p38 MAPK activation upregulates proinflammatory pathways in skeletal muscle cells from insulin-resistant type 2 diabetic patients

Abstract

Skeletal muscle is the key site of peripheral insulin resistance in type 2 diabetes. Insulin-stimulated glucose uptake is decreased in differentiated diabetic cultured myotubes, which is in keeping with a retained genetic/epigenetic defect of insulin action. We investigated differences in gene expression during differentiation between diabetic and control muscle cell cultures. Microarray analysis was performed using skeletal muscle cell cultures established from type 2 diabetic patients with a family history of type 2 diabetes and clinical evidence of marked insulin resistance and nondiabetic control subjects with no family history of diabetes. Genes and pathways upregulated with differentiation in the diabetic cultures, compared with controls, were identified using Gene Spring and Gene Set Enrichment Analysis. Gene sets upregulated in diabetic myotubes were associated predominantly with inflammation. p38 MAPK was identified as a key regulator of the expression of these proinflammatory gene sets, and p38 MAPK activation was found to be increased in the diabetic vs. control myotubes. Although inhibition of p38 MAPK activity decreased cytokine gene expression from the cultured diabetic myotubes significantly, it did not improve insulin-stimulated glucose uptake. Increased cytokine expression driven by increased p38 MAPK activation is a key feature of cultured myotubes derived from insulin-resistant type 2 diabetic patients. p38 MAPK inhibition decreased cytokine expression but did not affect the retained defect of impaired insulin action in the diabetic muscle cells.

skeletal muscle is the key peripheral tissue site of the insulin resistance in type 2 diabetes, manifested as decreased insulin-stimulated glucose uptake and storage (3). Evidence supporting the role of genetic factors in the development of insulin resistance in type 2 diabetes includes the familial clustering of insulin resistance (13), the study of rare severe phenotypes (18), and the retention of defects of insulin action in cultured human muscle cells (8, 9, 14). We and others have shown defects of insulin action in cultured muscle cells from patients with type 2 diabetes and nondiabetic first-degree relatives of type 2 diabetic patients (8, 9, 14). However, although recent genome-wide association studies of type 2 diabetes have identified more than 40 susceptibility loci, few appear to impact upon insulin action (4).

We sought to optimize the chance of identifying genetic variants related to insulin resistance and type 2 diabetes. We established skeletal muscle cell cultures from patients with both a familial predisposition to type 2 diabetes and clinical evidence of marked insulin resistance and from nondiabetic control subjects with normal glucose tolerance and no family history of diabetes. As reported previously, insulin action was normal in the diabetic myoblasts, but upon differentiation to mature multinucleated myotubes there was both decreased insulin-stimulated glucose uptake and glycogen synthesis (14).

This observation led us to the hypothesis that changes in gene expression during myotube differentiation contributed to the impaired action of insulin in the diabetic muscle cultures. Therefore, the specific aim of this study was to use microarray technology to compare gene expression between the diabetic and control differentiated myotube cultures.

METHODS

Study subjects.

Muscle biopsies were obtained from six type 2 diabetic patients with clinical evidence of marked insulin resistance. None of the patients had partial lipodystrophy. Specifically, we recruited type 2 diabetic patients who were insulin treated, which required >100 U/day in the absence of marked obesity (BMI <32kg/m²), and who had at least one first-degree relative with type 2 diabetes. All patients had been treated with diet and oral hypoglycemic agents for ≥3 yr after diagnosis before starting insulin treatment. Skeletal muscle was acquired from six nondiabetic control subjects with no family history of type 2 diabetes. The control and diabetic subjects were matched for age and BMI. All subjects gave written informed consent, and the study was approved by the Newcastle and North Tyneside Joint Ethics Committee. Clinical characteristics are summarized in Table 1.

Table 1.

Metabolic and anthropometric characteristics of recruited subjects

	Diabetic Patients	Controls
Age, yr	59 ± 7	59 ± 11
Sex (males/females)	5/1	3/3
Time to insulin treatment, yr	10 ± 5
Units of insulin/day	131.2 ± 9.6
Fasting serum insulin, mU/l		7.1 ± 0.6
Fasting plasma glucose, mmol/l		5.4 ± 0.2
Hb A1c, %	9.0 ± 0.5	5.2 ± 0.1**
BMI, kg/m2	30 ± 0.7	28.5 ± 1.0
Waist/hip ratio	1.0 ± 0.03	0.9 ± 0.02**
Systolic BP, mmHg	142.8 ± 6.2	131.7 ± 5.4
Diastolic BP, mmHg	82.3 ± 3.0	76.7 ± 2.1
Total cholesterol, mmol/l	4.8 ± 0.2	5.9 ± 0.3**
Triglycerides, mmol/l	3.3 ± 0.5	1.6 ± 0.4*

Data are presented as means ± SE; diabetic vs. control.

