- Email: [email protected]
Correlation Between CD14+CD16++ Monocytes in Peripheral Blood and Hypertriglyceridemia After Allograft Renal Transplantation
Correlation Between CD14DCD16DD Monocytes in Peripheral Blood and Hypertriglyceridemia After Allograft Renal Transplantation D. Xue, X. He, C. Zhou, X. Xu, R. Xu, and N. Xu ABSTRACT Background. Cardio-cerebrovascular diseases are key factors causing recipient the death after kidney transplantation (KT). Hypertriglyceridemia (HTG), a complication commonly occurring among KT patients, is a major risk factor for cardio-cerebrovascular diseases. The objective of this study was to examine the correlation between peripheral CD14þCD16þþ monocytes in KT patients and blood lipids as well as factors affecting hyperglycemia, seeking to understand mechanisms of inflammatory immune reactions. Methods. KT patients (n ¼ 60) were divided into subjects with HTG (n ¼ 35) versus without HTG (n ¼ 25). A cohort of healthy participants (55 cases) was divided into the cases without (n ¼ 30) versus with HTG (n ¼ 25). The proportion of peripheral CD14þCD16 þþ monocytes was determined using flow cytometry and hematology, and biochemical indicators were measured by conventional methods. We correlated HTG with these indicators. Results. The proportion of peripheral blood CD14þCD16þþ monocytes among the renal transplant group was significantly lower (P < .05) than that of normal controls. The expression of CD14þCD16þþ monocytes among transplant recipients positively correlated with triglycerides (R ¼ 0.449 and R ¼ 0.008, respectively). Conclusion. CD14þCD16þþ mononcytes in peripheral blood may represent an independent risk factor for HTG after KT.
C
ARDIO-CEREBROVASCULAR diseases are the key factors that cause the death of patients. Kidney transplantations (KT). Hypertriglyceridemia (HTG), a commonly complication among recipients, is a major risk factor leading to cardio-cerebrovascular diseases.1 As an important pathogenic mechanism of HTG, inflammatory reactions play important roles in thrombopoiesis and in the development of cardio-cerebrovascular diseases such as atherosclerosis.2 Mononuclear cells have a single round nucleus. They include lymphocytes, monocytes, and dendritic cells. These elements are divided into different subpopulations based on their functions and phenotypes of lipopolysaccharides receptor, CD14, Fcg receptor, and CD16. The two major monocyte subpopulations are CD14þþ CD16 and CD14þþ CD16þ cells. CD14þCD16þþ monocytes show greater expression of proinflammatory cytokines and greater efficiency in antigen presentation.3,4 Patients experiencing chronic renal insufficiency and hemodialysis show a high expression of CD14þCD16þþ monocytes putatively associated with atherosclerosis.5 The restoration of renal functional and the prescription of immunosuppressants after KT
may alter the distribution of monocyte subpopulations. The specific aim of the present study was to analyze possible correlations between of CD14þCD16þþ monocytes and HTG after allogenic renal transplantation, seeking to decipher underlying molecular mechanisms and roles of these cells in allo-immunity. MATERIALS AND METHODS Subjects The participants involved in this study were 60 level KT patients and 55 normal controls. The sixty 60 KT patients were divided into
From the Department of Urology, Third Affiliated Hospital, Suzhou University, Changzhou, China, and Lund Universities, Lund, Sweden. Supported by a grant (ZD201209) for the Key Projects awarded by the Department of Health, Changzhou City, Jiangsu Province. Address reprint requests to Xiaozhou He, Department of Urology, Third Affiliated Hospital, Suzhou University, Changzhou 213003, China. E-mail: [email protected]
ª 2013 by Elsevier Inc. All rights reserved. 360 Park Avenue South, New York, NY 10010-1710
