Macrophage markers in skeletal muscle of obese subjects are elevated and inversely relate to insulin sensitivity. The present study aimed to investigate whether short-term high-fat high-calorie (HFHC) diet already increases macrophage markers and affects glucose metabolism in skeletal muscle of healthy lean subjects. Muscle biopsies were obtained from 24 healthy lean young men before and after a 5-day HFHC-diet. mRNA expression levels of relevant genes in muscle and glucose, insulin, C-peptide and cholesteryl ester transfer protein (CETP) levels in plasma were measured. In addition, we assessed hepatic triacylglycerol (‘triglyceride’) (HTG) content by magnetic resonance spectroscopy and subcutaneous white adipose tissue (sWAT) biopsies were analysed histologically from a subset of subjects (n=8). A 5-day HFHC-diet markedly increased skeletal muscle mRNA expression of the general macrophage markers CD68 (3.7-fold, P<0.01) and CD14 (3.2-fold, P<0.01), as well as the M1 macrophage markers MARCO (11.2-fold, P<0.05), CD11c (1.8-fold, P<0.05) and MRC1 (1.7-fold, P<0.05). This was accompanied by down-regulation of SLC2A4 and GYS1 mRNA expression, and elevated plasma glucose (+4%, P<0.001) and insulin (+55%, P<0.001) levels together with homoeostasis model assessment of insulin resistance (HOMA-IR) (+48%, P<0.001), suggesting development of insulin resistance (IR). Furthermore, the HFHC-diet markedly increased HTG (+118%, P<0.001) and plasma CETP levels (+21%, P<0.001), a marker of liver macrophage content, whereas sWAT macrophage content remained unchanged. In conclusion, short-term HFHC-diet increases expression of macrophage markers in skeletal muscle of healthy men accompanied by reduced markers of insulin signalling and development of IR. Therefore, recruitment of macrophages into muscle may be an early event in development of IR in response to short-term HFHC-feeding.

CLINICAL PERSPECTIVES

  • HFD feeding induces whole-body IR, of which the major contributor is muscle IR. The exact molecular mechanism by which HFD induces skeletal muscle IR is currently unknown and may involve recruitment of pro-inflammatory macrophages in muscle.

  • In the present study, we found that short-term HFD resulted in a markedly increased expression of both general and pro-inflammatory macrophage markers in muscle biopsies of healthy male subjects, accompanied by down-regulation of genes related to uptake and storage of glucose, and elevation of plasma glucose and insulin levels together with HOMA-IR, suggesting development of IR.

  • To our knowledge, this is the first study supporting the concept that recruitment of pro-inflammatory macrophages into muscle may be an early event in development of IR in the course of obesity. Moreover, the present study underscores the significant deleterious effects of fat overfeeding in healthy humans.

INTRODUCTION

Skeletal muscle is the primary site of dietary glucose disposal in vivo. Insulin stimulates glucose uptake into muscle through an elaborate signalling cascade eventually resulting in mobilization of glucose transporter 4 (GLUT-4) channels to the plasma membrane that mediate glucose uptake [1]. High-fat diet (HFD) feeding impairs whole-body insulin sensitivity and substrate homoeostasis in both mice and humans [2,3]. Skeletal muscle insulin resistance (IR) is the major contributor to development of whole-body IR [4] but the exact underlying molecular mechanism remains to be elucidated, although various hypotheses have been proposed.

First, lipid accumulation inside muscle cells and the formation of subsequent lipid metabolites (e.g. diacylglycerols, ceramides and acylcarnitines) contribute to muscle IR by interfering with the insulin signalling cascade [5].

Second, fatty acids (FAs) trigger activation of inflammatory signals in myocytes, and also in innate immune cells such as macrophages, leading to the release of pro-inflammatory cytokines that result in low-grade systemic inflammation [6,7]. In vitro studies support this concept, showing that FAs promote release of pro-inflammatory cytokines by macrophages that, in turn, induce IR in skeletal muscle cells [8]. Of note, cytokines can directly influence insulin actions on muscle. For example, the pro-inflammatory cytokine tumour necrosis factor-α (TNFα) caused IR and impaired glucose uptake in primary human myocytes [9].

A third mechanism underlying the development of muscle IR in response to HFD may involve recruitment of macrophages into the muscle tissue itself. Hong et al. [10] showed that HFD increased the number of M1-activated (CD11c+) macrophages in skeletal muscle in mice. Of note, this was corrected by transgenic overexpression of the anti-inflammatory cytokine interleukin (IL)-10 in skeletal muscle, which also improved whole-body insulin sensitivity. In humans, Varma et al. [8] showed that the skeletal muscle from obese subjects contained 2.5-fold higher CD68+ macrophage numbers in skeletal muscle compared with lean subjects. Strikingly, their study showed that macrophage content in muscle was strongly associated with body mass index (BMI) and inversely related to insulin sensitivity. This finding was corroborated in a recent other study by Fink et al. [11] in which CD68 expression in muscle of obese patients correlated positively with BMI, fasting plasma insulin and glucose levels and negatively with glucose disposal during clamp.

Taken together, these data suggest that HFD results in recruitment of pro-inflammatory macrophages in muscle which contribute to the development of muscle IR by releasing pro-inflammatory cytokines. However, the timing at which macrophages are recruited into skeletal muscle in the time course of HFD-induced obesity and the possible involvement of other, adaptive, immune cell types is currently unknown and may either be an early event or a late consequence when chronic low-grade inflammation has already developed. To investigate this issue, we subjected healthy, male lean subjects for 5 days to a high-fat high-calorie (HFHC) diet and studied expression of markers for macrophages, T-cells, pattern recognition receptors, as well as markers for glucose metabolism, in skeletal muscle biopsies before and after the diet. Furthermore, to investigate whether short-term HFD results in influx of macrophages in other tissues besides muscle, we investigated expression of macrophage markers in subcutaneous white adipose tissue (sWAT) biopsies as well as plasma cholesteryl ester transfer protein (CETP) levels as a marker of the liver macrophage content [12]. In addition, we assessed hepatic triacylglycerol (‘triglyceride’) (HTG) content by means of proton magnetic resonance (MR) spectroscopy.

MATERIALS AND METHODS

Study participants

Twenty-four Dutch, lean (BMI < 25 kg/m2) and healthy males of Caucasian (n=12) and South Asian (n=12) ethnicity between 19 and 25 years of age and with a positive family history of type 2 diabetes were enrolled via local advertisements (Clinical trial registry NTR 2473; http://www.trialregister.nl). All subjects underwent a medical screening including their medical history, a physical examination, blood chemistry tests and an oral glucose tolerance test to exclude individuals with Type 2 diabetes according to the American Diabetes Association (ADA) 2010 criteria. Other exclusion criteria were rigorous exercise, smoking and recent body weight change. The present study was approved by the Medical Ethical Committee of the Leiden University Medical Centre and performed in accordance with the principles of the revised Declaration of Helsinki. All volunteers gave written informed consent before participation.