BP, blood pressure. Groups were matched for age and BMI. The diabetics had significantly higher Hb A_1c, waist/hip ratio, and triglycerides. Controls had significantly higher total cholesterol attributed to statin therapy in the diabetics.

^**P < 0.01;

^*P < 0.05.

General chemicals and reagents.

Cell culture medium was obtained from Lonza. Foetal bovine serum (FBS) and Trizol reagent were obtained from Life Technologies (Paisley, UK). Chick embryo extract was purchased from Sera Labs International (Sussex, UK), and antibodies were obtained from New England Biolabs (Herts, UK). The Human U133 Plus 2.0 expression arrays were obtained from Affymetrix. 2-Deoxy-d-[2,6-³H]glucose was purchased from NEN (Boston, MA). Cytokine ELISA kits were from Qiagen (Sussex, UK). The p38 MAPK inhibitor SB-203580 was purchased from Tocris Bioscience (Bristol, UK).

Cell culture.

Muscle biopsies were obtained from the vastus lateralis and satellite cells isolated, as described previously (1). Cultures were purified as described previously (14) using a magnetic bead system (Miltenyi Biotec). Briefly, cells were harvested and resuspended in PBS containing 2 mM EDTA and 5% (vol/vol) FBS and incubated with anti-CD56 antibody, which recognizes a muscle-specific cell surface antigen. After washing and incubation with microbead-conjugated secondary antibody, the cell suspension was applied to an MS column within a magnetic field. The cells with microbeads attached were retained on the column, and other cells passed through the column. The cells retained in the column were eluted and returned to culture. Muscle cell origin was confirmed immunohistochemically using antibodies to the muscle-specific protein desmin. Myoblasts were cultured in Ham's F-10 medium supplemented with 20% (vol/vol) FBS and 2% (vol/vol) chick embryo extract. Differentiation was induced by changing the media to minimal essential media supplemented with 2% (vol/vol) FBS. All experiments were performed on day 7 differentiated myotubes between passages 5 and 8.

RNA isolation, cDNA synthesis, and array hybridization.

RNA was extracted from myoblasts and myotubes differentiated for 7 days using Trizol as per the manufacturer's instructions. Briefly, cells were lysed in Trizol, homogenized, and incubated at room temperature for 5 min. After the addition of 0.2 volumes of chloroform, the samples were mixed and centrifuged at 12,000 g for 15 min at 4°C; 0.5 volumes of isopropanol was added to the upper aqueous phase before centrifugation at 12,000 g for 10 min at 4°C. The pellet was washed with 75% ethanol and centrifuged at 7,500 g for 5 min at 4°C before being resuspended in 20 μl of RNase-free water. cDNA synthesis was performed using Superscript II (Life Technologies) and the cDNA cleaned up using the recommended protocol. Fragmented, biotinylated cRNA was produced using recommended protocols (Affymetrix). Hybridization of the cRNA took place at 45°C for 16 h in a GeneChip Hybridization Oven 640 (Affymetrix) to Affymetrix Human Genome U133 Plus 2.0 Arrays. The arrays were subsequently washed and stained in a GeneChip Fluidics Station 400. Finally, the arrays were scanned in a GeneChip Scanner 3000.

Array data analysis.

The arrays were normalized in GeneSpring GX software (Agilent) by RMA and baseline transformation to the median of all samples. Data were log transformed to obtain a normal distribution and differences in expression between the controls and diabetic myotubes and myoblasts determined. P values were calculated in GeneSpring using Student's t-test adjusted for false discovery rate correction using the Benjamini-Hochberg method. Pathway analysis was performed with gene set enrichment analysis (GSEA) (20), using both myoblast and myotube data. Curated gene sets (c2) in MSigDB were used in the analysis. Gene set size filters filtered out 1,053 gene sets, leaving 3,669 curated gene sets to take part in the analysis, with 2,000 gene set permutations to obtain the nominal P values. The data have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession no. GSE55650 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55650).

Quantitative real-time PCR.

