Higher Levels of Stress-Related Hair Steroid Hormones Are Associated with the Increased SCORE2 Risk Prediction Algorithm in Apparently Healthy Women.
Eglė MazgelytėNeringa BurokienėAgata VysockaMartynas NarkevičiusTomas PetrėnasAndrius KaminskasJurgita SongailienėAlgirdas UtkusDovilė KarčiauskaitėPublished in: Journal of cardiovascular development and disease (2022)
Cardiovascular diseases (CVDs) are the major cause of death worldwide. Although the importance of conventional CVD risk factors, including older age, male gender, hypertension, obesity, dyslipidemia and hyperglycemia, is well-studied, psychosocial stress, which is considered an independent CVD risk factor, requires further investigation. Thus, we aimed to investigate the association between long-term secretion of stress-related steroid hormones, including cortisol, cortisone and dehydroepiandrosterone, and the 10-year fatal and non-fatal CVD risk estimated by the SCORE2 risk prediction algorithm, as well as traditional CVD risk factors in a group of apparently healthy women. A total of 145 women (aged 50-64 years) participating in the national CVD prevention program were enrolled in the study. Sociodemographic, lifestyle, health-related characteristics, stress, anxiety and sleep quality indicators were evaluated using specific questionnaires. Anthropometric and arterial blood pressure measures were assessed by trained personnel, lipid and glucose metabolism biomarkers were measured using routine methods, and hair steroid hormone levels were determined by ultra-high-performance liquid chromatography-tandem mass spectrometry. The results showed that higher levels of hair cortisol and cortisone are associated with increased SCORE2 values. Moreover, significant associations between hair glucocorticoids and individual cardiovascular risk factors, including obesity, hypertension, dyslipidemia and hyperglycemia, were found. These findings indicate that stress-related hair steroid hormones might be valuable biomarkers for CVD prediction and prevention.
Keyphrases
- risk factors
- blood pressure
- sleep quality
- cardiovascular risk factors
- metabolic syndrome
- liquid chromatography tandem mass spectrometry
- cardiovascular disease
- polycystic ovary syndrome
- weight loss
- insulin resistance
- physical activity
- stress induced
- type diabetes
- machine learning
- deep learning
- mental health
- pregnancy outcomes
- depressive symptoms
- quality improvement
- hypertensive patients
- heart rate
- high resolution
- body composition
- breast cancer risk
- ms ms
- adipose tissue
- mass spectrometry
- community dwelling
- clinical practice
- pregnant women
- cardiovascular events
- psychometric properties