Monocyte-to-macrophage differentiation is a critical event that accentuates atherosclerosis by promoting an inflammatory environment within the vessel wall. In this study, we investigated the molecular mechanisms responsible for monocyte-to-macrophage differentiation and, subsequently, the effect of metformin in regressing angiotensin II (Ang-II)-mediated atheromatous plaque formation in ApoE−/− mice. AMPK activity was dose and time dependently downregulated during phorbol myristate acetate (PMA)-induced monocyte-to-macrophage differentiation, which was accompanied by an upregulation of proinflammatory cytokine production. Of note, AMPK activators metformin and AICAR significantly attenuated PMA-induced monocyte-to-macrophage differentiation and proinflammatory cytokine production. However, inhibition of AMPK activity alone by compound C was ineffective in promoting monocyte-to-macrophage differentiation in the absence of PMA. On the other hand, inhibition of c-Jun N-terminal kinase activity inhibited PMA-induced inflammation but not differentiation, suggesting that inflammation and differentiation are independent events. In contrast, inhibition of STAT3 activity inhibited both inflammation and monocyte-to-macrophage differentiation. By decreasing STAT3 phosphorylation, metformin and AICAR through increased AMPK activation caused inhibition of monocyte-to-macrophage differentiation. Metformin attenuated Ang-II–induced atheromatous plaque formation and aortic aneurysm in ApoE−/− mice partly by reducing monocyte infiltration. We conclude that the AMPK-STAT3 axis plays a pivotal role in regulating monocyte-to-macrophage differentiation and that by decreasing STAT3 phosphorylation through increased AMPK activity, AMPK activators inhibit monocyte-to-macrophage differentiation.

Substantial evidence implicates macrophages as abundantly present at all stages of the atherosclerotic disease process (1). Macrophages fuel an inflammatory environment in atherosclerotic neointima by exuding a diverse repertoire of inflammatory mediators (2). Continuous production of proinflammatory cytokines and chemokines augment the influx and retention of other inflammatory cells' migration of vascular smooth muscle cells from media to intima (2,3). All these events lead to the proximal exacerbation of arterial damage. Restraining monocyte/macrophage recruitment into the aortic wall may attenuate the risk of atherosclerosis; hence, strategies to prevent monocyte infiltration and differentiation comprise an attractive approach for the treatment of atherosclerosis and other related vascular disorders.

Metformin, a widely used antidiabetic drug, has beneficial effects in reducing cardiovascular complications in addition to glycemic control (4). The UK Prospective Diabetes Study demonstrated that metformin is associated with a significant decrease in the incidence of myocardial infarction (5). Another clinical study reported that metformin in diabetic patients significantly attenuates the progression of carotid artery intima-media thickness, a known index of atherosclerotic progression (6). Earlier studies showed that the pleiotropic effects of metformin are partly mediated by the activation of AMPK (7,8). AMPK functions as a fuel gauge, sensing the changes in the energy status of the cell and, thus, playing a critical role in regulating systemic energy balance (9,10). AMPK is activated allosterically by an increase in the intracellular AMP/ATP ratio (10). AMPK is also sensitive to the lipid status of a cell, and its activation is influenced by the availability of intracellular fat deposits (11). AMPK-mediated signaling events are downregulated by lipopolysaccharides (LPSs), free fatty acids, high-fat diets, and lipid infusion in macrophages and endothelial cells (12,13). Activation of the AMPK signaling pathway suppresses proinflammatory responses and promotes macrophage polarization to an anti-inflammatory functional phenotype in macrophages (14). In addition, decreased AMPK activity with increased STAT3 in smooth muscle cells has been shown to promote receptor for advanced glycation end product signaling–induced neointima formation in response to arterial injury (15).

Monocyte-to-macrophage differentiation is characterized by the activation of various metabolic and inflammatory signaling networks. Although the potential role of AMPK in mediating anti-inflammatory effects against various stimulations is known, its specific role in regulating monocyte-to-macrophage differentiation still remains elusive. In this study, we investigated the effects of metformin and AICAR on the monocyte-to-macrophage differentiation process using a human monocytic leukemia (THP-1) cell line. AMPK activators attenuated the monocyte-to-macrophage differentiation and the proinflammatory signaling events associated during the differentiation process by a novel mechanism involving AMPK-1α–mediated STAT3 regulation. Furthermore, metformin significantly attenuated angiotensin II (Ang-II)-induced plaque formation and aortic aneurysm (AA) in apolipoprotein E knockout (ApoE−/−) mice, possibly by impairing monocyte recruitment and its differentiation into macrophages in the arterial vessel wall.

Cell Culture and Differentiation

Cell culture procedures are described in the Supplementary Data. For differentiation of monocytes to macrophages, THP-1 cells were seeded at a density of 2 × 105/mL and stimulated with phorbol myristate acetate (PMA).

Animal Experiments

Experiments were conducted in 2-month-old male ApoE−/− mice according to the guidelines formulated for the care and use of animals in scientific research (Indian Council of Medical Research, India) at a CPCSEA (Committee for the Purpose of Control and Supervision of Experiments on Animals)–registered animal facility. The experimental protocols were approved by the Institutional Animal Ethical Committee at the Council of Scientific and Industrial Research (CSIR)–Indian Institute of Chemical Technology (IICT/CB/SK/20/12/2013/10). Animals were randomly divided into three groups of 12: 1) control, 2) Ang-II treatment, and 3) Ang-II + metformin treatment. Ang-II and metformin treatment groups received Ang-II (Sigma) at a dose of 1.44 mg/kg/day as described previously (1618) for 6 weeks through a subcutaneous route, whereas the control group received normal saline. The metformin treatment group received the drug at a dose of 100 mg/kg/day in normal drinking water. All animals were fed normal chow throughout the study. After 6 weeks, animals were killed per standard protocol. The Supplementary Data describe the other methodologies adopted in this study.