Study design

Subjects were studied before and after a 5-day HFHC-diet, consisting of the subject's regular diet, supplemented with 375 ml of cream per day (=1275 kcal/day extra containing 94% fat; 1 kcal ≡ 4.184 kJ). They were instructed not to alter life style habits, and not to perform physical activity in the last 48 h prior to the study days. Furthermore, subjects were asked to keep a food diary before and during the HFHC-diet to estimate normal dietary intake, and to check for compliance and compensation behaviour, respectively. Diaries were entered and analysed using a specialized internet application (http://www.dieetinzicht.nl, Dutch). MR studies were performed shortly before and on the fifth day of the HFHC-diet. In addition, 1 day before and 1 day after the diet anthropometric measurements were performed and muscle and subcutaneous white adipose tissue biopsies were obtained from all subjects in fasted condition.

Magnetic resonance studies

HTG was assessed by proton magnetic resonance (MR) spectroscopy (1H-MRS; Gyroscan ACS-NT15; Philips) in the postprandial state (5 h after the last meal), as described previously [13]. Vertebra Th12 was used as a marker to ascertain the same position of the 8-ml-voxel at both study days. A spectrum with water suppression as internal standard was obtained, and 64 averages were collected without water suppression. The spectra were fitted using Java-base MR user interface software (jMRUI version 2.2) [13]. The percentage of HTG signals was calculated as: (signal amplitude HTG/signal amplitude water) × 100.

Anthropometric measurements

Anthropometric measurements were performed after an overnight fast. Body composition (fat and lean body mass) was assessed by bioelectrical impedance analysis (BIA; Bodystat®).

Skeletal muscle biopsies

Muscle biopsies from the musculus vastus lateralis (~75–100 mg) were collected 1 day before and 1 day after the diet intervention in fasted condition under localized anaesthesia, using a modified Bergström needle, as described previously [14]. Muscle samples were snap-frozen in liquid nitrogen and stored at −80°C until further analysis.

White adipose tissue biopsies

Subcutaneous fat biopsies were obtained from the umbilical region in fasted condition under localized anaesthesia, using a syringe with needle while applying suction. Fat samples were immediately submersed into a medium [Dulbecco's modified Eagle's medium (DMEM)/F12 + Glutamax], stored in formalin for up to 48 h and then embedded in paraffin. Of note, analysis was done in a subset of subjects (n=8) due to limited availability of tissue in lean subjects.

Laboratory analysis

Fasting serum glucose, total cholesterol, high-density lipoprotein (HDL)-cholesterol and TGs were measured on a Modular P800 analyser (Roche). low-density lipoprotein (LDL)-cholesterol was calculated according to Friedewald's formula [15]. Serum insulin and C-peptide levels were analysed on an Immulite 2500 (Siemens). The homoeostasis model assessment of insulin resistance (HOMA-IR) index was calculated using the formula: fasting insulin (pmol/l) × fasting glucose (mmol/l)/22.5. Plasma non-esterified ‘free’ fatty acid (NEFA) concentrations were determined by a colourimetric method (Wako Chemicals). ELISA kits were used to measure serum levels of high-sensitive C-reactive protein (hsCRP) (Meso Scale Discovery), adiponectin (Cayman Chemical) and CETP concentration (ALPCO Diagnostics) according to the manufacturers’ instructions.

RNA isolation

Total RNA was isolated from skeletal muscle biopsies (~25–30 mg) using the phenol–chloroform extraction method (Tripure RNA Isolation reagent, Roche) and treated with a DNAse kit (TURBO DNAse, Life Technologies) according to the manufacturer's instruction. Amount of RNA was determined by NanoDrop.

cDNA synthesis and real-time PCR

For RT-PCR, first-strand cDNA was synthesized from 1 μg of total RNA using a Superscript first strand synthesis kit (Invitrogen). Real-time PCR was carried out on the IQ5 PCR machine (Bio-Rad) using the Sensimix SYBRGreen RT-PCR mix (Quantace). Melt curve analysis was included to assure a single PCR product was formed. Expression levels were normalized to ribosomal protein S18 (RPS18). Primer sequences are listed in Supplementary Table S1.

dcRT-MLPA assay

A dual-colour reverse transcriptase multiplex ligation-dependent probe amplification (dcRT-MLPA) assay was performed as described previously [16]. Briefly, for each target-specific sequence, a specific RT primer was designed located immediately downstream of the left and right hand half-probe target sequence. Following reverse transcription, left and right hand half-probes were hybridized to the cDNA at 60°C overnight. Annealed half-probes were ligated and subsequently amplified by PCR (33 cycles of 30 s at 95°C, 30 s at 58°C and 60 s at 72°C, followed by 1 cycle of 20 min at 72°C). PCR amplification products were 1:10 diluted in HiDi formamide-containing 400HD ROX size standard and analysed on an Applied Biosystems 3730 capillary sequencer in GeneScan mode (Applied Biosystems).

Trace data were analysed using the GeneMapper software package (Applied Biosystems). The areas of each assigned peak (in arbitrary units) were exported for further analysis in Microsoft Excel spreadsheet software. Data were normalized to β-2-microglobulin (B2M) and signals below the threshold value for noise cutoff in GeneMapper (log2 transformed peak area: 7.64) were assigned the threshold value for noise cutoff.

Immunohistochemical stainings

Formalin-fixed-paraffin-embedded subcutaneous adipose tissue sections were used for immunohistochemistry of CD68. Antigens were retrieved using citrate buffer. The primary antibody was mouse-anti-human CD68 (1:800 dilution, clone KP1, from Dako). Staining and counterstaining was done with Nova Red (Vector labs) and haematoxylin, respectively. Crown-like structures (CLS) were counted according to the criterion that a CLS consisted of three or more CD68 positive cells surrounding an adipocyte.

To examine if any putative changes in mRNA of macrophage markers originates from invasion of muscle cell by macrophages, we performed immunofluorescence staining in muscle cross-sections. In brief, 7-μm-thick cryosections were thaw-mounted on glass slides and incubated (1:100) at room temperature with a monoclonal mouse antibody directed against human CD68 (M0178, Clone EBM11, Dako), a generic macrophage marker protein. The primary antibody was visualized with a proper fluorescein isothiocyanate (FITC)-conjugated seconday antibody. Nuclei were counter stained with 4′,6-diamidino-2-phenylindole (DAPI). Images were grabbed with an Nikon ER800 fluorescence microsocope.

Statistical analysis

The data of South Asian and Caucasian subjects were pooled for all analyses since no significant differences were observed between ethnicities for baseline values or diet effects. Data are presented as means±S.E.M. Paired Student's t tests were applied to assess mean differences before and after the diet intervention. Significance level was set at P<0.05. Statistical analyses were performed using SPSS for Windows version 20.0 (IBM).

