Social support at work and mental distress: A three-wave study of normal, reversed, and reciprocal relationships.

OBJECTIVES: This longitudinal study aimed to investigate the causal relationships between social support at work and mental health in terms of mental distress. Despite assuming social support at work to be associated with less mental distress, reversed and reciprocal relationships were investigated as well. METHODS: Self-reports in questionnaires of social support and mental distress were collected longitudinally, with annual measurements over three consecutive years, among 301 office workers (57% women) in Sweden. Cross-lagged structural equation modeling was used to test the hypotheses. RESULTS: The reciprocal causation model was considered the best-fitting model. The results suggest that social support and mental distress influenced each other negatively, but with a delayed effect. Specifically, this involves Time 1 levels of social support being negatively associated with Time 2 levels of mental distress, while Time 2 levels of mental distress were negatively associated with Time 3 levels of support. CONCLUSIONS: The findings partly align with the hypothesis that social support is related to lower levels of mental distress but also suggest that mental distress can reduce levels of social support. While the findings also suggest a mutual interrelation between social support and mental distress, this is not a consistent reciprocal causation. Rather, and due to the variation in reciprocity between time points, it appears to be a cyclical process, which needs further investigation.

S-adenosylhomocysteine is associated with subclinical atherosclerosis and renal function in a cardiovascular low-risk population.

OBJECTIVE: Although homocysteine has been proposed as a cardiovascular risk factor, interventional trials lowering homocysteine have not consistently demonstrated clinical benefit. Recent evidence proposed the homocysteine metabolite S-adenosylhomocysteine (SAH) rather than homocysteine itself as the real culprit in cardiovascular disease. Of note, SAH is predominantly excreted by the kidneys, and cannot be lowered by vitamin supplementation. Due to its cumbersome measurement, data from large studies on the association between SAH, kidney function and cardiovascular disease are not available. METHODS: We recruited 420 apparently healthy subjects into our I Like HOMe FU study. Among all study participants, we assessed parameters of C1 metabolism (homocysteine, SAH and S-adenosylmethionine), renal function (estimated glomerular filtration rate [eGFR]) and subclinical atherosclerosis (common carotid intima-media-thickness [IMT]). eGFR was estimated by the CKD-EPIcreat-cys equation. RESULTS: Traditional cardiovascular risk factors and subclinical atherosclerosis were associated with SAH, but not with homocysteine (IMT vs SAH: r = 0.129; p = 0.010; IMT vs homocysteine: r = 0.009; p = 0.853). Moreover, renal function was more closely correlated with SAH than with homocysteine (eGFR vs SAH: r = -0.335; p < 0.001; eGFR vs homocysteine: r = -0.250; p < 0.001). The association between eGFR and SAH remained significant after adjustment for traditional cardiovascular risk factors. CONCLUSION: In summary, cardiovascular risk factors, subclinical atherosclerosis and eGFR are more strongly associated with SAH than with homocysteine in apparently healthy subjects. Thus, SAH might represent a more promising target to prevent cardiovascular disease than homocysteine.

SuperTAG methylation-specific digital karyotyping reveals uremia-induced epigenetic dysregulation of atherosclerosis-related genes.

BACKGROUND: Accelerated atherosclerosis is a hallmark of chronic kidney disease (CKD). Although the role of epigenetic dysregulation in atherosclerosis is increasingly appreciated, only a few studies focused on epigenetics in CKD-associated cardiovascular disease, virtually all of which assessed epigenetic dysregulation globally. We hypothesized that gene-specific epigenetic dysregulation in CKD exists, affecting genes pertinent to inflammation and atherosclerosis. METHODS AND RESULTS: Ten clinically stable patients undergoing hemodialysis therapy and 10 healthy age- and sex-matched controls were recruited. Genome-wide analysis of DNA methylation was performed by SuperTAG methylation-specific digital karyotyping, in order to identify genes differentially methylated in CKD. Analysis of 27 043 436 tags revealed 4288 genomic loci with differential DNA methylation (P<10(-10)) between hemodialysis patients and control subjects. Annotation of UniTags to promoter databases allowed us to identify 52 candidate genes associated with cardiovascular disease and 97 candidate genes associated with immune/infection diseases. These candidate genes could be classified to distinct proatherogenic processes, including lipid metabolism and transport (eg, HMGCR, SREBF1, LRP5, EPHX2, and FDPS), cell proliferation and cell-cycle regulation (eg, MIK67, TP53, and ALOX12), angiogenesis (eg, ANGPT2, ADAMTS10, and FLT4), and inflammation (eg, TNFSF10, LY96, IFNGR1, HSPA1A, and IL12RB1). CONCLUSIONS: We provide a comprehensive analysis of genome-wide epigenetic alterations in CKD, identifying candidate genes associated with proatherogenic and inflammatory processes. These results may spur further research in the field of epigenetics in kidney disease and point to new therapeutic strategies in CKD-associated atherosclerotic disease.