Statistical Analysis

Data are expressed as mean ± SD. The significance of differences between groups was examined using either Student t test or one-way ANOVA as appropriate. P < 0.05 was considered statistically significant.

Metformin Inhibits PMA-Induced Monocyte-to-Macrophage Differentiation in THP-1 Monocytes

PMA-induced THP-1 monocyte differentiation is a well-accepted in vitro model for studying the monocyte-to-macrophage differentiation process (19). To study the effect of metformin on PMA-induced monocyte-to-macrophage differentiation, THP-1 monocytes were treated with PMA (100 nmol/L) for 48 h in the presence or absence of metformin (0–2 mmol/L). The morphological observations by phase contrast microscopy indicated that metformin dose dependently inhibited PMA-induced monocyte adherence (Fig. 1A). In addition, PMA-induced increase in autofluorescence, a distinguished feature of macrophage differentiation owing to the increased cell size by flow cytometry, was significantly inhibited in the presence of metformin (Fig. 1B). Under these conditions, the mitochondrial content, also a measure of monocyte differentiation by MitoTracker staining, was greatly reduced upon metformin treatment (Fig. 1C). To rule out the possibility that the inhibition of monocyte-to-macrophage differentiation by metformin was not due to its cytotoxic effect, we measured cell viability. Metformin did not elicit any appreciable cell death in monocytes at the indicated concentrations (Fig. 1D). Monocyte-to-macrophage differentiation is associated with a loss or gain of expression of an array of genes/proteins destined to perform specialized functions. Along these lines, we measured the transcript and protein levels of SR-A1, LOX-1, and CD-36 during monocyte differentiation in the presence or absence of metformin. As expected, the levels of CD-36 and LOX-1, known macrophage markers, were increased with PMA stimulation. However, metformin treatment dose dependently reduced PMA-induced CD-36, LOX-1, and SR-A1 levels (Fig. 1E and F), which are predominantly expressed in macrophages and are associated with the uptake of lipid molecules in these cells, enhancing the foam cell formation. Because metformin clearly abrogated PMA-induced monocyte-to-macrophage differentiation, we studied whether AICAR, another known AMPK activator, also imposes a similar effect. We found, similar to metformin, that AICAR significantly inhibited monocyte differentiation based on morphological observations by phase contrast microscopy (Fig. 1G) and altered the expression levels of CD-36, SR-A1, and LOX-1 in a dose-dependent fashion (Fig. 1H and I). These results confirm that AMPK activators metformin and AICAR not only inhibit monocyte-to-macrophage differentiation but also regulate the expression of scavenger receptors.

Figure 1

AMPK activators inhibit PMA-induced monocyte differentiation. THP-1 monocytes were pretreated with various concentrations (0–2 mmol/L) of metformin for 2 h followed by stimulation with PMA (100 nmol/L). A: Phase contrast images indicate the inhibition of PMA-induced monocyte adherence by metformin treatment after 48 h. B: Same as A except autofluorescence was measured by FACS analysis. C: Same as A except cell size was measured by MitoTracker dye. D: The effect of metformin in the presence or absence of PMA on cell viability measured after 48 h using the trypan blue dye exclusion method. E and F: Expression of differentiation markers: Transcript levels (E) of the indicated genes were measured by RT-PCR after 24 h, and protein levels (F) were measured by Western blotting after 48 h. G: Phase contrast images indicating the inhibition of PMA-induced monocyte adherence by AICAR after 48 h. H and I: Expression of differentiation markers showing protein levels after 48 h (H) and transcript levels of the indicated genes after 24 h (I). Data are mean ± SD. *P < 0.05 vs. no treatment; #P < 0.05 vs. PMA control. MFI, mean fluorescence intensity.

Figure 1

AMPK activators inhibit PMA-induced monocyte differentiation. THP-1 monocytes were pretreated with various concentrations (0–2 mmol/L) of metformin for 2 h followed by stimulation with PMA (100 nmol/L). A: Phase contrast images indicate the inhibition of PMA-induced monocyte adherence by metformin treatment after 48 h. B: Same as A except autofluorescence was measured by FACS analysis. C: Same as A except cell size was measured by MitoTracker dye. D: The effect of metformin in the presence or absence of PMA on cell viability measured after 48 h using the trypan blue dye exclusion method. E and F: Expression of differentiation markers: Transcript levels (E) of the indicated genes were measured by RT-PCR after 24 h, and protein levels (F) were measured by Western blotting after 48 h. G: Phase contrast images indicating the inhibition of PMA-induced monocyte adherence by AICAR after 48 h. H and I: Expression of differentiation markers showing protein levels after 48 h (H) and transcript levels of the indicated genes after 24 h (I). Data are mean ± SD. *P < 0.05 vs. no treatment; #P < 0.05 vs. PMA control. MFI, mean fluorescence intensity.

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Metformin Inhibits PMA-Induced Inflammation During Monocyte Differentiation

Besides monocyte-to-macrophage differentiation per se, inflammatory cascades evoked during the differentiation process are critically involved in the acceleration of the atherosclerotic process. To gain insight into the effect of AMPK activators in regulating proinflammatory signaling pathways during monocyte-to-macrophage differentiation, we measured interleukin (IL)-1β, tumor necrosis factor (TNF)-α, and MCP-1 levels in monocytes stimulated with PMA (100 nmol/L). All these cytokines started to increase from 12 h and reached maximum concentrations by 48 h (Fig. 2A–C), suggesting that PMA-induced monocyte differentiation is accompanied by an increased production of proinflammatory cytokines. Next, we measured PMA-induced proinflammatory cytokines in the presence of either metformin (0.5–2 mmol/L) or AICAR (0.5–2 mmol/L) and found that both dose dependently reduced PMA-induced IL-1β, TNF-α, and MCP-1 levels (Fig. 2D and E).

