DNA methylation profiling reveals differences in the 3 human monocyte subsets and identifies uremia to induce DNA methylation changes during differentiation.

Human monocytes are a heterogeneous cell population consisting of 3 subsets: classical CD14++CD16-, intermediate CD14++CD16+ and nonclassical CD14+CD16++ monocytes. Via poorly characterized mechanisms, intermediate monocyte counts rise in chronic inflammatory diseases, among which chronic kidney disease is of particular epidemiologic importance. DNA methylation is a central epigenetic feature that controls hematopoiesis. By applying next-generation Methyl-Sequencing we now tested how far the 3 monocyte subsets differ in their DNA methylome and whether uremia induces DNA methylation changes in differentiating monocytes. We found that each monocyte subset displays a unique phenotype with regards to DNA methylation. Genes with differentially methylated promoter regions in intermediate monocytes were linked to distinct immunological processes, which is in line with results from recent gene expression analyses. In vitro, uremia induced dysregulation of DNA methylation in differentiating monocytes, which affected several transcription regulators important for monocyte differentiation (e.g., FLT3, HDAC1, MNT) and led to enhanced generation of intermediate monocytes. As potential mediator, the uremic toxin and methylation inhibitor S-adenosylhomocysteine induced shifts in monocyte subsets in vitro, and associated with monocyte subset counts in vivo. Our data support the concept of monocyte trichotomy and the distinct role of intermediate monocytes in human immunity. The shift in monocyte subsets that occurs in chronic kidney disease, a proinflammatory condition of substantial epidemiological impact, may be induced by accumulation of uremic toxins that mediate epigenetic dysregulation.

Immunosuppression and monocyte subsets.

BACKGROUND: Monocytes are critical in innate immunity and transplantation. Three monocyte subsets exist, CD14(++)CD16(-), CD14(++)CD16(+) and CD14(+)CD16(++) monocytes; cell counts of CD14(++)CD16(+) and CD14(+)CD16(++) monocytes are increased in pre-transplant chronic kidney disease. Interestingly, the effect of immunosuppressants on monocyte heterogeneity has not been well studied. METHODS: The impact of immunosuppressants on monocyte subsets was studied: (i) in 152 kidney transplant (KTx) recipients to characterize subset distribution in the steady state, (ii) in patients after autologous (n = 10) versus allogenic (n = 9) haematopoietic stem cell transplantation (HSCT) to analyse monocyte subset development and (iii) in an in vitro model to compare the effect of immunosuppressants on monocyte subset biology. RESULTS: In KTx, steroid intake was associated with higher total, CD14(++)CD16(-) and CD14(++)CD16(+) monocyte counts, but fewer CD14(+)CD16(++) monocytes, whereas intake of mycophenolate, calcineurin inhibitors (CNI) and mammalian target of rapamycin inhibitors (mTORI) did not affect monocyte (subset) counts. In linear regression analysis, only steroid intake was a significant determinant of monocyte (subset) counts: total monocytes (ß = 0.331; P < 0.001), CD14(++)CD16(-) monocytes (ß = 0.374; P < 0.001), CD14(++)CD16(+) monocytes (ß = 0.221; P = 0.010) and CD14(+)CD16(++) monocytes (ß = -0.169; P = 0.049). After HSCT, CD14(++)CD16(-) monocytes were the first to arise, followed by CD14(++)CD16(+) and later by CD14(+)CD16(++) monocytes. Monocyte subset distribution did not differ significantly in patients after allogenic compared with autologous transplantation. CNI, mycophenolate and methotrexate did not influence monocyte subset development, but modified surface receptor expression (CCR2, HLA-DR, ENG, TEK and TLR4) in allogenic HSCT. CONCLUSION: Chronic low-dose steroids are associated with monocytosis and higher counts of CD14(++)CD16(-) and of proinflammatory CD14(++)CD16(+) monocytes.

Association of vascular endothelial factors with cardiovascular outcome and mortality in chronic kidney disease patients: a 4-year cohort study.