Quantitative real-time PCR was performed on a LightCycler 480 (Roche) using either SYBR green or Taqman primers and probes. Multiplex reactions were performed in a final volume of 20 μl using the Quantifast Multiplex master mix (Qiagen). Single-color reactions were performed with Probes Master mix (Roche), using β₂-microglobulin as a reference gene. IL-6 (Hs00985639_m1) was obtained from Applied Biosystems as a predesigned Taqman primer-probe mix. Other primers and probes used were IL-8 (forward: GCAGAGCACACAAGCTTCTAGG; reverse: ATCAGGAAGGCTGCCAAGAGA; probe: TxRed-ACTTCCAAGCTGGCCGTGGC-BHQ2), monocyte chemoattractant protein-1 (MCP-1; forward: CTCAGCCAGATGCAATCAATG; reverse: AGATCTCCTTGGCCACAATGG; probe: Cy5-CAGTGCAGAGGCTCGCGAGC-BHQ2), and β₂-microglobulin (forward: GCCTGCCGTGTGAACCAT; reverse: TTACATGTCTCGATCCCACTTACCTATC; probe: FAM-TGACTTTGTCACAGCCCA-TAMRA). SYBR green reactions were performed using LightCycler 480 SYBR green I mastermix (Roche). Primers used were myxovirus (influenza virus) resistance 1, interferon-inducible protein p78 (MX1; forward: GTTTCCGAAGTGGACATCGCA; rev: CTGCACAGGTTGTTCTCAGC) and bone marrow stromal cell antigen 2 (BST2; forward: CACACTGTGATGGCCCTAATG; reverse: GTCCGCGATTCTCACGCTT). Results were analyzed using the standard curve method from a six-point serially diluted standard curve.

Western blotting.

Cells were lysed in extraction buffer [100 mM Tris·HCl, pH 7.4, 100 mM KCl, 1 mM EDTA, 25 mM KF, 1 mM benzamidine, 0.5 mM Na₃VO₄, and 0.1% (vol/vol) Triton X-100] plus protease inhibitor cocktail (Pierce) before sonicating for 10 s. Protein concentrations were determined spectrophotometrically at 595 nm by a Coomassie binding method. Ten-microgram samples were prepared in Laemmli sample buffer [0.125 M Tris·HCl, pH 6.8, 4% (wt/vol) SDS, 20% (vol/vol) glycerol, 10% (vol/vol) 2-mercaptoethanol, and 0.004% (wt/vol) bromophenol blue] and boiled for 5 min. After separation on 10% SDS-PAGE gels, proteins were transferred to PVDF membranes using a mini-Hoeffer gel transfer system. After incubation with the appropriate antibodies, detection took place using enhanced chemiluminescence. Densitometry was performed using a Bio-Rad Molecular Imager GS-800 calibrated densitometer and Quantity One software.

Cytokine ELISA.

Secretion of specific molecules was determined by enzyme-linked immunosorbent assay (ELISA) using the Single-Analyte ELISArray (Qiagen). Skeletal muscle cell cultures were allowed to differentiate for 7 days. Cells were incubated in fresh medium for the last 24 h of differentiation. After 24 h, medium was removed, centrifuged at 1,000 g for 10 min, and assayed for secretion of specific cytokines according to the manufacturer's protocol. A standard curve was generated by serial dilution of the provided antigen standard, and absorbance was read at 450 nm. Background absorbance was subtracted from the values, and the protein concentrations of the samples were calculated from the standard curve. The detection limit for each ELISA was as follows: IL-6, 5.01 pg/ml; IL-8, 64.16 pg/ml; and MCP-1, 13.90 pg/ml. The coefficients of variation for all ELISAs were <15%.

Glucose uptake.

Measurement of 2-deoxy-d-[2,6-³H]glucose uptake took place in 12-well cluster plates. Diabetic myotubes were treated for the last 18 h of differentiation with 10 μM SB-203580 before incubation in Krebs' buffer (136 mM NaCl, 4.7 mM KCl, 1.25 mM MgSO₄, 1.2 mM CaCl₂, and 20 mM HEPES, pH 7.4) with or without 100 nM insulin or cytochalasin B (10 μM) for 20 min; 0.1 mM 2-deoxyglucose and 0.5 μCi 2-deoxy-d-[2,6-³H]glucose were added to each well and incubated for a further 10 min. The reaction was stopped by washing the plate rapidly in ice-cold PBS. Cells were lysed in 0.05% SDS before scintillation counting and protein determination.

