Cluster differentiation (CD) 163, a scavenger receptor for the haptoglobin-hemoglobin (Hb-Hp) complex specifically expressed on monocyte/macrophage lineages, has been extensively studied in hemoglobin-iron metabolism [
Recently, CD163 was also recognized to play a crucial role in various inflammatory diseases [
On the other hand, CD163 expression on the surface of monocytes, a precursor of macrophages, has not been fully investigated, even though monocytes (as well as macrophages) have been recognized as a key player in chronic inflammation. Under steady-state conditions, the expression of CD163 on monocytes is 10- to 15-fold less than that of macrophages [
In the present study, we investigated whether cell surface CD163 expression levels on peripheral blood monocytes (PBMs) as well as the level of sCD163 (in blood circulation) are associated with insulin resistance using homeostasis model assessment (HOMA-R) in a cross-sectional study involving 166 patients with type 2 diabetes.
One hundred sixty-six patients (96 males and 70 females) with type 2 diabetes who were admitted to the Diabetes Center of the Osaka City University Hospital from 2012 to 2014 were recruited for this study. The diagnosis of diabetes was based on a previous history of diabetes or on criteria from the American Diabetes Association [
Ten patients were treated with sulfonylureas monotherapy, 8 with dipeptidyl peptidase-4 (DPP-4) inhibitor monotherapy, 15 with biguanide (metformin) monotherapy, 2 with mitiglinide monotherapy, none with thiazolidine (pioglitazone) monotherapy, 61 were treated with a combination of these oral antidiabetic drugs, and 16 with diet therapy alone. Thirty-one patients were treated with insulin injections and 29 with a combination of oral antidiabetic drugs and insulin injections; 40.3% of subjects were treated with angiotensin II receptor blocker (ARB) and 47.6% of subjects were treated with statins.
Peripheral serum samples were collected after 8 h overnight fasting. Then, serum sCD163 was determined by enzyme-linked immune sorbent assay (ELISA) (Quantikine® ELISA human CD163 immunoassay, R&D Systems, Inc., Minneapolis, MN, USA) as previously reported [
For the assessment of cell surface CD163 levels on peripheral blood monocytes (monocyte CD163), 1 mL of peripheral whole blood was collected from each patient. Then, erythrocytes were lysed with lysing solution (lysing buffer, BD pharm Lyse™, BD Biosciences, San Diego, CA, USA) for 10 min; peripheral leukocytes were used in the assay. A fluorescent-conjugated monoclonal antibody against CD163 (phycoerythrin (PE) anti-human CD163 antibody, clone GHI/61, BioLegend Inc., San Diego, CA, USA) was used for labeling monocyte CD163. One hundred thousand-labeled leukocytes for each subject were measured by flow cytometry (BD FACSCanto™ flow cytometer, Becton Dickinson Biosciences, San Jose, CA, USA). Monocytes were first gated in a forward scatter and sideward scatter dot plot, and then the levels of CD163 mean florescent intensity (MFI) were measured within the monocyte gate.
Blood was drawn after an overnight fast; biochemical parameters were analyzed using standard laboratory methods as previously described [
HOMA-R was calculated from the fasting plasma glucose (FPG) and fasting plasma insulin (FIRI) levels according to the following formula previously reported by Matthews et al. [
The HOMA-R index is a well-established insulin resistance index that is highly correlated with the insulin resistance index assessed by euglycemic hyperinsulinemic clamp, a gold standard technique for the evaluation of insulin resistance in type 2 diabetes [
All values are the means ± SD or median (interquartile) as appropriate. Statistical analysis was performed using the JMP 10 (SAS Institute Inc., Cary, NC, USA). To analyze the relationships between monocyte CD163, sCD163, HOMA-R, and various clinical parameters, simple linear regression analyses or multiple regression analyses were performed as appropriate. Log transformations were performed to achieve a normal distribution and were utilized for regression analyses.
