Associations of Arterial Stiffness With Cognitive Performance, and the Role of Microvascular Dysfunction:The Maastricht Study

The mechanisms underlying cognitive impairment are incompletely understood but may include arterial stiffness and microvascular dysfunction. In the population-based Maastricht Study, we investigated the association between arterial stiffness and cognitive performance, and whether any such association was mediated by microvascular dysfunction. We included cross-sectional data of 2544 participants (age, 59.7 years; 51.0% men; 26.0% type 2 diabetes mellitus). We used carotid-femoral pulse wave velocity and carotid distensibility coefficient as measures of aortic and carotid stiffness, respectively. We calculated a composite score of microvascular dysfunction based on magnetic resonance imaging features of cerebral small vessel disease, flicker light-induced retinal arteriolar and venular dilation response, albuminuria, and plasma biomarkers of microvascular dysfunction (sICAM-1 [soluble intercellular adhesion molecule-1], sVCAM-1 [soluble vascular adhesion molecule-1], sE-selectin [soluble E-selectin], and vWF [von Willebrand factor]). Cognitive domains assessed were memory, processing speed, and executive function. A cognitive function score was calculated as the average of these domains. Higher aortic stiffness (per m/s) was associated with lower cognitive function (β, -0.018 SD [95% CI, -0.036 to -0.000]) independent of age, sex, education, and cardiovascular risk factors, but higher carotid stiffness was not. Higher aortic stiffness (per m/s) was associated with a higher microvascular dysfunction score (β, 0.034 SD [95% CI, 0.014 to 0.053]), and a higher microvascular dysfunction score (per SD) was associated with lower cognitive function (β, -0.089 SD [95% CI, -0.124 to -0.053]). Microvascular dysfunction significantly explained 16.2% of the total effect of aortic stiffness on cognitive function. The present study showed that aortic stiffness, but not carotid stiffness, is independently associated with worse cognitive performance, and that this association is in part explained by microvascular dysfunction

Occupational exposure to gases/fumes and mineral dust affect DNA methylation levels of genes regulating expression

Many workers are daily exposed to occupational agents like gases/fumes, mineral dust or biological dust, which could induce adverse health effects. Epigenetic mechanisms, such as DNA methylation, have been suggested to play a role. We therefore aimed to identify differentially methylated regions (DMRs) upon occupational exposures in never-smokers and investigated if these DMRs associated with gene expression levels. To determine the effects of occupational exposures independent of smoking, 903 never-smokers of the LifeLines cohort study were included. We performed three genome-wide methylation analyses (Illumina 450 K), one per occupational exposure being gases/fumes, mineral dust and biological dust, using robust linear regression adjusted for appropriate confounders. DMRs were identified using comb-p in Python. Results were validated in the Rotterdam Study (233 never-smokers) and methylation-expression associations were assessed using Biobank-based Integrative Omics Study data (n = 2802). Of the total 21 significant DMRs, 14 DMRs were associated with gases/fumes and 7 with mineral dust. Three of these DMRs were associated with both exposures (RPLP1 and LINC02169 (2x)) and 11 DMRs were located within transcript start sites of gene expression regulating genes. We replicated two DMRs with gases/fumes (VTRNA2-1 and GNAS) and one with mineral dust (CCDC144NL). In addition, nine gases/fumes DMRs and six mineral dust DMRs significantly associated with gene expression levels. Our data suggest that occupational exposures may induce differential methylation of gene expression regulating genes and thereby may induce adverse health effects. Given the millions of workers that are exposed daily to occupational exposures, further studies on this epigenetic mechanism and health outcomes are warranted

Author Correction: Distinct circadian mechanisms govern cardiac rhythms and susceptibility to arrhythmia

From Springer Nature via Jisc Publications RouterHistory: registration 2021-11-25, collection 2021-12, pub-electronic 2021-12-08, online 2021-12-08Publication status: Publishe

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways