http://informahealthcare.com/bmk ISSN: 1354-750X (print), 1366-5804 (electronic) Biomarkers, 2015; 20(1): 52–57 ! 2014 Informa UK Ltd. DOI: 10.3109/1354750X.2014.992475
RESEARCH ARTICLE
Proteins from the 18 glycosyl hydrolase family are associated with kidney dysfunction in patients with diabetes type 2 1 _ Ewa Zurawska-Płaksej #, Agnieszka Ługowska2, Katarzyna Hetman´czyk2, Maria Knapik-Kordecka3, 3 Rajmund Adamiec , and Agnieszka Piwowar4
Department of Pharmaceutical Biochemistry, Wroclaw Medical University, Wroclaw, Poland, 2Department of Genetics, Institute of Psychiatry and Neurology in Warsaw, Warsaw, Poland, 3Department and Clinic of Angiology, Hypertension and Diabetology, and 4Department of Toxicology, Wroclaw Medical University, Wroclaw, Poland
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Abstract
Keywords
Objectives: To investigate chitotriosidase (CHIT1) activity and chitinase-3-like protein 1 (YKL-40) concentration in plasma of type 2 diabetic patients and evaluate their relationship with kidney dysfunction. Materials and methods: 94 diabetic subjects and 33 controls were enrolled in the study. Plasma CHIT1 activity and YKL-40 concentration were measured along with routine laboratory parameters. Results: Levels of CHIT1 and YKL-40 in plasma of type 2 diabetic patients increased progressively with the degree of albuminuria. CHIT1 discriminated normoalbuminuric subjects from those with abnormal albuminuria better than YKL-40. Conclusions: CHIT1represent a supportive biomarker connected with development of diabetic vascular complications, especially kidney dysfunction.
Albuminuria, biomarker, chitotriosidase, diabetes mellitus, diabetic nephropathy, YKL-40
Introduction The glycosyl hydrolase family 18 (GH18), which is widely expressed in living organisms (from prokaryotes to eukaryotes), includes enzymes with chitinolytic activity (chitinases) and non-enzymatic chitinase-like proteins (CLPs). Although chitin is not a natural compound for humans, some members of this family have been unexpectedly discovered in the human species. The human genome encodes two chitinases – chitotriosidase (CHIT1) and acidic mammalian chitinase – and at least three CLPs: chitinase 3-like protein 1 (termed human cartilage glycoprotein-39 or YKL-40), chitinase 3-like protein 2 (YKL-39) and oviductin (Hussain & Wilson, 2013). CHIT1 is involved in the degradation of chitin and chitinlike substrates, due to hydrolysis of the N-acetyl-beta-Dglucosaminide-(1-4)-beta linkages. This ability confers its antibacterial, antifungal and antiparasitic properties and determines its physiological function in human organisms that is probably participation in immune defense. The enzyme is expressed mainly by activated phagocytes (macrophages and neutrophils). Some mutations in the CHIT1 gene may occur, which leads to alterations in enzyme expression (Boot et al., _ *Ewa Zurawska-Płaksej is responsible for statistical design/analysis. E-mail: [email protected] _ Address for correspondence: Ewa Zurawska-Płaksej, Department of Pharmaceutical Biochemistry, Wroclaw Medical University, Borowska St 211A, 50-556 Wroclaw, Poland. Tel: +48 717840468. Fax: +48 717840304. E-mail: [email protected]
History Received 17 October 2014 Accepted 24 November 2014 Published online 17 December 2014
1998; van Eijk et al., 2005). Increased plasma CHIT1 activity has been recognized as a useful marker in diagnosing and monitoring of Gaucher disease (Hollak et al., 1994). This enzyme is considered as a novel marker of inflammation (Kanneganti et al., 2012; Kundak et al., 2012). In the last few years, CHIT1 activity has also been examined in other pathological states, such as sarcoidosis, inflammatory bowel disease, infectious diseases, atherosclerosis, or newly diagnosed type 2 diabetes mellitus (T2D). In a previous study we revealed that activity of this enzyme is also increased in plasma _ of patients with ongoing T2D (Zurawska-Płaksej et al., in press). YKL-40 is a heparin- and chitin-binding lectin without chitinase activity. It is produced at the site of inflammation, secreted mainly by activated macrophages, neutrophils, and other types of cells, including differentiated vascular smooth muscle cells. It is reported to be an essential factor in extracellular matrix remodeling, but its exact function remains unclear (Johansen, 2006; Nishikawa & Millis, 2003). Early studies suggest its potential usefulness for researching such pathologies as rheumatoid arthritis, liver fibrosis and different types of cancer (including colorectal, lung and breast) (Riabov et al., 2014; Tao et al., 2014). Some studies have also reported increased levels of plasma YKL-40 in diabetes mellitus patients, both type 1 and type 2 (Rathcke et al., 2009; Røndbjerg et al., 2011). Type 2 diabetes, which makes up about 90% of cases of diabetes worldwide, is connected with a variety of metabolic
Proteins from the 18 glycosyl hydrolase family
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DOI: 10.3109/1354750X.2014.992475
abnormalities, such as hyperglycemia, obesity, hypertension, and dyslipidemia. These are the main systemic factors, that trigger proinflammatory events, leading to endothelial dysfunction and increased prevalence of vascular late complications in diabetic patients (Polovina & Potpara, 2014). Diabetic nephropathy (DN), a specific type of diabetic angiopathy (microangiopathy), is the leading cause of progressive kidney dysfunction and end-stage renal disease, and thus represents a serious risk of increased mortality in people with T2D (DuranSalgado & Rubio-Guerra, 2014). The exact pathomechanisms of the development of DN remains undetermined. Endothelial dysfunction is suggested as a key factor, but there is a continuing need to search for other contributing factors (Eleftheriadis et al., 2013; Sun et al., 2013). Since it was indicated that chitotriosidase activity predicts endothelial dysfunction in patients with newly diagnosed, untreated and uncomplicated T2D, and we revealed increased activity of this enzyme also in patients with ongoing diabetes, we have continued our research on the possible relationship of chitotriosidase with kidney dysfunction in these patients. In addition, we compared diagnostic accuracy of CHIT1 to differentiate patients with and without kidney impairment with another protein from the 18GH family, YKL-40, which has been previously reported as a proinflammatory biomarker in the early stage of DN (Rathcke et al., 2009).