Figure 2

Metformin and AICAR inhibit PMA-induced inflammation during monocyte differentiation. THP-1 monocytes were stimulated with PMA (100 nmol/L) for 6–48 h, and IL-1β (A), TNF-α (B), and MCP-1 (C) levels were measured in the conditioned medium by ELISA. D: Cells were pretreated with metformin (0–2 mmol/L) for 2 h followed by stimulation with PMA (100 nmol/L) for 48 h, and IL-1β, TNF-α, and MCP-1 were measured in the conditioned medium. E: Same as D except cells were pretreated with AICAR (0–2 mmol/L) for 2 h. F: Same as AC except MMP-9 and MMP-2 activities were measured using gelatin zymography. G: Same as D except MMP-9 and MMP-2 activities were measured. H: Same as G except cells were pretreated with AICAR (0–2 mmol/L). I and J: Same as D except mRNA levels of indicated inflammatory markers were measured after 24 h in cells pretreated with either metformin (I) or AICAR (J). Data are mean ± SD. *P < 0.05 vs. no treatment; #P < 0.05 vs. PMA control.

Figure 2

Metformin and AICAR inhibit PMA-induced inflammation during monocyte differentiation. THP-1 monocytes were stimulated with PMA (100 nmol/L) for 6–48 h, and IL-1β (A), TNF-α (B), and MCP-1 (C) levels were measured in the conditioned medium by ELISA. D: Cells were pretreated with metformin (0–2 mmol/L) for 2 h followed by stimulation with PMA (100 nmol/L) for 48 h, and IL-1β, TNF-α, and MCP-1 were measured in the conditioned medium. E: Same as D except cells were pretreated with AICAR (0–2 mmol/L) for 2 h. F: Same as AC except MMP-9 and MMP-2 activities were measured using gelatin zymography. G: Same as D except MMP-9 and MMP-2 activities were measured. H: Same as G except cells were pretreated with AICAR (0–2 mmol/L). I and J: Same as D except mRNA levels of indicated inflammatory markers were measured after 24 h in cells pretreated with either metformin (I) or AICAR (J). Data are mean ± SD. *P < 0.05 vs. no treatment; #P < 0.05 vs. PMA control.

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Macrophage-derived matrix metalloproteases (MMPs) are highly expressed in atherosclerotic plaques and have been implicated in the rupture of plaque structure. Because MMP-9 seems to be a key regulator of vascular complications, we studied the effect of PMA on MMP-9 activity during monocyte-to-macrophage differentiation. PMA time dependently increased MMP-9 activity (Fig. 2F). However, under these conditions, MMP-2 activity was unchanged (Fig. 2F). Of note, PMA-induced MMP-9 activity was dose dependently inhibited by both metformin and AICAR treatments (Fig. 2G and H). Next, to know whether the inhibitory effects of metformin and AICAR on proinflammatory cytokine production and MMP-9 activity were due to their ability to repress the transcriptional activation of these genes, mRNA levels by RT-PCR were measured after 24 h. Metformin and AICAR dose dependently decreased the transcript levels of IL-1β, TNF-α, lipoprotein lipase (LPL), MMP-1, and MMP-9 (Fig. 2I and J). All these data suggest that metformin and AICAR along with their ability to inhibit monocyte-to-macrophage differentiation also inhibit the inflammatory pathways associated with this process.

Inactivation of AMPK-1α Phosphorylation Promotes Monocyte-to-Macrophage Differentiation and Inflammation

Because metformin and AICAR, the two known activators of AMPK, inhibited monocyte differentiation as well as proinflammatory cytokine production in PMA-treated monocytes, we investigated whether AMPK phosphorylation status was altered during PMA-induced monocyte differentiation. Monocytes were treated with PMA (0–200 nmol/L) for a 48 h. PMA dose dependently reduced AMPK-1α phosphorylation (Fig. 3A). The levels of phospho-AMPK-1α started to decrease by 6 h upon PMA (100 nmol/L) stimulation and completely disappeared by 24 h (Fig. 3B). Furthermore, to see whether PKC activation was involved in regulating AMPK, we measured phospho-AMPK levels in PMA-stimulated monocytes in the presence or absence of calphostin C (0.5–4 μmol/L), a general PKC inhibitor, and found that calphostin C treatment could not restore the PMA-induced inhibition of phospho-AMPK levels (Supplementary Fig. 1A). Calphostin C also caused cell death beyond 2 μmol/L (Supplementary Fig. 1B). Additionally, calphostin C treatment did not have any effect on either PMA-induced monocyte-to-macrophage differentiation (data not shown) or inflammation (Supplementary Fig. 1C and D). Next, to see whether metformin-induced inhibition of monocyte-to-macrophage differentiation was AMPK dependent, we measured phospho-AMPK-1α levels in cells treated with various concentrations of metformin. Metformin dose and time dependently increased AMPK-1α phosphorylation in PMA-treated monocytes (Fig. 3C and D). Similar results were obtained in AICAR-treated cells (Fig. 3E). These findings suggest that phosphorylation of AMPK plays a significant role during monocyte-to-macrophage differentiation and that the PKC-mediated pathway is not involved in metformin-induced AMPK activation. To further understand the role of AMPK phosphorylation in regulating the extent of monocyte differentiation, we treated cells with compound C, an AMPK inhibitor, and found that compound C treatment alone dose dependently decreased AMPK-1α phosphorylation in monocytes (Fig. 3E). However, compound C failed to promote monocyte-to-macrophage differentiation on its own in the absence of PMA, as evidenced by morphological observations (Fig. 3F). In agreement with this result, compound C treatment alone, unlike PMA, failed to induce IL-1β, TNF-α, and MCP-1 production in monocytes (Fig. 3G). However, coincubation of compound C along with PMA exacerbated PMA-induced monocyte-to-macrophage differentiation and proinflammatory cytokine production (Fig. 3F and G). These results indicate that although AMPK-1α phosphorylation status plays a crucial role during the PMA-induced monocyte-to-macrophage differentiation process, alterations in AMPK-1α activity alone are not sufficient to regulate the differentiation process. This unexpected result led us to search for other signaling pathways responsible for monocyte differentiation that are dependent on or independent of AMPK phosphorylation induced by PMA.