Statistical analysis.

For GSEA, a false discovery rate of <0.25 and a family-wise error rate (FWER) of <0.05 were considered significant. Upstream regulator analysis in diabetic myotubes was performed using ingenuity pathway analysis (IPA) (Ingenuity). An overlapping P value of <0.01 and activation z-score >2 (activating) and smaller than −2 (inhibiting) were considered significant.

All results are expressed as means ± SE. Student's t-tests were used to compare two groups and to test for changes after treatment with P < 0.05 was considered significant.

RESULTS

Microarray and gene set enrichment analyses.

DNA microarray technology was used to compare the differences in gene expression in both myoblasts and differentiated myotubes in type 2 diabetic skeletal muscle cell cultures and age- and BMI-matched controls (Table 1). GeneSpring analysis showed that in both myoblasts and myotubes there were no genes significantly altered at an individual level in the diabetic muscle cultures compared with controls after correction for multiple testing.

Therefore, GSEA was used to identify any coordinated changes in gene expression within specific gene sets and pathways. Because the previously identified defects of insulin action in the diabetic muscle cell cultures were apparent only with differentiation from myoblasts to myotubes (14), we focused on the analysis between diabetic and control myotubes.

Applying the stringent cutoff of FWER <0.05, 49 gene sets were significantly upregulated in diabetic myotubes compared with control myotubes. The top 10 upregulated gene sets in the diabetic myotubes are listed in Table 2. Most of the significantly upregulated gene sets are related to inflammation. In particular, gene sets obtained by the incubation of cell lines with interferons are particularly highly represented. Conversely, 13 gene sets were significantly downregulated in the diabetic compared with the control myotubes (the top 10 are listed in Table 3). It is worth noting that the inflammatory-related gene sets upregulated in the diabetic myotubes (Table 2) were not upregulated in the corresponding diabetic myoblast cultures.

Table 2.

Top 10 gene sets significantly upregulated in diabetic myotubes compared with control myotubes

Gene Set Designation	Description of Gene Set	No. of Genes Involved in Enrichment Score	FWER
HECKER_IFNB1_TARGETS	Genes transcriptionally modulated by interferon-β in blood cells of patients with MS	50 (84)	<0.001
RADAEVA_RESPONSE_TO_IFNA1_UP	Genes upregulated in response to interferon-α in hepatocytes	23 (51)	<0.001
LIANG_SILENCED_BY_METHYLATION_2	Genes upregulated by treatment with decitabine in T24 cells	23 (51)	<0.001
MOSERLE_IFNA_RESPONSE	Top 50 genes upregulated by interferon-α in ovarian cancer progenitor cells	19 (28)	<0.001
FARMER_BREAST_CANCER_CLUSTER_1	Interferon, T and B lymphocyte genes clustered together across breast cancer samples	18 (37)	<0.001
DAUER_STAT3_TARGETS_DN	Top 50 genes downregulated in A549 cells expressing STAT3	26 (47)	<0.001
BROWNE_INTERFERON_RESPONSIVE_GENES	Genes upregulated in primary fibroblasts after 6 h of treatment with interferon-α	38 (63)	<0.001
ALTEMEIER_RESPONSE_TO_LPS_WITH_MECHANICAL_VENTILATION	Genes upregulated in lung tissue after lipopolysaccharide aspiration and mechanical ventilation	57 (117)	<0.001
UROSEVIC_RESPONSE_TO_IMIQUIMOD	Interferon cluster genes upregulated in skin tumors treated with imiquimod	16 (22)	<0.001
BOSCO_INTERFERON_INDUCED_ANTIVIRAL_MODULE	Genes representing interferon-induced antiviral module in sputum during asthma exacerbations	30 (68)	<0.001

Analysis was performed using gene set enrichment analysis (GSEA), and a family-wise error rate (FWER) of <0.05 was considered significant. Nos. in parentheses indicate the size of the gene set.

Table 3.

