# Peripheral Mononuclear Cell Resistin mRNA Expression Is Increased in Type 2 Diabetic Women

Authors: Panayoula C. Tsiotra; Constantine Tsigos; Eleni Anastasiou; Eleni Yfanti; Eleni Boutati; Emmanouil Souvatzoglou; Ioannis Kyrou; Sotirios A. Raptis
Journal: Mediators of Inflammation
 (2008)

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## Abstract

Resistin has been shown to cause insulin resistance and to impair glucose tolerance in rodents, but in humans its physiological role still remains elusive. The aim of this study was to examine whether resistin mRNA expression in human peripheral mononuclear cells (PBMCs) and its corresponding plasma levels are altered in type 2 diabetes. Resistin mRNA levels were easily detectable in human PBMC, and found to be higher in DM2 compared to healthy women(P=.05). Similarly, mononuclear mRNA levels of the proinflammatory cytokines IL-1β, TNF-α, and IL-6 were all significantly higher in DM2 compared to control women (P<.001). The corresponding plasma resistin levels were slightly, but not significantly, increased in DM2 women (P=.051), and overall, they correlated significantly with BMI (r=0.406, P=.010) and waist circumference (r=0.516, P=.003), but not with fasting insulin levels or HOMA-IR. Resistin mRNA expression is increased in PBMC from DM2 women, together with increased expression of the inflammatory cytokines IL-1β, TNF-α, and IL-6, independent of obesity. These results suggest that resistin and cytokines might contribute to the low-grade inflammation and the increased atherogenic risk observed in these patients.


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## Body

## 1. Introduction

Resistin  and other  molecules  commonly called adipokines, such as TNF-α, IL-6, and visfatin,
are produced and secreted by both adipocytes and macrophages, and have been
suggested to be important players in the pathogenesis of insulin resistance and
atherosclerosis [1, 2]. Increased production of these adipokines occurs with expanding
obesity, particularly visceral obesity, by both the adipocytes and the nonfat
cells, mostly macrophages that infiltrate the adipose tissue [3, 4]. Indeed,
the common origin of macrophages and adipocytes has been well documented as
well as their overlapping biology and function (accumulation of lipids,
expression and secretion of similar cytokines, such as TNF-α, IL-6, resistin,
visfatin, and expression of genes involved in lipid metabolism) [4, 5]. Furthermore,
recruitment and accumulation of macrophages in the adipose tissue are characteristics of
obesity [6]. Interestingly, in humans, the expression of resistin and visfatin
is predominantly detected in the macrophages populating the adipose tissue [7].
Several studies have also demonstrated increased expression and release of the proinflammatory cytokines, TNF-α, IL-1β, and IL-6, from the
adipocytes or the macrophages infiltrating the adipose tissue [3, 7].Notably, resistin belongs to  a family of molecules called found in
inflammatory zone (FIZZ), since a member of this family was found to be
expressed in bronchial epithelial cells during allergic pulmonary  inflammation in
mice [8]. In human mononuclear
cells, where resistin is highly expressed, its expression is markedly
upregulated by lipopolysaccharide (LPS) and the proinflammatory cytokines
(Il-6, TNF-α, and IL-1), acting via the NF-κB-dependent pathway [9]. Furthermore, intravenous administration of endotoxin in humans
markedly increased circulating resistin levels [9, 10]. In agreement with these
experimental data, patients with severe inflammatory disease have significantly
higher serum resistin concentrations, while patients with rheumatoid arthritis
(RA) show increased resistin levels in their inflamed joints that correlate
with markers of inflammation [11].
Furthermore, PPARγ agonists and HMG-CoA reductase inhibitors (statins), both recognized for
their anti-inflammatory properties, decrease macrophage resistin mRNA and
protein secretion, apparently via the NF-κB pathway [12, 13].Consistent with the proinflammatory nature of resistin, human resistin powerfully
stimulates TNF-α, IL-1β, IL-6, and IL-12 expression in human PBMC and murine
macrophages, an effect that can be abrogated by an NF-κB inhibitor, indicating
the importance of this signalling pathway in the resistin-mediated inflammation
[14]. Resistin was also shown to increase lipid accumulation in human
macrophages [15]. Resistin also acts on endothelial cells and promotes their activation,
by inducing the expression and release of monocyte chemoattractant protein
(MCP)-1, endothelin-1 (ET-1), and adhesion molecules, such as vascular cell
adhesion molecule -1 (VCAM-1) and intracellular adhesion molecule-1 (ICAM-1),
while at the same time adiponectin abrogates this effect [16]. Moreover,
resistin is secreted by the macrophages localizing to the atheromas, thereby
promoting atherosclerosis in humans [17]. Indeed, patients with coronary
artery disease (CAD) have higher serum resistin levels that correlate with
markers of inflammation, and are predictive of coronary atherosclerosis in
humans [18, 19]. High serum resistin levels have also been proposed as
predictors of early atherosclerosis in obese children [20].While resistin’s role as an inflammatory
marker in human’s and rodent’s physiology has been well documented, its role in
obesity and insulin resistance in humans is still under debate. It is important
that human resistin is expressed in much
higher levels in macrophages than in adipocytes [21], quite the opposite from
the case of mice, in which resistin clearly impairs insulin sensitivity [22, 23].
Several human studies have failed to confirm any relationship
of circulating resistin levels with BMI, insulin sensitivity, or other
metabolic parameters [24–26]. However,
there have been reports of increased serum resistin levels in individuals with
obesity and/or type 2 diabetes [27–29].In the present study,
we examined whether resistin TNF-α, IL-6, and IL-1β mRNA levels from human peripheral mononuclear
cells are altered in type 2 diabetes and whether they correlate with
circulating resistin levels and with indices of obesity or insulin resistance.


