Genetic, sociodemographic, lifestyle, and clinical risk factors of recurrent coronary artery disease events: a population-based cohort study

Polygenic Risk Is Associated With Long-Term Coronary Plaque Progression and High-Risk Plaque

BACKGROUND

The longitudinal relation between coronary artery disease (CAD) polygenic risk score (PRS) and long-term plaque progression and high-risk plaque (HRP) features is unknown.

OBJECTIVES

The goal of this study was to investigate the impact of CAD PRS on long-term coronary plaque progression and HRP.

METHODS

Patients underwent CAD PRS measurement and prospective serial coronary computed tomography angiography (CTA) imaging. Coronary CTA scans were analyzed with a previously validated artificial intelligence-based algorithm (atherosclerosis imaging-quantitative computed tomography imaging). The relationship between CAD PRS and change in percent atheroma volume (PAV), percent noncalcified plaque progression, and HRP prevalence was investigated in linear mixed-effect models adjusted for baseline plaque volume and conventional risk factors.

RESULTS

A total of 288 subjects (mean age 58 ± 7 years; 60% male) were included in this study with a median scan interval of 10.2 years. At baseline, patients with a high CAD PRS had a more than 5-fold higher PAV than those with a low CAD PRS (10.4% vs 1.9%; P < 0.001). Per 10 years of follow-up, a 1 SD increase in CAD PRS was associated with a 0.69% increase in PAV progression in the multivariable adjusted model. CAD PRS provided additional discriminatory benefit for above-median noncalcified plaque progression during follow-up when added to a model with conventional risk factors (AUC: 0.73 vs 0.69; P = 0.039). Patients with high CAD PRS had an OR of 2.85 (95% CI: 1.14-7.14; P = 0.026) and 6.16 (95% CI: 2.55-14.91; P < 0.001) for having HRP at baseline and follow-up compared with those with low CAD PRS.

CONCLUSIONS

Polygenic risk is strongly associated with future long-term plaque progression and HRP in patients suspected of having CAD.

Impact of lipoprotein(a) and fibrinogen on prognosis in patients with coronary artery disease: A retrospective cohort study

BACKGROUND

Despite the considerable progress made in preventative methods, medication, and interventional therapies, it remains evident that cardiovascular events (CVEs) continue to be the primary cause of both death and morbidity among individuals diagnosed with coronary artery disease (CAD).

OBJECTIVE

To compare the connection between lipoprotein a (Lp[a]), fibrinogen (Fib), and both parameters combined with all-cause mortality to detect their value as prognostic biomarkers.

METHODS

This is a retrospective study. Patients diagnosed with CAD between January 2007 and December 2020 at the Guangdong Provincial People's Hospital (China) were involved in the study. 43,367 patients met the eligibility criteria. The Lp(a) and Fib levels were distributed into three tertile groups (low, medium, and high). All of the patients included in the study were followed up for all-cause mortality. Kaplan-Meier and Cox regression were performed to determine the relationship between Lp(a), Fib, and all-cause mortality. A concordance statistics model was developed to detect the impact of Fib and Lp(a) in terms of anticipating poor outcomes in patients with CAD.

RESULTS

Throughout a median follow-up of 67.0 months, 6,883 (15.9%) patients died. Participants with high Lp(a) (above 27.60 mg/dL) levels had a significantly higher risk for all-cause mortality than individuals with low Lp(a) levels (below 11.13 mg/dL; adjusted hazard ratio [aHR] 1.219, 95% confidence interval [CI]: 1.141-1.304, p< 0.001). Similarly, patients with high Fib levels (above 4.32 g/L) had a significantly greater risk of developing all-cause mortality compared with those with reduced Fib levels (below 3.41 g/L; aHR 1.415, 95% CI: 1.323-1.514, p< 0.001). Patients with raised Lp(a) and Fib levels had the maximum risk for all-cause mortality (aHR 1.702; 95% CI: 1.558-1.859, p< 0.001). When considered together, Lp(a) and Fib caused a significant elevation of the concordance statistic by 0.009 (p< 0.05), suggesting a higher value for predicting mortality when combining the two indicators.

CONCLUSION

High Lp(a) and Fib levels could be used as predictive biomarkers for all-cause mortality in individuals with CAD. The prediction accuracy for all-cause mortality improved after combining the two parameters.