Top significantly downregulated gene sets in diabetic myotubes

Gene Set Designation	Description of Gene Set	No. of Genes Involved in Enrichment Score	FWER
RICKMAN_HEAD_AND_NECK_CANCER_F	Genes identifying an intrinsic group in head and neck squamous carcinoma	31 (52)	<0.001
KUNINGER_IGF1_VS_PDGFB_TARGETS_UP	Genes upregulated in myoblasts by insulin-like growth factor I vs. platelet-derived growth factor	42 (72)	<0.001
TURASHVILI_BREAST_LOBULAR_CARCINOMA_VS_LOBULAR_NORMAL_DN	Genes downregulated in lobular carcinoma vs. normal lobular breast cells	32 (66)	<0.001
EBAUER_MYOGENIC_TARGETS_OF_PAX3_FOXO1_FUSION	Muscle development genes upregulated after knockdown of PAX3-FOXO1	26 (49)	<0.001
REACTOME_STRIATED_MUSCLE_CONTRACTION	Genes involved in striated muscle contraction	17 (27)	<0.001
TURASHVILI_BREAST_LOBULAR_CARCINOMA_VS_DUCTAL_NORMAL_UP	Genes upregulated in lobular carcinoma vs. normal ductal breast cells	29 (61)	<0.001
EBAUER_TARGETS_OF_PAX3_FOXO1_FUSION_UP	Genes upregulated after PAX3-FOXO1 knockdown	57 (184)	<0.001
REACTOME_MUSCLE_CONTRACTION	Genes involved in muscle contraction	18 (44)	<0.001
ANASTASSIOU_CANCER_MESENCHYMAL_TRANSITION_SIGNATURE	Genes in the mesenchymal transition signature common to all invasive cancer types	24 (60)	0.002
REACTOME_COLLAGEN_FORMATION	Genes involved in collagen formation	23 (56)	0.005

Analysis was performed using GSEA analysis, and a FWER of <0.05 was considered significant. Nos. in parentheses indicate the size of the gene set.

Upstream regulators of proinflammatory gene sets.

Given the preponderance of inflammatory-related gene sets upregulated in the diabetic myotubes, IPA was used to identify potential upstream regulators of these pathways. Table 4 lists the top regulators and their predicted activation state based on the direction of change in expression of genes in the diabetic myotubes compared with controls. The top predicted activator was TNF. Consistent with the GSEA, interferon-γ (IFNγ) was also predicted to activate the pathways upregulated in the diabetic myotubes. Taking the GSEA and IPA results together, gene expression of the top predicted regulators was measured by quantitative PCR to determine whether expression of these regulators was different between diabetic and control myotubes. TNF and interferon-α (IFNα) were expressed at very low levels in myoblasts, with levels increasing slightly in myotubes in both control and diabetic cells. However, there were no significant differences in expression between the diabetic and control myotubes. Similarly, interferon-β (IFNβ) and endothelial PAS domain protein 1 expression were also comparable between diabetic and control cells. IFNγ expression was undetectable in muscle cells, thus suggesting that these molecules are not the upstream regulators mediating the increased inflammatory profile observed in the isolated diabetic muscle cells (data not shown).

Table 4.

Upstream regulator analysis using IPA

Upstream Regulator	Molecule Type	Predicted Activation State	Activation z-Score	P Value of Overlap
TNF	Cytokine	Activated	3.424	1.14E-22
EPAS1	Transcription regulator	Activated	3.374	2.72E-07
IFNγ	Cytokine	Activated	3.246	2.53E-10
IGF-IR	Transmembrane receptor	Activated	3.231	1.32E-02
IFNα2	Cytokine	Activated	3.063	5.43E-04
Poly rl:rC-RNA	Chemical reagent	Activated	3.022	3.79E-04
IKZF1	Transcription regulator	Activated	2.967	1.45E-03
AHR	Ligand-dependent nuclear receptor	Activated	2.843	1.50E-06
IRF7	Transcription regulator	Activated	2.781	1.69E-02
8-Bromo-cAMP	Chemical reagent	Activated	2.774	1.00E-02
Sirolimus	Chemical drug	Inhibited	−2.943	6.16E-06
SB-203580	Chemical kinase inhibitor	Inhibited	−2.940	2.10E-10
Actinomycin D	Chemical drug	Inhibited	−2.917	1.24E-05
Staurosporine	Chemical kinase inhibitor	Inhibited	−2.600	1.80E-05
SREBF1	Transcription regulator	Inhibited	−2.598	1.68E-03
SREBF2	Transcription regulator	Inhibited	−2.588	4.21E-04

EPAS1, endothelial PAS domain protein 1; IGF-IR, IGF-I receptor; IKZF1, IKAROS family zinc finger 1; AHR, aryl hydrocarbon receptor; IRF7, interferon regulatory factor 7; SREBF1 and -2, sterol regulatory element-binding transcription factor 1 and 2, respectively. Upstream regulator analysis was used to identify potential upstream factors involved in the increased inflammatory profile observed in the diabetic myotubes compared with control myotubes. The top 10 predicted activators and the 6 predicted inhibitors are ranked based on activation score.

p38 MAPK activation and inhibition in diabetic myotubes.