RESULTS

Clinical characteristics

Clinical characteristics are shown in Table 1. Mean age was 22.1±0.4 years and mean BMI was 21.5±0.4 kg/m2. Five days of HFHC-diet resulted in a small but significant increase in body weight (+0.7%, P<0.01) and BMI (+0.9%, P<0.01), whereas waist circumference and percentage of fat mass remained unchanged. Although plasma NEFA, serum TG and total cholesterol levels did not change significantly upon the HFHC-diet, HDL-C and LDL-C did increase (both +9%, P<0.01). Furthermore, the HFHC-diet significantly increased fasting glucose (+4%), insulin (+55%) and C-peptide (+29%) levels, as well as the HOMA-IR index (+48%) (all P<0.001).

Table 1
Anthropometrics and metabolic characteristics before and after a 5-day HFHC-diet in healthy, young male subjects

Data are presented as means±S.E.M. **P<0.01, ***P<0.001 compared with before diet.

Before HFHC-diet (n=24)After HFHC-diet (n=24)
Age (years) 22.1±0.4  
Length (m) 1.79±0.01  
Weight (kg) 69.1±1.9 69.6±1.9** 
BMI (kg/m221.5±0.4 21.7±0.4** 
Waist (cm) 80.1±1.5 80.8±1.7 
Fat mass (%) 13.2±0.7 13.0±0.7 
Total cholesterol (mmol/l) 4.16±0.19 4.51±0.17 
HDL-C (mmol/l) 1.22±0.05 1.33±0.04** 
LDL-C (mmol/l) 2.51±0.17 2.74±0.15** 
Triglycerides (mmol/l) 0.96±0.08 0.97±0.08 
NEFA (mmol/l) 0.49±0.03 0.48±0.03 
Glucose (mmol/l) 5.17±0.06 5.37±0.06*** 
Insulin (pmol/l) 4.53±1.00 7.02±1.16*** 
C-peptide (nmol/l) 0.49±0.03 0.63±0.04*** 
HOMA-IR 1.62±0.26 2.39±0.32*** 
hsCRP (μg/ml) 0.94±0.23 1.16±0.24 
Adiponectin (μg/ml) 6.27±0.63 6.58±0.50 
HTG content (%) 1.57±0.27 3.43±0.49*** 
CETP mass (μg/ml) 1.69±0.09 2.02±0.10*** 
Before HFHC-diet (n=24)After HFHC-diet (n=24)
Age (years) 22.1±0.4  
Length (m) 1.79±0.01  
Weight (kg) 69.1±1.9 69.6±1.9** 
BMI (kg/m221.5±0.4 21.7±0.4** 
Waist (cm) 80.1±1.5 80.8±1.7 
Fat mass (%) 13.2±0.7 13.0±0.7 
Total cholesterol (mmol/l) 4.16±0.19 4.51±0.17 
HDL-C (mmol/l) 1.22±0.05 1.33±0.04** 
LDL-C (mmol/l) 2.51±0.17 2.74±0.15** 
Triglycerides (mmol/l) 0.96±0.08 0.97±0.08 
NEFA (mmol/l) 0.49±0.03 0.48±0.03 
Glucose (mmol/l) 5.17±0.06 5.37±0.06*** 
Insulin (pmol/l) 4.53±1.00 7.02±1.16*** 
C-peptide (nmol/l) 0.49±0.03 0.63±0.04*** 
HOMA-IR 1.62±0.26 2.39±0.32*** 
hsCRP (μg/ml) 0.94±0.23 1.16±0.24 
Adiponectin (μg/ml) 6.27±0.63 6.58±0.50 
HTG content (%) 1.57±0.27 3.43±0.49*** 
CETP mass (μg/ml) 1.69±0.09 2.02±0.10*** 

HFHC-diet and markers of glucose uptake/metabolism and muscle inflammation

The HFHC-diet did not affect mRNA expression of the insulin receptor (INSR) and its downstream signalling target TBC1D4 (encoding AS160) in muscle biopsies (Figure 1A). However, a diminished expression of SLC2A4 encoding GLUT-4 (−34%, P<0.001) and GYS-1 (−35%, P<0.001), both involved in uptake and storage of glucose, was evident.

Effect of short-term HFHC-diet on expression of insulin signalling and macrophage markers in muscle in healthy male subjects

Figure 1
Effect of short-term HFHC-diet on expression of insulin signalling and macrophage markers in muscle in healthy male subjects

mRNA expression levels of genes related to glucose uptake/metabolism (A) and macrophage markers (B) were measured in skeletal muscle biopsies of healthy male subjects (n=24) obtained before (white bars) and after (black bars) a 5-day HFHC-diet. Expression levels are normalized to the housekeeping gene S18 and expressed as fold change compared with baseline as means±S.E.M. (C) Immunofluorescence staining of C68 in skeletal muscle cross-sections. *P<0.05, **P<0.01 and ***P<0.001 compared with before diet.

Figure 1
Effect of short-term HFHC-diet on expression of insulin signalling and macrophage markers in muscle in healthy male subjects

mRNA expression levels of genes related to glucose uptake/metabolism (A) and macrophage markers (B) were measured in skeletal muscle biopsies of healthy male subjects (n=24) obtained before (white bars) and after (black bars) a 5-day HFHC-diet. Expression levels are normalized to the housekeeping gene S18 and expressed as fold change compared with baseline as means±S.E.M. (C) Immunofluorescence staining of C68 in skeletal muscle cross-sections. *P<0.05, **P<0.01 and ***P<0.001 compared with before diet.

Using the dcRT-MLPA assay, we measured mRNA expression of a large panel of inflammatory genes, including markers for innate and adaptive immune cells, pattern recognition receptors and cytokines in muscle biopsies before and after the HFHC-diet (Table 2). Of note, the HFHC-diet significantly up-regulated the expression of CD14 (+118%, P<0.05), a general macrophage marker, and the expression of MARCO (+415%, P<0.05), a scavenger receptor that is mainly present on pro-inflammatory M1 macrophages [17]. In line with this, expression of the anti-inflammatory cytokine IL10 tended to be down-regulated (−27%, P=0.10).

Table 2
Expression of adaptive and innate immune markers in muscle biopsies before and after a 5-day HFHC-diet in healthy male subjects

Data are presented as means±S.E.M. and expressed relative to baseline. *P<0.05 compared with before diet. #Low expression of gene.