0041-1345/13/$esee front matter http://dx.doi.org/10.1016/j.transproceed.2013.08.022
Transplantation Proceedings, 45, 3279e3283 (2013)
3279
3280
XUE, HE, ZHOU ET AL Table 1. Comparisons of Data About the General Biochemical Indicators Among Different Groups of Participants (x ± s)
Age (y) Gender (males, %) KT time (m) Concentration of Tacrolimus (ng/mL) Urea (mmol/L) Creatinine (umol/L) GFR (mL/min) Hemoglobin (g/L) TC (mg/L) TG (mg/L) HDL-C (mg/L) LDL-C (mg/L) Total proteins (g/L) Albumin (g/L)
Group With HTG After KT (n ¼ 35)
Group with Non-HTG After KT (n ¼ 25)
Group With HTG in Healthy Controls (n ¼ 25)
Group With Non-HTG in Healthy Controls (n ¼ 30)
P
45.3 15.6 53.3 43.6 30.1 7.7 1.8 7.64 2.18 124.6 34.6 48.5 12.65 145.8 19.43 4.94 1.57 3.01 4.06 1.42 0.53 2.89 0.78 59.88 8.76 32.75 5.72
42.1 12.5 60 48.2 35.7 7.6 2.0 7.79 2.37 113.1 30.3 49.8 11.62 141.2 16.76 3.22 1.43 1.61 0.35 1.24 0.36 2.24 0.81 60.63 8.94 31.24 5.83
38.6 8.2 46.7 5.64 1.75 88.2 17.3 146.4 19.52 153.2 15.1 4.52 1.85 2.89 2.88 1.45 0.35 2.73 0.81 66.73 11.42 38.6 5.73
35.6 7.9 53.3 5.73 1.26* 85.3 15.7* 140.2 18.49* 150.4 14.09* 3.76 1.06 1.59 0.36* 1.29 0.24 2.31 0.72 65.05 10.32 35.78 6.62
.42 .49 .31 .47 .46 .02 .03 .04 .41 .01 .35 .28 .17 .33
two groups: those with (n ¼ 35) versus without HTG (n ¼ 25). The after KT HTG group included 19 men and 16 women of overall mean age of 45.3 þ 15.6 years (range, 29e61) with follow-up of 43.6 þ 30.1 months. The group free of HTG included 15 men and 9 women of overall mean age of 42.1 þ 12.5 years (range, from 29e55 y) with follow-up of 48.2 þ 35.7 months. There were no significant differences in age and gender between the two groups. Fifty five normal healthy control participants were divided into the two subgroups: with (n ¼ 25) versus without HTG (n ¼ 30). The HTG healthy controls included 12 men and 13 women of overall mean age of 38.6 þ 8.2 years (range, 30e47 y). The healthy group free of HTG included 16 men and 14 women of overall mean age of 35.6 þ 7.9 years (range, 27e44). There were no significant differences in age and gender between transplanted or healthy subgroups. The protocols of this study were approved by our Institutional Ethics Committee; all participants provided informed consent. All the KT patients were presented oral tacrolimus (Prograf, Astellas Pharma, US), cellcept (Shanghai Roche Pharmaceuticals Ltd, China), and prednisone. Their kidney functions were normal. The exclusions for entry included: a prior acute rejection episode, presence of an acute inflammatory reaction (C-reactive protein >6 mg/L), abnormal hepatic function (prothrombin time and alanine transaminase), malignant tumor history for heart and lung diseases.
Detection of CD14þCD16þþ Monocytes in Peripheral Blood Flow cytometry was used to detect CD14þCD16þþ monocytes. Fifty microliters fasting venous blood sample containing EDTAK2-anticoagulant was admitted with 5 mL of fluorescent-labeled monoclonal antibodies phycoerythrin-anti-human-CD14 and FITCanti-human-CD16 (BioLegend, San Diego, Calif, United States) were successively added into 50 mL of blood sample, before mixing well and incubating in the dark at room temperature for 30 minutes. Following addition of 1 mL of hemolysin (Q-prep, Beckman Coulter, United States) and reactions were incubated in the dark at 37 C for 10 minutes and then centrifuged at 250g for 5 minutes. The supernate was removed, 1 mL of PBS added, and the cell pellet was resuspended and centrifuged at 250g for 5 minutes. The supernate was discarded; 0.5 mL of PBS was added, mixed, and incubated in the dark at 4 C for 1 hour. The cell sample was loaded on to the flow cytometer (FC500
flow cytometer, Beckman Coulter). CD14þCD16þþ-expressing monocytes were counted among 10,000 monocytes. Results were expressed as the percentage of CD14þCD16þþ monocytes among the counted total cells.
