SummaryWhile many disease-associated variants have been identified through genome-wide association studies, their downstream molecular consequences remain unclear.To identify these effects, we performed cis- and trans-expression quantitative trait locus (eQTL) analysis in blood from 31,684 individuals through the eQTLGen Consortium.We observed that cis-eQTLs can be detected for 88% of the studied genes, but that they have a different genetic architecture compared to disease-associated variants, limiting our ability to use cis-eQTLs to pinpoint causal genes within susceptibility loci.In contrast, trans-eQTLs (detected for 37% of 10,317 studied trait-associated variants) were more informative. Multiple unlinked variants, associated to the same complex trait, often converged on trans-genes that are known to play central roles in disease etiology.We observed the same when ascertaining the effect of polygenic scores calculated for 1,263 genome-wide association study (GWAS) traits. Expression levels of 13% of the studied genes correlated with polygenic scores, and many resulting genes are known to drive these traits.

Hyperhomocysteinemia has been associated with premature atherothrombotic vascular disease. It is not known whether hyperhomocysteinemia induces a distinct type of vascular disease. Its interaction, if any, with traditional risk factors also remains unclear. The pathophysiological mechanisms linking hyperhomocysteinemia to vascular disease have been extensively studied in vitro and in animals. From these studies, it has been suggested that homocysteine limits the bioavailability of nitric oxide (NO), increases oxidative stress, stimulates smooth cell proliferation, and alters elastic wall properties. The relevance of these proposed mechanisms in vivo is unclear, because clinical studies have yielded controversial results with regard to the relation between plasma homocysteine levels and indices of endothelial function, such as brachial artery flow-mediated vasodilatation and plasma levels of endothelium-derived marker proteins. Up till now, there have been no controlled data on the effects of homocysteine-lowering treatment on vascular function or clinical end points. The precise mechanisms (if any) by which homocysteine mediates its adverse vascular effects are in fact unknown but may relate to impaired endothelial and smooth muscle cell function.

The results of the present study show that in this group of patients with uncomplicated IDDM, vessel wall properties of elastic and muscular large arteries were not obviously reduced when compared with healthy control subjects. However, distensibility of the FA was lower in IDDM patients. Early atherosclerotic changes in IDDM frequently occur at this site. A difference related to the duration of diabetes could not be excluded.

In subjects with a recent history of impaired glucose tolerance, we observed an increase in carotid artery diameter and a decrease in distensibility. Change in blood pressure level and baseline fasting glucose and HbA1c levels were positively related to the increase in diameter. In men, but not in women, baseline fasting insulin levels were associated with an acceleration of these changes.

In large population-based cohort studies, magnetic resonance imaging (MRI) is often used to study the structure and function of the brain. Advanced MRI techniques such as diffusiontensor (dMRI) or resting-state functional MRI (rs-fMRI) can be used to study connections between distinct brain regions. However, brain connectivity measures are likely affected by biases introduced during MRI data acquisition and/or processing.We identified three sources that may lead to bias, i.e. signal-to-noise ratio (SNR), head motion, and spatial mismatch between MRI-based anatomy and a brain atlas. After quantifying these sources, we determined the associations between the image quality metrics and brain connectivity measures derived from dMRI and rs-fMRI in 5,110 participants of the population-based Maastricht Study.More head motion and low SNR were negatively associated with structural and functional brain connectivity, respectively, and these metrics substantially affected (>10%) associations of brain connectivity with age, sex and body mass index (BMI), whereas associations with diabetes status, educational level, history of cardiovascular disease, and white matter hyperintensities were less or not affected. In addition, age, sex, and BMI were associated with head motion, SNR, and atlas mismatch (all p < 0.001). Based on our results, we strongly advise that, in large population-based cohort neuroimaging studies, statistical analyses on structural and functional brain connectivity should adjust for potentially confounding effects of image quality.