Lipoprotein(a) associated with coronary artery disease in older women: age and gender analysis

Abstract Background Coronary vascular dysfunction is a common cause of symptoms in patients with angina and no obstructed coronary arteries (ANOCA). Several endotypes have been defined but there are big gaps in our understanding of the underlying pathophysiology. Proteomic analyses may improve the understanding of the pathophysiology. Purpose Exploratory approach to 1) compare the proteomic biomarker profile across different types of vascular dysfunction in ANOCA and 2) assess the value of prediction models with protein biomarkers for vascular dysfunction in ANOCA. Methods We included 107 angina patients without previous coronary artery disease, left ventricular ejection fraction >45% and no obstructive coronary artery disease (CAD) (<50% stenosis of epicardial vessels) on coronary angiography. Three types of vascular dysfunction were assessed: 1) Vasomotor dysfunction (VMD) defined as epicardial or microvascular vasospasm on acetylcholine provocation, 2) Coronary microvascular dysfunction (CMD) defined as coronary flow velocity reserve (CFVR) ≤2.5 on echocardiography of the LAD on adenosine stimulation and 3) Reactive Hyperaemia Index (RHI) ≤1.67 as a measure of peripheral endothelial dysfunction. Blood samples were analysed for 184 protein biomarkers related to cardiovascular disease. Correlations between biomarkers and results of vascular function assessments were analysed with Pearson's correlation coefficient and visualized with volcano plots. Significantly correlated biomarkers (p<0.05) were tested in prediction models for their incremental value over age and gender with C-statistics. Results CFVR was correlated to 24 biomarkers before (figure 1a) and 2 biomarkers after adjustment for age and gender. The basic prediction model had AUC of 0.68 and was not significantly improved by adding biomarkers (figure 2a). RHI was correlated to 27 biomarkers before (figure 1b) and 10 biomarkers after adjustment for age and gender. The clinical prediction model was significantly improved (p=0.037) by adding TRAIL R2 and IL-18, in addition to age and gender, with an AUC of 84.4 (figure 2b). VMD was correlated to 14 biomarkers before (figure 1c) and 6 biomarkers after adjustment for age and gender. The prediction model was significantly improved (p=0.011) by adding HSP-27, RARRES-2 and SERPINA-12 in addition to age and gender in prediction of VMD with an AUC of 85.4 (figure 2c). Conclusion Several biomarkers were associated with vascular dysfunction in ANOCA patients with little overlap between different endotypes. We identified biomarkers that may contribute to the understanding of the underlying pathophysiology and have applications for screening. Results need to be confirmed in larger studies. FUNDunding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Department of Cardiology, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Denmark.Department of Cardiology and Angiology, Robert Bosch Krankenhaus, Stuttgart, Germany

Download Full-text

Epidemiological Analysis of Major Cardiovascular Risk Factors in 1,508 Indian Adults Stratified by Age and Gender

Journal of Evidence Based Medicine and Healthcare ◽

10.18410/jebmh/2021/119 ◽

2021 ◽

Vol 8 (11) ◽

pp. 608-612

Author(s):

Sunil S. Thanvi ◽

Sunil K. Karna ◽

Utsav B Patel

Keyword(s):

Risk Factors ◽

Coronary Artery Disease ◽

Cardiovascular Risk ◽

Coronary Artery ◽

Cardiovascular Risk Factors ◽

Vitamin D3 ◽

Density Lipoprotein ◽

Age And Gender ◽

Artery Disease ◽

And Gender

BACKGROUND Routine screening of healthy individuals for the presence of cardiovascular risk factors is important for identification of high-risk coronary artery disease (CAD) patients at early stage and to provide preventive care. Considering the high burden of CAD, such investigations are of significant importance in Indian context. METHODS In this cross-sectional study, adult individuals (18 – 68 years) were evaluated for pre-existing diseases, lipid profile, blood glucose profile, thyroid profile, haemoglobin (Hb) and vitamins D3 and B12 levels after obtaining informed consent. These variables were compared between patients stratified based on their gender and age (< 40, 40 – 60, > 60 years). RESULTS A total of 1,508 participants (mean age: 49 ± 11 years; 49.9 % females) were investigated. Hypertension, diabetes, dyslipidaemia, anaemia, vitamin D3 and B12 deficiencies, hyperthyroidism, and hypothyroidism were observed in 31.2 %, 26.5 %, 32.0 %, 8.6 %, 35.3 %, 25.1 %, 21.0 % and 0.6 % of patients respectively. Prevalence of hypertension, diabetes, and dyslipidaemia increased with ageing, while deficiencies of Hb, vitamin D3, and vitamin B12 as well as hyperthyroidism and hypothyroidism were comparable across all age groups. Males were more prone to hypertension, diabetes, and dyslipidaemia, while females were more prone to have Hb deficiency, hyperthyroidism, and hypothyroidism. Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), fasting blood sugar (FBS), vitamin D3, and vitamin B12 were elevated with increase in age, while Hb levels decreased. Males exhibited higher levels of TG, low-density lipoprotein cholesterol (LDL-C), TC / HDL, LDL / HDL, FBS, and Hb, while females displayed higher levels of vitamin D3 and B12. CONCLUSIONS Our findings verify the role of age and gender on majority of cardiovascular risk factors. The high prevalence of cardiovascular risk factors is alarming and demands the need for appropriate health-care measures. KEYWORDS Age, Coronary Artery Disease, Gender, Risk Factor

Download Full-text