Measurement of Related Biochemical Indicators Fasting venous blood samples collected in the morning were sent for measurement of biochemical indicators: tacrolimus, urea, creatinine, glomerular filtration rate (GFR), and hemoglobin, using ABBOTT LABS Cell Dyn 3700CS Auto hematology analyzer (Abbott Park, Ill, United States) and Shimadzu CL-7300 Biochemistry Analyzer (Japan). Routine blood examination, functional assays for liver and kidney, for total cholesterol (TC), triglycerides (TG), high-density lipoproteins-cholesterol (HDL-C), and low-density lipoprotein-cholesterol (LDL-C) were studied.
Statistical Analysis SPSS13.0 statistical software was used to perform statistical analyses. The data were examined for normality by homogeneity tests; the results were expressed as mean values standard deviations (SD). The comparison of mean values between the two groups was performed with students t test. Tukey method was used to perform single-step multiple comparisons. One-way analysis of variance (ANOVA) examined the equality of multiple means at a given time. Pearson correlation analysis was used to evaluate correlations among variants. Nonparametric tests tested the heterogeneity of the variance. KruskaleWallis one-way ANOVA was used for multiple
Table 2. Cox Proportional Hazards Model Parameters
HR
CI
P
CD14þCD16þþ monocytes Age GFR TC TG HDL-C LDL-C
1.32 1.63 1.26 0.98 0.97 1.72 1.83
1.14e1.63 0.85e2.41 1.02e1.44 0.92e1.03 0.91e0.98 0.95e1.05 0.92e2.17
.012 .125 .023 .156 <.01 .148 .163
Abbreviations: HR, hazard ratio; CI, confidence interval. Note: Indicated are (HR), their 95% CI, and level of significance.
CD14+CD16++ MONOCYTES
3281 Table 3. Changes in Expression of CD14DCD16DD Monocytes
CD14þCD16þþ CD14þþCD16þ CD14þþCD16 -
Group With HTG After KT (n ¼ 35)
Group Without HTG After KT (n ¼ 25)
Group With HTG in Controls (n ¼ 25)
Group Without HTG in Controls (n ¼ 30)
1.72 0.75 6.54 5.93 91.32 6.86
1.86 0.81 6.78 6.87 90.62 7.48
2.97 1.62* 6.45 4.89 91.21 5.78
2.84 1.81* 6.31 5.69 89.69 6.91
*Significantly higher (P < .01).
group comparisons. The Mann-Whitney U test was used for multiple comparisons. Differences with a P < .05 value were considered to be statistically significant.
RESULTS Comparisons of General Biochemical Indicators of the Participants
Table 1 shows data about biochemical indicators: tacrolimus, urea, creatinine, hemoglobin, TC, TG, HDL-C, and LDL-C in the blood samples from all groups. Urea and creatinine concentrations in both patient groups were significantly higher and hemoglobin results lower in than those among the healthy cohort (P < .05). The TC context in HTG-positive KT cases (4.94 þ 1.57 mg/L) was significantly higher than (P < .05) the mean HTG value in healthy controls (4.52 þ 1.85 mg/L), recipients free of
HTG (3.22 þ 1.43 or healthy subjects versus 3.76 þ 1.06 mg/L, respectively). The TG levels among HTG transplanted subjects and HTG healthy controls were significantly higher than those among non-HTG cohort (P < .01). Although there was a significant difference in GFR between patient and healthy control groups (P < .05), there were no significant differences in HDL-C, LDL-C, and TC (Table 2).
Expression of CD14þCD16þþ Monocytes
Values of CD14þCD16þþ monocytes among these cohort are shown in Table 3, and Figure 1. Expression of CD14þCD16þþ on monocytes among the KT groups (1.72 0.75 and 1.86 0.81%) were lower than those of healthy participants (2.97 1.62 and 2.84 1.81%, respectively), differences that were significant (P < .01)
Fig 1. Distribution of CD14þCD16þþ monocytes. Flow cytometry analysis for expression of CD14þCD16þþ monocytes. (A) Group with HTG after KT; (B) Group without HTG after KT; (C) Group with HTG in control; (D) Group without HTG in control.