## 2. Subjects and Methods

### 2.1. Subjects

The
study was approved by the “Alexandra”
Hospital Ethical Committee and all subjects gave
informed consent. Forty eight (48) women, all premenopausal, aged between 21
and 49 years, participated in our study. Twenty two had type 2 diabetes (DM2), and
twenty six were healthy controls with normal glucose tolerance (NGT). Both groups
were further divided into two groups: those with BMI< 27 and those with BMI > 27
(Table 1). All women have had a stable weight, and they were on a normal
eucaloric diet and normal physical activity, not participating in any specific
exercise program for the last three months preceding the test. Of the DM2 women,
15 were on diet alone, 4 on oral hypoglycaemic agents, 2 on insulin, and 1 on combined
insulin and oral hypoglycaemic agents. No DM2 or healthy woman  was on thiazolidinedione or statin medication. All control subjects had no history of endocrine abnormality and
were on no medications.Table 1
Patients' characteristics, their fasting
glucose, fasting insulin, triglycerides, HDL and FFA levels, the HOMA-IR and
Matsuda indices.
nBMI
(Kg/m2)Waist
(cm)Fasting glucose (mg/dL)Fasting insulin (μU/mL)HOMA-IRMatsudaTriglycerides (mg/dL)HDL (mg/dL)FFA (mmol/L)NGTBMI< 271422.5±0.776.5±2.387.5±3.66.4±0.61.4±0.19.3±0.963.2±5.046.5±3.40.43±0.05BMI> 271232.9±1.5*95.7±3.0*98.3±2.1*12.7±2.1*3.0±0.5*5.0±1.3*100.2±18.944.0±3.30.47±0.05DM2BMI< 27823.7±0.7§78.2±3.4§156.9±32.9*§8.3±1.94.2±2.16.3±1.480.3±17.439.0±2.90.55±0.10BMI> 271436.4±1.4*108.1±3.0*§136.7±13.0*§16.6±2.6*5.6±1.0*2.4±0.3*§150.8±26.5*27.4±1.5*§0.59±0.04*Mean ± SEM:P*<.03 versus NGT-BMI < 27; P§<.05 versus
NGT-BMI > 27.Body mass index (BMI) was calculated as the
ratio of body weight (Kg) per height (m2). Insulin resistance was
calculated by the homeostasis model assessment index (HOMA-IR) as [fasting
insulin (μU/mL) × fasting glucose (mmol/L)]/22.5. Insulin sensitivity was
calculated by the  Matsuda index as (10 000/sqare root of [fasting glucose ×
fasting insulin] × [mean glucose during OGTT × mean insulin during OGTT]). Fasting glucose, triglycerides,
and free fatty acid (FFA) levels were analyzed on a Falcor 300 Chemical
Analyser (Menarini
Diagnostics, Italy) and fasting plasma insulin
levels were measured by IRMA (INSI-CTK, DiaSorin, Italy),
in all individuals.


### 2.2. RNA Preparation

Peripheral  blood was collected from all
women after an overnight fast and the mononuclear cells were separated using a
Histopaque-1077 gradient (Sigma-Aldrich,
USA). At the same time,
plasma was kept at−80C° for subsequent measurement of adipokines.The mononuclear cells were then left to
adhere for 1 hour for the selective isolation of the primary monocyte-derived
macrophages, and total RNA was extracted from cells as previously described
[30]. Briefly, after the RNA isolation, cDNA synthesis was performed  in all
samples using oligo random primers (NEB, Mass, USA) and MMLV reverse
transcriptase (Promega Corp., Wis, USA) [30]. We developed
a quantitative real-time PCR using fluorescently labeled hybridization probes
to detect resistin and proinflammatory (IL-1β, TNF-α, and IL-6) mRNA expression
in human mononuclear cells, in a spectrofluorometric  thermal cycler
(LightCycler, ROCHE, Mannheim, Germany).


### 2.3. Primer Design

Hybridization-specific  primers and
hybridization-specific probes for all genes were designed and manufactured by the (TIB MOLBIOL Berlin, Germany). Hybridization
primers and probes for all target and reference genes were showen in Table2.Table 25′-sense primer-3′5′-a-sense primer-3′ResistinGGGCTGTTGGTGTCTAGCAAGGTCTCGGCGCGCACATIL-1βCAGGGACAGGATATGGAGCAAGCAGACTCAAATTCCAGCTTGTTATNF-αACAAGCCTGTAGCCATGTTAAAGTAGACCTGCCCAGACTIL-6CCAATCTGGATTCAATGAGGAGACTGAGCCCTCAGGCTGGACTGβ-actinCTTCTACAATGAGCTGCGTGTGGTGAGGATCTTCATGAGGTAGTCAGTCPBGDGGCTGCAACGGCGGAACCTGTGGTGGACATAGCAATGATT5′-FL probe-3′5′-LC Red640/LCRed705 probe-3′ResistinGCGACCTCCTGGATCCTCTCATTGAGCTTCTTCCATGGAGCACAGGGTCIL-1βGCTTATCATCTTTCAACACGCAGGACAGTACAGATTCTTTTCCTTGAGGCCCATNF-αGCATTGGCCCGGCGGTTCCCACTGGAGCTGCCCCTCAGCTIL-6AGATGCAATAACCACCCCTGACCCAACACAAATGCCAGCCTGCTGACGAAβ-actinGGTATGCCCTCCCCCATGCCTCCTGCGTCTGGACCTGGCTGPBGDCATACAGACGGACAGTGTGGTGGCAACTGAAAGCCTCGTACCCTGGCCTGPrimers  were chosen to
lie between exons whenever possible and the analysis was performed basically
with the program OLIGO 6.0 (Molecular
Biology Insights, Cascade, Colo, USA).