Figure 3

Inhibition of AMPK-1α phosphorylation promotes monocyte differentiation and inflammation. A: THP-1 monocytes were treated with increasing concentrations of PMA (0–200 nmol/L) for 48 h, and p-AMPK-1α and AMPK-1α protein levels were measured by Western blotting. B: Same as A except cells were treated with PMA (100 nmol/L) for 6–48 h. C: THP-1 monocytes were pretreated with metformin (0–2 mmol/L) for 2 h followed by stimulation with PMA (100 nmol/L) for 24 h, and p-AMPK-1α and AMPK-1α protein levels were measured. D: Same as C except cells were pretreated with metformin (2 mmol/L) followed by stimulation with PMA (100 nmol/L) for 6–48 h. E: Same as C except cells were pretreated with AICAR (0–2 mmol/L). F: Monocytes were treated with compound C (0–5 μmol/L) alone for 24 h, and p-AMPK-1α and AMPK-1α levels were measured by Western blotting. G: Cells were pretreated with compound C (5 μmol/L) in the presence or absence of PMA (100 nmol/L) for 48 h, and cell adherence was monitored by phase contrast microscopy. H: Cells were pretreated with compound C (0–5 μmol/L) in the presence or absence of PMA (100 nmol/L) for 48 h, and IL-1β, TNF-α, and MCP-1 levels were measured in the conditioned medium by ELISA. Data are mean ± SD. #P < 0.05 vs. PMA control. Thr, threonine.

Figure 3

Inhibition of AMPK-1α phosphorylation promotes monocyte differentiation and inflammation. A: THP-1 monocytes were treated with increasing concentrations of PMA (0–200 nmol/L) for 48 h, and p-AMPK-1α and AMPK-1α protein levels were measured by Western blotting. B: Same as A except cells were treated with PMA (100 nmol/L) for 6–48 h. C: THP-1 monocytes were pretreated with metformin (0–2 mmol/L) for 2 h followed by stimulation with PMA (100 nmol/L) for 24 h, and p-AMPK-1α and AMPK-1α protein levels were measured. D: Same as C except cells were pretreated with metformin (2 mmol/L) followed by stimulation with PMA (100 nmol/L) for 6–48 h. E: Same as C except cells were pretreated with AICAR (0–2 mmol/L). F: Monocytes were treated with compound C (0–5 μmol/L) alone for 24 h, and p-AMPK-1α and AMPK-1α levels were measured by Western blotting. G: Cells were pretreated with compound C (5 μmol/L) in the presence or absence of PMA (100 nmol/L) for 48 h, and cell adherence was monitored by phase contrast microscopy. H: Cells were pretreated with compound C (0–5 μmol/L) in the presence or absence of PMA (100 nmol/L) for 48 h, and IL-1β, TNF-α, and MCP-1 levels were measured in the conditioned medium by ELISA. Data are mean ± SD. #P < 0.05 vs. PMA control. Thr, threonine.

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Inflammation and Differentiation Are Independent Events During Monocyte-to-Macrophage Differentiation: c-Jun N-Terminal Kinase Plays a Role in Regulating Inflammation but Not Differentiation

Induction of peroxisome proliferator–activated receptor (PPAR)-γ expression and LPL activity is a common feature during monocyte and adipocyte differentiation (20,21). Activation of c-Jun N-terminal kinase (JNK) plays a central role in IL-1β induction during monocyte differentiation (22). To study the possible involvement of JNK and other signaling pathways during monocyte-to-macrophage differentiation, we evaluated the effect of pioglitazone (PPAR-γ agonist), GW9882 (PPAR-γ antagonist), orlistat (LPL inhibitor), p38 inhibitor, SP600125 (JNK inhibitor), U-0126 (extracellular signal–related kinase 1/2 inhibitor), and Bay-117085 (nuclear factor-κB inhibitor), with concentrations ranging from 1 to 40 μmol/L, on PMA-induced monocyte-to-macrophage differentiation and the associated inflammation during this process. Except for U-0126 (2.5 μmol/L) and Bay-117085 (2.5 μmol/L), other inhibitors did not cause cell death at these concentrations in monocytes (data not shown). Additionally, none of these compounds showed an appreciable effect on monocyte-to-macrophage differentiation (data not shown). However, only SP600125 significantly inhibited IL-1β, TNF-α, and MCP-1 concentrations (Fig. 4A) and MMP-9 activity (Fig. 4B) in monocytes stimulated with PMA. Along these lines, SP600125 dose dependently inhibited proinflammatory cytokine production in PMA-stimulated monocytes (Fig. 4C), suggesting that PMA promotes an inflammatory environment by activating the JNK signaling pathway in monocytes. Furthermore, it appears that PPAR-γ, LPL, and JNK signaling pathways may not be directly involved in monocyte-to-macrophage differentiation. To confirm this result, we measured the transcript levels of LOX-1 and CD-36 (macrophage markers) along with proinflammatory cytokines in monocytes treated with JNK inhibitor in the presence of PMA. As expected and in agreement with the results shown in Fig. 4A, JNK inhibitor dose dependently decreased mRNA levels of IL-1β, TNF-α, and MCP-1 but not LOX-1 and CD-36 (Fig. 4D). These observations clearly indicate that PMA-induced inflammation and differentiation are independent events. Because metformin inhibited proinflammatory cytokine production in PMA-treated monocytes, we were interested in its effect on JNK phosphorylation status and its substrate c-Jun. For this, we treated monocytes with metformin (0.5–2 mmol/L) in the presence of PMA (100 nmol/L) and found that metformin dose dependently reduced phosphorylation of both JNK and c-Jun (Fig. 4E). This finding suggests that JNK activation is pivotal in mediating the inflammatory signaling cascade and that metformin exerts its anti-inflammatory effects at least in part by inhibiting the activation of the JNK signaling cascade during monocyte-to-macrophage differentiation.