3282
XUE, HE, ZHOU ET AL
Table 4. Correlations of Expression of CD14DCD16DD Monocytes With TG Group of Patients After KT
TG
Group of Healthy Participants
R
P
R
P
0.449
.008
0.124
.514
The Multivariate Analysis of CD14þCD16þþ Monocytes Expression and TG Levels
The positive correlation on multivariate analysis is shown in Table 4 and Figure 2. (P < .05).
DISCUSSION
Cardio-cerebrovascular complications affect long-term survival of kidney transplanted recipients. HTG is an important cause leading to the death of these patients. HTG, one of the common complications among KT patients, can produce deposits in the venous tunica intima, leading to vascular sclerosis as well as increased blood viscosity that aggravates arteriosclerosis and thrombopoiesis. Some data have suggested that tacrolimus produces significantly less effect on blood lipids of transplanted patients of compared with cyclosporine (CsA). In selected cases high TC levels of patients on oral CsA have been reversed by switching to oral tacrolimus; however, the high blood TG levels were not reduced by this maneuver. Deleuze et al compared 76 KT cases on tacrolimus with 126 on CsA, observing that the TC and LDL-C blood levels of the former cohort were significantly lower: 1.64 1.37 mmol/L vs 5.28 1.32 mmol/L (P < .05), and 3.26 1.03 mmol/L vs 3.98 1.05 mmol/L (P < .05), respectively. The incidence of the newly-onset hypercholesterolemia and hyperlow-density lipoprotein-cholesterolemias were both significantly lower in the tacrolimus than the CsA group: 8% vs 28% and 31% vs 65% (P < .001), respectively. However, neither the differences in TG and HDL-C between groups nor the rates of HTG were significantly different.6 Monocyte infiltration is a characteristic of the damage caused by HTG. CD14þCD16þþ monocytes, a subpopulation that has strong capability to secrete proinflammatory
Fig 2. The correlation between expression of CD14þCD16þþ monocytes and TG and interleukin IL-6.
cytokines and for antigen presentation, activities that relate to the pathogenic features of HTG, can cause cardiocerebrovascular disease.7 In this study, we investigated the changes in expression of CD14þCD16þþ monocytes in patients who were followed up after KT and revealed a positive correlation between proinflammatory cytokines produced in CD14þCD16þþ monocytes in patients after KT and HTG. This study has provided new methods for clinical diagnosis and treatment for HTG. We detected expression of CD14þCD16þþ on monocytes of patients after KT for comparison with healthy participants. There was a significant difference (P < .05) in CD14þCD16þþ monocytes. The expression of the patient group was lower than the healthy participants. It positively correlated with TG levels. It has been reported previously that reduced numbers of monocytes in heart transplant recipients relate to the immunosuppression.8 Our study demonstrated that expression of CD14þCD16þþ monocytes is also reduced in KT patients. However, subjects with chronic renal insufficiency show significantly increased expression of CD14þCD16þþ monocytes that has been associated with cardio-cerebrovascular diseases, as an independent risk factor.9 The differences in expression of CD14þCD16þþ monocytes before versus after KT may be due to the restoration of kidney functions and the use of immunosuppressants, which may change the distribution of these subpopulations. In vitro and in vivo experiments have shown that glucocorticoids stimulate aspartic deaminasedependent apoptosis, reducing the expression of CD16þ on monocytes.10 In our study, tacrolimus was used as the major immunosuppressant, presumably mediating the lower number of CD14þCD16þþ monocytes, consistent with observations by other investigators.11 Changes in expression of CD14þCD16þþ monocytes after KT seen to be correlated with blood lipids, which play important roles in development and progression of atherosclerosis. CD16þ monocytes in individuals with normal kidney functions are closely related to coronary artery heart diseases.7 The regulatory mechanisms underlying the relationships between CD14þCD16þþ monocytes and micro-inflammation, secretion of proinflammatory cytokines, and the resultant HTG after KT merit further investigation.