GeneBaselineHFHC (fold change compared with baseline)P-value
Immune cell subset markers    
 CD14 1.00±0.16 2.18±0.23 0.04* 
 CD163 1.00±0.10 0.84±0.15 0.31 
 NCAM1 1.00±0.14 1.15±0.13 0.37 
 CD19 1.00±0.12 1.09±0.16 0.61 
 BLR1 1.00±0.15 0.84±0.14 0.42 
 FCGR1A# 1.00±0.00 1.68±0.26 0.13 
T-cell subsets 
 CD3E# 1.00±0.00 1.01±0.01 0.33 
CD4 1.00±0.09 1.48±0.15 0.04* 
 CD8A 1.00±0.14 0.89±0.15 0.61 
 IL7-R 1.00±0.06 0.93±0.10 0.53 
 CCR7 1.00±0.08 0.87±0.11 0.26 
Th1 response    
 CXCL10 1.00±0.10 0.98±0.11 0.88 
 IFNG 1.00±0.27 1.62±0.28 0.28 
 IL-2 1.00±0.17 1.06±0.17 0.84 
 IL-1B 1.00±0.13 0.93±0.15 0.78 
 TNF 1.00±0.08 1.09±0.10 0.52 
Th2 response 
 IL-4# 1.00±0.29 0.79±0.24 0.56 
 IL-4d2 1.00±0.35 0.79±0.35 0.65 
 IL-5 1.00±0.24 1.04±0.24 1.00 
 IL-6 1.00±0.11 1.08±0.14 0.70 
 IL-9# 1.00±0.00 1.17±0.10 0.16 
 IL-10 1.00±0.17 0.73±0.19 0.13 
 IL-13 1.00±0.45 1.94±0.28 0.26 
Treg markers 
 CCL4 1.00±0.16 1.11±0.15 0.80 
 CTLA4 1.00±0.13 0.88±0.13 0.38 
 LAG3 1.00±0.29 0.43±0.42 0.08 
 TGF-B1 1.00±0.13 1.12±0.11 0.42 
Key MF1 and MF2 cytokines 
 IL-12A 1.00±0.32 0.89±0.46 0.82 
 IL-12B 1.00±0.39 1.10±0.36 0.85 
 IL-23A 1.00±0.08 0.81±0.13 0.22 
 CCL2# 1.00±0.44 1.78±0.40 0.37 
 CCL5 1.00±0.09 0.90±0.10 0.51 
 CCL19 1.00±0.11 1.07±0.13 0.66 
 CCL22 1.00±0.08 0.85±0.06 0.16 
 CXCL13# 1.00±0.40 0.97±0.38 0.96 
Scavenger receptors 
MARCO 1.00±0.23 5.15±0.37 0.04* 
Pattern recognition receptors 
 TLR1# 1.00±0.00 1.55±0.36 0.33 
 TLR2# 1.00±0.51 0.17±0.00 0.11 
 TLR3 1.00±0.11 1.07±0.14 0.68 
 TLR4 1.00±0.29 1.20±0.33 0.67 
 TLR5 1.00±0.57 0.46±0.65 0.33 
 TLR6 1.00±0.37 1.28±0.32 0.64 
 TLR7 1.00±0.12 0.96±0.15 0.83 
 TLR8 1.00±0.10 0.96±0.17 0.85 
 TLR9 1.00±0.11 0.79±0.14 0.21 
 TLR10# 1.00±0.00 2.36±0.59 0.33 
 NOD1 1.00±0.24 1.06±0.15 0.83 
 NOD2# 1.00±0.00 1.33±0.26 0.33 
 MRC1 1.00±0.23 1.63±0.18 0.06 
 MRC2 1.00±0.05 0.91±0.11 0.48 
 CD209 1.00±0.14 1.02±0.16 0.94 
 CLEC7A 1.00±0.17 1.23±0.19 0.38 
Inflammasome components 
 NLRP1# 1.00±0.51 0.21±0.00 0.13 
 NLRP2 1.00±0.10 1.00±0.15 0.99 
 NLRP3# 1.00±0.42 0.85±0.32 0.77 
 NLRP4 1.00±0.16 0.86±0.22 0.56 
 NLRP7 1.00±0.37 0.88±0.35 0.78 
 NLRC4 1.00±0.05 0.89±0.10 0.37 
GeneBaselineHFHC (fold change compared with baseline)P-value
Immune cell subset markers    
 CD14 1.00±0.16 2.18±0.23 0.04* 
 CD163 1.00±0.10 0.84±0.15 0.31 
 NCAM1 1.00±0.14 1.15±0.13 0.37 
 CD19 1.00±0.12 1.09±0.16 0.61 
 BLR1 1.00±0.15 0.84±0.14 0.42 
 FCGR1A# 1.00±0.00 1.68±0.26 0.13 
T-cell subsets 
 CD3E# 1.00±0.00 1.01±0.01 0.33 
CD4 1.00±0.09 1.48±0.15 0.04* 
 CD8A 1.00±0.14 0.89±0.15 0.61 
 IL7-R 1.00±0.06 0.93±0.10 0.53 
 CCR7 1.00±0.08 0.87±0.11 0.26 
Th1 response    
 CXCL10 1.00±0.10 0.98±0.11 0.88 
 IFNG 1.00±0.27 1.62±0.28 0.28 
 IL-2 1.00±0.17 1.06±0.17 0.84 
 IL-1B 1.00±0.13 0.93±0.15 0.78 
 TNF 1.00±0.08 1.09±0.10 0.52 
Th2 response 
 IL-4# 1.00±0.29 0.79±0.24 0.56 
 IL-4d2 1.00±0.35 0.79±0.35 0.65 
 IL-5 1.00±0.24 1.04±0.24 1.00 
 IL-6 1.00±0.11 1.08±0.14 0.70 
 IL-9# 1.00±0.00 1.17±0.10 0.16 
 IL-10 1.00±0.17 0.73±0.19 0.13 
 IL-13 1.00±0.45 1.94±0.28 0.26 
Treg markers 
 CCL4 1.00±0.16 1.11±0.15 0.80 
 CTLA4 1.00±0.13 0.88±0.13 0.38 
 LAG3 1.00±0.29 0.43±0.42 0.08 
 TGF-B1 1.00±0.13 1.12±0.11 0.42 
Key MF1 and MF2 cytokines 
 IL-12A 1.00±0.32 0.89±0.46 0.82 
 IL-12B 1.00±0.39 1.10±0.36 0.85 
 IL-23A 1.00±0.08 0.81±0.13 0.22 
 CCL2# 1.00±0.44 1.78±0.40 0.37 
 CCL5 1.00±0.09 0.90±0.10 0.51 
 CCL19 1.00±0.11 1.07±0.13 0.66 
 CCL22 1.00±0.08 0.85±0.06 0.16 
 CXCL13# 1.00±0.40 0.97±0.38 0.96 
Scavenger receptors 
MARCO 1.00±0.23 5.15±0.37 0.04* 
Pattern recognition receptors 
 TLR1# 1.00±0.00 1.55±0.36 0.33 
 TLR2# 1.00±0.51 0.17±0.00 0.11 
 TLR3 1.00±0.11 1.07±0.14 0.68 
 TLR4 1.00±0.29 1.20±0.33 0.67 
 TLR5 1.00±0.57 0.46±0.65 0.33 
 TLR6 1.00±0.37 1.28±0.32 0.64 
 TLR7 1.00±0.12 0.96±0.15 0.83 
 TLR8 1.00±0.10 0.96±0.17 0.85 
 TLR9 1.00±0.11 0.79±0.14 0.21 
 TLR10# 1.00±0.00 2.36±0.59 0.33 
 NOD1 1.00±0.24 1.06±0.15 0.83 
 NOD2# 1.00±0.00 1.33±0.26 0.33 
 MRC1 1.00±0.23 1.63±0.18 0.06 
 MRC2 1.00±0.05 0.91±0.11 0.48 
 CD209 1.00±0.14 1.02±0.16 0.94 
 CLEC7A 1.00±0.17 1.23±0.19 0.38 
Inflammasome components 
 NLRP1# 1.00±0.51 0.21±0.00 0.13 
 NLRP2 1.00±0.10 1.00±0.15 0.99 
 NLRP3# 1.00±0.42 0.85±0.32 0.77 
 NLRP4 1.00±0.16 0.86±0.22 0.56 
 NLRP7 1.00±0.37 0.88±0.35 0.78 
 NLRC4 1.00±0.05 0.89±0.10 0.37 