Another predicted regulator was the p38 MAPK inhibitor SB-203580 (Table 4). p38 MAPK is a stress kinase that occupies a central point in the pathway regulating inflammatory processes, and increased activation of this protein has been reported previously in skeletal muscle from type 2 diabetic patients (11). Therefore, activation of p38 MAPK was examined in the control and diabetic cultures in day 7 myotubes. Phosphorylation of p38 MAPK was found to be significantly increased under both basal (P = 0.02) and 30-min insulin stimulation (P = 0.002) conditions in the diabetic myotubes compared with controls (Fig. 1). Of all the key predicted regulators identified using IPA and described above, p38 MAPK was the only one examined that was significantly different between diabetic and control myotube cultures.

Fig. 1.

Phospho-p38 MAPK in 6 control and 6 diabetic day 7-differentiated myotubes. Muscle cell cultures were differentiated for 7 days before being treated with 100 nM insulin for 30 min and before protein extracts were made. Western blots were performed using the appropriate antibodies. Densitometry is presented as the mean ± SE from 6 separate cultures in each group. −, Basal; +, insulin stimulation. Open bars, basal; black bars, insulin stimulated. *P = 0.02; **P = 0.002.

This increase in p38 MAPK phosphorylation led to the following question: Would inhibition of p38 MAPK with SB-203580 improve the inflammatory profile of the diabetic myotubes and increase insulin-stimulated glucose uptake? We examined the expression and secretion of the proinflammatory cytokines IL-6, IL-8, and MCP-1 and the expression of MX1 and BST2. These were chosen because they satisfy one or more of the following criteria: 1) they are in the list of top genes upregulated in the diabetic cells compared with controls (Table 5), 2) they are molecules identified by GSEA as being involved in the enrichment score for the top gene sets upregulated in the diabetic myotubes, or 3) they are target molecules of the upstream regulators identified by Ingenuity. Ingenuity analysis predicted that SB-203580 would affect 31 target molecules, 17 of which were also present in the other upstream regulator groups. Day 7-differentiated control and diabetic myotubes were treated for either the last 18 h of differentiation or for the 7-day duration of differentiation with 10 μM SB-203580. In keeping with the gene set analysis data, there was a pattern of upregulation of cytokine expression in the diabetic myotubes (Figs. 2 and 3). After 18 h of treatment, expression of IL-6, IL-8, and MCP-1 decreased in both control and diabetic myotubes (Fig. 2A). There were no significant changes in MX1 or BST2 expression (Fig. 2B). Similarly, after 7 days of treatment, IL-6, IL-8, and MCP-1 decreased in both the control and diabetic cultures (Fig. 3A). There was no change in MX1 or BST2 expression in control cultures, whereas BST2 was significantly decreased in the diabetic cultures (Fig. 3B). Release of IL-6, IL-8, and MCP-1 into the medium was also significantly decreased after SB-203580 treatment (data not shown). However, SB-203580 treatment did not improve insulin-stimulated glucose uptake in the diabetic myotube cultures after either 18 h (Fig. 4A) or 7 days of treatment (Fig. 4B).

Table 5.

Top 20 probe sets and their corresponding GO process, upregulated with differentiation in the diabetic subjects compared with the controls and ranked by fold change

Probe Set ID	Gene Symbol	Fold Change	P Value	GO Biological Process	Secreted?
202859_x_at	IL8	11.7	0.03	Inflammatory response	Yes
233533_at	KRTAP1-5	8.7	0.01	Unknown
202086_at	MX1	7.3	0.04	Defense response
203001_s_at	STMN2	6.1	0.04	Microtubule organization
202410_x_at	IGF2	5.7	0.01	MAPK cascade	Yes
211356_x_at	LEPR	5.0	0.02	Cytokine-mediated signaling pathway
201641_at	BST2	4.5	0.02	Immune response
202803_s_at	ITGB2	4.5	0.0009	Toll-like receptor signaling pathway
52837_at	KIAA1644	4.2	0.01	Unknown
204602_at	DKK1	4.2	0.04	Wnt receptor signaling pathway	Yes
219602_s_at	PIEZO2	3.9	0.03	Ion transport
204415_at	IFI6	3.9	0.02	Cytokine-mediated signaling pathway
201348_at	GPX3	3.8	0.04	Glutathione metabolic process	Yes
209869_at	ADRA2A	3.7	0.04	Cytokine production
242871_at	PAQR5	3.6	0.03	Cell differentiation
218469_at	GREM1	3.6	0.01	Cell differentiation	Yes
205258_at	INHBB	3.5	0.008	Defense response	Yes
229450_at	IFIT3	3.5	0.04	Cytokine-mediated signaling pathway
204597_x_at	STC1	3.4	0.01	Ca2+ homeostasis	Yes
203698_s_at	FRZB	3.4	0.02	Wnt receptor signaling pathway	Yes