The clinical characteristics of all subjects are shown in Table
Clinical characteristics of 166 patients with type 2 diabetes.
|
166 (96/70) |
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Age (years) | 61.0 ± 13.0 |
Duration (years) | 13.6 ± 11.4 |
BMI (kg/m2) | 25.7 ± 5.48 |
SBP (mmHg) | 128 ± 17.4 |
DBP (mmHg) | 73.8 ± 9.3 |
HbA1c (%) | 8.31 ± 1.66 |
HOMA-R | 2.12 (1.22–3.05) |
TC (mg/dL) | 174 ± 51.2 |
TG (mg/dL) | 110 (81–136) |
LDL-C (mg/dL) | 104 ± 36.6 |
HDL-C (mg/dL) | 41.9 ± 11.9 |
FFA (mEq/L) | 0.52 ± 0.23 |
Cre (mg/dL) | 0.80 ± 0.23 |
ARB (yes/no) | 67/99 |
Statin (yes/no) | 79/87 |
hsTNF |
1.57 (1.16–1.92) |
hsCRP (ng/mL) | 604.3 (291.1–1681.5) |
Soluble CD163 (ng/mL) | 582.9 (472.4–720.0) |
Monocyte CD163 (MFI) | 6061 (4486–7876) |
Data are expressed as
The median serum sCD163 level was 582.9 ng/mL (interquartile ranged from 472.4 to 720.0 ng/mL), and the median monocyte CD163 levels were 6061 MFI (interquartile ranged from 4486 to 7876 MFI), as shown in Figures
Level (ng/mL) of serum soluble CD163 (sCD163) (a) as measured by ELISA and (b) determination of monocyte surface CD163 level by flow cytometer (MFI, mean florescent intensity) in 166 patients with type 2 diabetes. The box denotes the median as well as the 10, 25, 75, and 90 percentiles.
The association between possible clinical factors and insulin resistance was analyzed by simple regression analyses as shown in Table
Correlation between insulin resistance by log-transformed HOMA-R values and possible clinical factors in 166 patients with type 2 diabetes by single regression analyses.
Log [HOMA-R] | ||
---|---|---|
|
|
|
Age | −0.172 | 0.076 |
Duration | −0.146 | 0.139 |
BMI | 0.392 | <0.001 |
SBP | 0.085 | 0.396 |
DBP | 0.144 | 0.148 |
HbA1c | 0.037 | 0.700 |
Log [TG] | 0.195 | 0.043 |
LDL-C | 0.114 | 0.241 |
HDL-C | −0.255 | 0.008 |
Log [FFA] | 0.086 | 0.374 |
Cre | −0.002 | 0.981 |
Log [hsTNF |
0.200 | 0.038 |
Log [hsCRP] | 0.306 | 0.001 |
Soluble CD163 | 0.198 | 0.042 |
Monocyte CD163 | −0.257 | 0.010 |
The association of soluble CD163 (sCD163) (a) and monocyte surface CD163 (b) using log-transformed HOMA-R as an insulin resistance index in 166 patients with type 2 diabetes. In a simple regression analysis, both the serum sCD163 and monocyte CD163 levels were significantly correlated with log-transformed HOMA-R (
To explore the independent contribution of sCD163, monocyte CD163, and possible clinical factors to insulin resistance, multiple regression analyses were performed. Log [HOMA-R] was set as the dependent variable, and sCD163, monocyte CD163, and possible clinical factors such as age, sex, BMI, log [TG], HDL-C, Cre, log [hsTNF
Multiple regression analysis of sCD163, monocyte CD163, and possible clinical factors in insulin resistance by log-transformed HOMA-R values in 166 patients with type 2 diabetes.
Model 1 | Model 2 | Model 3 | ||||
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|
|
|
|
|
|
|
Age | 0.035 | 0.775 | 0.061 | 0.610 | 0.026 | 0.831 |
Sex (male = 1, female = 0) | 0.074 | 0.505 | 0.071 | 0.525 | 0.065 | 0.558 |
BMI | 0.308 | 0.011 | 0.304 | 0.012 | 0.277 | 0.023 |
HbA1c | 0.063 | 0.514 | 0.084 | 0.381 | 0.064 | 0.506 |
Log [TG] | 0.021 | 0.838 | 0.025 | 0.807 | 0.035 | 0.736 |
HDL-C | −0.157 | 0.120 | −0.167 | 0.106 | −0.174 | 0.090 |
Cre | 0.043 | 0.704 | 0.026 | 0.821 | 0.024 | 0.835 |
Log [hsTNF |
0.011 | 0.916 | 0.024 | 0.825 | 0.007 | 0.946 |
Log [hsCRP] | 0.174 | 0.137 | 0.130 | 0.205 | 0.113 | 0.271 |
Soluble CD163 | 0.135 | 0.143 | — | — | 0.137 | 0.153 |
Monocyte CD163 | — | — | −0.212 | 0.025 | −0.220 | 0.020 |
|
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|
0.236 (0.003) | 0.264 (0.001) | 0.281 (0.001) |
The present study demonstrated the inverse association of monocyte CD163 level in patients with type 2 diabetes having insulin resistance, even after adjusting for various clinical factors related to insulin resistance, as evaluated by HOMA-R in multivariate analysis as well as by univariate analysis. On the other hand, the serum sCD163 level was not significantly associated with insulin resistance in multivariate analysis after adjustment, despite a significant positive association with it in univariate analysis. Our findings provide the first demonstration of the stronger contribution of monocyte CD163 levels in the peripheral blood compared to the serum sCD163 level for insulin resistance in patients with type 2 diabetes, suggesting the possibility of its use as a novel clinical surrogate marker for insulin resistance and providing new insight into the role of CD163 in insulin resistance and inflammation.