Furthermore, expression of the general T-cell marker CD3 was undetectable in the muscle biopsies, pointing to absence or very low presence of T-cells. Expression of CD4, a T-helper cell marker that is also expressed by innate immune cells such as monocytes and macrophages [18], was detectable and increased upon the HFHC-diet (+48%, P<0.05). Given the absence of CD3 in the muscle biopsies, the increase in CD4 expression probably reflects increased expression by innate immune cells. Other inflammatory markers remained unaffected.

Thus, these data suggested that upon a short-term HFHC-diet, especially markers of innate immunity were up-regulated in muscle. We confirmed these findings by performing RT-PCR analyses on several macrophage markers in the muscle biopsies (Figure 1B). More specifically, the HFHC-diet up-regulated the general macrophage markers CD68 (3.7-fold, P<0.01) and CD14 (3.2-fold, P<0.01), as well as the M1 markers MARCO (11.2-fold, P<0.05), CD11c (1.8-fold, P<0.05) and MRC1 (1.7-fold, P<0.05). Hence, short-term HFHC-diet resulted in increased expression of pro-inflammatory M1 macrophages in muscle.

To investigate whether the enhanced expression of macrophage markers could be due to recruitment of macrophages, we stained muscle biopsies for CD68 by immunofluorescence. Indeed, the HFHC-diet enhanced the amount of CD68-expressing cells pointing to infiltration of macrophages (stained in green, see Figure 1C for three representative subjects).

HFHC-diet and markers of inflammation in other tissues

Since HFD-induced obesity is often associated with influx of pro-inflammatory macrophages and appearance of CLS in WAT [19], we next investigated whether markers of macrophage infiltration were also evident in WAT after 5 days of HFHC-diet in healthy lean subjects. Due to the very small amount of WAT retrieved from the single biopsy, we could only perform immunohistological staining of CD68 in subcutaneous WAT taken before and after the diet intervention, and only in a subset of subjects (n=8). At baseline, solitary macrophages were identified sporadically in the WAT biopsies, whereas no CLS were observed. After the HFHC-diet, influx of solitary macrophages increased in a few subjects as did the appearance of CLS in WAT (Supplementary Figures S1A and S1B), however, these effects were not statistically significant, probably due to the limited sample size number. Furthermore, plasma adiponectin, an adipocyte-derived hormone that is suggested to play a role in suppression of the development of obesity and IR [20], did not change upon the dietary intervention (Table 1).

The HFHC-diet increased HTG (+118%, P<0.001; Table 1). For obvious reasons we could not obtain liver biopsies from our healthy subjects to measure macrophage content. However, we have recently shown that plasma CETP levels highly correlate with levels of general macrophage markers in liver biopsies [21] (Y. Wang and P. C. N. Rensen et al., unpublished work) and therefore, we measured plasma CETP levels as a marker of liver macrophage content. Intriguingly, plasma CETP levels increased upon the HFHC-diet (+21%, P<0.001; Table 1), suggesting influx of macrophages into the liver. Furthermore, after the HFHC-diet plasma CRP levels tended to increase (+24%, P=0.06; Table 1), pointing to low-grade systemic inflammation.

DISCUSSION

Recent studies have detected elevated numbers of macrophage markers in skeletal muscle during chronic HFD feeding and obesity, but the timing at which these macrophages are recruited and their role in the development of muscle and whole-body IR is unknown. The present study demonstrates that only 5 days of HFHC-diet resulted in a marked increase in expression of macrophage markers in muscle of healthy lean male subjects. Moreover, this was accompanied by down-regulation of genes involved in glucose metabolism and elevation of fasting plasma glucose and insulin levels and HOMA-IR index. Of note, plasma CETP levels, which were previously shown by our group to correlate with liver macrophage content (Y. Wang and S. J. vander Tuin et al., unpublished work), increased whereas macrophage content in the subcutaneous WAT depot remained unchanged with the current sample size.

As in other organs, resident macrophages are present in human skeletal muscle [8] where they contribute to regeneration and revascularization in case of damage [22]. In accordance with these data, we found that the general macrophage markers CD14 and CD68 were significantly expressed in skeletal muscle of healthy lean men. Of note, the homoeostatic functions of muscle macrophages are exerted only when the macrophages are in their M2 (anti-inflammatory) phenotypic polarization stage [23,24]. In response to different stimuli, such as circulating FA, macrophages are polarized towards an M1-like (inflammatory) phenotype, leading to release of pro-inflammatory cytokines which can induce IR in myocytes [8]. Indeed, previous mouse and human studies have repeatedly observed increased numbers of activated M1 (CD11c+) macrophages in skeletal muscle tissue in the context of obesity and IR [2528]. Intriguingly, our data demonstrate that the increased expression of M1 macrophages in skeletal muscle occurs already after short-term HFD and even in healthy young subjects, supporting the concept that recruitment of M1 macrophages into skeletal muscle is an early event in the time course of HFD-induced obesity. Indeed, these data are in line with a recent mouse study in which 1 week of HFD increased the content of CD11c-expressing pro-inflammatory macrophages in muscle together with decreased whole-body insulin sensitivity [11]. Intriguingly, muscle gene expression of Ly6b, a surface marker of neutrophils, monocytes and macrophages, showed a 10-fold increase after only 3 days of HFD.