Methods Initially, 94 patients with type 2 diabetes mellitus, having an average duration of 11 years, were recruited from the Clinic of Angiology, Hypertension and Diabetology of Wroclaw Medical University. T2D was diagnosed according to the standards set by the Polish Diabetes Association (Recommendation of the PDA, 2012). The control group (CTRL) consisted of 33 nondiabetic subjects (glucose level 55.5 mmol/l) with no evidence of inflammatory states during the last 3 months, matched for sex and age. All participants were informed about the aim of the study, and their written permission was given. The use of human blood and urine was approved by the Local Bioethics Committee of Wroclaw Medical University. Venous blood was collected after overnight fasting into standard vacuum tubes with heparin (16 IU/mL) to obtain plasma. Routine laboratory parameters were measured by standard laboratory methods. Plasma samples were stored at 80 C until assayed. Plasma activity of chitotriosidase was measured by a spectrofluorometric method according to Hollak et al. (1994) using the synthetic substrate 4-methylumbelliferylb-N-N0 -N00 -triacetylchitotrioside (Sigma Chemical Co, St. Louis, MO). Fluorometric measurements were made at excitation ¼ 365 nm and emission ¼ 445 nm (Perkin Elmer LS 50B, Waltham, MA). Plasma concentration of YKL-40 was measured by an ELISA test (MicroVue, Quidel, San Diego, CA). Plasma activity of N-acetyl-b-D-glucosaminidase (NAG) was measured by a fluorometric method according to Miralles et al. (1982). The presence of a common 24-bp duplication in exon 10 of the CHIT1gene was examined by polymerase chain reaction (PCR) in a T100 Thermal-Cycler (Bio-Rad, Hercules, CA) as described by Boot et al. (1998) in genomic DNA extracted
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from plasma (GeneMATRIX Tissue DNA Purification Kit, EURx, Gdan´sk, Poland). Due to deficient chitotriosidase activity, homozygotus individuals were excluded from further analysis and finally examined groups consisted of 90 patients and 32 controls. Single-spot early morning urine specimens were collected and urinary albumin and creatinine concentrations were measured according to methods described previously (Helger et al., 1974; Schosinsky et al., 1987). The value of the urinary albumin-to-creatinine ratio (UACR) was calculated, and on this basis patients were stratified into three subgroups: with normoalbuminuria (NORM, UACR530 mg/g), with microalbuminuria (MICR, UACR 30-300 mg/g) and with macroalbuminuria (MACR, UACR4300 mg/g). Moreover, the estimated glomerular filtration rate (eGFR) was calculated according to the MDRD formula (Levey et al., 1999) The statistical analysis was done using Statistica PL, StatSoft (Tulsa, OK) for Windows, version 10.0. Comparisons between controls and diabetic patients were made with the Mann–Whitney U-test or chi-squared test as necessary. Differences between subgroups were estimated by analysis of variance (ANOVA), followed by Fisher’s test. Analysis of covariance in subgroups with different degrees of albuminuria was used for adjusting for CHIT1 gene 24 bp duplication. A p value below 0.05 was considered as statistically significant. All results were expressed as a mean value and a standard deviation or number and percent. Receiver operating characteristic (ROC) curves were calculated to evaluate the discriminative power of CHIT1 in comparison with YKL-40 for patients with different degrees of kidney dysfunction. Spearman rank correlation was used to estimate of CHIT1 and YKL-40 with selected laboratory parameters in the examined population. Multiple regression analysis was performed to adjust for confounding variables and regression coefficients before and after adjustment were compared.
Results The main anthropometric and biochemical characteristic of the examined subjects are given in Table 1. Age, BMI, diastolic blood pressure (DBP), total cholesterol and lowdensity lipoprotein (LDL) cholesterol and white blood cell (WBC) count did not vary significantly between patients with diabetes and the control group. CRP concentration was significantly higher in diabetic patients, but it was still below the upper reference value (510 mg/L). CHIT1 gene genotyping revealed presence of the 24-bp duplication in 41% of subjects, among which 4% were homozygotes (excluded from further analysis) and 37% were heterozygotes. There were no differences in distribution of the mutant allele in examined subgroups of participants (the frequency varied from 34 to 40%). Plasma chitotriosidase activities and YKL-40 concentrations in control subjects and subgroups of patients with different degrees of albuminuria are presented in Figure 1. As shown, both CHIT1 and YKL-40 were significantly higher in patients with T2D in comparison to the control group (nondiabetic subjects) and increased progressively with the degree of kidney dysfunction evidenced by albuminuria; however, this ‘‘trend’’ is more evident for CHIT1. Activities
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Biomarkers, 2015; 20(1): 52–57
Table 1. Anthropometric and clinical characteristics of participants. Patients with
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Parameter n Sex, male/female Age, years Diabetes duration, years BMI, kg/m2 SBP, mmHg DBP, mmHg CRP, mg/l WBC, 109/l Glucose, mmol/l HbA1c, % Chol, mmol/l LDL-Chol, mmol/l HDL-Chol, mmol/l TG, mmol/l Plasma creatinine, mmol/l eGFR NAG activity (nmol/h/ml) UACR (mg/g) Smoking (%) Hypotensive treatment (n) Use of statins (n) Use of (OAD/OAD + ins)
Control subjects
Diabetic patients
normo-albuminuria
micro-albuminuria
macro-albuminuria
32 12/20 61.90 ± 5.61 – 29.59 ± 4.16 129.95 ± 9.93 80.54 ± 8.86 2.91 ± 1.92 7.03 ± 1.03 5.19 ± 0.30 5.47 ± 0.22 5.22 ± 1.01 3.09 ± 0.62 1.51 ± 0.38 1.32 ± 0.35 77.79 ± 20.55 85.20 ± 20.51 136.41 ± 40.52 3.37 ± 3.35 29 0 0 0
90 32/58 62.87 ± 6.11 10.82 ± 4.31 30.33 ± 5.03 143.00*** ± 12.19 80.58 ± 8.75 5.80*** ± 2.98 7.60 ± 2.52 8.73*** ± 1.50 7.80*** ± 1.48 5.18 ± 2.15 3.04* ± 0.80 1.17*** ± 0.41 2.25*** ± 0.81 106.08*** ± 29.17 66.45*** ± 15.86 207.45*** ± 58.11 149.00*** ± 80.91 25 29*** 22.5*** 43/47***
29 11/18 62.76 ± 5.19 10.04 ± 4.12 30.95 ± 5.06 137.73 ± 16.11 77.84 ± 9.11 5.52 ± 2.77 7.60 ± 2.70 8.78 ± 1.48 7.74 ± 1.35 5.25 ± 2.10 3.02 ± 0.78 1.22 ± 0.43 2.23 ± 0.81 86.63 ± 22.84 73.26 ± 19.20 194.04 ± 55.41 22.57 ± 13.88 27 29 21 14/15
32 11/21 63.40 ± 6.60 9.58 ± 4.59 29.82 ± 4.78 141.88 ± 12.59 80.09 ± 9.31 4.02 ± 1.75 7.49 ± 2.55 8.67 ± 1.51 7.93 ± 1.58 4.97 ± 2.21 2.90 ± 0.80 1.16 ± 0.43 2.28 ± 0.83 106.96 ± 30.54 66.93 ± 15.34 199.20 ± 58.89 221.19 ± 100.3 26 30 26 14/18
29 10/19 62.39 ± 6.37 12.96 ± 4.19 30.27 ± 5.16 149.50 ± 7.83 83.80 ± 6.78 8.04 ± 4.58 7.72 ± 2.25 8.74 ± 1.60 7.72 ± 1.49 5.34 ± 2.16 3.21 ± 0.81 1.14 ± 0.39 2.23 ± 0.80 123.73 ± 33.76 59.12 ± 14.85 230.50 ± 59.97 583.93 ± 325.87 22 28 20 15/14
Data are presented as mean ± standard deviation or number/percent. Statistical significance of differences between control subjects and diabetic patients, checked by Mann–Whitney U-test: *–p50.05, ***–p50.001. Abbreviations: BMI – body mass index, Chol – total cholesterol, CRP – C-reactive protein, DBP – diastolic blood pressure, eGFR – estimated glomerular filtration rate, HbA1c – glycated hemoglobin, HDL-Chol – high-density lipoprotein cholesterol, ins – insulin, LDL-Chol – low-density lipoprotein cholesterol, n – number of subjects, NAG – N-acetyl-b-D-glucosaminidase, OAD – oral antidiabetics, SBP – systolic blood pressure, TG – triglyceride, UACR – urinary albumin-to-creatinine ratio, WBC – white blood cells.
