AK098656: a new biomarker of coronary stenosis severity in hypertensive and coronary heart disease patients

Background AK098656 may be an adverse factor for coronary heart disease (CHD), especially in patients with hypertension. This study aimed to analyze the effect of AK098656 on CHD and CHD with various complications. Methods A total of 117 CHD patients and 27 healthy control subjects were enrolled in the study. Plasma AK098656 expression was determined using the quantitative real-time polymerase chain reaction. Student’s t-test was used to compare AK098656 expression levels in different groups. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to quantify the discrimination ability between CHD patients and health controls and between CHD and CHD + complications patients. The relationship between AK098656 and coronary stenosis was analyzed using Spearman’s correlation. Results AK098656 expression was remarkably higher in CHD patients than in healthy controls (P = 0.03). The ROC curve revealed an effective predictive AK098656 expression value for CHD risk, with an AUC of 0.656 (95% CI 0.501–0.809). Moreover, AK098656 expression was increased in CHD + complications patients compared to CHD patients alone (P = 0.005), especially in patients with hypertension (CHD + hHTN, P = 0.030). The ROC curve revealed a predictive AK098656 prognostic value for discriminating between CHD and CHD + hHTN patients, with an AUC of 0.666 (95% CI 0.528–0.805). There was no significant difference in AK098656 expression in CHD patients with diabetes mellitus compared to CHD patients alone. In addition, AK098656 expression in CHD patients was positively correlated with stenosis severity (R = 0.261, P = 0.006). Conclusion AK098656 expression was significantly increased in patients with CHD, especially those with hypertension, and its expression level was positively correlated with the degree of coronary stenosis. This implied that AK098656 may be a risk factor for CHD and can potentially be applied in clinical diagnosis or provide a novel target for treatment.

Association Between Thyroid Cancer and Cardiovascular Disease Risk: A Nationwide Observation Study

BackgroundResearch findings on the long-term cardiovascular risk associated with thyroid cancer and treatment are unclear. This study aimed to investigate the standardized incidence rate (SIR) of coronary heart disease (CHD), ischemic stroke (IS), and atrial fibrillation (AF) among thyroid cancer patients in comparison with the general population across different age groups. MethodsDesign, setting, and participantsThis observational cohort study enrolled patients between January 1, 2011 and December 31, 2016 with follow-up until December 31, 2018. This study analyzed the data of Taiwanese thyroid cancer patients registered on the National Taiwan Cancer Registry Database, with CHD and IS. Main outcomes and measuresSIR models were used to evaluate the association between thyroid cancer and CHD, IS, AF, and cardiovascular disease outcome, stratified by age and sex. SIR analyses were also conducted for both sexes, age groups (<60, ≥60 years), and different follow-up years.ResultsAfter excluding 128 individuals <20 years or >85 years and with missing index data, 4274 eligible thyroid cancer patients without CHD history, 4343 patients without IS history, and 4247 patients without AF history were included for analysis. During the median follow-up of 3.5 (1.2) years, CHD incidence was 70; IS, 30; and AF, 20. Compared with the general population, thyroid cancer patients had higher CHD risk throughout the age spectrum (SIR, 1.33; 95% confidence interval [CI], 1.02 to 1.65). The overall CHD risk gradually declined, but it was persistent for more than 5 years after thyroid cancer diagnosis. CHD risk was observed in both males and females, especially in young thyroid cancer patients <65 years. However, lower SIRs for IS (SIR, 0.74; 95% CI, 0.47 to 1), AF (SIR, 0.74; 95% CI, 0.42 to 1.06), and cardiovascular disease (SIR, 0.88; 95% CI, 0.7 to 1.05) were observed among thyroid cancer patients (not significant). ConclusionsThyroid cancer survivors have a substantial CHD risk even at long-term follow-up, especially in those patients <65 years. Further research on the association between thyroid cancer and CHD risk is warranted.

