COPD and CIMT.

METHODS

CIMT was measured using Doppler ultrasound (USG) in 668 stable COPD patients at 24 centers. Patients were followed-up for 2 years.

RESULTS

There were 610 patients who completed the study. There were 200 patients CIMT with <0.78 mm (group 1), and 410 with CIMT ≥ 0.78 mm (group 2). There was a significant difference at the parameters of age, gender, smoking load, biomass exposure, GOLD groups and degree of airway obstruction (FEV1) between groups 1 and 2. Our results revealed positive correlations between mean CIMT and age, smoking load (pack-years), biomass exposure (years), exacerbation rate (last year), duration of hypertension (years) and cholesterol level; negative correlations between CIMT and FEV₁ (P < 0.05). According to logistic regression model, compared with group A, risk of CIMT increase was 2.2-fold in group B, 9.7-fold in group C and 4.4-fold in group D (P < 0.05). Risk of CIMT increase was also related with cholesterol level (P < 0.05). Compared with infrequent exacerbation, it was 2.8-fold in the patients with frequent exacerbation (P < 0.05). The mean survival time was slightly higher in group 1, but not significant (23.9 vs 21.8 months) (P > 0.05).

CONCLUSION

This study is the first regarding CIMT with combined GOLD assessment groups. It has revealed important findings supporting the increase in atherosclerosis risk in COPD patients. We recommend Doppler USG of the carotid artery in COPD patients at severe stages.

Rosmarinic acid inhibits nicotine-induced C-reactive protein generation by inhibiting NLRP3 inflammasome activation in smooth muscle cells

Atherosclerosis is widely known to be a chronic inflammatory disease. C-reactive protein (CRP), an important inflammatory factor, plays an essential role in the pathogenesis of atherosclerosis. Nicotine, the main addictive component of cigarette, has been shown to induce the production of CRP. The aim of this study was to investigate the effect of rosmarinic acid (RA), a polyphenol with antiinflammatory activity, on nicotine-induced elevation of CRP in vascular smooth muscle cells (VSMCs). We found that pretreatment of VSMCs with RA attenuated nicotine-induced expression of CRP in a time- and dose-dependant manner. In addition, RA also inhibited the activation of NLR family pyrin domain containing 3 (NLRP3) inflammasome and reactive oxygen species (ROS) production resulting from nicotine treatment in VSMCs. To confirm these findings in vivo, we constructed a nicotine-induced atherosclerosis rat model. RA did not significantly reduce the serum nicotine level of the rats, whereas it significantly decreased the levels of serum lipids, including concentrations of cholesterol, triglycerides, and low-density lipoprotein cholesterol, and the serum level of CRP. RA also led to diminished nicotine-induced activation of NLRP3 inflammasome and elevation in the CRP level in the aortic tissue of the model rats. The results of this study suggested a protective role of RA in nicotine-induced atherosclerosis by inhibiting the ROS-NLRP3 inflammasome-CRP axial, and RA therefore represented a potential effective therapeutic approach to atherosclerosis, in particular for those who smoke.

Performance evaluation of 10-year ultrasound image-based stroke/cardiovascular (CV) risk calculator by comparing against ten conventional CV risk calculators: A diabetic study

MOTIVATION

AtheroEdge Composite Risk Score (AECRS1.0_10yr) is an integrated stroke/cardiovascular risk calculator that was recently developed and computes the 10-year risk of carotid image phenotypes by integrating conventional cardiovascular risk factors (CCVRFs). It is therefore important to understand how closely AECRS1.0_10yr is associated with the ten other currently available conventional cardiovascular risk calculators (CCVRCs).

METHODS

The Institutional Review Board of Toho University approved the examination of the left/right common carotid arteries of 202 Japanese patients. Step 1 consists of measurement of AECRS1.0_10yr, given current image phenotypes and CCVRFs. Step 2 consists of computing the risk score using ten different CCVRCs given CCVR factors: QRISK3, Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study (UKPDS) 56, UKPDS60, Reynolds Risk Score (RRS), Pooled cohort Risk Score (PCRS or ASCVD), Systematic Coronary Risk Evaluation (SCORE), Prospective Cardiovascular Munster Study (PROCAM) calculator, NIPPON, and World Health Organization (WHO) risk. Step 3 consists of computing the closeness factor between AECRS1.0_10yr and ten CCVRCs using cumulative ranking index derived using eight different statistically derived metrics.

RESULTS

AECRS1.0_10yr reported the highest area-under-the-curve (0.927;P < 0.001) among all the risk calculators. The top three CCVRCs closest to AECRS1.0_10yr were QRISK3, FRS, and UKPDS60 with cumulative ranking scores of 2.1, 3.0, and 3.8, respectively.

CONCLUSION

AECRS1.0_10yr produced the largest AUC due to the integration of image-based phenotypes with CCVR factors, and ranked at first place with the highest AUC. Cumulative ranking of ten CCVRCs demonstrated that QRISK3 was the closest calculator to AECRS1.0_10yr, which is also consistent with the industry trend.