### 2.4. Quantitative Real-Time PCR

Relative
quantification is the method that determines the changes in steady-state mRNA
levels of a gene across various samples and expresses them relative to the levels
of an internal reference control gene, usually a housekeeping gene. In order to
quantify resistin, IL-1β, TNF-α, and IL-6 relative mRNA levels, we used the
calibrator—normalized standard curve and the LightCycler Relative
Quantification 1.0.1 Software (Roche, Mannheim, Germany), as previously described [30].
Briefly, using this quantification method, results are expressed as the
target/reference ratio of the sample divided by the target/reference ratio of
the calibrator, and it does not require a standard curve in each run (Roche
Applied Science, Technical Note No. LC 13/2001-Relative Quantification). The
human housekeeping genes of β-actin and porphobilinogen deaminase (PBGD) were
used as standards for normalization. Selection of either β-actin or PBGD as
housekeeping genes was necessary because the copy number of the housekeeping
gene should be in a similar range with that of the target gene to make
comparative quantification possible (Roche Applied Science, Technical Note No.
LC 15/2002-Selection of Housekeeping Genes). Thus, the PBGD house keeping gene
was chosen for the relative quantification of the IL-6 mRNA expression because
of the very low level of IL-6 expression in the calibrator (HL60 induced with
phorbol myristyl acetate (PMA)) mRNA.Standard curves
describing the PCR efficiencies of the target (resistin, IL-1β, TNF-α, or IL-6)
and the reference genes (β-actin or PBGD) were created from a dilution series
of the calibrator cDNA, using the Second derivative maximum method with the arithmetic
baseline adjustment. The second derivative maximum method was used for the
determination of the various crossing points (Cps) of the target and the
reference gene in each sample. Finally, a corresponding coefficient file was
created, which determines the efficiency for the target and the reference gene.
Amplification of each sample was performed in triplicate, in different runs,
and fluorescence resulting from the close proximity of the annealed
hybridization probes was detected at the end of the annealing step of each PCR cycle.The results from
different PCR runs were run randomly in ethidium bromide-stained agarose gels
and photographed in an Image Analyser VDS System (Amersham-Pharmacia Biotech, Sweden).Immunoassays
Circulating levels of resistin (BioVender, Canal zone, USA),
TNF-α (R&D Systems, UK), and IL-6 (R&D Systems,
UK) were measured in the plasma of all women, using standard commercial enzyme-linked
immunosorbent assays according to the manufacturers’-recommended protocols. IL-1β
circulating protein levels were measured in the plasma of all women, using a
high sensitivity multiplex assay (xMAP technology) and the fluorescently
labeled microsphere beads (Linco-Millipore
Corp., USA), in a LUMINEX 200 instrument (Luminex Corp., USA). We could not
detect IL-1β in the majority of our subjects (in 57% of controls and 55% of DM2),
making the analysis of circulating IL-1β problematic.
The sensitivities of the assays were 0.2 ng/mL
(resistin), 0.12 pg/mL (TNF-α), <0.094 pg/mL (IL-6), 0.06 pg/mL (IL-1β), the intra- and the interassay
coefficients of variation were, respectively,
3.6% and 6.7% (resistin), 6.6% and 13.4% (TNF-α), 6.9% and 14.1% (IL-6), 3.11% and 2.16% (IL-1β).
All samples were measured in duplicate.


### 2.5. Statistical Analysis

Statistical analysis
was performed using the SPSS version 14.0.1 software
(Chicago, Ill, USA). Data are
expressed as mean ± SEM ofn-independent
experiments. Nonparametric statistical analyses were applied (Spearman's correlation test and nonparametric
Mann-Whitney test), where appropriate. A P-value
of less than .05 was considered statistically significant.