Figure 4

Effect of PPAR-γ modulators and MAPK inhibitors on PMA-induced inflammation and differentiation in monocytes. A and B: THP-1 monocytes were pretreated with 40 μmol/L pioglitazone, GW9662, orlistat, p38 inhibitor, or SP600125 for 2 h followed by stimulation with PMA (100 nmol/L) for 48 h, and IL-1β, TNF-α, MCP-1 levels were measured by ELISA (A) and MMP-9 and MMP-2 activities by gelatin zymography (B) in the conditioned media. C: Monocytes were pretreated with JNK inhibitor SP600125 (0–40 μmol/L) for 2 h followed by PMA (100 nmol/L) stimulation for 48 h, and IL-1β, TNF-α, MCP-1 levels were measured. D: Same as C except transcript levels of indicated genes were measured by RT-PCR after 24 h. E: Same as C except monocytes were pretreated with metformin (0–2 mmol/L) for 24 h, and p-JNK, JNK, p-c-Jun, and c-Jun were measured by Western blotting. Data are mean ± SD. #P < 0.05 vs. PMA control. Ser, serine; Thr, threonine; Tyr, tyrosine.

Figure 4

Effect of PPAR-γ modulators and MAPK inhibitors on PMA-induced inflammation and differentiation in monocytes. A and B: THP-1 monocytes were pretreated with 40 μmol/L pioglitazone, GW9662, orlistat, p38 inhibitor, or SP600125 for 2 h followed by stimulation with PMA (100 nmol/L) for 48 h, and IL-1β, TNF-α, MCP-1 levels were measured by ELISA (A) and MMP-9 and MMP-2 activities by gelatin zymography (B) in the conditioned media. C: Monocytes were pretreated with JNK inhibitor SP600125 (0–40 μmol/L) for 2 h followed by PMA (100 nmol/L) stimulation for 48 h, and IL-1β, TNF-α, MCP-1 levels were measured. D: Same as C except transcript levels of indicated genes were measured by RT-PCR after 24 h. E: Same as C except monocytes were pretreated with metformin (0–2 mmol/L) for 24 h, and p-JNK, JNK, p-c-Jun, and c-Jun were measured by Western blotting. Data are mean ± SD. #P < 0.05 vs. PMA control. Ser, serine; Thr, threonine; Tyr, tyrosine.

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Activation of STAT3 Is Involved in Monocyte-to-Macrophage Differentiation and Inflammation

STAT3 plays a role in regulating cellular differentiation, and AMPK negatively regulates STAT3 phosphorylation (23,24). In the present study, we saw a downregulation of AMPK phosphorylation during monocyte-to-macrophage differentiation, and although metformin and AICAR treatments restored it with concomitant inhibition of monocyte differentiation, we wanted to know whether a cross-talk exists between AMPK and STAT3 during PMA-induced monocyte-to-macrophage differentiation. The results show that PMA treatment alone induced STAT3 phosphorylation as early as 6 h (Fig. 5A), and under the same conditions, metformin dose dependently inhibited PMA-induced STAT3 phosphorylation (Fig. 5B). We then studied the effect of stattic (STAT3 inhibitor) on PMA-induced monocyte-to-macrophage differentiation. Stattic dose dependently (5–20 μmol/L) inhibited the adherence of PMA-treated monocytes (Fig. 5C), which is in line with the reduction in mRNA levels of macrophage differentiation markers (Fig. 5D). These observations support that STAT3 phosphorylation promotes monocyte-to-macrophage differentiation. Next, to know whether STAT3 phosphorylation also plays a role in PMA-induced inflammation, we measured proinflammatory cytokine production and MMP-9 activity in the presence of stattic. Stattic dose dependently inhibited the secretion of IL-1β, TNF-α, and MCP-1 into the medium (Fig. 5E) along with a significant inhibition of MMP-9 activity (Fig. 5F). Furthermore, stattic treatment decreased the mRNA levels of IL-1β, TNF-α, and MCP-1 (Fig. 5G), suggesting that STAT3 phosphorylation promotes transcription of proinflammatory genes during monocyte-to-macrophage differentiation. The inhibitory effect of stattic on monocyte differentiation and inflammation were not a result of its cytotoxic effects (Fig. 5H). To gain more insight into the cross-talk among AMPK, STAT3, and JNK, we measured the phosphorylation statuses of these proteins under various experimental conditions, using their respective inhibitors in the presence or absence of PMA as shown in Fig. 5I. First, treatment of cells with stattic inhibited JNK phosphorylation, whereas incubation of cells with SP600125 failed to affect STAT3 phosphorylation (Fig. 5I), suggesting that JNK is a downstream target of STAT3. Second, to understand the effect of AMPK in regulating JNK and STAT3 activation, we examined the phosphorylation statuses of these proteins by inhibiting AMPK activation with compound C in both the presence and the absence of PMA stimulation. We did not notice any change in the phosphorylation status of either STAT3 or JNK with compound C treatment in the absence of PMA stimulation. However, there was a significant increase in their phosphorylation statuses with cotreatment of compound C and PMA (Fig. 5I). From these results, it appears that although a causal reciprocal relationship exists between AMPK and STAT3 phosphorylation (Fig. 5A and B), it may happen only under PMA-stimulated conditions, which in turn suggests that other additional factors may be regulated by PMA stimulation, enabling AMPK-dependent phosphorylation of STAT3 protein. Additionally, we observed that neither SP600125 nor stattic was able to rescue PMA-mediated inhibition of p-AMPK-1α (Fig. 5I). Taken together, these observations indicate that STAT3 phosphorylation plays a critical role in mediating monocyte-to-macrophage differentiation and inflammation.

