Return to sports after COVID-19: a position paper from the Dutch Sports Cardiology Section of the Netherlands Society of Cardiology.

The coronavirus disease 2019 (COVID-19) pandemic has led to preventive measures worldwide. With the decline of infection rates, less stringent restrictions for sports and exercise are being implemented. COVID-19 is associated with significant cardiovascular complications; however there are limited data on cardiovascular complications and long-term outcomes in both competitive (elite) athletes and highly active individuals. Based on different categories of disease severity (asymptomatic, regional/systemic symptoms, hospitalisation, myocardial damage, and/or myocarditis), in this point-of-view article we offer the (sports) cardiologist or sports physician in the Netherlands a practical guide to pre-participation screening, and diagnostic and management strategies in all athletes >16 years of age after COVID-19 infection.

Genome-wide association analysis of coffee drinking suggests association with CYP1A1/CYP1A2 and NRCAM.

Coffee consumption is a model for addictive behavior. We performed a meta-analysis of genome-wide association studies (GWASs) on coffee intake from 8 Caucasian cohorts (N=18 176) and sought replication of our top findings in a further 7929 individuals. We also performed a gene expression analysis treating different cell lines with caffeine. Genome-wide significant association was observed for two single-nucleotide polymorphisms (SNPs) in the 15q24 region. The two SNPs rs2470893 and rs2472297 (P-values=1.6 × 10(-11) and 2.7 × 10(-11)), which were also in strong linkage disequilibrium (r(2)=0.7) with each other, lie in the 23-kb long commonly shared 5' flanking region between CYP1A1 and CYP1A2 genes. CYP1A1 was found to be downregulated in lymphoblastoid cell lines treated with caffeine. CYP1A1 is known to metabolize polycyclic aromatic hydrocarbons, which are important constituents of coffee, whereas CYP1A2 is involved in the primary metabolism of caffeine. Significant evidence of association was also detected at rs382140 (P-value=3.9 × 10(-09)) near NRCAM-a gene implicated in vulnerability to addiction, and at another independent hit rs6495122 (P-value=7.1 × 10(-09))-an SNP associated with blood pressure-in the 15q24 region near the gene ULK3, in the meta-analysis of discovery and replication cohorts. Our results from GWASs and expression analysis also strongly implicate CAB39L in coffee drinking. Pathway analysis of differentially expressed genes revealed significantly enriched ubiquitin proteasome (P-value=2.2 × 10(-05)) and Parkinson's disease pathways (P-value=3.6 × 10(-05)).

Does aortic stiffness improve the prediction of coronary heart disease in elderly? The Rotterdam Study.

It has been demonstrated that aortic stiffness is an independent predictor of cardiovascular disease. We investigated whether this measure is of use in cardiovascular risk stratification in clinical practice for elderly subjects (mean age 71.5 years). Within the framework of the Rotterdam Study, we stratified subjects free of coronary heart disease (CHD) at baseline into categories of low (<10%), intermediate (10-20%) and high (>20%) 10-year risk of CHD based on Framingham risk factors. Within each risk category, we determined the percentages of subjects moving into a higher or lower risk category when adding aortic stiffness to the Framingham risk factors. Among 2849 participants, 223 CHD events occurred during a median follow-up of 7.9 years. In the low risk group, 5% of the subjects could be reclassified and in the high-risk group, 6% of the subjects could be reclassified to the intermediate-risk group. In the intermediate-risk group 3% could be reclassified to the high-risk group and 6% to the low-risk group. In a population of elderly subjects, aortic stiffness measurement in addition to Framingham risk factors leads to a limited reclassification of subjects in 10-year cardiovascular disease-risk categories. Therefore, aortic stiffness is associated with the risk of CHD in elderly, but provides no additional value in cardiovascular risk stratification.

Measures of body composition and risk of heart failure in the elderly: the Rotterdam study.

OBJECTIVES: The incidence of heart failure increases with aging. Aim of the present study was to determine whether measures body composition predict incident heart failure in older adults. SETTING: Prospective community-based cohort study. 5, 868 men and women aged 55 years and older participating the Rotterdam study. Measures of body mass index and waist circumference were obtained at baseline. Information on incident heart failure was obtained during follow-up. Cox regression analyses were performed to investigate the possible association between measure of body composition and incident heart failure. RESULTS: During a mean follow up of 10.9 (SD ±4.4) years, 765 participants had heart failure. After adjustment for age and gender, 1-standard deviation of body mass index, waist circumference and the waist-hip ratio predicted heart failure (HR 1.25; 95% CI 1.17-1.34; HR 1.26; 95% CI 1.18-1.36; and HR 1.17; 95% CI 1.08-1.27), respectively. In age-stratified analyses, 1-standard deviation of body mass index (1.17; 95% CI 1.06- 1.29) and waist circumference (1.16; 95% CI 1.05- 1.29) were still associated with the risk of heart failure in the oldest participants, whereas the waist-hip ratio was not (1.06; 95% CI 0.945-1.18). CONCLUSION: Although estimates decrease with age, measures of overall and central adiposity predict incident heart failure among community dwelling older adults.