Figure 1. Chitotriosidase and YKL-40 in plasma of control subjects and subgroups of diabetic patients differentiated according to level of albuminuria. CHIT1 – chitotriosidase, YKL-40 – human cartilage glycoprotein-39, CTRL – control group, NORM – diabetic patients with normoalbuminuria, MICR – diabetic patients with microalbuminuria, MACR – diabetic patients with macroalbuminuria. Statistical significance of differences in comparison to: a – CTRL, b – NORM, c – MICR, d – MACR subgroup, checked by Fisher test: ^ – not significant, * – p50.05, ** – p50.01, *** – p50.001.
of chitotriosidase were significantly different among all examined subgroups of patients with type 2 diabetes. All differences remained significant also after adjustment for CHIT1 genotype. The only observed change was a slight decrease of statistical significance between normo- and microalbuminuric patients (before and after adjustment p ¼ 0.009 and 0.029, respectively). Among patients with T2D, the lowest activity of CHIT1 was observed in the NORM subgroup, being almost 2-fold higher in the MICR subgroup and 3.5-fold higher in the MACR one. Enzyme activity in the control group was at the similar level as in subgroup of normoalbuminuric patients. YKL-40
concentration also increased progressively with the degree of albuminuria (almost 1.2- and 2-fold increase in MICR and MACR subgroup, respectively, in comparison with the NORM one), but differences between subgroups were statistically significant only in patients with macroalbuminuria versus other subgroups. Concentration of YKL-40 in the control group was 1.3-fold lower than in the subgroup of normoalbuminuric patients, but the difference was still not significant. ROC curves used to evaluate and to compare the potential utility of CHIT1 and YKL-40 for differentiating subjects with normal (UACR530 mg/g) and impaired (UACR430 mg/g)
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Figure 2. Comparison of diagnostic utility of plasma chitotriosidase and YKL-40 in discrimination of subjects with and without albuminuria. CHIT1 – chitotriosidase (upper line), YKL-40 – human cartilage glycoprotein-39 (lower line).
kidney function are shown in Figure 2. The area under the curve (AUC) was statistically larger (p50.001) for CHIT1(0.869) than for YKL-40 (0.668). The optimum discriminative value, calculated at 80.64 nmol/h/ml of CHIT1 activity, provided sensitivity of 86% and specificity of 74%. For comparison, the optimum discriminative value for YKL-40 concentration, calculated at 146.17 ng/mL, was characterized by 76% sensitivity and 63% specificity. Spearman rank correlation analysis revealed a significant mutual relationship between CHIT1 and YKL-40 (r ¼ 0.27, p ¼ 0.020). Moreover, CHIT1 activity was significantly associated with systolic blood pressure (SBP) (r ¼ 0.27, p ¼ 0.017), plasma creatinine (r ¼ 0.31, p50.001), and UACR (r ¼ 0.60, p50.001) in the total group of participants, while YKL-40 concentration was significantly associated only with UACR (r ¼ 0.37, p ¼ 0.011). After adjustment for SBP and plasma creatinine, the UACR remains significantly associated with CHIT1 activity, but the magnitude of the association was slightly lower (the regression coefficient decreased from 0.603 to 0.552 after adjustment). Neither CHIT1 nor YKL-40 was significantly associated with eGFR. We did not reveal any association of either CHIT1 or YKL-40 with the presence of an inflammatory state, reflected by CRP. However, a significant association was found with WBC count: r ¼ 0.236 (p ¼ 0.005) for CHIT1, r ¼ 0.313 (p ¼ 0.014) for YKL-40. There were no significant associations of these proteins with parameters of glycemic control (fasting glucose and HbA1c) or with NAG activity.
Discussion The late vascular complications of diabetes remain a causal factor of worsening of life quality and life expectancy in T2D patients. Diabetic nephropathy develops in 30% of T2D
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patients (despite treatment) and leads to progression of arterial hypertension, increased risk of cardiovascular disease or directly to life-threatening kidney damage. Endothelial dysfunction is reported to be implicated in the pathogenesis of DN. Structural abnormalities of the endothelium (such as impairment of endothelial glycocalyx) may lead to permeability in the glomerular basement membrane, which might partially account for microalbuminuria in diabetic patients (Nakagawa et al., 2011). Albuminuria is an established marker of endothelial dysfunction as well as a predictor of progression of DN (Piwowar et al., 2008; Roshan & Stanton, 2013). However, in recent times, the significance of albuminuria measurement as a single parameter has been questioned. Some authors suggest that in type 2 diabetes aging, hypertension and development of intrarenal vascular disturbances may contribute to the decrease in renal function independently of albuminuria, and precise estimation of the risk for development and progression of diabetic kidney disease requires additional markers. eGFR seems to be a valuable tool for predicting renal events in these patients (MacIsaac et al., 2014). However, there is a constant need for searching other risk markers of progressive renal impairment in diabetes. Progressive DN is characterized by pathological changes in multiple cellular compartments, including mesangial matrix expansion, culminating in glomerulosclerosis, podocyte injury and apoptosis, and tubulointerstitial fibrosis. Immune and inflammatory involvement in development of diabetic nephropathy is evidenced, but the detailed pathogenesis still requires explanation (Duran-Salgado & Rubio-Guerra, 2014). Recently it has been shown that both CHIT1 and YKL-40 may affect endothelial function in T2D (Nishikawa & Millis, 2003; Sonmez et al., 2010). We have also revealed increased plasma CHIT1 activity in patients with ongoing T2D _ (Zurawska-Płaksej et al., in press). Phagocyte accumulation is associated with declining renal function in diabetic patients, and both macrophages (as a source of proinflammatory cytokines) and neutrophils (as a source of reactive oxygen species), the major cells infiltrating the kidneys, are indicated as a source of examined proteins (Akcay et al., 2009). Therefore, we hypothesized that proteins from the GH18 family may play a role in development of diabetic complications, in particular nephropathy. So far, only YKL-40 has been indicated as a factor engaged in the progressing vascular complications in patients with T2D (Røndbjerg et al., 2011). In the present study, we revealed for the first time a relationship of CHIT1 activity with the severity of diabetic kidney dysfunction according to their albuminuria status. A progressive increase of this enzyme’s activity was observed in subgroups of diabetic patients with different degrees of albuminuria being the most significant in micro- and macroalbuminuric patients, independently from CHIT1 genotype. CHIT1 was also correlated with plasma creatinine and UACR. It may indicate possible participation of this enzyme in the progression of nephropathy in T2D patients. Interestingly, although severity of albuminuria was parallel to the decline of glomerular filtration in T2D patients, we did not reveal any significant association of CHIT1 with eGFR. We considered whether increased activity of this enzyme results more from dysfunction within kidneys or rather from