What would be the trigger of the extensive increase in macrophage markers in muscle and does this mainly reflect activation of resident macrophages or increased influx from blood-derived monocytes? We speculate that both mechanisms are involved. The fact that the expression of general macrophage markers (CD68 and CD14) was increased, even on the immunohistochemical level, is most easily explained by an increased influx of these cells into muscle, rather than by up-regulation of the expression of these genes in resident macrophages. The trigger that stimulated this influx is probably the high load of saturated FAs ingested with the HFHC-diet. Saturated FAs can signal via Toll-like receptors (TLRs), particularly TLR-4 that is present on both macrophages and myocytes [29]. Activation of TLR-4 stimulates the transcription and release of various chemokines and pro-inflammatory cytokines, such as MCP-1 or TNFα, which attract other macrophages and may also directly impair insulin signalling in skeletal muscle [5,30,31]. Indeed, in the above-mentioned mouse study [11], the HFD-induced increase in muscle macrophages was prevented by knockout of CCL2 (also called MCP-1), suggesting that MCP-1 is involved in the influx of macrophages upon HFD. In the present study, MCP-1 expression was very low in muscle. Therefore, it is difficult to draw conclusions on a possible role of MCP-1 in the recruitment of macrophages in human skeletal muscle. Furthermore, in the present study, we did not find effects of the HFHC-diet on gene expression of TLRs or pro-inflammatory cytokines such as TNFα in skeletal muscle. However, we cannot exclude that either local release of pro-inflammatory cytokines or activation of TLR-4-driven signalling pathways might have occurred in this tissue.

Although we found that expression of macrophage markers was markedly increased in skeletal muscle upon the HFHC-diet, no significant increase could be identified in the subcutaneous WAT depot. This may be due to the small number of samples in which we were able to perform measurements, as it is clear from Supplementary Figure S1(A) that in part of the subjects the number of solitary macrophages increased. Furthermore, visceral adipose tissue (VAT) seems to be more closely associated with the inflammatory state than subcutaneous adipose tissue [32]. In addition, muscle cells might be more prone to release macrophage attractant factors in the presence of pro-inflammatory stimuli compared with adipocytes. Indeed, a previous study demonstrated that the presence of both macrophages and the saturated FA palmitate exerted a synergistic effect on MCP-1 release by muscle cells, resulting in greater attraction of macrophages [8]. To our knowledge, such a positive feedback-loop has not been demonstrated for adipocytes.

Besides a large increase in macrophage markers in muscle upon the HFHC-diet, the increased plasma CETP levels suggest increased hepatic macrophage content as well [21]. Our group has previously shown that the hepatic macrophage is the main producer of plasma CETP (Y. Wang et al., unpublished work), meaning that an increase in plasma CETP levels reflects an increase in hepatic macrophages. Interestingly, various studies have shown that pro-inflammatory cytokines also impaired insulin signalling in hepatocytes [33]. Thus, it is tempting to speculate that dietary saturated FAs may have resulted in influx of pro-inflammatory M1 macrophages in the liver, leading to release of pro-inflammatory cytokines and subsequent impairment of hepatic insulin signalling. This mechanism may also explain the previously found reduced suppression of endogenous glucose production in response to 5 days of HFHC-diet [34].

A potential limitation of the present study could be that we determined immune cell markers via MLPA assay and RT-PCR instead of performing flow cytometry analyses, a method by which true cell counts are determined. However, performing flow cytometry analyses would require relatively large amounts of muscle tissues, the collection of which was not feasible in the present study.

In conclusion, we show that 5 days of HFHC-diet resulted in a marked increase in gene expression of M1 macrophage markers in skeletal muscle of healthy lean male subjects, a feature associated with apparent impairment in whole-body insulin sensitivity and glucose homoeostasis. Future studies should be directed at unraveling the precise contribution of muscle macrophages in the development of peripheral IR, with the ultimate goal to develop novel therapeutic targets that decrease inflammation-induced IR without interfering with all innate immune functions.

AUTHOR CONTRIBUTION

Mariëtte Boon, Leontine Bakker, Edo Meinders Ingrid Jazet and Patrick Rensen designed the research; Mariëtte Boon, Leontine Bakker, Mariëlle Haks, Gert Schaart, Edwin Quinten, Lianne van Beek, Yanan Wang, Vanessa van Harmelen and Bruno Guigas conducted the research; Mariëtte Boon, Leontine Bakker and Mariëlle Haks analysed the data; Mariëtte Boon, Leontine Bakker, Bruno Guigas, Ingrid Jazet and Patrick Rensen wrote the paper; Mariëlle Haks, Edwin Quinten, Lianne van Beek, Yanan Wang, Vanessa van Harmelen, Gert Schaart, Edo Meinders, Tom Ottenhoff, Ko Willems van Dijk, Bruno Guigas, Ingrid Jazet and Patrick Rensen contributed to the discussion, reviewed and edited the paper; Mariëtte Boon and Leontine Bakker had primary responsibility for final content. All authors read and approved the final manuscript. Leontine Bakker, Mariëtte Boon, Ingrid Jazet and Patrick Rensen are the guarantors of this work and, as such, have full access to all the data generated in the framework of the study and take responsibility for their integrity and the accuracy of their analysis.

We thank Annemieke Visser (LUMC, Department of Immunohaematobiology) and Lianne van der Wee-Pals (LUMC, Department of of Endocrinology) for their help with performing WAT staining, and to Gerard van der Zon (LUMC, Department of Molecular Cell Biology) for his help with performing the RT-PCR analyses on muscle biopsies. Furthermore, we thank Bep Ladan-Eygenraam (LUMC, Department of Endocrinology) for her excellent technical assistance during conductance of the study.

FUNDING

The present study was financed by the Dutch Diabetes Research Foundation [grant number 2012.11.1500 (to P.C.N.R. and M.R.B.)]; the Board of Directors of the Leiden University Medical Center (LUMC) (to M.R.B.); the Netherlands Heart Foundation [grant number 2009T038 (to P.C.N.R.)]; Roba Metals, IJsselstein (Utrecht, the Netherlands); European Union's Seventh Framework Programme projects TANDEM [grant number 305279]; ADITEC [grant number 280873]; and the Netherlands Relief Foundation. The funders did not have any role in the design or interpretation of the study.

Abbreviations

     
  • BMI

    body mass index

  •  
  • CETP

    cholesteryl ester transfer protein

  •  
  • CLS

    crown-like structures

  •  
  • FA

    fatty acid

  •  
  • GLUT-4

    glucose transporter 4

  •  
  • GYS1

    glycogen synthase 1

  •  
  • HFD

    high-fat diet

  •  
  • HDL-C

    high-density lipoprotein-cholesterol

  •  
  • HFHC

    high-fat high-calorie

  •  
  • HOMA-IR

    homoeostasis model assessment of insulin resistance

  •  
  • hsCRP

    high sensitive C-reactive protein

  •  
  • HTG

    hepatic triacylglycerol

  •  
  • IL

    interleukin

  •  
  • INSR

    insulin receptor

  •  
  • LDL-C

    low-density lipoprotein-cholesterol

  •  
  • IR

    insulin resistance

  •  
  • MR

    magnetic resonance

  •  
  • NEFA

    non-esterified ‘free’ fatty acid

  •  
  • RT-MLPA

    dual-colour reverse transcriptase multiplex ligation-dependent probe amplification

  •  
  • SLC2A4

    solute carrier family 2

  •  
  • TBC1D4

    TBC1 domain family member 4

  •  
  • TLR

    Toll-like receptor

  •  
  • TG

    triacylglycerol

  •  
  • TNF

    tumour necrosis factor

  •  
  • (s)WAT

    (subcutaneous) white adipose tissue

References

References
1
Zaid
 
H.
Antonescu
 
C. N.
Randhawa
 
V. K.
Klip
 
A.
 