Figure 5

PMA-induced monocyte differentiation alters STAT3 phosphorylation status: effect of metformin. A: THP-1 monocytes were treated with PMA (100 nmol/L) for 6–24 h, and p-STAT3 and STAT3 were measured by Western blotting. B: Same as A except cells were pretreated with metformin (0–2 mmol/L) for 2 h followed by stimulation with PMA for 24 h. Monocytes were pretreated with stattic (0–20 μmol/L) for 2 h followed by stimulation with PMA (100 nmol/L). C: Phase contrast images indicating the inhibition of PMA-induced monocyte adherence by stattic treatment after 48 h. D: Same as C except transcript levels of monocyte differentiation marker genes were measured by RT-PCR after 24 h. E: Same as C except IL-1β, TNF-α, and MCP-1 levels were measured by ELISA. F: MMP-9 and MMP-2 activities were measured by gelatin zymography in the conditioned medium after 48 h. G: Same as C except transcript levels of proinflammatory cytokine gene expression were measured by RT-PCR after 24 h. H: The effect of stattic in the presence or absence of PMA on cell viability measured after 48 h. I: Monocytes were treated with either SP600125 (40 μmol/L), stattic (20 μmol/L), or compound C (5 μmol/L) in either the presence or the absence of PMA stimulation for 24 h, and p-AMPK-1α, AMPK-1α, p-JNK, JNK, p-STAT3, and STAT3 were analyzed by Western blotting. Data are mean ± SD. #P < 0.05 vs. PMA control. Thr, threonine; Tyr, tyrosine.

Figure 5

PMA-induced monocyte differentiation alters STAT3 phosphorylation status: effect of metformin. A: THP-1 monocytes were treated with PMA (100 nmol/L) for 6–24 h, and p-STAT3 and STAT3 were measured by Western blotting. B: Same as A except cells were pretreated with metformin (0–2 mmol/L) for 2 h followed by stimulation with PMA for 24 h. Monocytes were pretreated with stattic (0–20 μmol/L) for 2 h followed by stimulation with PMA (100 nmol/L). C: Phase contrast images indicating the inhibition of PMA-induced monocyte adherence by stattic treatment after 48 h. D: Same as C except transcript levels of monocyte differentiation marker genes were measured by RT-PCR after 24 h. E: Same as C except IL-1β, TNF-α, and MCP-1 levels were measured by ELISA. F: MMP-9 and MMP-2 activities were measured by gelatin zymography in the conditioned medium after 48 h. G: Same as C except transcript levels of proinflammatory cytokine gene expression were measured by RT-PCR after 24 h. H: The effect of stattic in the presence or absence of PMA on cell viability measured after 48 h. I: Monocytes were treated with either SP600125 (40 μmol/L), stattic (20 μmol/L), or compound C (5 μmol/L) in either the presence or the absence of PMA stimulation for 24 h, and p-AMPK-1α, AMPK-1α, p-JNK, JNK, p-STAT3, and STAT3 were analyzed by Western blotting. Data are mean ± SD. #P < 0.05 vs. PMA control. Thr, threonine; Tyr, tyrosine.

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Metformin Administration Attenuates the Incidence of Ang-II–Induced Atheromatous Plaque Formation and AA in ApoE−/− Mice

It is reasonably well known that monocyte-to-macrophage differentiation is a prerequisite step in the development and progression of the atherosclerotic disease process (2). In this context, we studied the ability of metformin to inhibit monocyte-to-macrophage differentiation and inflammation during Ang-II–induced atherogenesis in an ApoE−/− mouse model. Morphologically, thoracic and abdominal aorta of the Ang-II–treated group showed severe incidence of plaque extension, multiple numbers of micro/pseudoaneurysm formation, and maximal aortic diameters (Fig. 6A–C) at the end of 6 weeks. However, the incidence of plaque extension and AA was significantly less in the Ang-II + metformin–treated group similar to control animals (Fig. 6A and B). We further analyzed the vascular remodeling in tissue sections of thoracic aortas. Hematoxylin-eosin (H-E) staining of the Ang-II–treated group showed severe atherosclerotic lesions with both thick internal and external walls and intimal plaques (Fig. 6D–F). These changes were greatly reduced in Ang-II + metformin–treated animals (Fig. 6D–F), which was further confirmed by Masson trichrome staining in which thick fibrous capsules comprising mature connective tissue surrounding and in between atheroma were observed (Fig. 7A). Additionally, Van Gieson staining indicated a ruptured medial layer lamella (light brown) with a dark brown nucleus in Ang-II–treated mice (Fig. 7B). The collagen tissue in the atheroma, intimal, medial, and external regions appeared as red in the atheromatous region of Ang-II–treated mice. However, in control and metformin-treated groups, collagen tissue accumulation in the intimal region was not observed (Fig. 7A, B, E, and F). Along these lines, Ang-II treatment markedly elevated macrophage infiltration, as evidenced by Mac-3 immunofluorescence and H-E staining of the atheromatous region (Fig. 7C, D, G, and H). Mac-3 is a general marker of macrophage abundance often seen under inflammatory conditions. Metformin treatment significantly inhibited Ang-II–induced macrophage accumulation comparable to control mice (Fig. 7C, D, G, and H). This observation also coincides with the increased presence of the foam cell population detected by Sudan black staining in the plaque region of Ang-II–treated animals (Fig. 8A and B). To further corroborate the ability of metformin to inhibit monocyte-to-macrophage differentiation, we measured CD-36 and LOX-1 protein levels in total lysates of aorta, and the results are consistent with cell culture studies, showing that metformin treatment significantly inhibited Ang-II–induced CD-36 and LOX-1 (Fig. 8C). Additionally, metformin treatment rescued Ang-II–mediated loss of AMPK-1α phosphorylation (Fig. 8C). In line with this, metformin-treated mice showed decreased levels of serum proinflammatory cytokines (MCP-1 and TNF-α) compared with the Ang-II–treated group (Fig. 8D). On the other hand, IL-10 (anti-inflammatory cytokine) levels were significantly increased in metformin-treated mice compared with Ang-II–treated and control mice (Fig. 8E). These in vivo observations agreed with the ability of metformin to inhibit the proinflammatory cytokine production during PMA-induced monocyte-to-macrophage differentiation in THP-1 cells (Figs. 1 and 2). To understand the basis for the increased incidence of AA in Ang-II–treated mice, we measured the transcript levels of MMP-1, -2, and -9 by RT-PCR and found that MMP-1 and -9 were significantly elevated in Ang-II–treated mouse aortas (Fig. 8F). Metformin treatment significantly decreased Ang-II–induced MMP levels (Fig. 8F). Finally, to extend the vasculoprotective effects of metformin, we observed that metformin treatment significantly reduced the Ang-II–mediated increase in LDL and triglyceride levels while increasing serum HDL levels (Fig. 8G–I). Overall, these results demonstrate that metformin administration significantly attenuates the incidence of vascular complications, including plaque formation and AA.