Clinical Significance of Intermediate-Density Lipoprotein Cholesterol Determination as a Predictor for Coronary Heart Disease Risk in Middle-Aged Men

Background: Not only low-density lipoprotein (LDL) cholesterol but also non-high-density lipoprotein cholesterol (non-HDL-C), very low-density lipoprotein (VLDL) cholesterol (VLDL-C), and intermediate-density lipoprotein (IDL) cholesterol (IDL-C) are reported to be significant risk markers for coronary heart disease (CHD). We reported the relevance of IDL-C to Framingham risk score (F-score), but the present study addressed the relevance of IDL-C to Suita score (S-score), a risk score for coronary heart disease (CHD) developed for the Japanese individuals in addition to F-score.Methods: The cholesterol levels of lipoproteins, including triglyceride (TG)-rich lipoproteins (IDL and VLDL), were measured by an anion exchange high-performance liquid chromatography (AEX-HPLC). This study enrolled 476 men, aged mean 51 years and free of CHD and stroke.Results: Non-HDL-C, IDL-C, and VLDL-C significantly correlated with F-score and S-score. In the multiple stepwise regression analysis, IDL-C as well as body mass index (BMI) significantly correlated with both F-score and S-score in both the total subjects and the subjects without drug therapy. The multivariate logistic analysis with the model composed of BMI and IDL-C as the predictor variables demonstrated that 1 SD increase in IDL-C was an independent predictor for 10-year CHD risk &gt;10% of F-score (OR 1.534, 95% CI 1.266–1.859, p &lt; 0001) and that of S-score (OR 1.372, 95% CI 1.130–1.667, p = 0.0014) in the total subjects. Even in the subjects without the drug therapy, the increased IDL-C, as well as BMI, were significant predictors for 10-year CHD risk &gt;10% of S-score as well as F-score.Conclusion: These results suggest the significant relevance of the increased IDL-C for CHD risk scores in middle-aged men free of CHD and stroke. Further investigations are needed in women and elderly subjects.

Comparative Risk of Incident Coronary Heart Disease Across Chronic Inflammatory Diseases

Background: Chronic inflammatory diseases (CIDs) are considered risk enhancing factors for coronary heart disease (CHD). However, sparse data exist regarding relative CHD risks across CIDs.Objective: Determine relative differences in CHD risk across multiple CIDs: psoriasis, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), human immunodeficiency virus (HIV), systemic sclerosis (SSc), and inflammatory bowel disease (IBD).Methods: The cohort included patients with CIDs and controls without CID in an urban medical system from 2000 to 2019. Patients with CIDs were frequency-matched with non-CID controls on demographics, hypertension, and diabetes. CHD was defined as myocardial infarction (MI), ischemic heart disease, and/or coronary revascularization based on validated administrative codes. Multivariable-adjusted Cox models were used to determine the risk of incident CHD and MI for each CID relative to non-CID controls. In secondary analyses, we compared CHD risk by disease severity within each CID.Results: Of 17,049 patients included for analysis, 619 had incident CHD (202 MI) over an average of 4.4 years of follow-up. The multivariable-adjusted risk of CHD was significantly higher for SLE [hazard ratio (HR) 1.9, 95% confidence interval (CI) 1.2, 3.2] and SSc (HR 2.1, 95% CI 1.2, 3.9). Patients with SLE also had a significantly higher risk of MI (HR 3.6, 95% CI 1.9, 6.8). When CIDs were categorized by markers of disease severity (C-reactive protein for all CIDs except HIV, for which CD4 T cell count was used), greater disease severity was associated with higher CHD risk across CIDs.Conclusions: Patients with SLE and SSc have a higher risk of CHD. CHD risk with HIV, RA, psoriasis, and IBD may only be elevated in those with greater disease severity. Clinicians should personalize CHD risk and treatment based on type and severity of CID.

External validation of the UK Prospective Diabetes Study (UKPDS) risk engine in patients with type 2 diabetes identified in the national diabetes program in Iran

Background Cardiovascular diseases are the first leading cause of mortality in the world. Practical guidelines recommend an accurate estimation of the risk of these events for effective treatment and care. The UK Prospective Diabetes Study (UKPDS) has a risk engine for predicting CHD risk in patients with type 2 diabetes, but in some countries, it has been shown that the risk of CHD is poorly estimated. Hence, we assessed the external validity of the UKPDS risk engine in patients with type 2 diabetes identified in the national diabetes program in Iran. Methods The cohort included 853 patients with type 2diabetes identified between March 21, 2007, and March 20, 2018 in Lorestan province of Iran. Patients were followed for the incidence of CHD. The performance of the models was assessed in terms of discrimination and calibration. Discrimination was examined using the c-statistic and calibration was assessed with the Hosmer–Lemeshow χ2 statistic (HLχ2) test and a calibration plot was depicted to show the predicted risks versus observed ones. Results During 7464.5 person-years of follow-up 170 first Coronary heart disease occurred. The median follow-up was 8.6 years. The UKPDS risk engine showed moderate discrimination for CHD (c-statistic was 0.72 for 10-year risk) and the calibration of the UKPDS risk engine was poor (HLχ2=69.9, p<0.001) and overestimated the risk of heart disease. Conclusion This study shows that the ability of the UKPDS Risk Engine to discriminate patients who got CHD events from those who did not was moderate and the ability of the risk prediction model to accurately predict the absolute risk of CHD (calibration) was poor and it overestimated the CHD risk. To improve the prediction of CHD in patients with type 2 diabetes, this model should be updated in the Iranian diabetic population.