Insulin action on glucose transporters through molecular switches, tracks and tethers
Biochem. J.
2008
, vol. 
413
 (pg. 
201
-
215
)
[PubMed]
2
Kim
 
J. K.
Gimeno
 
R. E.
Higashimori
 
T.
Kim
 
H. J.
Choi
 
H.
Punreddy
 
S.
Mozell
 
R. L.
Tan
 
G.
Stricker-Krongrad
 
A.
Hirsch
 
D. J.
, et al 
Inactivation of fatty acid transport protein 1 prevents fat-induced insulin resistance in skeletal muscle
J. Clin. Invest.
2004
, vol. 
113
 (pg. 
756
-
763
)
[PubMed]
3
Shulman
 
G. I.
 
Unraveling the cellular mechanism of insulin resistance in humans: new insights from magnetic resonance spectroscopy
Physiology
2004
, vol. 
19
 (pg. 
183
-
190
)
[PubMed]
4
DeFronzo
 
R. A.
 
Bantin lecture. From the triumvirate to the ominous octet: a new paradigm for the treatment of type 2 diabetes mellitus
Diabetes
2009
, vol. 
58
 (pg. 
773
-
795
)
[PubMed]
5
Kewalramani
 
G.
Bilan
 
P. J.
Klip
 
A.
 
Muscle insulin resistance: assault by lipids, cytokines and local macrophages
Curr. Opin. Clin. Nutr. Metab. Care
2010
, vol. 
13
 (pg. 
382
-
390
)
[PubMed]
6
Bilan
 
P. J.
Samokhvalov
 
V.
Koshkina
 
A.
Schertzer
 
J. D.
Samaan
 
M. C.
Klip
 
A.
 
Direct and macrophage-mediated actions of fatty acids causing insulin resistance in muscle cells
Arch. Physiol. Biochem.
2009
, vol. 
115
 (pg. 
176
-
190
)
[PubMed]
7
Shi
 
H.
Kokoeva
 
M. V.
Inouye
 
K.
Tzameli
 
I.
Yin
 
H.
Flier
 
J. S.
 
TLR4 links innate immunity and fatty acid-induced insulin resistance
J. Clin. Invest.
2006
, vol. 
116
 (pg. 
3015
-
3025
)
[PubMed]
8
Varma
 
V.
Yao-Borengasser
 
A.
Rasouli
 
N.
Nolen
 
G. T.
Phanavanh
 
B.
Starks
 
T.
Gurley
 
C.
Simpson
 
P.
McGehee
 
R. E.
Kern
 
P. A.
Peterson
 
C. A.
 
Muscle inflammatory response and insulin resistance: synergistic interaction between macrophages and fatty acids leads to impaired insulin action
Am. J. Physiol. Endocrinol. Metab.
2009
, vol. 
296
 (pg. 
E1300
-
E1310
)
[PubMed]
9
Austin
 
R. L.
Rune
 
A.
Bouzakri
 
K.
Zierath
 
J. R.
Krook
 
A.
 
siRNA-mediated reduction of inhibitor of nuclear factor-kappaB kinase prevents tumor necrosis factor-alpha-induced insulin resistance in human skeletal muscle
Diabetes
2008
, vol. 
57
 (pg. 
2066
-
2073
)
[PubMed]
10
Hong
 
E. G.
Ko
 
H. J.
Cho
 
Y. R.
Kim
 
H. J.
Ma
 
Z.
Yu
 
T. Y.
Friedline
 
R. H.
Kurt-Jones
 
E.
Finberg
 
R.
Fischer
 
M. A.
, et al 
Interleukin-10 prevents diet-induced insulin resistance by attenuating macrophage and cytokine response in skeletal muscle
Diabetes
2009
, vol. 
58
 (pg. 
2525
-
2535
)
[PubMed]
11
Fink
 
L. N.
Costford
 
S. R.
Lee
 
Y. S.
Jensen
 
T. E.
Bilan
 
P. J.
Oberbach
 
A.
Blüher
 
M.
Olefsky
 
J. M.
Sams
 
A.
Klip
 
A.
 
Pro-inflammatory macrophages increase in skeletal muscle of high fat-Fed mice and correlate with metabolic risk markers in humans
Obesity
2014
, vol. 
22
 (pg. 
747
-
757
)
[PubMed]
12
Widya
 
R. L.
Hammer
 
S.
Boon
 
M. R.
Van der Meer
 
R. W.
Smit
 
J. W. A.
De Roos
 
A.
Rensen
 
P. C.
Lamb
 
H. J.
 
Effects of short-term nutritional interventions on right ventricular function in healthy men
PLoS One
2013
, vol. 
8
 pg. 
e76406
 
[PubMed]
13
van der Meer
 
R. W.
Hammer
 
S.
Lamb
 
H. J.
Frolich
 
M.
Diamant
 
M.
Rijzewijk
 
L. J.
de Roos
 
A.
Romijn
 
J. A.
Smit
 
J. W.
 
Effects of short-term high-fat, high-energy diet on hepatic and myocardial triglyceride content in healthy men
J. Clin. Endocrinol. Metab.
2008
, vol. 
93
 (pg. 
2702
-
2708
)
[PubMed]
14
Bergstrom
 
J.
 
Percutaneous needle biopsy of skeletal muscle in physiological and clinical research
Scand. J. Clin. Lab. Invest.
1975
, vol. 
35
 (pg. 
609
-
616
)
[PubMed]
15
Friedewald
 
W. T.
Levy
 
R. I.
Fredrickson
 
D. S.
 
Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge
Clin. Chem.
1972
, vol. 
18
 (pg. 
499
-
502
)
[PubMed]
16
Joosten
 
S. A.
Goeman
 
J. J.
Sutherland
 
J. S.
Opmeer
 
L.
de Boer
 
K. G.
Jacobsen
 
M.
Kaufmann
 
S. H.
Finos
 
L.
Magis-Escurra
 
C.
Ota
 
M. O.
Ottenhoff
 
T. H.
, et al 
Identification of biomarkers for tuberculosis disease using a novel dual-color RT-MLPA assay
Genes Immun.
2012
, vol. 
13
 (pg. 
71
-
82
)
[PubMed]
17
Murray
 
P. J.
Wynn
 
T. A.
 
Protective and pathogenic functions of macrophage subsets
Nat. Rev. Immunol.
2011
, vol. 
11
 (pg. 
723
-
737
)
[PubMed]
18
Gibbings
 
D.
Befus
 
A. D.
 
CD4 and CD8: an inside-out coreceptor model for innate immune cells
J. Leukoc. Biol.
2009
, vol. 
86
 (pg. 
251
-
259
)
[PubMed]
19
Weisberg
 
S. P.
McCann
 
D.
Desai
 
M.
Rosenbaum
 
M.
Leibel
 
R. L.
Ferrante
 
A. W.
 
Obesity is associated with macrophage accumulation in adipose tissue
J. Clin. Invest.
2003
, vol. 
11
 (pg. 
1796
-
1808
)
20
Ukkola
 
O.
Santaniemi
 
M.
 
