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1.
Front Cell Dev Biol ; 8: 739, 2020.
Article in English | MEDLINE | ID: mdl-32850849

ABSTRACT

BACKGROUND: Patients with chronic kidney disease (CKD) show a chronic microinflammatory state that promotes premature aging of the vascular system. Currently, there is a growth interest in the search of novel biomarkers related to vascular aging to identify CKD patients at risk to develop cardiovascular complications. METHODS: Forty-five CKD patients were divided into three groups according to CKD-stages [predialysis (CKD4-5), hemodialysis (HD) and kidney transplantation (KT)]. In all these patients, we evaluated the quantitative changes in microRNAs (miRNAs), CD14+C16++ monocytes number, and microvesicles (MV) concentration [both total MV, and monocytes derived MV (CD14+Annexin V+CD16+)]. To understand the molecular mechanism involved in senescence and osteogenic transdifferentation of vascular smooth muscle cells (VSMC), these cells were stimulated with MV isolated from THP-1 monocytes treated with uremic toxins (txMV). RESULTS: A miRNA array was used to investigate serum miRNAs profile in CKD patients. Reduced expression levels of miRNAs-126-3p, -191-5p and -223-3p were observed in CKD4-5 and HD patients as compared to KT. This down-regulation disappeared after KT, even when lower glomerular filtration rates (eGFR) persisted. Moreover, HD patients had higher percentage of proinflammatory monocytes (CD14+CD16++) and MV derived of proinflammatory monocytes (CD14+Annexin V+CD16+) than the other groups. In vitro studies showed increased expression of osteogenic markers (BMP2 and miRNA-223-3p), expression of cyclin D1, ß-galactosidase activity and VSMC size in those cells treated with txMV. CONCLUSION: CKD patients present a specific circulating miRNAs expression profile associated with the microinflammatory state. Furthermore, microvesicles generated by monocytes treated with uremic toxins induce early senescence and osteogenic markers (BMP2 and miRNA-223-3p) in VSMC.

2.
Clin J Am Soc Nephrol ; 4(7): 1176-82, 2009 Jul.
Article in English | MEDLINE | ID: mdl-19423567

ABSTRACT

BACKGROUND AND OBJECTIVES: Anemia and hemoglobin (Hb) variability are associated with mortality in hemodialysis patients who are on erythropoiesis-stimulating agents (ESA). Our aim was to describe the degree of Hb variability present in nondialysis patients with chronic kidney disease (CKD), including those who were not receiving ESA, and to investigate the association between Hb variability and mortality. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Hb variability was determined using 6 mo of "baseline" data between January 1, 2003, and October 31, 2005. A variety of definitions for Hb variability were examined to ensure consistency and robustness. RESULTS: A total of 6165 patients from 22 centers in seven countries were followed for a mean of 34.0 +/- 15.8 mo; 49% were prescribed an ESA. There was increased Hb variability with ESA use; the residual SD of Hb was 4.9 +/- 4.4 g/L in patients who were not receiving an ESA, compared with 6.8 +/- 4.8 g/L. Hb variability was associated with a small but significantly increased risk for death per g/L residual SD, irrespective of ESA use. Multivariate linear regression model explained only 11% of the total variance of Hb variability. CONCLUSIONS: Hb variability is increased in patients who have CKD and are receiving ESA and is associated with an increased risk for death (even in those who are not receiving ESAs). This analysis cannot determine whether Hb variability causally affects mortality. Thus, the concept of targeting Hb variability with specific agents needs to be examined within the context of factors that affect both Hb variability and mortality.


Subject(s)
Anemia/drug therapy , Anemia/mortality , Erythropoietin/therapeutic use , Hemoglobins/metabolism , Renal Insufficiency, Chronic/mortality , Aged , Aged, 80 and over , Anemia/blood , Female , Follow-Up Studies , Humans , Linear Models , Male , Middle Aged , Multivariate Analysis , Predictive Value of Tests , Renal Insufficiency, Chronic/blood , Survival Analysis
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