GO, gene ontology.

Uncorrected P values were calculated by t-test with equal variance. P < 0.05 was considered significant.

Fig. 2.

A: quantitative PCR (qPCR) analysis of cytokines after 18 h of SB-203580 treatment. Control (left) and diabetic cultures (right) were differentiated for 7 days and treated with 10 μM SB-203580 for the last 18 h of differentiation prior to RNA extraction. Data are normalized to the reference gene β₂-microglobulin and are expressed as the mean ± SE from 6 cultures performed in triplicate. Black bars, untreated; open bars, SB-203580 treated. *P < 0.05, **P = 0.003, and ***P < 0.005 vs. untreated. B: qPCR analysis of MX1 and BST2 expression after 18 h of SB-203580 treatment. Control (left) and diabetic cultures (right) were differentiated for 7 days and treated with 10 μM SB-203580 for the last 18 h of differentiation prior to RNA extraction. Data are normalized to the reference gene β₂-microglobulin and are expressed as the mean ± SE from 6 cultures performed in triplicate. Black bars, untreated; open bars, SB-203580 treated. GOI, gene of interest; MX1, myxovirus (influenza virus) resistance 1, interferon-inducible protein p78; BST2, bone marrow stromal cell antigen 2.

Fig. 3.

A: qPCR analysis of cytokines after 7 days of SB-203580 treatment. Control (left) and diabetic cultures (right) were differentiated for 7 days and treated with 10 μM SB-203580 for the duration of differentiation prior to RNA extraction. Data are normalized to the reference gene β₂-microglobulin and are expressed as the mean ± SE from 6 cultures performed in triplicate. Black bars, untreated; open bars, SB-203580 treated. B: qPCR analysis of MX1 and BST2 expression after 7 days of SB-203580 treatment. Control (left) and diabetic cultures (right) were differentiated for 7 days and treated with 10 μM SB-203580 for the duration of differentiation prior to RNA extraction. Data are normalized to the reference gene β₂-microglobulin and are expressed as the mean ± SE from 6 cultures performed in triplicate. Black bars, untreated; open bars, SB-203580 treated. *P < 0.05, **P = 0.002, and ****P < 0.0001 vs. untreated.

Fig. 4.

A: insulin-stimulated glucose uptake in diabetic muscle cultures after 18 h of SB-203580 treatment. Day 7 myotubes were treated with p38 MAPK inhibitor for the last 18 h of differentiation before glucose uptake was measured. Data are presented as the mean ± SE from 5 cultures. Open bars, basal; black bars, insulin stimulated. B: insulin-stimulated glucose uptake in diabetic muscle cultures after 7 days of SB-203580 treatment. Myotubes were treated for the duration of differentiation before glucose uptake was measured. Data are presented as the mean ± SE from 6 cultures. Open bars, basal; black bars, insulin stimulated. **P = 0.001; ***P = 0.0007; ****P < 0.0001.

DISCUSSION

The key finding of this work was the coordinated upregulation of inflammatory pathways in differentiated diabetic myotubes identified using both GSEA and Ingenuity analyses. Of the potential upstream regulators of these pathways, we found that p38 MAPK activation was increased in the diabetic myotubes and selective p38 MAPK inhibition decreased the inflammatory profile in these cultures. The implications of these findings are that skeletal muscle contributes to the inflammatory process in type 2 diabetes and involves activation of the p38 MAPK pathway.

