ABSTRACT
BACKGROUND: Environmental metal exposures have been associated with multiple deleterious health endpoints. DNA methylation (DNAm) may provide insight into the mechanisms underlying these relationships. Toenail metals are non-invasive biomarkers, reflecting a medium-term time exposure window. OBJECTIVES: This study examined variation in leukocyte DNAm and toenail arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg) among elderly men in the Normative Aging Study, a longitudinal cohort. METHODS: We repeatedly collected samples of blood and toenail clippings. We measured DNAm in leukocytes with the Illumina HumanMethylation450 K BeadChip. We first performed median regression to evaluate the effects of each individual toenail metal on DNAm at three levels: individual cytosine-phosphate-guanine (CpG) sites, regions, and pathways. Then, we applied a Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of metal mixtures on DNAm. Significant CpGs were identified using a multiple testing correction based on the independent degrees of freedom approach for correlated outcomes. The approach considers the effective degrees of freedom in the DNAm data using the principal components that explain >95% variation of the data. RESULTS: We included 564 subjects (754 visits) between 1999 and 2013. The numbers of significantly differentially methylated CpG sites, regions, and pathways varied by metals. For example, we found six significant pathways for As, three for Cd, and one for Mn. The As-associated pathways were associated with cancer (e.g., skin cancer) and cardiovascular disease, whereas the Cd-associated pathways were related to lung cancer. Metal mixtures were also associated with 47 significant CpG sites, as well as pathways, mainly related to cancer and cardiovascular disease. CONCLUSIONS: This study provides an approach to understanding the potential epigenetic mechanisms underlying observed relations between toenail metals and adverse health endpoints.
ABSTRACT
AIMS: Diabetes mellitus has been reported to be one of the most prevalent comorbidity in patients with Coronavirus Disease 2019 (COVID-19). We aimed to assess the association of comorbid diabetes with COVID-19 severity or mortality in China. METHODS: We performed a systematic literature search from six electronic databases on diabetes and COVID-19. The outcome of interest was disease severity or mortality. Heterogeneity among the studies was assessed by the Cochran Q test and the I2 statistic. A random effects model was applied to calculate the pooled risk ratio (RR) with 95% confidence interval (CI). RESULTS: Nine studies from different provinces/cities were identified according to the predefined inclusion and exclusion criteria. There were a total of 1070 patients with diabetes, out of the 8807 COVID-19 cases. The majority of the cases were derived from Hubei Province. A low degree of heterogeneity in the risk estimates was observed in the included studies. Meta-analysis showed that there was a significant association of preexisting diabetes with disease severity or death. The pooled RR was 2.96 (95% CI: 2.31-3.79; p < 0.001). Sensitivity analysis demonstrated no significant changes in the pooled estimates. CONCLUSIONS: Comorbid diabetes was associated with an increased risk of disease severity or death in Chinese COVID-19 patients.