## 2.1. Subjects

The
study was approved by the “Alexandra”
Hospital Ethical Committee and all subjects gave
informed consent. Forty eight (48) women, all premenopausal, aged between 21
and 49 years, participated in our study. Twenty two had type 2 diabetes (DM2), and
twenty six were healthy controls with normal glucose tolerance (NGT). Both groups
were further divided into two groups: those with BMI< 27 and those with BMI > 27
(Table 1). All women have had a stable weight, and they were on a normal
eucaloric diet and normal physical activity, not participating in any specific
exercise program for the last three months preceding the test. Of the DM2 women,
15 were on diet alone, 4 on oral hypoglycaemic agents, 2 on insulin, and 1 on combined
insulin and oral hypoglycaemic agents. No DM2 or healthy woman  was on thiazolidinedione or statin medication. All control subjects had no history of endocrine abnormality and
were on no medications.Table 1
Patients' characteristics, their fasting
glucose, fasting insulin, triglycerides, HDL and FFA levels, the HOMA-IR and
Matsuda indices.
nBMI
(Kg/m2)Waist
(cm)Fasting glucose (mg/dL)Fasting insulin (μU/mL)HOMA-IRMatsudaTriglycerides (mg/dL)HDL (mg/dL)FFA (mmol/L)NGTBMI< 271422.5±0.776.5±2.387.5±3.66.4±0.61.4±0.19.3±0.963.2±5.046.5±3.40.43±0.05BMI> 271232.9±1.5*95.7±3.0*98.3±2.1*12.7±2.1*3.0±0.5*5.0±1.3*100.2±18.944.0±3.30.47±0.05DM2BMI< 27823.7±0.7§78.2±3.4§156.9±32.9*§8.3±1.94.2±2.16.3±1.480.3±17.439.0±2.90.55±0.10BMI> 271436.4±1.4*108.1±3.0*§136.7±13.0*§16.6±2.6*5.6±1.0*2.4±0.3*§150.8±26.5*27.4±1.5*§0.59±0.04*Mean ± SEM:P*<.03 versus NGT-BMI < 27; P§<.05 versus
NGT-BMI > 27.Body mass index (BMI) was calculated as the
ratio of body weight (Kg) per height (m2). Insulin resistance was
calculated by the homeostasis model assessment index (HOMA-IR) as [fasting
insulin (μU/mL) × fasting glucose (mmol/L)]/22.5. Insulin sensitivity was
calculated by the  Matsuda index as (10 000/sqare root of [fasting glucose ×
fasting insulin] × [mean glucose during OGTT × mean insulin during OGTT]). Fasting glucose, triglycerides,
and free fatty acid (FFA) levels were analyzed on a Falcor 300 Chemical
Analyser (Menarini
Diagnostics, Italy) and fasting plasma insulin
levels were measured by IRMA (INSI-CTK, DiaSorin, Italy),
in all individuals.


## 2.2. RNA Preparation

Peripheral  blood was collected from all
women after an overnight fast and the mononuclear cells were separated using a
Histopaque-1077 gradient (Sigma-Aldrich,
USA). At the same time,
plasma was kept at−80C° for subsequent measurement of adipokines.The mononuclear cells were then left to
adhere for 1 hour for the selective isolation of the primary monocyte-derived
macrophages, and total RNA was extracted from cells as previously described
[30]. Briefly, after the RNA isolation, cDNA synthesis was performed  in all
samples using oligo random primers (NEB, Mass, USA) and MMLV reverse
transcriptase (Promega Corp., Wis, USA) [30]. We developed
a quantitative real-time PCR using fluorescently labeled hybridization probes
to detect resistin and proinflammatory (IL-1β, TNF-α, and IL-6) mRNA expression
in human mononuclear cells, in a spectrofluorometric  thermal cycler
(LightCycler, ROCHE, Mannheim, Germany).


## 2.3. Primer Design

Hybridization-specific  primers and
hybridization-specific probes for all genes were designed and manufactured by the (TIB MOLBIOL Berlin, Germany). Hybridization
primers and probes for all target and reference genes were showen in Table2.Table 25′-sense primer-3′5′-a-sense primer-3′ResistinGGGCTGTTGGTGTCTAGCAAGGTCTCGGCGCGCACATIL-1βCAGGGACAGGATATGGAGCAAGCAGACTCAAATTCCAGCTTGTTATNF-αACAAGCCTGTAGCCATGTTAAAGTAGACCTGCCCAGACTIL-6CCAATCTGGATTCAATGAGGAGACTGAGCCCTCAGGCTGGACTGβ-actinCTTCTACAATGAGCTGCGTGTGGTGAGGATCTTCATGAGGTAGTCAGTCPBGDGGCTGCAACGGCGGAACCTGTGGTGGACATAGCAATGATT5′-FL probe-3′5′-LC Red640/LCRed705 probe-3′ResistinGCGACCTCCTGGATCCTCTCATTGAGCTTCTTCCATGGAGCACAGGGTCIL-1βGCTTATCATCTTTCAACACGCAGGACAGTACAGATTCTTTTCCTTGAGGCCCATNF-αGCATTGGCCCGGCGGTTCCCACTGGAGCTGCCCCTCAGCTIL-6AGATGCAATAACCACCCCTGACCCAACACAAATGCCAGCCTGCTGACGAAβ-actinGGTATGCCCTCCCCCATGCCTCCTGCGTCTGGACCTGGCTGPBGDCATACAGACGGACAGTGTGGTGGCAACTGAAAGCCTCGTACCCTGGCCTGPrimers  were chosen to
lie between exons whenever possible and the analysis was performed basically
with the program OLIGO 6.0 (Molecular
Biology Insights, Cascade, Colo, USA).