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generalized vascular damage reflected by albuminuria. We attempted to resolve this question by measuring CHIT1 activity in urine. Unfortunately, the levels of this enzyme in urine samples were extremely low, and we did not observe any statistically significant differences between subjects with and without diabetes (data not shown). Seeking to explain the increased activity of plasma chitotriosidase in patients with diabetic kidney dysfunction, and in view of the lack of a natural substrate for this enzyme in humans, we hypothesize that CHIT1 may cooperates with other enzymes (such as matrix metalloproteinases, serine proteases or NAG) in catabolism of glycoproteins and glycosaminoglycans, which cumulate in the mesangium and the tubulointerstitial space during development of DN. Therefore, increased CHIT1 activity in T2D patients may be a ‘‘natural weapon’’ against deepening disturbances (Kolset et al., 2012). However, we did not find any significant association between activity of CHIT1 and NAG, which is indicated as a marker of early endothelial dysfunction that increases before occurrence of albuminuria (Wiela-Hojen´ska & Orzechowska-Juzwenko, 1999). This may due to nonsynchronized time of actions or different mechanisms of regulation of these enzymes, and this matter needs to be verified. We have also evaluated associations of CHIT1 with biochemical parameters, which directly influence on the development of diabetic vascular complications such as blood glucose and HbA1c. In this study, CHIT1 was not found to be significantly correlated with parameters of glycemic control. However, in newly diagnosed and untreated T2D a positive correlation of CHIT1 activity with plasma glucose was revealed by Sonmez et al. (2010). We suppose that lack of this association in our study may derive from quite good compensation of diabetes in the examined population or that increased activity of CHIT1 in T2D patients may result from glucose-independent pathways. Indeed, levels of CHIT1 in diabetic patients with normoalbuminuria were similar to those in the control group, which may indicate that the presence of diabetes per se is not enough to cause increased activity of this enzyme. However, the possible impact of applied medication on CHIT1 activity, including hypoglycemic, hypotensive and hypolipidemic, has not been investigated so far and this aspect should be verified in the next studies with a sufficient number of patients. We also revealed a significant relationship of CHIT1 activity with SBP, which was obtained despite hypotensive treatment of these patients. It is known that increased SBP is frequently connected with arterial stiffness caused by calcification and atherosclerotic lesion development. Some studies have demonstrated previously high levels of chitotriosidase activity within atherosclerotic plaque and a relation between CHIT1 activity and atherosclerosis extent in humans (Artieda et al., 2003; Boot et al., 1999). This may indicate that CHIT1 is an agent intermediating in endothelial dysfunction within vessel walls and participates in a novel pathway of vascular injury. Numerous studies show, that YKL-40 acts as a modulatory agent, promoting chemotaxis, cell attachment and migration of vascular endothelial cells, and it has been described as a factor of inflammatory events initiated by endothelial dysfunction
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(Rathcke & Vestergaard, 2006). In our study we have confirmed the progressive increase of plasma YKL-40 concentration with the degree of albuminuria in type 2 diabetes. Previously, such an association was found by Rondbjerg et al. (2011). However, the authors obtained significant differences in YKL-40 concentration only between the control group and patients with normo- and macroalbuminuria. In our study, YKL-40 additionally significantly differed between controls and patients with microalbuminuria. Additionally, in the present study we examined an association of CHIT1 and YKL-40 with CRP as a marker of inflammation, but we did not reveal a significant correlation. Several studies have previously demonstrated a divergent relationship of these proteins with inflammatory markers, but in most cases the correlation of these proteins with CRP was weak or nonexistent. It was posited that YKL-40 reflect local, site-specific inflammation rather than general systemic inflammation, and CHIT1 may act similarly (Aziz et al., 2014; Kundak et al., 2012; Rathcke & Vestergaard, 2006; Yildiz et al., 2013). The diabetic patients examined by us displayed low-grade chronic systemic inflammation, which was reflected by the CRP level within the upper reference range. The correlation of CHIT1 with YKL-40, as well as their positive association with WBC, indicates leukocytes as a common source of these proteins in patients with T2D and may suggest involvement of these proteins in the inflammatory response in diabetes (Aydogdu et al., 2012; Kim et al., 2012). In this aspect, the perception of albuminuria as a marker of cardiovascular risk in diabetic patients supports a causal link between chronic low grade inflammation (reflected by increased levels of CHIT1 and YKL-40 in the circulation) and vascular diabetic complications. Comparing the increase of CHIT1 and YKL-40, we observed that it was more significant for CHIT1, which suggests that chitotriosidase, despite the possibility of genetic variation influencing its activity, reflects the intensity of vascular damage in diabetic patients better than YKL-40. This suggestion was confirmed by ROC curves analysis. As we collated diagnostic performance of examined proteins from the GH18 family, we observed apparently greater accuracy of CHIT1 than YKL-40 in differentiating patients with and without albuminuria. Observed sensitivity and specificity at the calculated cut-off point (80.64 nmol/h/mL) for CHIT1 seem to be clinically relevant for this purpose, even though we analyzed both patients without the mutant allele and heterozygotes. However, the possibility of potential overlap of CHIT1 values in adjacent subgroups, resulting from genetic differences, may exist. This results suggest, that CHIT1 may be a candidate for a pool of supplemental biomarkers, which may be useful for correct evaluation of renal involvement in T2D. We are aware that the population examined by us was quite heterogeneous and diabetes was complicated with other metabolic disturbances (including hypertension or dyslipidemia), which was because of difficulties in selecting patients who had DN solely. However, differentiated subgroups of patients did not differ among each other in this respect, and they were also matched for applied treatment. Further longitudinal studies are needed to confirm the value of CHIT1 in prediction of kidney injury in diabetic patients.
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Conclusions In summary, our study provides additional data about the role of two proteins from the GH18 family, CHIT1 and YKL-40, in development of vascular diabetic complications, with the indication for kidney dysfunction. We revealed a simultaneous increase of plasma levels of these proteins with albuminuria in patients with T2D. CHIT1 activity seems to better reflect the degree of dysfunction in diabetic kidney than YKL-40. We suggest that CHIT1 may be a novel pathological component engaged in development of diabetic vascular complications in this patient population, as well as a promising and noninvasive tool for the evaluation of severity of renal impairment in these patients.
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Declaration of interest The authors declare no conflict of interest at the time of submission.