Ischaemic heart disease in patients with cancer

Cardiologists are encountering a growing number of cancer patients with ischaemic heart disease (IHD). Several factors account for the interrelationship between these two conditions, in addition to improving survival rates in the cancer population. Established cardiovascular (CV) risk factors, such as hypercholesterolaemia and obesity, predispose to both IHD and cancer, through specific mechanisms and via low-grade, systemic inflammation. This latter is also fuelled by clonal haematopoiesis of indeterminate potential. Furthermore, experimental work indicates that IHD and cancer can promote one another, and the CV or metabolic toxicity of anticancer therapies can lead to IHD. The connections between IHD and cancer are reinforced by social determinants of health, non-medical factors that modify health outcomes and comprise individual and societal domains, including economic stability, educational and healthcare access and quality, neighbourhood and built environment, and social and community context. Management of IHD in cancer patients is often challenging, due to atypical presentation, increased bleeding and ischaemic risk, and worse outcomes as compared to patients without cancer. The decision to proceed with coronary revascularization and the choice of antithrombotic therapy can be difficult, particularly in patients with chronic coronary syndromes, necessitating multidisciplinary discussion that considers both general guidelines and specific features on a case by case basis. Randomized controlled trial evidence in cancer patients is very limited and there is urgent need for more data to inform clinical practice. Therefore, coexistence of IHD and cancer raises important scientific and practical questions that call for collaborative efforts from the cardio-oncology, cardiology, and oncology communities.

Association between Head and Neck Cancer and Increased Risk of Ischemic Heart Disease: A Retrospective Cohort Study Using National Population Data

Although cancer and ischemic heart disease (IHD) frequently manifest in the same individual, the risk of IHD events in cancer, especially head and neck cancer (HNC), remains unclear. We aimed to examine the incidence and risk of IHD events in patients with HNC using a population-based cohort dataset in South Korea (2002-2013). Through rigorous propensity score matching, we compared data from 2816 individuals without HNC and 704 individuals with HNC. Key independent variables were matched between groups, and the Charlson Comorbidity Index was used to match comorbidities. The Kaplan-Meier method depicted the cumulative probability of IHD throughout the follow-up period for both the study and control groups. The overall IHD incidence was significantly higher (19.93) in patients with HNC than in those without HNC (14.81), signifying an augmented IHD risk in the HNC cohort. Subsequent temporal analysis revealed a significant surge in IHD risk commencing 4 years after HNC diagnosis and persisting throughout the follow-up period. Subgroup analysis revealed an increased IHD risk in men with HNC and patients with cancers affecting the oral and sinonasal regions. This retrospective cohort study provides valuable scientific insights into the nuanced relationship between HNC and IHD, underscoring the need for tailored monitoring protocols and specialized care for susceptible individuals.

Associations of Lower-Carbohydrate and Lower-Fat Diets with Mortality among People with Cardiovascular Disease

BACKGROUND

Although low-carbohydrate and low-fat diets have been shown to have short-term metabolic benefits, the associations of these dietary patterns, particularly different food sources and macronutrient quality, with mortality in people with cardiovascular disease (CVD) remain unclear.

OBJECTIVES

To examine the associations of different types of lower-carbohydrate diets (LCDs) and lower-fat diets (LFDs) with mortality in individuals with CVD.

METHODS

This study included 3971 adults with CVD from the NHANES 1999-2014. Mortality status was linked to National Death Index mortality data through 31 December 2019. Overall, unhealthy and healthy LCD and LFD scores were determined based on the percentages of energy from total and subtypes of carbohydrate, fat, and protein. Cox proportional hazards regression models were applied to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

Higher healthy LCD score was associated with favorable blood lipids and higher homeostasis model assessment of insulin resistance, whereas higher unhealthy LFD score was associated with lower high-density lipoprotein and higher C-reactive protein at baseline (all P-trend < 0.05). During 35,150 person-years of follow-up, 2163 deaths occurred. For per 20-percentile increment in dietary scores, the multivariate-adjusted HRs of all-cause mortality were 0.91 (95% CI: 0.86, 0.96) for healthy LCD score (P < 0.001), 0.94 (95% CI: 0.89, 1.00) for healthy LFD score (P = 0.04), and 1.07 (95% CI: 1.00, 1.14) for unhealthy LFD score (P = 0.04).

CONCLUSIONS

Overall LCD and LFD scores are not associated with total mortality. Unhealthy LFD scores are associated with higher total mortality, whereas healthy LCD and LFD scores are associated with lower mortality in people with CVD.

Clinical applications of polygenic risk score for coronary artery disease through the life course

Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide, highlighting the limitations of current primary and secondary prevention frameworks. In this review, we detail how the polygenic risk score for CAD can improve our current preventive and treatment frameworks across three clinical applications that span the life course: (i) identification and treatment of people at increased risk early in the life course prior to the onset of clinical risk factors, (ii) improving the precision around risk estimation in middle age, and (ii) guiding treatment decisions and enabling more efficient clinical trials even after the onset of CAD. We end by summarizing the efforts needed as we head towards more widespread use of polygenic risk score for CAD in clinical practice.