Increased activation of p38 MAPK has been demonstrated previously in both skeletal muscle (11) and adipocytes (2) from type 2 diabetes patients. However, neither study explored whether p38 MAPK inhibition directly affected insulin action in the tissues derived from the diabetic patients. We are the first to show that p38 MAPK inhibition in diabetic skeletal muscle cells did not improve the retained defect of insulin-stimulated glucose uptake despite decreasing inflammatory cytokine expression. We also observed a decrease in cytokine expression after p38 MAPK inhibition in the control cultures. This indicates that p38 MAPK regulates cytokine expression in nondiabetic muscle but also that the activation is increased in muscle from diabetic subjects. Conflicting findings have been reported in relation to p38 MAPK activation and insulin action under other conditions. In a model of insulin resistance in 3T3-L1 adipocytes, inhibition of p38 MAPK did not prevent insulin-induced loss of IRS-1 protein (2). Hepatic expression of a dominant-negative p38 MAPK in vivo lowered fasting insulin levels, whereas overexpression of wild-type p38 resulted in increased serine phosphorylation on IRS-1 (7). Conversely, in the liver of ob/ob mice expressing constitutively active MKK6, an upstream activator of p38 MAPK, increased p38 MAPK activity was associated with improved glucose tolerance (12).

Cytokine expression can be increased via a number of signaling pathways in skeletal muscle, including p38 MAPK, NF-κB, JNK, and the JAK-STAT pathway. However, the pattern of inflammatory expression may differ. This is illustrated by the recent report of Green at al. (6). They studied cultured skeletal muscle cells from obese diabetic patients and found evidence of increased NF-κB activation. This was associated with a trend toward increased TNFα and decreased IL-6 expression. They found that suppression of NF-κB activity via AMPK activation normalized the cytokine response but did not improve insulin action. This is in keeping with our own findings and indicates that although upregulation of inflammatory-related genes through the activation of different signaling pathways is a feature of cultured diabetic muscle cells, the accumulating evidence suggests that this proinflammatory state does not contribute directly to the retained defects of insulin action.

A number of studies describing microarray data from native skeletal muscle have been published (15, 16, 19), and they have identified altered expression of genes involved with metabolism in diabetic muscle. However, this altered gene expression is likely to result from the combination of retained primary genetic/epigenetic and secondary metabolic/lifestyle effects. It is worth noting that glycemic control was generally poor in our diabetic patients despite high-dose insulin treatment. Hyperglycemia per se can contribute to the insulin-resistant state in vivo, and so to limit any residual confounding effect, we cultured the diabetic and control muscle cells under standardized conditions out to passages 5–8 before conducting our experiments. An earlier study of gene expression by microarray in cultured human diabetic and control muscle cells found no robust differences between the two groups (5). However, it is interesting to note that a proinflammatory interferon-γ pathway was in the top 10 gene sets upregulated in the diabetic cultures, although this was of nominal statistical significance. This latter study was conducted on male participants. Although our study included males and females, it has been shown previously that age, but not sex, influences gene expression patterns in skeletal muscle (10).

It is widely accepted that low-grade inflammation is a feature of type 2 diabetes. Our work supports the growing body of evidence that skeletal muscle is involved in this proinflammatory state. This could in turn contribute indirectly to the peripheral insulin resistance in type 2 diabetes. Increased cytokine release, particularly MCP-1, would be predicted to promote local inflammatory cell infiltration and amplification of the inflammatory process. This is supported by the observation that CD163 macrophage-specific antigen concentration and macrophage content are increased in skeletal muscle from type 2 diabetic patients (21) and in murine models of obesity and insulin resistance (17), respectively.

In conclusion, we found an increased inflammatory profile and p38 MAPK activation in differentiated myotubes from insulin-resistant type 2 diabetic patients and that inhibition of p38 MAPK decreased cytokine expression but did not affect insulin-stimulated glucose uptake.

GRANTS

This research was supported by Diabetes UK, Newcastle Hospitals National Health Service (NHS) charity, and by the National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre based at Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health. D. A. Gunn is supported by Unilever.

DISCLOSURES

No potential conflicts of interest relevant to this article, financial or otherwise, are reported. The authors have nothing to disclose.

AUTHOR CONTRIBUTIONS

A.E.B., J.P., R.B., P.D.M., S.J.Y., and M.W. conception and design of research; A.E.B. and J.P. performed experiments; A.E.B., R.B., P.A., and D.A.G. analyzed data; A.E.B., P.A., D.A.G., and M.W. interpreted results of experiments; A.E.B. prepared figures; A.E.B. and M.W. drafted manuscript; A.E.B., J.P., R.B., P.A., P.D.M., S.J.Y., and M.W. edited and revised manuscript; A.E.B., J.P., R.B., P.A., D.A.G., P.D.M., S.J.Y., and M.W. approved final version of manuscript.