## 2.4. Quantitative Real-Time PCR

Relative
quantification is the method that determines the changes in steady-state mRNA
levels of a gene across various samples and expresses them relative to the levels
of an internal reference control gene, usually a housekeeping gene. In order to
quantify resistin, IL-1β, TNF-α, and IL-6 relative mRNA levels, we used the
calibrator—normalized standard curve and the LightCycler Relative
Quantification 1.0.1 Software (Roche, Mannheim, Germany), as previously described [30].
Briefly, using this quantification method, results are expressed as the
target/reference ratio of the sample divided by the target/reference ratio of
the calibrator, and it does not require a standard curve in each run (Roche
Applied Science, Technical Note No. LC 13/2001-Relative Quantification). The
human housekeeping genes of β-actin and porphobilinogen deaminase (PBGD) were
used as standards for normalization. Selection of either β-actin or PBGD as
housekeeping genes was necessary because the copy number of the housekeeping
gene should be in a similar range with that of the target gene to make
comparative quantification possible (Roche Applied Science, Technical Note No.
LC 15/2002-Selection of Housekeeping Genes). Thus, the PBGD house keeping gene
was chosen for the relative quantification of the IL-6 mRNA expression because
of the very low level of IL-6 expression in the calibrator (HL60 induced with
phorbol myristyl acetate (PMA)) mRNA.Standard curves
describing the PCR efficiencies of the target (resistin, IL-1β, TNF-α, or IL-6)
and the reference genes (β-actin or PBGD) were created from a dilution series
of the calibrator cDNA, using the Second derivative maximum method with the arithmetic
baseline adjustment. The second derivative maximum method was used for the
determination of the various crossing points (Cps) of the target and the
reference gene in each sample. Finally, a corresponding coefficient file was
created, which determines the efficiency for the target and the reference gene.
Amplification of each sample was performed in triplicate, in different runs,
and fluorescence resulting from the close proximity of the annealed
hybridization probes was detected at the end of the annealing step of each PCR cycle.The results from
different PCR runs were run randomly in ethidium bromide-stained agarose gels
and photographed in an Image Analyser VDS System (Amersham-Pharmacia Biotech, Sweden).Immunoassays
Circulating levels of resistin (BioVender, Canal zone, USA),
TNF-α (R&D Systems, UK), and IL-6 (R&D Systems,
UK) were measured in the plasma of all women, using standard commercial enzyme-linked
immunosorbent assays according to the manufacturers’-recommended protocols. IL-1β
circulating protein levels were measured in the plasma of all women, using a
high sensitivity multiplex assay (xMAP technology) and the fluorescently
labeled microsphere beads (Linco-Millipore
Corp., USA), in a LUMINEX 200 instrument (Luminex Corp., USA). We could not
detect IL-1β in the majority of our subjects (in 57% of controls and 55% of DM2),
making the analysis of circulating IL-1β problematic.
The sensitivities of the assays were 0.2 ng/mL
(resistin), 0.12 pg/mL (TNF-α), <0.094 pg/mL (IL-6), 0.06 pg/mL (IL-1β), the intra- and the interassay
coefficients of variation were, respectively,
3.6% and 6.7% (resistin), 6.6% and 13.4% (TNF-α), 6.9% and 14.1% (IL-6), 3.11% and 2.16% (IL-1β).
All samples were measured in duplicate.


## 2.5. Statistical Analysis

Statistical analysis
was performed using the SPSS version 14.0.1 software
(Chicago, Ill, USA). Data are
expressed as mean ± SEM ofn-independent
experiments. Nonparametric statistical analyses were applied (Spearman's correlation test and nonparametric
Mann-Whitney test), where appropriate. A P-value
of less than .05 was considered statistically significant.


## 3. Results

### 3.1. Clinical Characteristics of Study Subjects

Table1 shows the clinical characteristics
of the DM2 and healthy NGT women, who were further divided into two subgroups according to their BMI, one with
BMI < 27 and one with BMI > 27. The groups were generally well matched
between them. DM2 women, however, had significantly higher waist circumference,
triglyceride and FFA levels, and lower HDL cholesterol levels compared to the
BMI-matched controls.Resistin, TNF-α, IL-6, IL-1β mRNA expression from
human mononuclear-monocytic cells is elevated in DM2 women.Resistin mRNA
expression was easily detected in human
mononuclear-monocytic cells in both
DM2 and NGT women, and was significantly higher (0.57±0.1 versus 0.52±0.1 arbitrary
units, P=.05) in the former group (Figure 1(a)), while no significant
differences were observed between the two BMI
subgroups (Table 3).Table 3
Relative resistin, TNF-α, IL-6, and IL-1β
mRNA levels from mononuclear cells between
the subgroups of the NGT- and the DM2- women.
Resistin/β-actinTNF-α/β-actinIL-6/PBGDIL-1β/β-actinNGTBMI< 270.50±0.140.03±0.00820.1±16.15.4±1.7BMI> 270.54±0.260.03±0.0123.5±20.723.1±17.6DM2BMI< 270.70±0.250.31±0.16*§242.0±120.5*§79.9±44.0BMI> 270.48±0.070.37±0.16*§405.1±194.9*§169.1±55.1*§Data expressed as mean ± SE:P*<.017 versus NGT-(BMI < 27)-women; P§<.013
versus NGT-(BMI > 27)-women.(a) Bar graphs compare relative
resistin/β-actin mRNA levels,  (b) TNF-α/β-actin mRNA levels,
(c) IL-6/PBGD mRNA levels, and (d) IL-1β/β-actin mRNA levels, from peripheral
mononuclear-enriched monocytes from NGT-control and DM2 women. P*<.05 versus NGT-women.
(a)(b)(c)(d)TNF-α, IL-6 mRNA and IL-1β mRNA levels were significantly higher (~10-, 15-, and 10-fold, resp.) in DM2 women
compared to NGT women [0.34±0.1 versus 0.03±0.01 (P<.001), 342.98±127.9 versus 21.64±12.6 (P<.001),
and 139.36±40.2 versus 13.21±7.8 arbitrary units (P=.001), resp.] (Figures
1(b), 1(c), and 1(d)).Resistin mRNA levels correlated
positively with mononuclear IL-1β, and TNF-α, mRNA levels (r=0.324,P<.05 and
r=0.447,P<.01, resp.). Furthermore, TNF-α
and IL-6 mRNA levels correlated positively between them
(r=0.687,P<.001) and also each one of them with the IL-1β mRNA levels
(r=0.767,P<.001 and r=0.765,P<.001, resp.), the 2-hour OGTT
glucose levels (r=0.462,P=.005 and r=0.486,P=.004, resp.) and
negatively with HDL cholesterol levels (r=−0.367,P<.02 and r=−0.372,P<.02, resp.), while IL-1β mRNA levels correlated positively with BMI
(r=0.374,P=.017), waist circumference (r=0.414,P=.019), fasting glucose levels (r=0.365,P=.022), HOMA-IR (r=0.325,P=.043),
glycosylated hemoglobin (r=0.542,P=.001), FFA levels (r=0.335,P=.043),
and negatively with HDL cholesterol levels (r=−0.395,P=.015).