CD14+CD16++ MONOCYTES
REFERENCES 1. Kasiske BL, Chakkera HA, Roel J. Explained and unexplained ischemic heart disease in renal transplant recipients. J Am Soc Nephrol. 2000;11:1735e1743. 2. Hansson GK. Inflammation, atherosclerosis, and coronary artery disease. N Engl J Med. 2005;352:1685e1695. 3. Belge KU, Dayyani F, Horelt A, et al. The proinflammatory CD14þCD16þDRþþ monocytes are a major source of TNF. J Immunol. 2002;168:3536e3542. 4. Ziegler-Heitbrock L. The CD14þ CD16þ blood monocytes: their role in infection and inflammation. J Leukocyte Biol. 2007;81: 584e592. 5. Scherberich JE. Proinflammatory blood monocytes: main effector and target cells in systemic and renal disease; background and therapeutic implications. Int J Clin Pharmacol Ther. 2003;41: 459e464. 6. Deleuze S, Garrigue V, Delmas S, et al. New onset dyslipidemia after renal transplantation: is there a difference
3283 between tacrolimus and cyclosporine? Transplant Proc. 2006;38: 2311e2313. 7. Schlitt A, Heine GH, Blankenberg S, et al. CD14þCD16þ monocytes in coronary artery disease and their relationship to serum TNF-alpha levels. Thromb Haemost. 2004;92:419e424. 8. Fildes JE, Shaw SM, Mitsidou A, et al. HMG-CoA reductase inhibitors deplete circulating classical and non-classical monocytes following human heart transplantation. Transpl Immunol. 2008;19(2):152e157. 9. Rogacev KS, Seiler S, Adam M, et al. CD14þþCD161þ monocytes and cardiovascular outcome in patients with chronic kidney disease. Europ Heart J. 2011;32:84e92. 10. Dayyani F, Belge KU, Frankenberger M, Mack M, Berki T, Ziegler-Heitbrock L. Mechanism of glucocorticoid-induced depletion of human CD14þCD16þ monocytes. J Leukoc Biol. 2003;74:33e39. 11. Scherberich JE, Estner H, Segerer W. Impact of different immunosuppressive regimens on antigen-presenting blood cells in kidney transplant patients. Kidney Blood Press Res. 2004;27:177e180.
C
ARDIO-CEREBROVASCULAR diseases are the key factors that cause the death of patients. Kidney transplantations (KT). Hypertriglyceridemia (HTG), a commonly complication among recipients, is a major risk factor leading to cardio-cerebrovascular diseases.1 As an important pathogenic mechanism of HTG, inflammatory reactions play important roles in thrombopoiesis and in the development of cardio-cerebrovascular diseases such as atherosclerosis.2 Mononuclear cells have a single round nucleus. They include lymphocytes, monocytes, and dendritic cells. These elements are divided into different subpopulations based on their functions and phenotypes of lipopolysaccharides receptor, CD14, Fcg receptor, and CD16. The two major monocyte subpopulations are CD14þþ CD16 and CD14þþ CD16þ cells. CD14þCD16þþ monocytes show greater expression of proinflammatory cytokines and greater efficiency in antigen presentation.3,4 Patients experiencing chronic renal insufficiency and hemodialysis show a high expression of CD14þCD16þþ monocytes putatively associated with atherosclerosis.5 The restoration of renal functional and the prescription of immunosuppressants after KT
may alter the distribution of monocyte subpopulations. The specific aim of the present study was to analyze possible correlations between of CD14þCD16þþ monocytes and HTG after allogenic renal transplantation, seeking to decipher underlying molecular mechanisms and roles of these cells in allo-immunity. MATERIALS AND METHODS Subjects The participants involved in this study were 60 level KT patients and 55 normal controls. The sixty 60 KT patients were divided into
From the Department of Urology, Third Affiliated Hospital, Suzhou University, Changzhou, China, and Lund Universities, Lund, Sweden. Supported by a grant (ZD201209) for the Key Projects awarded by the Department of Health, Changzhou City, Jiangsu Province. Address reprint requests to Xiaozhou He, Department of Urology, Third Affiliated Hospital, Suzhou University, Changzhou 213003, China. E-mail: [email protected]