Milk intake and incident stroke and coronary heart disease in populations of European descent: A Mendelian Randomization study

Higher milk intake has been associated with a lower stroke risk, but not with risk of coronary heart disease (CHD). Residual confounding or reverse causation cannot be excluded. Therefore, we estimated the causal association of milk consumption with stroke and CHD risk through instrumental variable (IV) and gene-outcome analyses. IV analysis included 29,328 participants (4,611 stroke; 9,828 CHD) of the EPIC-CVD (8 European countries) and EPIC-NL case-cohort studies. rs4988235, a lactase persistence (LP) single nucleotide polymorphism which enables digestion of lactose in adulthood was used as genetic instrument. Intake of milk was first regressed on rs4988235 in a linear regression model. Next, associations of genetically predicted milk consumption with stroke and CHD were estimated using Prentice-weighted Cox regression. Gene-outcome analysis included 777,024 participants (50,804 cases) from MEGASTROKE (including EPIC-CVD), UK Biobank and EPIC-NL for stroke, and 483,966 participants (61,612 cases) from CARDIoGRAM, UK Biobank and EPIC-CVD and EPIC-NL for CHD. In IV analyses, each additional LP allele was associated with a higher intake of milk in EPIC-CVD (β=13.7 g/day; 95%CI: 8.4-19.1) and EPIC-NL (36.8 g/day; 20.0-53.5). Genetically predicted milk intake was not associated with stroke (HR per 25 g/day 1.05; 95%CI: 0.94-1.16) or CHD (1.02; 0.96-1.08). In gene-outcome analyses, there was no association of rs4988235 with risk of stroke (odds ratios 1.02; 0.99-1.05) or CHD (0.99; 0.95-1.03). Current Mendelian Randomization analysis does not provide evidence for a causal inverse relationship between milk consumption and stroke or CHD risk.

Prediction of coronary heart disease in rural Chinese adults: a cross sectional study

Background Coronary heart disease (CHD) is a common cardiovascular disease with high morbidity and mortality in China. The CHD risk prediction model has a great value in early prevention and diagnosis. Methods In this study, CHD risk prediction models among rural residents in Xinxiang County were constructed using Random Forest (RF), Support Vector Machine (SVM), and the least absolute shrinkage and selection operator (LASSO) regression algorithms with identified 16 influencing factors. Results Results demonstrated that the CHD model using the RF classifier performed best both on the training set and test set, with the highest area under the curve (AUC = 1 and 0.9711), accuracy (one and 0.9389), sensitivity (one and 0.8725), specificity (one and 0.9771), precision (one and 0.9563), F1-score (one and 0.9125), and Matthews correlation coefficient (MCC = one and 0.8678), followed by the SVM (AUC = 0.9860 and 0.9589) and the LASSO classifier (AUC = 0.9733 and 0.9587). Besides, the RF model also had an increase in the net reclassification index (NRI) and integrated discrimination improvement (IDI) values, and achieved a greater net benefit in the decision curve analysis (DCA) compared with the SVM and LASSO models. Conclusion The CHD risk prediction model constructed by the RF algorithm in this study is conducive to the early diagnosis of CHD in rural residents of Xinxiang County, Henan Province.

Trajectories of body mass index and risk for coronary heart disease: A 38-year follow-up study

Objective Obesity is a well-known risk factor for coronary heart disease (CHD), but there is little evidence on the effect of long-term trajectories of body mass index (BMI) over the life course. By using repeated assessments, the aim was to study the risk of CHD in adults during 38 years in different trajectories of BMI. Methods A sample of 2129 men and women, aged 20–59 years at baseline, took part in four repeated interviews between 1980 and 2005. Data on BMI, medical history, lifestyle and socioeconomy were collected. Based on the World Health Organization categories of BMI, life course trajectories of stable normal weight, stable overweight, stable obesity, increasing BMI and fluctuating BMI were created. The individuals were followed through national registers for first hospitalization of CHD (389 events) until the end of 2017, and Hazard Ratios (HRs) were calculated, adjusted for age, sex, socioeconomic factors, lifestyle factors and metabolic comorbidities. Results Stable normal weight in all assessments was the reference group. Those who had an increase in BMI from normal weight in the first assessment to overweight or obesity in later assessments had no increased risk of CHD, HR 1.04 (95% CI: 0.70–1.53). The HR for individuals with fluctuating BMI was 1.25 (0.97–1.61), for stable overweight 1.43 (1.03–1.98), for stable obesity 1.50 (0.92–2.55), and for stable overweight or obesity 1.45 (1.07–1.97), after full adjustments. Conclusion Having a stable overweight or obesity throughout adult life was associated with increased CHD risk but changing from normal weight at baseline to overweight or obesity was not associated with increased CHD risk. Prevention of obesity early in life may be particularly important to reduce CHD risk.