### 3.2. Circulating Resistin, Tnf-α, Il-6, and Il-1β Protein Levels

Plasma resistin levels tended to be overall
significantly higher in DM2 women compared to NGT control women (P=.051)
(Figure 2), but no significant
differences were observed between the two BMI subgroups. Circulating TNF-α,
IL-6, and IL-1β protein  levels did not
differentiate between the DM2 and the
NGT-control women (Figure 2), although in the subgroup of DM2 with BMI > 27, TNF-α and IL-6 plasma
levels were significantly higher compared to NGT women (Table 4).Table 4
Circulating resistin, TNF-α, IL-6, and IL-1β protein levels between the subgroups of the NGT- and the DM2-women.
Resistin (ng/mL)TNF-α
(pg/mL)IL-6 (pg/mL)IL-1β
(pg/mL)NGTBMI< 272.65±0.192.07±0.190.80±0.141.37±0.39BMI> 272.98±0.232.32±0.201.77±0.36*0.97±0.52DM2BMI< 273.24±0.452.14±0.450.93±0.18§1.19±0.85BMI> 273.36±0.293.24±0.36*1.84±0.28*0.79±0.42Data expressed as mean ± SE:P*<.015 versus NGT-(BMI < 27)-women; P§<.05
versus NGT-(BMI > 27)-women.Figure 2
Comparison of circulating resistin, TNF-α, IL-6, and IL-1β protein levels between the NGT-healthy control and DM2 women.  P*<.051 versus
NGT-women.Circulating resistin correlated positively
with mononuclear resistin, IL-6 and IL-1β mRNA expression (r=0.526,P=.001 and
r=0.354,P=.029 and r=0.425,P=.009, resp.), BMI and waist circumference
(r=0.406,P=.010 and r=0.516,P=.003), but not with HOMA-IR, fasting insulin,
or glucose plasma levels. TNF-α and IL-6 plasma levels also correlated with BMI
and waist circumference (r=0.361,P=.013 and r=0.651,P<.001 and r=0.379,P=.023
and r=0.676,P<.001, resp.) as well as with fasting glucose, insulin and
triglyceride levels, the HOMA-IR, while they correlated negatively with the
Matsuda index and HDL cholesterol levels.


## 3.1. Clinical Characteristics of Study Subjects

Table1 shows the clinical characteristics
of the DM2 and healthy NGT women, who were further divided into two subgroups according to their BMI, one with
BMI < 27 and one with BMI > 27. The groups were generally well matched
between them. DM2 women, however, had significantly higher waist circumference,
triglyceride and FFA levels, and lower HDL cholesterol levels compared to the
BMI-matched controls.Resistin, TNF-α, IL-6, IL-1β mRNA expression from
human mononuclear-monocytic cells is elevated in DM2 women.Resistin mRNA
expression was easily detected in human
mononuclear-monocytic cells in both
DM2 and NGT women, and was significantly higher (0.57±0.1 versus 0.52±0.1 arbitrary
units, P=.05) in the former group (Figure 1(a)), while no significant
differences were observed between the two BMI
subgroups (Table 3).Table 3
Relative resistin, TNF-α, IL-6, and IL-1β
mRNA levels from mononuclear cells between
the subgroups of the NGT- and the DM2- women.
Resistin/β-actinTNF-α/β-actinIL-6/PBGDIL-1β/β-actinNGTBMI< 270.50±0.140.03±0.00820.1±16.15.4±1.7BMI> 270.54±0.260.03±0.0123.5±20.723.1±17.6DM2BMI< 270.70±0.250.31±0.16*§242.0±120.5*§79.9±44.0BMI> 270.48±0.070.37±0.16*§405.1±194.9*§169.1±55.1*§Data expressed as mean ± SE:P*<.017 versus NGT-(BMI < 27)-women; P§<.013
versus NGT-(BMI > 27)-women.(a) Bar graphs compare relative
resistin/β-actin mRNA levels,  (b) TNF-α/β-actin mRNA levels,
(c) IL-6/PBGD mRNA levels, and (d) IL-1β/β-actin mRNA levels, from peripheral
mononuclear-enriched monocytes from NGT-control and DM2 women. P*<.05 versus NGT-women.
(a)(b)(c)(d)TNF-α, IL-6 mRNA and IL-1β mRNA levels were significantly higher (~10-, 15-, and 10-fold, resp.) in DM2 women
compared to NGT women [0.34±0.1 versus 0.03±0.01 (P<.001), 342.98±127.9 versus 21.64±12.6 (P<.001),
and 139.36±40.2 versus 13.21±7.8 arbitrary units (P=.001), resp.] (Figures
1(b), 1(c), and 1(d)).Resistin mRNA levels correlated
positively with mononuclear IL-1β, and TNF-α, mRNA levels (r=0.324,P<.05 and
r=0.447,P<.01, resp.). Furthermore, TNF-α
and IL-6 mRNA levels correlated positively between them
(r=0.687,P<.001) and also each one of them with the IL-1β mRNA levels
(r=0.767,P<.001 and r=0.765,P<.001, resp.), the 2-hour OGTT
glucose levels (r=0.462,P=.005 and r=0.486,P=.004, resp.) and
negatively with HDL cholesterol levels (r=−0.367,P<.02 and r=−0.372,P<.02, resp.), while IL-1β mRNA levels correlated positively with BMI
(r=0.374,P=.017), waist circumference (r=0.414,P=.019), fasting glucose levels (r=0.365,P=.022), HOMA-IR (r=0.325,P=.043),
glycosylated hemoglobin (r=0.542,P=.001), FFA levels (r=0.335,P=.043),
and negatively with HDL cholesterol levels (r=−0.395,P=.015).


