Higher Serum Levels of Osteoglycin Are Associated with All-Cause Mortality and Cardiovascular and Cerebrovascular Events in Patients with Advanced Chronic Kidney Disease

Abstract

Patients with chronic kidney disease (CKD) have markedly increased rates of major adverse cardiovascular and cerebrovascular events (MACCEs) and mortality. Therefore, identifying early biomarkers predicting clinical outcomes in patients with CKD is critical. We aimed to determine whether osteoglycin, a basic component of the vascular extracellular matrix, was associated with MACCEs or all-cause mortality, using data from a prospective randomized controlled study, K-STAR (Kremezin STudy Against Renal disease progression in Korea: NCT 00860431). A total of 383 patients (mean age: 56.4 years, men/women = 252/131) with CKD stage 3 to 4 from the original trial were enrolled in the present study. We measured serum osteoglycin level and examined the impact of osteoglycin on clinical outcomes. The mean value of osteoglycin levels was 13.3 ± 9.4 ng/mL (healthy control: 5.3 ± 2.1 ng/mL). In multivariable analysis, lower levels of proteinuria and hemoglobin and higher levels of C-reactive protein were significantly associated with higher osteoglycin levels. Estimated glomerular filtration rate was not related to osteoglycin level. During a mean follow-up period of 56 months, 25 deaths, 61 MACCEs, and 76 composite outcomes (all-cause mortality or MACCEs) occurred. In the non-diabetic group, each 1-ng/mL increase in serum osteoglycin was associated with all-cause mortality and composite outcome (hazard ratio [HR] = 1.058, P = 0.031; HR = 1.041, P = 0.036). However, osteoglycin levels were not associated with mortality, MACCEs, or composite outcome in the diabetic group. Our results indicate that serum osteoglycin is a potential predictor of adverse outcomes in patients with CKD.

Identification hub genes of consensus molecular subtype correlation with immune infiltration and predict prognosis in gastric cancer

“…While the work model of OGN in GC is not clear and needs to be further explored. Moreover, OGN, as one of the biologically active elements of the vascular extracellular matrix, could be tested in plasma/serum and acted as a biomarker in disease [ 29 , 30 ]. For instance, serum OGN was an independent risk predictor for patients with chronic kidney disease [ 29 ].…”

Efficacy of AST-120 for Patients With Chronic Kidney Disease: A Network Meta-Analysis of Randomized Controlled Trials

“…Finally, 21 references for 15 RCTs met the eligibility criteria of the present study (Figure 1). (Sanaka et al, 1988;Koide et al, 1991;Owada et al, 1997;Nakamura et al, 2004;Morita et al, 2005;Marier et al, 2006;Schulman et al, 2006;Shoji et al, 2007;Asano et al, 2008;Konishi et al, 2008;Takahashi et al, 2008;Yorioka et al, 2008;Akizawa et al, 2010;Toyoda et al, 2014;Wu et al, 2014;, 2015; Cha et al, 2016;Schulman et al, 2016;Baek et al, 2017;Cha et al, 2017;Schulman et al, 2018)…”

Bioinformatics analysis of differentially expressed genes in non alcoholic fatty liver disease using next generation sequencing data

“…[624] and Matejas et al [625] showed that EGR1, NR4A1, SIK1, CCN1, CEBPD (CCAAT enhancer binding protein delta), SOCS2, RGS2, KL (klotho), SOCS3, MMP1, CXCR4, CCN2, FST (follistatin), OGN (osteoglycin), CTLA4, KLF4, PTGER3, HBEGF (heparin binding EGF like growth factor), CCL2, OSM (oncostatin M), ERBB4, TNFSF11, MSTN (myostatin), ADAMTS1, CALCR (calcitonin receptor), INHBB (inhibin subunit beta B), EPO (erythropoietin), IL10, CEBPB (CCAAT enhancer binding protein beta), FOXO1, DKK1, GAS1, NPHP3, FGF2, ATF3, ANGPT2, SOCS1, IL1RAP, C9ORF72, BASP1, AKR1B10, SLC22A12, ACHE (acetylcholinesterase), TREM2, SCD (stearoyl-CoA desaturase), GCK (glucokinase), FOXP3, SLC22A2, EPHB2, LPL (lipoprotein lipase), ANGPTL8, HCN2, HSPA8, MB (myoglobin), KCNJ11, GLIS2, TNFSF13, LSS (lanosterol synthase), GAS6, AGRN (agrin), ACE2, NLRP6, DPEP1, TIMP3, CHI3L1, RASAL1, FAT1, GPBAR1, TREH (trehalase), CFB (complement factor B), FNDC5, HLA-G, MMP9, C4A and LAMB2 were associated with kidney disease, but these genes might be novel targets for NAFLD. [657], SOCS3 [658], MMP1 [659], CXCR4 [660], RASD1 [661], SLC7A11 [662], OGN (osteoglycin) [341], KLF4 [663], IL1RL1 [664], CCL2 [665], EPO (erythropoietin) [666], IL10 [667], ESR2 [668], VIP (vasoactive intestinal peptide) [669], FOXC1 [670], FOXO1 [671], S100B [672], DKK1 [673], SOCS1 [674], C9ORF72 [675], CTCFL (CCCTC-binding factor like) [676], S1PR2 [677], ACHE (acetylcholinesterase) [678], TREM2 [679], EPHB2 [680], LPL (lipoprotein lipase) [681], P2RY2 [682], ACE2 [683], CHI3L1 [684], HLA-G [685] and MMP9 [686] are found in cerebrovascular diseases, but these genes might be novel targets for NAFLD.…”