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Kolset SO, Reinholt FP, Jenssen T. (2012). Diabetic nephropathy and extracellular matrix. J Histochem Cytoche. 60:976–86. Kundak AA, Tascilar ME, Abaci A, et al. (2012). Serum chitotriosidase activity: is it a new inflammatory marker in obese children? J Pediatr Endocrinol Metab 25:63–7 Levey AS, Bosch JP, Lewis JB, et al. (1999). A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 130:461–70. MacIsaac RJ, Ekinci EI, Jerums G. (2014). ‘Progressive diabetic nephropathy. How useful is microalbuminuria?: contra’. Kidney Int 86:50–7. Miralles JM, Corrales JJ, Garcia-Diez LC, et al. (1982). N-acetyl beta-Dglucosaminidase and alpha-L-fucosidase activities in relation to glycosylated hemoglobin levels and to retinopathy in diabetes. Clin Chim Acta 121:373–8. Nakagawa T, Tanabe K, Croker BP, et al. (2011). Endothelial dysfunction as a potential contributor in diabetic nephropathy. Nat Rev Nephrol 7:36–44. Nishikawa KC, Millis AJ. (2003). gp38k (CHI3L1) is a novel adhesion and migration factor for vascular cells. Exp Cell Res 287:79–87. Piwowar A, Knapik-Kordecka M, Warwas M. (2008). Oxidative stress and endothelium dysfunction in diabetes mellitus type 2. Pol Merkur Lekarski 25:120–3. Polovina MM, Potpara TS. (2014). Endothelial dysfunction in metabolic and vascular disorders. Postgrad Med 126:38–53. Rathcke CN, Persson F, Tarnow L, et al. (2009). YKL-40, a marker of inflammation and endothelial dysfunction, is elevated in patients with type 1 diabetes and increases with levels of albuminuria. Diabetes Care 32:323–8. Rathcke CN, Vestergaard H. (2006). YKL-40, a new inflammatory marker with relation to insulin resistance and with a role in endothelial dysfunction and atherosclerosis. Inflamm Res 55:221–7. Recomendation of the Polish Society of Diabetology. (2012). Clinical guidelines for management of diabetes. Diabetol Klin 1:A1–54. Riabov V, Gudima A, Wang N, et al. (2014). Role of tumor associated macrophages in tumor angiogenesis and lymphangiogenesis. Front Physiol 5:75. doi:10.3389/fphys.2014.00075. Røndbjerg AK, Omerovic E, Vestergaard H. (2011). YKL-40 levels are independently associated with albuminuria in type 2 diabetes. Cardiovasc Diabetol 10:54. doi: 10.1186/1475-2840-10-54. Roshan B, Stanton RC. (2013). A story of microalbuminuria and diabetic nephropathy. J Nephropathol 2:234–40. Schosinsky KH, Vargas M, Luz Esquivel A, Chavarria MA. (1987). Simple spectrophotometric determination of urinary albumin by dyebinding with use of bromphenol blue. Clin Chem 33:223–26. Sonmez A, Haymana C, Tapan S, et al. (2010). Chitotriosidase activity predicts endothelial dysfunction in type-2 diabetes mellitus. Endocrine 37:455–9. Sun YM, Su Y, Li J, Wang LF. (2013). Recent advances in understanding the biochemical and molecular mechanism of diabetic nephropathy. Biochem Biophys Res Commun 433:359–61. Tao H, Yang JJ, Shi KH, et al. (2014). The significance of YKL-40 protein in liver fibrosis. Inflamm Res 63:249–54. van Eijk M, van Roomen CP, Renkema GH, et al. (2005). Characterization of human phagocyte-derived chitotriosidase, a component of innate immunity. Int Immunol 17:1505–12. Wiela-Hojen´ska A, Orzechowska-Juzwenko K. (1999). N-acetyl-beta-Dglucosaminidase and its clinical significance. Pol Arch Med Wewn 101:359–66. Yildiz BS, Barutcuoglu B, Alihanoglu YI, et al. (2013). Serum chitotriosidase activity in acute coronary syndrome. J Atheroscler Thromb 20:134–41. _ Zurawska-Płaksej E, Rorbach-Dolata A, Knapik-Kordecka M, Piwowar A. (in press). Increased chitotriosidase activity in plasma with diabetes type 2. Arch Med Sci.
RESEARCH ARTICLE
Proteins from the 18 glycosyl hydrolase family are associated with kidney dysfunction in patients with diabetes type 2 1 _ Ewa Zurawska-Płaksej #, Agnieszka Ługowska2, Katarzyna Hetman´czyk2, Maria Knapik-Kordecka3, 3 Rajmund Adamiec , and Agnieszka Piwowar4
Department of Pharmaceutical Biochemistry, Wroclaw Medical University, Wroclaw, Poland, 2Department of Genetics, Institute of Psychiatry and Neurology in Warsaw, Warsaw, Poland, 3Department and Clinic of Angiology, Hypertension and Diabetology, and 4Department of Toxicology, Wroclaw Medical University, Wroclaw, Poland
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Abstract
Keywords
Objectives: To investigate chitotriosidase (CHIT1) activity and chitinase-3-like protein 1 (YKL-40) concentration in plasma of type 2 diabetic patients and evaluate their relationship with kidney dysfunction. Materials and methods: 94 diabetic subjects and 33 controls were enrolled in the study. Plasma CHIT1 activity and YKL-40 concentration were measured along with routine laboratory parameters. Results: Levels of CHIT1 and YKL-40 in plasma of type 2 diabetic patients increased progressively with the degree of albuminuria. CHIT1 discriminated normoalbuminuric subjects from those with abnormal albuminuria better than YKL-40. Conclusions: CHIT1represent a supportive biomarker connected with development of diabetic vascular complications, especially kidney dysfunction.
Albuminuria, biomarker, chitotriosidase, diabetes mellitus, diabetic nephropathy, YKL-40
Introduction The glycosyl hydrolase family 18 (GH18), which is widely expressed in living organisms (from prokaryotes to eukaryotes), includes enzymes with chitinolytic activity (chitinases) and non-enzymatic chitinase-like proteins (CLPs). Although chitin is not a natural compound for humans, some members of this family have been unexpectedly discovered in the human species. The human genome encodes two chitinases – chitotriosidase (CHIT1) and acidic mammalian chitinase – and at least three CLPs: chitinase 3-like protein 1 (termed human cartilage glycoprotein-39 or YKL-40), chitinase 3-like protein 2 (YKL-39) and oviductin (Hussain & Wilson, 2013). CHIT1 is involved in the degradation of chitin and chitinlike substrates, due to hydrolysis of the N-acetyl-beta-Dglucosaminide-(1-4)-beta linkages. This ability confers its antibacterial, antifungal and antiparasitic properties and determines its physiological function in human organisms that is probably participation in immune defense. The enzyme is expressed mainly by activated phagocytes (macrophages and neutrophils). Some mutations in the CHIT1 gene may occur, which leads to alterations in enzyme expression (Boot et al., _ *Ewa Zurawska-Płaksej is responsible for statistical design/analysis. E-mail: [email protected] _ Address for correspondence: Ewa Zurawska-Płaksej, Department of Pharmaceutical Biochemistry, Wroclaw Medical University, Borowska St 211A, 50-556 Wroclaw, Poland. Tel: +48 717840468. Fax: +48 717840304. E-mail: [email protected]
History Received 17 October 2014 Accepted 24 November 2014 Published online 17 December 2014
1998; van Eijk et al., 2005). Increased plasma CHIT1 activity has been recognized as a useful marker in diagnosing and monitoring of Gaucher disease (Hollak et al., 1994). This enzyme is considered as a novel marker of inflammation (Kanneganti et al., 2012; Kundak et al., 2012). In the last few years, CHIT1 activity has also been examined in other pathological states, such as sarcoidosis, inflammatory bowel disease, infectious diseases, atherosclerosis, or newly diagnosed type 2 diabetes mellitus (T2D). In a previous study we revealed that activity of this enzyme is also increased in plasma _ of patients with ongoing T2D (Zurawska-Płaksej et al., in press). YKL-40 is a heparin- and chitin-binding lectin without chitinase activity. It is produced at the site of inflammation, secreted mainly by activated macrophages, neutrophils, and other types of cells, including differentiated vascular smooth muscle cells. It is reported to be an essential factor in extracellular matrix remodeling, but its exact function remains unclear (Johansen, 2006; Nishikawa & Millis, 2003). Early studies suggest its potential usefulness for researching such pathologies as rheumatoid arthritis, liver fibrosis and different types of cancer (including colorectal, lung and breast) (Riabov et al., 2014; Tao et al., 2014). Some studies have also reported increased levels of plasma YKL-40 in diabetes mellitus patients, both type 1 and type 2 (Rathcke et al., 2009; Røndbjerg et al., 2011). Type 2 diabetes, which makes up about 90% of cases of diabetes worldwide, is connected with a variety of metabolic
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DOI: 10.3109/1354750X.2014.992475
abnormalities, such as hyperglycemia, obesity, hypertension, and dyslipidemia. These are the main systemic factors, that trigger proinflammatory events, leading to endothelial dysfunction and increased prevalence of vascular late complications in diabetic patients (Polovina & Potpara, 2014). Diabetic nephropathy (DN), a specific type of diabetic angiopathy (microangiopathy), is the leading cause of progressive kidney dysfunction and end-stage renal disease, and thus represents a serious risk of increased mortality in people with T2D (DuranSalgado & Rubio-Guerra, 2014). The exact pathomechanisms of the development of DN remains undetermined. Endothelial dysfunction is suggested as a key factor, but there is a continuing need to search for other contributing factors (Eleftheriadis et al., 2013; Sun et al., 2013). Since it was indicated that chitotriosidase activity predicts endothelial dysfunction in patients with newly diagnosed, untreated and uncomplicated T2D, and we revealed increased activity of this enzyme also in patients with ongoing diabetes, we have continued our research on the possible relationship of chitotriosidase with kidney dysfunction in these patients. In addition, we compared diagnostic accuracy of CHIT1 to differentiate patients with and without kidney impairment with another protein from the 18GH family, YKL-40, which has been previously reported as a proinflammatory biomarker in the early stage of DN (Rathcke et al., 2009).