## 3.2. Circulating Resistin, Tnf-α, Il-6, and Il-1β Protein Levels

Plasma resistin levels tended to be overall
significantly higher in DM2 women compared to NGT control women (P=.051)
(Figure 2), but no significant
differences were observed between the two BMI subgroups. Circulating TNF-α,
IL-6, and IL-1β protein  levels did not
differentiate between the DM2 and the
NGT-control women (Figure 2), although in the subgroup of DM2 with BMI > 27, TNF-α and IL-6 plasma
levels were significantly higher compared to NGT women (Table 4).Table 4
Circulating resistin, TNF-α, IL-6, and IL-1β protein levels between the subgroups of the NGT- and the DM2-women.
Resistin (ng/mL)TNF-α
(pg/mL)IL-6 (pg/mL)IL-1β
(pg/mL)NGTBMI< 272.65±0.192.07±0.190.80±0.141.37±0.39BMI> 272.98±0.232.32±0.201.77±0.36*0.97±0.52DM2BMI< 273.24±0.452.14±0.450.93±0.18§1.19±0.85BMI> 273.36±0.293.24±0.36*1.84±0.28*0.79±0.42Data expressed as mean ± SE:P*<.015 versus NGT-(BMI < 27)-women; P§<.05
versus NGT-(BMI > 27)-women.Figure 2
Comparison of circulating resistin, TNF-α, IL-6, and IL-1β protein levels between the NGT-healthy control and DM2 women.  P*<.051 versus
NGT-women.Circulating resistin correlated positively
with mononuclear resistin, IL-6 and IL-1β mRNA expression (r=0.526,P=.001 and
r=0.354,P=.029 and r=0.425,P=.009, resp.), BMI and waist circumference
(r=0.406,P=.010 and r=0.516,P=.003), but not with HOMA-IR, fasting insulin,
or glucose plasma levels. TNF-α and IL-6 plasma levels also correlated with BMI
and waist circumference (r=0.361,P=.013 and r=0.651,P<.001 and r=0.379,P=.023
and r=0.676,P<.001, resp.) as well as with fasting glucose, insulin and
triglyceride levels, the HOMA-IR, while they correlated negatively with the
Matsuda index and HDL cholesterol levels.