Figure 6

Metformin treatment inhibits Ang-II–induced AA and plaque formation in ApoE−/− mice. A: Thoracic and abdominal aortic diameters in control, Ang-II–, and Ang-II + metformin–treated groups. B: Percent AA incidence. C: Percent plaque incidence. D: Histopathological images of aorta stained with H-E. E: Quantitative analysis of plaque size. F: Quantitative analysis of intima-externa thickness. Data represent mean ± SD from 3 different animals. *P < 0.05 vs. control. #P < 0.05 vs. Ang-II–treated group.

Figure 6

Metformin treatment inhibits Ang-II–induced AA and plaque formation in ApoE−/− mice. A: Thoracic and abdominal aortic diameters in control, Ang-II–, and Ang-II + metformin–treated groups. B: Percent AA incidence. C: Percent plaque incidence. D: Histopathological images of aorta stained with H-E. E: Quantitative analysis of plaque size. F: Quantitative analysis of intima-externa thickness. Data represent mean ± SD from 3 different animals. *P < 0.05 vs. control. #P < 0.05 vs. Ang-II–treated group.

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Figure 7

Metformin treatment attenuates Ang-II–induced macrophage accumulation in ApoE−/− mouse aorta. A and B: Histopathological images of aorta stained with Masson trichrome and Van Gieson for analyzing fibrous and collagen tissue in the vessel wall. C: Confocal microscopic images representing Mac-3 immunofluorescence (green fluorescence represents positive staining for macrophages as indicated). D: Bright field microscopic images showing macrophage infiltration in the vessel wall. E and F: Quantitative analysis of fibrous and collagen content in the plaque and externa regions shown in A and B. G: Quantitative analysis of macrophage density in the plaque and externa regions shown in C. H: Quantitative analysis of macrophage population by counting large cells with a centrally located nucleus as macrophages in various regions of the vessel wall shown in D. Data are mean ± SD from three different animals. *P < 0.05 vs. control. #P < 0.05 vs. Ang-II–treated group.

Figure 7

Metformin treatment attenuates Ang-II–induced macrophage accumulation in ApoE−/− mouse aorta. A and B: Histopathological images of aorta stained with Masson trichrome and Van Gieson for analyzing fibrous and collagen tissue in the vessel wall. C: Confocal microscopic images representing Mac-3 immunofluorescence (green fluorescence represents positive staining for macrophages as indicated). D: Bright field microscopic images showing macrophage infiltration in the vessel wall. E and F: Quantitative analysis of fibrous and collagen content in the plaque and externa regions shown in A and B. G: Quantitative analysis of macrophage density in the plaque and externa regions shown in C. H: Quantitative analysis of macrophage population by counting large cells with a centrally located nucleus as macrophages in various regions of the vessel wall shown in D. Data are mean ± SD from three different animals. *P < 0.05 vs. control. #P < 0.05 vs. Ang-II–treated group.

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Figure 8

Metformin treatment attenuates Ang-II–induced foam cell formation and inflammation in ApoE−/− mice. A: Histopathological images of aorta were stained with Sudan black to detect foam cells (black spots represent foam cells as indicated). B: Quantitative analysis of A. C: Expression levels of p-AMPK-1α and macrophage cell markers CD-36 and LOX-1 proteins in the whole aortic tissue lysate by Western blotting. D and E: The levels of serum TNF-α, MCP-1, and IL-10 measured by ELISA. F: Quantitative measurement of MMPs in the whole aortic tissue by RT-PCR. G, H, and I: Serum triglyceride, LDL, and HDL levels. Data are mean ± SD from at least three independent animals. *P < 0.05 vs. control; #P < 0.05 vs. Ang-II–treated group. Thr, threonine.

Figure 8

Metformin treatment attenuates Ang-II–induced foam cell formation and inflammation in ApoE−/− mice. A: Histopathological images of aorta were stained with Sudan black to detect foam cells (black spots represent foam cells as indicated). B: Quantitative analysis of A. C: Expression levels of p-AMPK-1α and macrophage cell markers CD-36 and LOX-1 proteins in the whole aortic tissue lysate by Western blotting. D and E: The levels of serum TNF-α, MCP-1, and IL-10 measured by ELISA. F: Quantitative measurement of MMPs in the whole aortic tissue by RT-PCR. G, H, and I: Serum triglyceride, LDL, and HDL levels. Data are mean ± SD from at least three independent animals. *P < 0.05 vs. control; #P < 0.05 vs. Ang-II–treated group. Thr, threonine.