BACKGROUND: Angiogenic cytokines fms-like tyrosine kinase-1(sFlt-1) and placental growth factor (PlGF) are associated with increased risk for cardiovascular disease (CVD) in the general population. In this study we examine the association between these vascular endothelial factors and atherosclerosis, cardiovascular outcome, and mortality in chronic kidney disease (CKD) patients. METHODS: Serum level of PlGF and sFlt-1 were measured in 301 patients with CKD, who were followed for up to 4 years. Primary outcomes were CV events and all-cause mortality. Carotid-intima media thickness (CIMT) was used as marker of atherosclerosis. Kaplan-Meier survival curves and the Cox proportional hazard model were used to assess the association of biomarkers and clinical outcomes. RESULTS: Mean (SD) PlGF and sFlt-1 were 5.45 ng/ml (3.76) and 68.6 (28.0) pg/ml, respectively. During the follow up time, 60 patients (19.9%) experienced CV events and 22 patients (7.3%) died. Compared with low PlGF, patients with PlGF above median level had higher CV events (12.7% vs. 27.2%, p = 0.002) and mortality (2.0% vs. 12.6%, p < 0.001). The associations of PlGF and sFlt-1 with CV events were not statistically significant in the fully adjusted model. Higher PlGF was associated with greater death risk (HR = 5.22, 95% CI: 1.49-18.33, p = 0.01), which was robust to adjustment for sFlt-1 and other risk factors. Elevated sFlt-1 level was also an independent predictor of mortality (HR 3.41, 95% CI: 1.49-9.51, p = 0.019). CONCLUSION: In CKD patients not yet on dialysis, higher serum level of PlGF and sFlt-1 are associated with increased mortality, but not CV events.

Lower Apo A-I and lower HDL-C levels are associated with higher intermediate CD14++CD16+ monocyte counts that predict cardiovascular events in chronic kidney disease.

OBJECTIVE: Patients with chronic kidney disease (CKD) display impaired cholesterol efflux capacity and elevated CD14(++)CD16(+) monocyte counts. In mice, dysfunctional cholesterol efflux causes monocytosis. It is unknown whether cholesterol efflux capacity and monocyte subsets are associated in CKD. APPROACH AND RESULTS: In 438 patients with CKD, mediators of cholesterol efflux capacity (high-density lipoprotein cholesterol/apolipoprotein A-I) and monocyte subsets were analyzed as predictors of cardiovascular events. Monocyte subset-specific intracellular lipid content, CD36, CD68, and ABCA1 were measured in a subgroup. Experimentally, we analyzed subset-specific cholesterol efflux capacity and response to oxidized low-density lipoprotein cholesterol stimulation in CKD. Epidemiologically, both low Apo-I and low high-density lipoprotein cholesterol were associated with high CD14(++)CD16(+) monocyte counts in linear regression analyses (apolipoprotein A-I: ß=-0.171; P<0.001; high-density lipoprotein cholesterol: ß=-0.138; P=0.005), but not with counts of other monocyte subsets. In contrast to apolipoprotein A-I or high-density lipoprotein cholesterol, higher CD14(++)CD16(+) monocyte counts independently predicted cardiovascular events (hazard ratio per increase of 1 cell/µL: 1.011 [1.003-1.020]; P=0.007). Experimentally, CD14(++)CD16(+) monocytes demonstrated preferential lipid accumulation, high CD36, CD68, and low ABCA1 expression and, consequently, displayed low cholesterol efflux capacity, avid oxidized low-density lipoprotein cholesterol uptake, and potent intracellular interleukin-6, interleukin-1ß, and tumor necrosis factor-α production. CONCLUSIONS: Taken together, mediators of cholesterol efflux are associated with CD14(++)CD16(+) monocyte counts, which independently predict adverse outcome in CKD.

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.

Distinct immunologic effects of different intravenous iron preparations on monocytes.