## 4. Discussion

We have demonstrated that resistin mRNA
expression from human peripheral monocyte-enriched mononuclear cells is
elevated in type 2 diabetic women, compared to healthy control women, in
parallel with significant increases in mononuclear IL-1β, TNF-α, and IL-6 mRNA
expression.Resistin, a 12.5-kDa cysteine-rich
adipokine, which was shown to cause insulin resistance and to impair glucose
tolerance in rodents [1], is also highly
expressed in human mononuclear cells and macrophages [21]. While in rodents,
adipocyte-produced resistin is mainly involved in glucose metabolism and
insulin resistance: in humans, monocyte-produced resistin seems to have potent
proinflammatory properties. Various inflammatory stimuli could result in hyperresistinemia
in humans [9, 10], while human resistin can stimulate the expression of the
inflammatory cytokines TNF-α and IL-6 in both human and murine macrophages, via
an NF-κB-dependent pathway [11, 14]. The proinflammatory nature of resistin was
further documented by the findings that serum resistin concentrations were significantly
elevated in patients with severe inflammatory disease and in patients with previous myocardial infarction, in whom they positively correlated with markers of
inflammation, independent of CRP [11, 18–20].In the present study, we have demonstrated
that resistin mRNA levels from human peripheral monocyte-enriched mononuclear
cells were higher in the DM2 compared to healthy women, which was independent
of BMI. It should be noted that the difference did not reach significance
between the individuals groups, but only when all patients were grouped
together in NGT and DM2. This is obviously due to the small number of
individuals used in our study, which is a weakness of our data. The above overall
difference may suggest that, unlike inflammatory cytokine mRNA expression from
human mononuclear cells, mononuclear resistin mRNA is not appreciably increased
in vivo with chronic hyperinsulinemia that characterizes obesity. In
support of this, in vitro studies
demonstrated that insulin decreases resistin mRNA from human monocytes [31], while in the 3T3-L1 adipocytes, insulin downregulated resistin mRNA and
protein secretion—possibly through
the PI 3-kinase, ERK, or p38 MAP-kinase pathways—[32]. Recently, however, another study demonstrated
that acute hyperinsulinemia is associated with increased resistin mRNA
expression in human subcutaneous adipose tissue and a similar increase in
plasma resistin levels [33].Macrophages and
adipocytes share an overlapping biology and function [4], and infiltration of
the adipose tissue with the macrophages is characteristic of obesity [6].
Several recent studies suggest that obesity is associated with an increase in
adipose tissue macrophages, which also participate in the inflammatory process
through the elaboration of cytokines [3, 4, 34]. Proinflammatory cytokines
(TNF-α and IL-6) and adipokines (resistin and visfatin), produced by the peripheral
macrophages, can also be expressed in increased amounts in the fat tissue of
obese individuals acting in parallel as important regulators of inflammation,
atherosclerosis, and insulin sensitivity in both tissues. In a recent study,
the expression of two adipokines, resistin, and visfatin was detected
predominantly in the macrophages populating the human visceral fat tissue,
suggesting that these adipokines might have an important role in the
inflammatory load of obesity [7].The putative role of resistin
in obesity-induced insulin resistance was confirmed by studies, in rodents,
demonstrating that administration of recombinant resistin impairs hepatic
insulin sensitivity and glucose metabolism [22], while possibly playing a role
in maintaining fasting blood glucose levels [23]. This was debated by various
human studies demonstrating that there is no relationship of circulating resistin levels
with BMI, insulin sensitivity, or other metabolic parameters [24–26]. However,
other studies found increased serum resistin levels in individuals with obesity
and/or type 2 diabetes [27–29]. The above conflicting data lead to the
ascertainment that despite the initial belief that resistin could be the factor linking obesity and type 2 diabetes, its biologic
significance in the pathogenesis of insulin resistance, at least in humans, is
under controversy [35]. In fact,  while
in rodents adipose tissue is the only source of resistin production, in humans
resistin is barely detectable in adipocytes, and actual
resistin mRNA levels are much higher in monocytes and macrophages than in
adipocytes [21].In the present study,
we have additionally demonstrated that plasma resistin levels are marginally
increased in type 2 diabetic women compared to healthy women, and this increase
was detected in both subgroups, those withBMI<27 and those with BMI > 27.
Thus, our data are inline with previous reports that found elevated serum
resistin levels in type 2 diabetic subjects compared with nondiabetic subjects
[28, 29, 36]. Nevertheless, we observed no correlation of circulating resistin
with insulin resistance indices. However, the observed positive correlation of
circulating resistin with BMI and waist circumference might support some
association of resistin with obesity-induced insulin resistance. Therefore, the
observed increased plasma resistin levels in the DM2 women could be due to the
increased visceral obesity, as it reveals the higher waist circumference of
these patients.  Circulating Il-1β did not differentiate between the
healthy control and the DM2 women, a result that lines with previous studies in
which Il-1β alone cannot associate with the risk of developing type 2 diabetes,
while Il-1β was even decreased in an impaired glucose tolerance (IGT) group
compared to NGT subjects [37, 38]. It should be emphasized that due to the
large number of subjects in whom plasma IL-1β levels were undetectable, they
should be interpreted with caution. TNF-α and IL-6 plasma levels were also
similar between the NGT and the DM2 women of our study, although their levels
are significantly increased in the subgroup of DM2 women with BMI > 27,
compared to NGT with BMI < 27 women; moreover, they were significantly
correlated with the obesity and insulin resistance indices. While in the
EPIC-Potsdam study the elevated levels of TNF-α and IL-6 were found to be
strongly associated with future type 2 diabetes, other studies failed to
demonstrate increased TNF-α and IL-6 plasma levels in DM2 patients [37, 39].
The above discrepancy could be due to the small number of subjects used in the
later study, as it was also in our case, and due to ethnic differences between
the various studies.Obesity-induced insulin resistance is
characterized by a chronic, systemic low-grade state of inflammation and is
strongly associated with inflammatory markers, while inflammation may
contribute to insulin resistance and atherosclerosis [2, 5, 40]. Therefore,
with expanding obesity and increased macrophage infiltration of the adipose
tissue, there is an increased cytokine production by both cell populations,
with all the detrimental metabolic consequences on insulin resistance and on
the inflammatory status [4, 6, 41]. In the present study, we have demonstrated
that in type 2 diabetes, there is an increased mRNA expression of resistin,
along with significant increases in TNF-α, IL-6, and Il-1β mRNA expression by
the peripheral circulating mononuclear cells. The results from this study,
together with previous data, showing higher mononuclear visfatin mRNA expression
in the DM2 women [30], suggest that an overload of mRNA expression of
inflammatory cytokines and adipokines occurs in the mononuclear cells from type
2 diabetic patients, aggravating the proinflammatory status of this condition.
These data further support the notion that the peripheral circulating
mononuclear cells can indeed be an important source of resistin production in
humans. Thus, in type 2 diabetes, macrophages that infiltrate the stroma of the
adipose tissue and/or the vascular endothelium can locally produce and secrete increased
resistin and cytokine (Il-1β, TNF-α, and IL-6) levels, which may enhance the
inflammatory load and the associated insulin resistance and vascular dysfunction
observed in these patients.



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*Source: 892864-2008-12-21.xml*