Adiponectin: a link between excess adiposity and associated comorbidities?
J. Mol. Med.
2002
, vol. 
80
 (pg. 
696
-
702
)
[PubMed]
21
Li
 
Z.
Wang
 
Y.
van der Sluis
 
R. J.
van der Hoorn
 
J. W.
Princen
 
H. M.
Van Eck
 
M.
Van Berkel
 
T. J.
Rensen
 
P. C.
Hoekstra
 
M.
 
Niacin reduces plasma CETP levels by diminishing liver macrophage content in CETP transgenic mice
Biochem. Pharmacol.
2012
, vol. 
84
 (pg. 
821
-
829
)
[PubMed]
22
Olefsky
 
J. M.
Glass
 
C. K.
 
Macrophages, inflammation, and insulin resistance
Annu. Rev. Physiol.
2010
, vol. 
72
 (pg. 
219
-
246
)
[PubMed]
23
Verreck
 
F. A.
de Boer
 
T.
Langenberg
 
D. M.
Hoeve
 
M. A.
Kramer
 
M.
Vaisberg
 
E.
Kastelein
 
R.
Kolk
 
A.
de Waal-Malefyt
 
R.
Ottenhoff
 
T. H.
 
Human IL-23-producing type 1 macrophages promote but IL-10-producing type 2 macrophages subvert immunity to (myco)bacteria
Proc. Natl. Acad. Sci. U.S.A.
2004
, vol. 
101
 (pg. 
4560
-
4565
)
[PubMed]
24
Verreck
 
F. A.
de Boer
 
T.
Langenberg
 
D. M.
van der Zanden
 
L.
Ottenhoff
 
T. H.
 
Phenotypic and functional profiling of human proinflammatory type-1 and anti-inflammatory type-2 macrophages in response to microbial antigens and IFN-gamma- and CD40L-mediated costrimulation
J. Leukoc. Biol.
2006
, vol. 
79
 (pg. 
285
-
293
)
[PubMed]
25
Nguyen
 
M. T.
Favelyukis
 
S.
Nguyen
 
A. K.
Reichart
 
D.
Scott
 
P. A.
Jenn
 
A.
Liu-Bryan
 
R.
Glass
 
C. K.
Neels
 
J. G.
Olefsky
 
J. M.
 
A subpopulation of macrophages infiltrates hypertrophic adipose tissue and is activated by free fatty acids via toll-like receptors 2 and 4 and JNK-dependent pathways
J. Biol. Chem.
2007
, vol. 
282
 (pg. 
35279
-
35292
)
[PubMed]
26
Patsouris
 
D.
Li
 
P. P.
Thapar
 
D.
Chapman
 
J.
Olefsky
 
J. M.
Neels
 
J. G.
 
Ablation of CD11c-positive cells normalizes insulin sensitivity in obese insulin resistant animals
Cell Metab.
2008
, vol. 
8
 (pg. 
301
-
309
)
[PubMed]
27
Hevener
 
A. L.
Olefsky
 
J. M.
Reichart
 
D.
Nguyen
 
M. T.
Bandyopadyhay
 
G.
Leung
 
H. Y.
Watt
 
M. J.
Benner
 
C.
Febbraio
 
M. A.
Nguyen
 
A. K.
, et al 
Macrophage PPAR gamma is required for normal skeletal muscle and hepatic insulin sensitivity and full antidiabetic effects of thiazolidinediones
J. Clin. Invest.
2007
, vol. 
117
 (pg. 
1658
-
1669
)
[PubMed]
28
Fink
 
L. N.
Oberbach
 
A.
Jensen
 
T. E.
Sams
 
A.
Blüher
 
M.
Klip
 
A.
 
Muscle-infiltrating macrophages in type 2 diabetes
Diabetologia
2012
, vol. 
61
 pg. 
106.OR
 
29
Kraegen
 
E. W.
 
Development of muscle insulin resistance after liver insulin resistance in high-fat-fed rats
Diabetes
1991
, vol. 
40
 (pg. 
1397
-
1403
)
[PubMed]
30
Sell
 
H.
Eckel
 
J.
 
Monocyte chemotactic protein-1 and its role in insulin resistance
Curr. Opin. Lipidol.
2007
, vol. 
18
 (pg. 
258
-
262
)
[PubMed]
31
Yang
 
H.
Youm
 
Y.-H.
Vandanmagsar
 
B.
Ravussin
 
A.
Gimble
 
J. M.
Greenway
 
F.
Stephens
 
J. M.
Mynatt
 
R. L.
Dixit
 
V. D.
 
Obesity increases the production of proinflammatory mediators from adipose tissue T cells and compromises TCR repertoire diversity: implications for systemic inflammation and insulin resistance
J. Immunol.
2010
, vol. 
185
 (pg. 
1836
-
1845
)
[PubMed]
32
Bruun
 
J. M.
Helge
 
J. W.
Richelsen
 
B.
Stallknecht
 
B.
 
Diet and exercise reduce low-grade inflammation and macrophage infiltration in adipose tissue but not in skeletal muscle in severely obese subjects
Am. J. Physiol. Endocrinol. Metab.
2006
, vol. 
290
 (pg. 
E961
-
E967
)
[PubMed]
33
de Luca
 
C.
Olefsky
 
J. M.
 
Inflammation and insulin resistance
FEBS Lett.
2008
, vol. 
582
 (pg. 
97
-
105
)
[PubMed]
34
Brøns
 
C.
Jensen
 
C. B.
Storgaard
 
H.
Hiscock
 
N. J.
White
 
A.
Appel
 
J. S.
Jacobsen
 
S.
Nilsson
 
E.
Larsen
 
C. M.
Astrup
 
A.
, et al 
Impact of short-term high-fat feeding on glucose and insulin metabolism in young healthy men
J. Physiol.
2009
, vol. 
587
 (pg. 
2387
-
2397
)
[PubMed]

Author notes

1

These authors contributed equally to this work.

Supplementary data