ª 2013 by Elsevier Inc. All rights reserved. 360 Park Avenue South, New York, NY 10010-1710
0041-1345/13/$esee front matter http://dx.doi.org/10.1016/j.transproceed.2013.08.022
Transplantation Proceedings, 45, 3279e3283 (2013)
3279
3280
XUE, HE, ZHOU ET AL Table 1. Comparisons of Data About the General Biochemical Indicators Among Different Groups of Participants (x ± s)
Age (y) Gender (males, %) KT time (m) Concentration of Tacrolimus (ng/mL) Urea (mmol/L) Creatinine (umol/L) GFR (mL/min) Hemoglobin (g/L) TC (mg/L) TG (mg/L) HDL-C (mg/L) LDL-C (mg/L) Total proteins (g/L) Albumin (g/L)
Group With HTG After KT (n ¼ 35)
Group with Non-HTG After KT (n ¼ 25)
Group With HTG in Healthy Controls (n ¼ 25)
Group With Non-HTG in Healthy Controls (n ¼ 30)
P
45.3 15.6 53.3 43.6 30.1 7.7 1.8 7.64 2.18 124.6 34.6 48.5 12.65 145.8 19.43 4.94 1.57 3.01 4.06 1.42 0.53 2.89 0.78 59.88 8.76 32.75 5.72
42.1 12.5 60 48.2 35.7 7.6 2.0 7.79 2.37 113.1 30.3 49.8 11.62 141.2 16.76 3.22 1.43 1.61 0.35 1.24 0.36 2.24 0.81 60.63 8.94 31.24 5.83
38.6 8.2 46.7 5.64 1.75 88.2 17.3 146.4 19.52 153.2 15.1 4.52 1.85 2.89 2.88 1.45 0.35 2.73 0.81 66.73 11.42 38.6 5.73
35.6 7.9 53.3 5.73 1.26* 85.3 15.7* 140.2 18.49* 150.4 14.09* 3.76 1.06 1.59 0.36* 1.29 0.24 2.31 0.72 65.05 10.32 35.78 6.62
.42 .49 .31 .47 .46 .02 .03 .04 .41 .01 .35 .28 .17 .33
two groups: those with (n ¼ 35) versus without HTG (n ¼ 25). The after KT HTG group included 19 men and 16 women of overall mean age of 45.3 þ 15.6 years (range, 29e61) with follow-up of 43.6 þ 30.1 months. The group free of HTG included 15 men and 9 women of overall mean age of 42.1 þ 12.5 years (range, from 29e55 y) with follow-up of 48.2 þ 35.7 months. There were no significant differences in age and gender between the two groups. Fifty five normal healthy control participants were divided into the two subgroups: with (n ¼ 25) versus without HTG (n ¼ 30). The HTG healthy controls included 12 men and 13 women of overall mean age of 38.6 þ 8.2 years (range, 30e47 y). The healthy group free of HTG included 16 men and 14 women of overall mean age of 35.6 þ 7.9 years (range, 27e44). There were no significant differences in age and gender between transplanted or healthy subgroups. The protocols of this study were approved by our Institutional Ethics Committee; all participants provided informed consent. All the KT patients were presented oral tacrolimus (Prograf, Astellas Pharma, US), cellcept (Shanghai Roche Pharmaceuticals Ltd, China), and prednisone. Their kidney functions were normal. The exclusions for entry included: a prior acute rejection episode, presence of an acute inflammatory reaction (C-reactive protein >6 mg/L), abnormal hepatic function (prothrombin time and alanine transaminase), malignant tumor history for heart and lung diseases.
Detection of CD14þCD16þþ Monocytes in Peripheral Blood Flow cytometry was used to detect CD14þCD16þþ monocytes. Fifty microliters fasting venous blood sample containing EDTAK2-anticoagulant was admitted with 5 mL of fluorescent-labeled monoclonal antibodies phycoerythrin-anti-human-CD14 and FITCanti-human-CD16 (BioLegend, San Diego, Calif, United States) were successively added into 50 mL of blood sample, before mixing well and incubating in the dark at room temperature for 30 minutes. Following addition of 1 mL of hemolysin (Q-prep, Beckman Coulter, United States) and reactions were incubated in the dark at 37 C for 10 minutes and then centrifuged at 250g for 5 minutes. The supernate was removed, 1 mL of PBS added, and the cell pellet was resuspended and centrifuged at 250g for 5 minutes. The supernate was discarded; 0.5 mL of PBS was added, mixed, and incubated in the dark at 4 C for 1 hour. The cell sample was loaded on to the flow cytometer (FC500
flow cytometer, Beckman Coulter). CD14þCD16þþ-expressing monocytes were counted among 10,000 monocytes. Results were expressed as the percentage of CD14þCD16þþ monocytes among the counted total cells.