Methods Initially, 94 patients with type 2 diabetes mellitus, having an average duration of 11 years, were recruited from the Clinic of Angiology, Hypertension and Diabetology of Wroclaw Medical University. T2D was diagnosed according to the standards set by the Polish Diabetes Association (Recommendation of the PDA, 2012). The control group (CTRL) consisted of 33 nondiabetic subjects (glucose level 55.5 mmol/l) with no evidence of inflammatory states during the last 3 months, matched for sex and age. All participants were informed about the aim of the study, and their written permission was given. The use of human blood and urine was approved by the Local Bioethics Committee of Wroclaw Medical University. Venous blood was collected after overnight fasting into standard vacuum tubes with heparin (16 IU/mL) to obtain plasma. Routine laboratory parameters were measured by standard laboratory methods. Plasma samples were stored at 80 C until assayed. Plasma activity of chitotriosidase was measured by a spectrofluorometric method according to Hollak et al. (1994) using the synthetic substrate 4-methylumbelliferylb-N-N0 -N00 -triacetylchitotrioside (Sigma Chemical Co, St. Louis, MO). Fluorometric measurements were made at excitation ¼ 365 nm and emission ¼ 445 nm (Perkin Elmer LS 50B, Waltham, MA). Plasma concentration of YKL-40 was measured by an ELISA test (MicroVue, Quidel, San Diego, CA). Plasma activity of N-acetyl-b-D-glucosaminidase (NAG) was measured by a fluorometric method according to Miralles et al. (1982). The presence of a common 24-bp duplication in exon 10 of the CHIT1gene was examined by polymerase chain reaction (PCR) in a T100 Thermal-Cycler (Bio-Rad, Hercules, CA) as described by Boot et al. (1998) in genomic DNA extracted
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from plasma (GeneMATRIX Tissue DNA Purification Kit, EURx, Gdan´sk, Poland). Due to deficient chitotriosidase activity, homozygotus individuals were excluded from further analysis and finally examined groups consisted of 90 patients and 32 controls. Single-spot early morning urine specimens were collected and urinary albumin and creatinine concentrations were measured according to methods described previously (Helger et al., 1974; Schosinsky et al., 1987). The value of the urinary albumin-to-creatinine ratio (UACR) was calculated, and on this basis patients were stratified into three subgroups: with normoalbuminuria (NORM, UACR530 mg/g), with microalbuminuria (MICR, UACR 30-300 mg/g) and with macroalbuminuria (MACR, UACR4300 mg/g). Moreover, the estimated glomerular filtration rate (eGFR) was calculated according to the MDRD formula (Levey et al., 1999) The statistical analysis was done using Statistica PL, StatSoft (Tulsa, OK) for Windows, version 10.0. Comparisons between controls and diabetic patients were made with the Mann–Whitney U-test or chi-squared test as necessary. Differences between subgroups were estimated by analysis of variance (ANOVA), followed by Fisher’s test. Analysis of covariance in subgroups with different degrees of albuminuria was used for adjusting for CHIT1 gene 24 bp duplication. A p value below 0.05 was considered as statistically significant. All results were expressed as a mean value and a standard deviation or number and percent. Receiver operating characteristic (ROC) curves were calculated to evaluate the discriminative power of CHIT1 in comparison with YKL-40 for patients with different degrees of kidney dysfunction. Spearman rank correlation was used to estimate of CHIT1 and YKL-40 with selected laboratory parameters in the examined population. Multiple regression analysis was performed to adjust for confounding variables and regression coefficients before and after adjustment were compared.
Results The main anthropometric and biochemical characteristic of the examined subjects are given in Table 1. Age, BMI, diastolic blood pressure (DBP), total cholesterol and lowdensity lipoprotein (LDL) cholesterol and white blood cell (WBC) count did not vary significantly between patients with diabetes and the control group. CRP concentration was significantly higher in diabetic patients, but it was still below the upper reference value (510 mg/L). CHIT1 gene genotyping revealed presence of the 24-bp duplication in 41% of subjects, among which 4% were homozygotes (excluded from further analysis) and 37% were heterozygotes. There were no differences in distribution of the mutant allele in examined subgroups of participants (the frequency varied from 34 to 40%). Plasma chitotriosidase activities and YKL-40 concentrations in control subjects and subgroups of patients with different degrees of albuminuria are presented in Figure 1. As shown, both CHIT1 and YKL-40 were significantly higher in patients with T2D in comparison to the control group (nondiabetic subjects) and increased progressively with the degree of kidney dysfunction evidenced by albuminuria; however, this ‘‘trend’’ is more evident for CHIT1. Activities
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Table 1. Anthropometric and clinical characteristics of participants. Patients with
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Parameter n Sex, male/female Age, years Diabetes duration, years BMI, kg/m2 SBP, mmHg DBP, mmHg CRP, mg/l WBC, 109/l Glucose, mmol/l HbA1c, % Chol, mmol/l LDL-Chol, mmol/l HDL-Chol, mmol/l TG, mmol/l Plasma creatinine, mmol/l eGFR NAG activity (nmol/h/ml) UACR (mg/g) Smoking (%) Hypotensive treatment (n) Use of statins (n) Use of (OAD/OAD + ins)
Control subjects
Diabetic patients
normo-albuminuria
micro-albuminuria
macro-albuminuria
32 12/20 61.90 ± 5.61 – 29.59 ± 4.16 129.95 ± 9.93 80.54 ± 8.86 2.91 ± 1.92 7.03 ± 1.03 5.19 ± 0.30 5.47 ± 0.22 5.22 ± 1.01 3.09 ± 0.62 1.51 ± 0.38 1.32 ± 0.35 77.79 ± 20.55 85.20 ± 20.51 136.41 ± 40.52 3.37 ± 3.35 29 0 0 0
90 32/58 62.87 ± 6.11 10.82 ± 4.31 30.33 ± 5.03 143.00*** ± 12.19 80.58 ± 8.75 5.80*** ± 2.98 7.60 ± 2.52 8.73*** ± 1.50 7.80*** ± 1.48 5.18 ± 2.15 3.04* ± 0.80 1.17*** ± 0.41 2.25*** ± 0.81 106.08*** ± 29.17 66.45*** ± 15.86 207.45*** ± 58.11 149.00*** ± 80.91 25 29*** 22.5*** 43/47***
29 11/18 62.76 ± 5.19 10.04 ± 4.12 30.95 ± 5.06 137.73 ± 16.11 77.84 ± 9.11 5.52 ± 2.77 7.60 ± 2.70 8.78 ± 1.48 7.74 ± 1.35 5.25 ± 2.10 3.02 ± 0.78 1.22 ± 0.43 2.23 ± 0.81 86.63 ± 22.84 73.26 ± 19.20 194.04 ± 55.41 22.57 ± 13.88 27 29 21 14/15
32 11/21 63.40 ± 6.60 9.58 ± 4.59 29.82 ± 4.78 141.88 ± 12.59 80.09 ± 9.31 4.02 ± 1.75 7.49 ± 2.55 8.67 ± 1.51 7.93 ± 1.58 4.97 ± 2.21 2.90 ± 0.80 1.16 ± 0.43 2.28 ± 0.83 106.96 ± 30.54 66.93 ± 15.34 199.20 ± 58.89 221.19 ± 100.3 26 30 26 14/18
29 10/19 62.39 ± 6.37 12.96 ± 4.19 30.27 ± 5.16 149.50 ± 7.83 83.80 ± 6.78 8.04 ± 4.58 7.72 ± 2.25 8.74 ± 1.60 7.72 ± 1.49 5.34 ± 2.16 3.21 ± 0.81 1.14 ± 0.39 2.23 ± 0.80 123.73 ± 33.76 59.12 ± 14.85 230.50 ± 59.97 583.93 ± 325.87 22 28 20 15/14
Data are presented as mean ± standard deviation or number/percent. Statistical significance of differences between control subjects and diabetic patients, checked by Mann–Whitney U-test: *–p50.05, ***–p50.001. Abbreviations: BMI – body mass index, Chol – total cholesterol, CRP – C-reactive protein, DBP – diastolic blood pressure, eGFR – estimated glomerular filtration rate, HbA1c – glycated hemoglobin, HDL-Chol – high-density lipoprotein cholesterol, ins – insulin, LDL-Chol – low-density lipoprotein cholesterol, n – number of subjects, NAG – N-acetyl-b-D-glucosaminidase, OAD – oral antidiabetics, SBP – systolic blood pressure, TG – triglyceride, UACR – urinary albumin-to-creatinine ratio, WBC – white blood cells.