Several previous studies have reported serum sCD163 levels in obesity and atherosclerotic disease and its association with insulin resistance [
Regarding insulin resistance, the level of sCD163 was also reported to be associated with insulin resistance by HOMA-R in subjects with obesity and glucose intolerance [
In our study, we focused on monocyte cell surface CD163 rather than sCD163, hypothesizing that monocyte surface CD163 might have a stronger anti-inflammatory effect. Currently, macrophages are categorized into two subsets, inflammatory macrophages (M1) with low CD163 expression and anti-inflammatory macrophages (M2) with high CD163 expression, which produce anti-inflammatory cytokines such as Interleukin-10 (IL-10) [
As a result, monocyte surface CD163 was found to have a close inverse relationship with insulin resistance by HOMA-R, even after adjusting for other possible clinical factors related to insulin resistance, whereas sCD163 levels showed no association (Table
The mechanisms underlying the role of monocyte CD163 in insulin resistance were not determined from our clinical study. However, other studies provide some clues. One possibility is that oxidative stress induced by hyperglycemia and various factors in diabetes and/or insulin resistance may cause shedding of surface monocyte CD163 by TACE/ADAM17 activation, resulting in an increase of CD163low monocytes and, subsequently, an increase in preM1 and M1-like monocytes [
Another possibility is improved insulin resistance resulting from IL-10. The M2 macrophage, which is thought to differentiate from CD163high-expressed monocyte, produces IL-10 in local adipose tissue and skeletal muscles [
There are a few limitations in our study. First, our study is of cross-sectional design and is therefore not able to draw conclusive causal relationship between monocyte CD163 and insulin resistance. Second, insulin resistance was evaluated by the simple surrogate index of HOMA-R, which is not a direct quantitative index of insulin-mediated glucose uptake in skeletal muscles and/or adipose tissue. However, HOMA-R has been established as an excellent surrogate marker for insulin resistance and has been used by many investigators as a surrogate marker for insulin resistance in patients with both obesity and type 2 diabetes with various conditions [
In conclusion, the present study demonstrated the closer association between surface monocyte CD163-expressing monocytes from the peripheral blood, rather than serum sCD163 levels, and insulin resistance, independent of known clinical factors in patients with type 2 diabetes. These findings suggest not only the possible use of monocyte CD163 as a novel surrogate marker for insulin resistance in diabetes and/or obesity but also provide insight into the pathophysiological role of monocyte CD163 in the development of insulin resistance states. In order to clinically clarify the causal relationship between monocyte CD163 and insulin resistance, interventional trials for insulin resistance will be needed, in which monocyte CD163 will be evaluated with some cytokines (e.g., IL-6, IL-10, and/or TNF
The authors declare no conflicts of interest.
Reina Kawarabayashi performed all steps of this work. Koka Motoyama wrote the protocol, analyzed the data, and wrote the draft. Masanori Emoto managed all steps of the study and wrote and edited the draft. Miyuki Nakamura and Yuko Yamazaki contributed to the data collection and assays. Tomoaki Morioka, Katsuhito Mori, Shinya Fukumoto, Yasuo Imanishi, Atsushi Shioi, and Tetsuo Shoji recruited the subjects. Tomoaki Morioka, Katsuhito Mori, Tetsuo Shoji, Yasuo Imanishi, and Masaaki Inaba contributed to the discussion and critically reviewed/revised the manuscript. Koka Motoyama and Masanori Emoto are guarantors of this work, had full access to all data, and take responsibility for the integrity of the data and accuracy of the data analysis. All authors read and approved the final manuscript.
The authors acknowledge the excellent technical assistance of Mrs. Masayo Monden from the research laboratory in the Department of Metabolism, Endocrinology, and Molecular Medicine, Osaka City University Graduate School of Medicine. This study was supported by a Grant-in-Aid for Scientific Research (C) (no. 15K08925) from the Japan Society for the Promotion of Science (to Koka Motoyama).