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Atherosclerosis is a chronic immune-mediated inflammatory disease of the arterial vessel wall characterized by the thickening of intima primarily due to monocyte recruitment into the subendothelial space (14). The current study shows that metformin, a widely used antidiabetic drug and an AMPK activator, effectively inhibits PMA-induced monocyte-to-macrophage differentiation. Metformin also elicits potent anti-inflammatory effects by inhibiting IL-1β, TNF-α, and MCP-1 levels in vitro and in vivo, thereby emphasizing its apparent beneficial effect in the context of atherogenesis. Similar results were observed with AICAR, a distinct AMPK activator. AMPK activity in the blood is predominantly located in monocytes and lymphocytes as the 1α isoform (25), and a reduction in AMPK activity is associated with various pathophysiological effects (26). Vascular suppression of AMPK stimulates arterial deposition of excess lipids, resulting in the development of atherosclerotic lesions (27). AMPK signaling in macrophages is significantly downregulated by inflammatory stimuli and external free fatty acids (13,14). The results of this study indicate that by activating AMPK-1α phosphorylation, metformin potently inhibits monocyte-to-macrophage differentiation. This effect of AMPK was counteracted in the presence of AMPK inhibitor, but compound C failed to cause monocyte-to-macrophage differentiation in the absence of PMA. Inactivation of AMPK-1α triggers inflammation only in the presence of external stimuli, like LPS (14). These findings suggest that inactivation of AMPK alone seems to be inadequate to promote either cellular differentiation or inflammatory signaling pathways. Nevertheless, inactivation of AMPK accelerates both these events in the presence of an external stimulus (e.g., LPS, PMA, macrophage colony-stimulating factor). Of note, JNK inhibition effectively attenuated only PMA-induced inflammation, but not PMA-induced monocyte-to-macrophage differentiation. This result agrees with a finding showing that JNK signaling plays a crucial role in inducing IL-1β in monocytes (22). Metformin-activated AMPK inhibited LPS-induced proinflammatory cytokine levels by inhibiting JNK1 phosphorylation in macrophages (28). To this end, the present data show that the reversal of PMA-induced inhibition of AMPK phosphorylation by metformin is accompanied by a decrease in JNK1 phosphorylation, indicating that AMPK activators can modulate the inflammatory pathways during monocyte-to-macrophage differentiation through targeting JNK signaling and emphasizing that inflammation and differentiation are independent events. The results also indicate that by negatively regulating STAT3 phosphorylation through increased activation of AMPK, metformin inhibits monocyte-to-macrophage differentiation. Activation of STAT3 signaling is essential for neointima formation in vivo in response to carotid artery angioplasty (15). Metformin- and AICAR-activated AMPK was shown to inhibit proinflammatory gene expression in human liver cells by repressing IL-6–stimulated STAT3 phosphorylation (24). The present work shows that by decreasing the PMA-induced STAT3 phosphorylation, metformin significantly inhibited monocyte-to-macrophage differentiation and proinflammatory cytokine production.

In support of the observed favorable effects of metformin, we also found a complete regression of atherosclerotic plaque formation in the aorta of Ang-II + metformin–treated mice compared with Ang-II treatment alone. Gross pathological investigations revealed extensive plaque reduction in the entire aorta and pseudoaneurysm in abdominal and thoracic aorta of mice treated with Ang-II + metformin compared with Ang-II treatment alone. The aorta of metformin-treated mice also showed a significant reduction in the recruitment of inflammatory macrophages as evidenced by Mac-3 staining compared with mice treated with Ang-II alone. Additionally, in agreement with the effects of metformin in THP-1 monocytes, Ang-II + metformin–treated mice showed a significant downregulation of CD-36 and LOX-1 compared with mice treated with Ang-II alone. Apart from the regression of plaque formation, metformin treatment also resulted in the reduction of Ang-II–induced AA. This appears to be an important observation, and the molecular basis for reduced AA with metformin treatment along with changes in blood pressure under these conditions need to be investigated. One of the other important observations of this study is that metformin treatment significantly inhibited an Ang-II–mediated increase in LDL and triglyceride levels, which are known to be associated with proatherosclerotic effects. Moreover, metformin treatment significantly increased HDL levels. Metformin has been shown to improve the lipid profile by reducing LDL cholesterol as well as triglyceride levels in type 2 diabetic patients (29,30).

In conclusion, we show that AMPK activators can effectively inhibit monocyte-to-macrophage differentiation and associated inflammatory pathways. It is likely that the antiatherosclerotic effects of metformin are in part mediated by perturbing monocyte-to-macrophage differentiation during Ang-II–mediated atherosclerosis in ApoE−/− mice.

See accompanying article, p. 1907.

Funding. This work was supported by grants from the Department of Science and Technology, Department of Biotechnology, and CSIR, India, under 12th Five Year Plan projects SMiLE and EpiHeD. S.B.V. and A.K.K. acknowledge CSIR and S.Ka. acknowledges the Indian Council of Medical Research, New Delhi, India, for the award of research fellowships.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. S.B.V. contributed to the experimental design, data analysis, and writing of the manuscript. S.Ka. and A.K.K. contributed to the animal experiments. A.R.T. contributed to the histology studies. J.M.K. contributed to the experimental design, provision of animals for in vivo experiments, data analysis, and writing of the manuscript. S.Ko. contributed to the experimental design, provision of reagents and other material required for performing both in vitro and in vivo experiments, data analysis, and writing of the manuscript. S.Ko. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

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Supplementary data