Measurement of Related Biochemical Indicators Fasting venous blood samples collected in the morning were sent for measurement of biochemical indicators: tacrolimus, urea, creatinine, glomerular filtration rate (GFR), and hemoglobin, using ABBOTT LABS Cell Dyn 3700CS Auto hematology analyzer (Abbott Park, Ill, United States) and Shimadzu CL-7300 Biochemistry Analyzer (Japan). Routine blood examination, functional assays for liver and kidney, for total cholesterol (TC), triglycerides (TG), high-density lipoproteins-cholesterol (HDL-C), and low-density lipoprotein-cholesterol (LDL-C) were studied.
Statistical Analysis SPSS13.0 statistical software was used to perform statistical analyses. The data were examined for normality by homogeneity tests; the results were expressed as mean values standard deviations (SD). The comparison of mean values between the two groups was performed with students t test. Tukey method was used to perform single-step multiple comparisons. One-way analysis of variance (ANOVA) examined the equality of multiple means at a given time. Pearson correlation analysis was used to evaluate correlations among variants. Nonparametric tests tested the heterogeneity of the variance. KruskaleWallis one-way ANOVA was used for multiple
Table 2. Cox Proportional Hazards Model Parameters
HR
CI
P
CD14þCD16þþ monocytes Age GFR TC TG HDL-C LDL-C
1.32 1.63 1.26 0.98 0.97 1.72 1.83
1.14e1.63 0.85e2.41 1.02e1.44 0.92e1.03 0.91e0.98 0.95e1.05 0.92e2.17
.012 .125 .023 .156 <.01 .148 .163
Abbreviations: HR, hazard ratio; CI, confidence interval. Note: Indicated are (HR), their 95% CI, and level of significance.
CD14+CD16++ MONOCYTES
3281 Table 3. Changes in Expression of CD14DCD16DD Monocytes
CD14þCD16þþ CD14þþCD16þ CD14þþCD16 -
Group With HTG After KT (n ¼ 35)
Group Without HTG After KT (n ¼ 25)
Group With HTG in Controls (n ¼ 25)
Group Without HTG in Controls (n ¼ 30)
1.72 0.75 6.54 5.93 91.32 6.86
1.86 0.81 6.78 6.87 90.62 7.48
2.97 1.62* 6.45 4.89 91.21 5.78
2.84 1.81* 6.31 5.69 89.69 6.91
*Significantly higher (P < .01).
group comparisons. The Mann-Whitney U test was used for multiple comparisons. Differences with a P < .05 value were considered to be statistically significant.
RESULTS Comparisons of General Biochemical Indicators of the Participants
Table 1 shows data about biochemical indicators: tacrolimus, urea, creatinine, hemoglobin, TC, TG, HDL-C, and LDL-C in the blood samples from all groups. Urea and creatinine concentrations in both patient groups were significantly higher and hemoglobin results lower in than those among the healthy cohort (P < .05). The TC context in HTG-positive KT cases (4.94 þ 1.57 mg/L) was significantly higher than (P < .05) the mean HTG value in healthy controls (4.52 þ 1.85 mg/L), recipients free of
HTG (3.22 þ 1.43 or healthy subjects versus 3.76 þ 1.06 mg/L, respectively). The TG levels among HTG transplanted subjects and HTG healthy controls were significantly higher than those among non-HTG cohort (P < .01). Although there was a significant difference in GFR between patient and healthy control groups (P < .05), there were no significant differences in HDL-C, LDL-C, and TC (Table 2).
Expression of CD14þCD16þþ Monocytes
Values of CD14þCD16þþ monocytes among these cohort are shown in Table 3, and Figure 1. Expression of CD14þCD16þþ on monocytes among the KT groups (1.72 0.75 and 1.86 0.81%) were lower than those of healthy participants (2.97 1.62 and 2.84 1.81%, respectively), differences that were significant (P < .01)
Fig 1. Distribution of CD14þCD16þþ monocytes. Flow cytometry analysis for expression of CD14þCD16þþ monocytes. (A) Group with HTG after KT; (B) Group without HTG after KT; (C) Group with HTG in control; (D) Group without HTG in control.