AK098656 – A New Biomarker of Coronary Stenosis Severity in Hypertensive and Coronary Heart Disease Patients

Background: AK098656 may be an adverse factor for coronary heart disease (CHD), especially in patients with hypertension. This study aimed to analyze the effect of AK098656 on CHD and CHD with various complications.Methods: A total of 117 CHD patients and 27 healthy control subjects were enrolled in the study. Plasma AK098656 expression was determined using the quantitative real-time polymerase chain reaction. Student’s t-test was used to compare AK098656 expression levels in different groups. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to quantify the discrimination ability between CHD patients and health controls and between CHD and CHD+complications patients. The relationship between AK098656 and coronary stenosis was analyzed using Spearman’s correlation.Results: AK098656 expression was remarkably higher in CHD patients than in healthy controls (P=0.03). The ROC curve revealed an effective predictive AK098656 expression value for CHD risk, with an AUC of 0.656 (95% CI: 0.501–0.809). Moreover, AK098656 expression was increased in CHD+complications patients compared to CHD patients alone (P=0.005), especially in patients with hypertension (CHD+hHTN, P=0.030). The ROC curve revealed a predictive AK098656 prognostic value for discriminating between CHD and CHD+hHTN patients, with an AUC of 0.666 (95% CI: 0.528–0.805). There was no significant difference in AK098656 expression in CHD patients with diabetes mellitus compared to CHD patients alone. In addition, AK098656 expression in CHD patients was positively correlated with stenosis severity (R=0.261, P=0.006).Conclusion: AK098656 expression was significantly increased in patients with CHD, especially those with hypertension, and its expression level was positively correlated with the degree of coronary stenosis. This implied that AK098656 may be a risk factor for CHD and can potentially be applied in clinical diagnosis or provide a novel target for treatment.

Role of Plasma Proteomics in Predicting the Prognosis of Older Adult Patients with Chronic Coronary Syndrome

Background: Chronic coronary syndrome (CCS) is a newly proposed concept and is hallmarked by more long-term major adverse cardiovascular events (MACEs), calling for accurate prognostic biomarkers for initial risk stratification.Methods: Data-independent acquisition liquid chromatography tandem mass spectrometry (DIA LC-MS/MS) quantitative proteomics was performed on 38 patients with CCS; 19 in the CCS events group and 19 in the non-events group as the controls. We also developed a machine-learning-based pipeline to identify proteins as potential biomarkers and validated the target proteins by enzyme-linked immunosorbent assay (ELISA) in an independent prospective cohort (n = 352).Results: Fifty-seven differentially expressed proteins were identified by quantitative proteomics and three final biomarkers were preliminarily selected from the machine-learning-based pipeline. Further validation with the prospective cohort showed that endothelial protein C receptor (EPCR) and cholesteryl ester transfer protein (CETP) levels at admission were significantly higher in the CCS events group than they were in the non-events group, whereas the carboxypeptidase B2 (CPB2) level was similar in the two groups. A correlation analysis showed that CETP was positively related to high-density lipoprotein cholesterol and triglyceride, and EPCR was positively related to fibrinogen. In the Cox survival analysis, EPCR and CETP were independent risk factors for MACEs. The cumulative risk duration of patients with high EPCR and CETP levels was significantly shorter than that of patients with low EPCR and CETP levels. We constructed a new prognostic model by combining the Framingham coronary heart disease (CHD) risk model with EPCR and CETP levels. This new model significantly improved the C-statistics for MACE prediction compared with that of the Framingham CHD risk model alone (AUC 0.732 vs. 0.684, p<0.05).Conclusions: Plasma proteomics was used to find biomarkers of predicting MACEs in patients with CCS. EPCR and CETP were identified as promising prognostic biomarkers for CCS. The Framingham CHD risk model combined with EPCR and CETP levels was shown to be a high-performance prognostic model for CCS.