Figure 1. Chitotriosidase and YKL-40 in plasma of control subjects and subgroups of diabetic patients differentiated according to level of albuminuria. CHIT1 – chitotriosidase, YKL-40 – human cartilage glycoprotein-39, CTRL – control group, NORM – diabetic patients with normoalbuminuria, MICR – diabetic patients with microalbuminuria, MACR – diabetic patients with macroalbuminuria. Statistical significance of differences in comparison to: a – CTRL, b – NORM, c – MICR, d – MACR subgroup, checked by Fisher test: ^ – not significant, * – p50.05, ** – p50.01, *** – p50.001.
of chitotriosidase were significantly different among all examined subgroups of patients with type 2 diabetes. All differences remained significant also after adjustment for CHIT1 genotype. The only observed change was a slight decrease of statistical significance between normo- and microalbuminuric patients (before and after adjustment p ¼ 0.009 and 0.029, respectively). Among patients with T2D, the lowest activity of CHIT1 was observed in the NORM subgroup, being almost 2-fold higher in the MICR subgroup and 3.5-fold higher in the MACR one. Enzyme activity in the control group was at the similar level as in subgroup of normoalbuminuric patients. YKL-40
concentration also increased progressively with the degree of albuminuria (almost 1.2- and 2-fold increase in MICR and MACR subgroup, respectively, in comparison with the NORM one), but differences between subgroups were statistically significant only in patients with macroalbuminuria versus other subgroups. Concentration of YKL-40 in the control group was 1.3-fold lower than in the subgroup of normoalbuminuric patients, but the difference was still not significant. ROC curves used to evaluate and to compare the potential utility of CHIT1 and YKL-40 for differentiating subjects with normal (UACR530 mg/g) and impaired (UACR430 mg/g)
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Figure 2. Comparison of diagnostic utility of plasma chitotriosidase and YKL-40 in discrimination of subjects with and without albuminuria. CHIT1 – chitotriosidase (upper line), YKL-40 – human cartilage glycoprotein-39 (lower line).
kidney function are shown in Figure 2. The area under the curve (AUC) was statistically larger (p50.001) for CHIT1(0.869) than for YKL-40 (0.668). The optimum discriminative value, calculated at 80.64 nmol/h/ml of CHIT1 activity, provided sensitivity of 86% and specificity of 74%. For comparison, the optimum discriminative value for YKL-40 concentration, calculated at 146.17 ng/mL, was characterized by 76% sensitivity and 63% specificity. Spearman rank correlation analysis revealed a significant mutual relationship between CHIT1 and YKL-40 (r ¼ 0.27, p ¼ 0.020). Moreover, CHIT1 activity was significantly associated with systolic blood pressure (SBP) (r ¼ 0.27, p ¼ 0.017), plasma creatinine (r ¼ 0.31, p50.001), and UACR (r ¼ 0.60, p50.001) in the total group of participants, while YKL-40 concentration was significantly associated only with UACR (r ¼ 0.37, p ¼ 0.011). After adjustment for SBP and plasma creatinine, the UACR remains significantly associated with CHIT1 activity, but the magnitude of the association was slightly lower (the regression coefficient decreased from 0.603 to 0.552 after adjustment). Neither CHIT1 nor YKL-40 was significantly associated with eGFR. We did not reveal any association of either CHIT1 or YKL-40 with the presence of an inflammatory state, reflected by CRP. However, a significant association was found with WBC count: r ¼ 0.236 (p ¼ 0.005) for CHIT1, r ¼ 0.313 (p ¼ 0.014) for YKL-40. There were no significant associations of these proteins with parameters of glycemic control (fasting glucose and HbA1c) or with NAG activity.