3282
XUE, HE, ZHOU ET AL
Table 4. Correlations of Expression of CD14DCD16DD Monocytes With TG Group of Patients After KT
TG
Group of Healthy Participants
R
P
R
P
0.449
.008
0.124
.514
The Multivariate Analysis of CD14þCD16þþ Monocytes Expression and TG Levels
The positive correlation on multivariate analysis is shown in Table 4 and Figure 2. (P < .05).
DISCUSSION
Cardio-cerebrovascular complications affect long-term survival of kidney transplanted recipients. HTG is an important cause leading to the death of these patients. HTG, one of the common complications among KT patients, can produce deposits in the venous tunica intima, leading to vascular sclerosis as well as increased blood viscosity that aggravates arteriosclerosis and thrombopoiesis. Some data have suggested that tacrolimus produces significantly less effect on blood lipids of transplanted patients of compared with cyclosporine (CsA). In selected cases high TC levels of patients on oral CsA have been reversed by switching to oral tacrolimus; however, the high blood TG levels were not reduced by this maneuver. Deleuze et al compared 76 KT cases on tacrolimus with 126 on CsA, observing that the TC and LDL-C blood levels of the former cohort were significantly lower: 1.64 1.37 mmol/L vs 5.28 1.32 mmol/L (P < .05), and 3.26 1.03 mmol/L vs 3.98 1.05 mmol/L (P < .05), respectively. The incidence of the newly-onset hypercholesterolemia and hyperlow-density lipoprotein-cholesterolemias were both significantly lower in the tacrolimus than the CsA group: 8% vs 28% and 31% vs 65% (P < .001), respectively. However, neither the differences in TG and HDL-C between groups nor the rates of HTG were significantly different.6 Monocyte infiltration is a characteristic of the damage caused by HTG. CD14þCD16þþ monocytes, a subpopulation that has strong capability to secrete proinflammatory
Fig 2. The correlation between expression of CD14þCD16þþ monocytes and TG and interleukin IL-6.
cytokines and for antigen presentation, activities that relate to the pathogenic features of HTG, can cause cardiocerebrovascular disease.7 In this study, we investigated the changes in expression of CD14þCD16þþ monocytes in patients who were followed up after KT and revealed a positive correlation between proinflammatory cytokines produced in CD14þCD16þþ monocytes in patients after KT and HTG. This study has provided new methods for clinical diagnosis and treatment for HTG. We detected expression of CD14þCD16þþ on monocytes of patients after KT for comparison with healthy participants. There was a significant difference (P < .05) in CD14þCD16þþ monocytes. The expression of the patient group was lower than the healthy participants. It positively correlated with TG levels. It has been reported previously that reduced numbers of monocytes in heart transplant recipients relate to the immunosuppression.8 Our study demonstrated that expression of CD14þCD16þþ monocytes is also reduced in KT patients. However, subjects with chronic renal insufficiency show significantly increased expression of CD14þCD16þþ monocytes that has been associated with cardio-cerebrovascular diseases, as an independent risk factor.9 The differences in expression of CD14þCD16þþ monocytes before versus after KT may be due to the restoration of kidney functions and the use of immunosuppressants, which may change the distribution of these subpopulations. In vitro and in vivo experiments have shown that glucocorticoids stimulate aspartic deaminasedependent apoptosis, reducing the expression of CD16þ on monocytes.10 In our study, tacrolimus was used as the major immunosuppressant, presumably mediating the lower number of CD14þCD16þþ monocytes, consistent with observations by other investigators.11 Changes in expression of CD14þCD16þþ monocytes after KT seen to be correlated with blood lipids, which play important roles in development and progression of atherosclerosis. CD16þ monocytes in individuals with normal kidney functions are closely related to coronary artery heart diseases.7 The regulatory mechanisms underlying the relationships between CD14þCD16þþ monocytes and micro-inflammation, secretion of proinflammatory cytokines, and the resultant HTG after KT merit further investigation.
CD14+CD16++ MONOCYTES
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