BACKGROUND: Iron deficiency contributes to anaemia in patients with chronic kidney disease. I.v. iron is therefore widely used for anaemia treatment, although it may induce oxidative stress and activate monocytes. Different i.v. iron preparations are available, but interestingly their substance-specific immunologic effects are poorly studied. METHODS: We analysed the effect of iron sucrose, ferric carboxymaltose, iron isomaltoside 1000, low-molecular-weight iron dextran and ferumoxytol on classical, intermediate and nonclassical monocyte biology. We therefore stimulated in vitro mature monocytes and haematopoietic CD34(+) stem cells during their differentiation into monocytes with different concentrations (0.133, 0.266, 0.533 mg/mL) of i.v. iron preparations. Alterations of monocyte subset distribution, expression of surface markers (CD86, CCR5, CX3CR1), as well as production of pro-inflammatory cytokines (TNF-α, IL-1ß) and reactive oxygen species were measured using flow cytometry. Additionally, we analysed phagocytosis and antigen presentation capacity. RESULTS: We found specific immunologic effects after stimulation with iron sucrose which were not induced by the other iron preparations. Iron sucrose activated monocyte subsets leading to significantly increased CD86 expression. Simultaneously CD16 and CX3CR1 expression and monocytic phagocytosis capacity were decreased. Additionally, differentiation of monocytes from haematopoietic CD34(+) stem cells was almost completely abolished after stimulation with iron sucrose. CONCLUSIONS: Our findings demonstrate that specific immunologic effects of distinct i.v. iron preparations exist. The clinical relevance of these findings requires further investigation.

The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation incorporating both cystatin C and creatinine best predicts individual risk: a cohort study in 444 patients with chronic kidney disease.

BACKGROUND: The recently introduced CKD-EPIcreat-cys equation surpassed creatinine-based equations for GFR estimation in a large cross-sectional analysis. However, its performance to predict individual risk of CKD progression and death in patients with various underlying CKD etiologies is unknown. METHODS: We recruited 444 patients with CKD GFR categories 2-4 (eGFR 15-89 mL/min/1.73 m2); baseline eGFR was estimated by the established MDRD and CKD-EPIcreat equations and by the novel CKD-EPIcreat-cys equation. RESULTS: Patients were followed for 2.7±1.2 years for the occurrence of the combined predefined endpoint event: death, need for renal replacement therapy or halving of eGFR. The endpoint occurred in 62 patients. Reclassification from MDRD determined categories to CKD-EPIcreat-cys categories yielded net reclassification improvements for those with the endpoint event (NRIevents) of 27.4% (95% CI: 16.7-40.0%) and for those without the event (NRInon-events) of -3.1% (-8.2 to 1.6%). Similarly, reclassification from CKD-EPIcreat categories to CKD-EPIcreat-cys categories yielded an NRIevents of 22.6% (10.2-34.3%) and NRInon-events of -11.3% (-15.9 to -6.5%). Addition of albuminuria to each eGFR equation increased the calculated risk of the outcome for a net 26-32% of those who subsequently reached the endpoint, and reduced the calculated risk in a net 21-23% in non-event patients, but only minimally. CONCLUSIONS: The CKD-EPIcreat-cys equation assigned patients who went on to have the event to more appropriate CKD risk categories than MDRD and CKD-EPIcreat, but patients without the event to less appropriate categories than CKD-EPIcreat. Addition of albuminuria marginally improved risk classification for those who had the event.

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.

Monocyte heterogeneity in obesity and subclinical atherosclerosis.

AIMS: Monocytes and monocyte-derived macrophages have been recognised as the cellular hallmark of atherosclerosis decades ago. Recently, they have also been shown to play a pivotal role in obesity. Monocytes display immunophenotypic heterogeneity with functionally distinct subpopulations. We initiated the I LIKE HOMe study to examine monocyte heterogeneity in obesity and subclinical atherosclerosis. METHODS AND RESULTS: We assessed carotid intima media thickness (IMT), body mass index (BMI), and other cardiovascular risk factors in 622 healthy volunteers. Using flow-cytometry, we differentiated monocytes into CD14(++)CD16(-) and CD16(+) cells, which we further subdivided into CD14(++)CD16(+) and CD14((+))CD16(+) cells. Body mass index was significantly correlated with carotid IMT. High CD16(+) monocyte counts were significantly associated with both higher BMI and increased carotid IMT. Adjustment for CD16(+) monocyte counts weakened the correlation between BMI and carotid IMT, suggesting that the increase in CD16(+) monocyte numbers in obesity may partly explain the association between obesity and IMT. CONCLUSION: Our results reveal a significant univariate association between CD16(+) monocytes and both obesity and subclinical atherosclerosis in low-risk individuals. They are in line with recent observations that CD16(+) monocytes show high endothelial affinity and a potent capacity to invade vascular lesions and to transform into pro-inflammatory cytokine producing macrophages.