Discussion The late vascular complications of diabetes remain a causal factor of worsening of life quality and life expectancy in T2D patients. Diabetic nephropathy develops in 30% of T2D
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patients (despite treatment) and leads to progression of arterial hypertension, increased risk of cardiovascular disease or directly to life-threatening kidney damage. Endothelial dysfunction is reported to be implicated in the pathogenesis of DN. Structural abnormalities of the endothelium (such as impairment of endothelial glycocalyx) may lead to permeability in the glomerular basement membrane, which might partially account for microalbuminuria in diabetic patients (Nakagawa et al., 2011). Albuminuria is an established marker of endothelial dysfunction as well as a predictor of progression of DN (Piwowar et al., 2008; Roshan & Stanton, 2013). However, in recent times, the significance of albuminuria measurement as a single parameter has been questioned. Some authors suggest that in type 2 diabetes aging, hypertension and development of intrarenal vascular disturbances may contribute to the decrease in renal function independently of albuminuria, and precise estimation of the risk for development and progression of diabetic kidney disease requires additional markers. eGFR seems to be a valuable tool for predicting renal events in these patients (MacIsaac et al., 2014). However, there is a constant need for searching other risk markers of progressive renal impairment in diabetes. Progressive DN is characterized by pathological changes in multiple cellular compartments, including mesangial matrix expansion, culminating in glomerulosclerosis, podocyte injury and apoptosis, and tubulointerstitial fibrosis. Immune and inflammatory involvement in development of diabetic nephropathy is evidenced, but the detailed pathogenesis still requires explanation (Duran-Salgado & Rubio-Guerra, 2014). Recently it has been shown that both CHIT1 and YKL-40 may affect endothelial function in T2D (Nishikawa & Millis, 2003; Sonmez et al., 2010). We have also revealed increased plasma CHIT1 activity in patients with ongoing T2D _ (Zurawska-Płaksej et al., in press). Phagocyte accumulation is associated with declining renal function in diabetic patients, and both macrophages (as a source of proinflammatory cytokines) and neutrophils (as a source of reactive oxygen species), the major cells infiltrating the kidneys, are indicated as a source of examined proteins (Akcay et al., 2009). Therefore, we hypothesized that proteins from the GH18 family may play a role in development of diabetic complications, in particular nephropathy. So far, only YKL-40 has been indicated as a factor engaged in the progressing vascular complications in patients with T2D (Røndbjerg et al., 2011). In the present study, we revealed for the first time a relationship of CHIT1 activity with the severity of diabetic kidney dysfunction according to their albuminuria status. A progressive increase of this enzyme’s activity was observed in subgroups of diabetic patients with different degrees of albuminuria being the most significant in micro- and macroalbuminuric patients, independently from CHIT1 genotype. CHIT1 was also correlated with plasma creatinine and UACR. It may indicate possible participation of this enzyme in the progression of nephropathy in T2D patients. Interestingly, although severity of albuminuria was parallel to the decline of glomerular filtration in T2D patients, we did not reveal any significant association of CHIT1 with eGFR. We considered whether increased activity of this enzyme results more from dysfunction within kidneys or rather from
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generalized vascular damage reflected by albuminuria. We attempted to resolve this question by measuring CHIT1 activity in urine. Unfortunately, the levels of this enzyme in urine samples were extremely low, and we did not observe any statistically significant differences between subjects with and without diabetes (data not shown). Seeking to explain the increased activity of plasma chitotriosidase in patients with diabetic kidney dysfunction, and in view of the lack of a natural substrate for this enzyme in humans, we hypothesize that CHIT1 may cooperates with other enzymes (such as matrix metalloproteinases, serine proteases or NAG) in catabolism of glycoproteins and glycosaminoglycans, which cumulate in the mesangium and the tubulointerstitial space during development of DN. Therefore, increased CHIT1 activity in T2D patients may be a ‘‘natural weapon’’ against deepening disturbances (Kolset et al., 2012). However, we did not find any significant association between activity of CHIT1 and NAG, which is indicated as a marker of early endothelial dysfunction that increases before occurrence of albuminuria (Wiela-Hojen´ska & Orzechowska-Juzwenko, 1999). This may due to nonsynchronized time of actions or different mechanisms of regulation of these enzymes, and this matter needs to be verified. We have also evaluated associations of CHIT1 with biochemical parameters, which directly influence on the development of diabetic vascular complications such as blood glucose and HbA1c. In this study, CHIT1 was not found to be significantly correlated with parameters of glycemic control. However, in newly diagnosed and untreated T2D a positive correlation of CHIT1 activity with plasma glucose was revealed by Sonmez et al. (2010). We suppose that lack of this association in our study may derive from quite good compensation of diabetes in the examined population or that increased activity of CHIT1 in T2D patients may result from glucose-independent pathways. Indeed, levels of CHIT1 in diabetic patients with normoalbuminuria were similar to those in the control group, which may indicate that the presence of diabetes per se is not enough to cause increased activity of this enzyme. However, the possible impact of applied medication on CHIT1 activity, including hypoglycemic, hypotensive and hypolipidemic, has not been investigated so far and this aspect should be verified in the next studies with a sufficient number of patients. We also revealed a significant relationship of CHIT1 activity with SBP, which was obtained despite hypotensive treatment of these patients. It is known that increased SBP is frequently connected with arterial stiffness caused by calcification and atherosclerotic lesion development. Some studies have demonstrated previously high levels of chitotriosidase activity within atherosclerotic plaque and a relation between CHIT1 activity and atherosclerosis extent in humans (Artieda et al., 2003; Boot et al., 1999). This may indicate that CHIT1 is an agent intermediating in endothelial dysfunction within vessel walls and participates in a novel pathway of vascular injury. Numerous studies show, that YKL-40 acts as a modulatory agent, promoting chemotaxis, cell attachment and migration of vascular endothelial cells, and it has been described as a factor of inflammatory events initiated by endothelial dysfunction
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(Rathcke & Vestergaard, 2006). In our study we have confirmed the progressive increase of plasma YKL-40 concentration with the degree of albuminuria in type 2 diabetes. Previously, such an association was found by Rondbjerg et al. (2011). However, the authors obtained significant differences in YKL-40 concentration only between the control group and patients with normo- and macroalbuminuria. In our study, YKL-40 additionally significantly differed between controls and patients with microalbuminuria. Additionally, in the present study we examined an association of CHIT1 and YKL-40 with CRP as a marker of inflammation, but we did not reveal a significant correlation. Several studies have previously demonstrated a divergent relationship of these proteins with inflammatory markers, but in most cases the correlation of these proteins with CRP was weak or nonexistent. It was posited that YKL-40 reflect local, site-specific inflammation rather than general systemic inflammation, and CHIT1 may act similarly (Aziz et al., 2014; Kundak et al., 2012; Rathcke & Vestergaard, 2006; Yildiz et al., 2013). The diabetic patients examined by us displayed low-grade chronic systemic inflammation, which was reflected by the CRP level within the upper reference range. The correlation of CHIT1 with YKL-40, as well as their positive association with WBC, indicates leukocytes as a common source of these proteins in patients with T2D and may suggest involvement of these proteins in the inflammatory response in diabetes (Aydogdu et al., 2012; Kim et al., 2012). In this aspect, the perception of albuminuria as a marker of cardiovascular risk in diabetic patients supports a causal link between chronic low grade inflammation (reflected by increased levels of CHIT1 and YKL-40 in the circulation) and vascular diabetic complications. Comparing the increase of CHIT1 and YKL-40, we observed that it was more significant for CHIT1, which suggests that chitotriosidase, despite the possibility of genetic variation influencing its activity, reflects the intensity of vascular damage in diabetic patients better than YKL-40. This suggestion was confirmed by ROC curves analysis. As we collated diagnostic performance of examined proteins from the GH18 family, we observed apparently greater accuracy of CHIT1 than YKL-40 in differentiating patients with and without albuminuria. Observed sensitivity and specificity at the calculated cut-off point (80.64 nmol/h/mL) for CHIT1 seem to be clinically relevant for this purpose, even though we analyzed both patients without the mutant allele and heterozygotes. However, the possibility of potential overlap of CHIT1 values in adjacent subgroups, resulting from genetic differences, may exist. This results suggest, that CHIT1 may be a candidate for a pool of supplemental biomarkers, which may be useful for correct evaluation of renal involvement in T2D. We are aware that the population examined by us was quite heterogeneous and diabetes was complicated with other metabolic disturbances (including hypertension or dyslipidemia), which was because of difficulties in selecting patients who had DN solely. However, differentiated subgroups of patients did not differ among each other in this respect, and they were also matched for applied treatment. Further longitudinal studies are needed to confirm the value of CHIT1 in prediction of kidney injury in diabetic patients.
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Conclusions In summary, our study provides additional data about the role of two proteins from the GH18 family, CHIT1 and YKL-40, in development of vascular diabetic complications, with the indication for kidney dysfunction. We revealed a simultaneous increase of plasma levels of these proteins with albuminuria in patients with T2D. CHIT1 activity seems to better reflect the degree of dysfunction in diabetic kidney than YKL-40. We suggest that CHIT1 may be a novel pathological component engaged in development of diabetic vascular complications in this patient population, as well as a promising and noninvasive tool for the evaluation of severity of renal impairment in these patients.
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Declaration of interest The authors declare no conflict of interest at the time of submission.
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Proteins from the 18 glycosyl hydrolase family
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