JACC: Cardiovascular Imaging
Effects of p38 Mitogen-Activated Protein Kinase Inhibition on Vascular and Systemic Inflammation in Patients With Atherosclerosis
Author + information
- Received September 10, 2011
- Revision received January 13, 2012
- Accepted February 29, 2012
- Published online September 1, 2012.
Author Information
- Maysoon Elkhawad, MBBChir, MA⁎,†,
- James H.F. Rudd, MBChB, PhD†,
- Lea Sarov-Blat, PhD‡,
- Gengqian Cai, PhD‡,
- Richard Wells, BA⁎,
- L. Ceri Davies, MD, MBBS§,
- David J. Collier, PhD, MBBS§,
- Michael S. Marber, MBBS, PhD∥,
- Robin P. Choudhury, BMBCh, MA, DM¶,
- Zahi A. Fayad, PhD#,
- Ahmed Tawakol, MD⁎⁎,
- Fergus V. Gleeson, MBBS¶,
- John J. Lepore, MD‡,
- Bill Davis, PhD††,
- Robert N. Willette, PhD‡,
- Ian B. Wilkinson, BMBCh, DM⁎,
- Dennis L. Sprecher, MD‡,⁎ (dennis.l.sprecher{at}gsk.com) and
- Joseph Cheriyan, MBChB⁎,††,‡‡
- ↵⁎Reprint requests and correspondence:
Dr. Dennis Sprecher, GlaxoSmithKline, 709 Swedeland Road, UW2421, King of Prussia, Pennsylvania 19406
Abstract
Objectives This study sought to determine the effects of a p38 mitogen-activated protein kinase inhibitor, losmapimod, on vascular inflammation, by 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography imaging.
Background The p38 mitogen-activated protein kinase cascade plays an important role in the initiation and progression of inflammatory diseases, including atherosclerosis.
Methods Patients with atherosclerosis on stable statin therapy (n = 99) were randomized to receive losmapimod 7.5 mg once daily (lower dose [LD]), twice daily (higher dose [HD]) or placebo for 84 days. Vascular inflammation was assessed by FDG positron emission tomography/computed tomography imaging of the carotid arteries and aorta; analyses focused on the index vessel (the artery with the highest average maximum tissue-to-background ratio [TBR] at baseline). Serum inflammatory biomarkers and FDG uptake in visceral and subcutaneous fat were also measured.
Results The primary endpoint, change from baseline in average TBR across all segments in the index vessel, was not significantly different between HD and placebo (ΔTBR: −0.04 [95% confidence interval [CI]: −0.14 to +0.06], p = 0.452) or LD and placebo (ΔTBR: −0.02 [95% CI: −0.11 to +0.06], p = 0.579). However, there was a statistically significant reduction in average TBR in active segments (TBR ≥1.6) (HD vs. placebo: ΔTBR: −0.10 [95% CI: −0.19 to −0.02], p = 0.0125; LD vs. placebo: ΔTBR: −0.10 [95% CI: −0.18 to −0.02], p = 0.0194). The probability of a segment being active was also significantly reduced for HD when compared with placebo (OR: 0.57 [95% CI: 0.41 to 0.81], p = 0.002). Within the HD group, reductions were observed in placebo-corrected inflammatory biomarkers including high-sensitivity C-reactive protein (% reduction: −28% [95% CI: −46 to −5], p = 0.023) as well as FDG uptake in visceral fat (ΔSUV: −0.05 [95% CI: −0.09 to −0.01], p = 0.018), but not subcutaneous fat.
Conclusions Despite nonsignificant changes for the primary endpoint of average vessel TBR, HD losmapimod reduced vascular inflammation in the most inflamed regions, concurrent with a reduction in inflammatory biomarkers and FDG uptake in visceral fat. These results suggest a systemic anti-inflammatory effect. (A Study to Evaluate the Effects of 3 Months Dosing With GW856553, as Assessed FDG-PET/CT Imaging; NCT00633022)
- atherosclerosis
- biomarkers
- imaging
- inflammation
- p38 mitogen-activated protein kinase inhibition
- randomized controlled trial
Atherosclerosis is considered to be a complex, chronic, progressive inflammatory condition (1), involving cytokines that direct the adhesion and transmigration of monocytes into the vascular wall. This complex process requires the modulation of a number of cell signaling pathways in which p38 mitogen-activated protein kinases (MAPK) play a fundamental role (2,3). Four p38 MAPK isoforms have been identified, with the alpha and beta isotypes being prominent in the heart and vasculature, and delta and lambda isotypes in skeletal muscle, lung, and renal tissues. The expression and activity of p38 MAPKs are relatively low in healthy vasculature yet markedly elevated in macrophages of atherosclerotic lesions (2).
In pre-clinical models of cardiovascular disease, p38 MAPK inhibition improves endothelial dysfunction, limits atherogenesis, and improves survival (4,5). Additionally, p38 MAPK inhibition reduces macrophage-associated plaque inflammation in apolipoprotein E–deficient mice, assessed using magnetic resonance imaging (6). We have previously demonstrated that p38 MAPK inhibition attenuates release of high-sensitivity C-reactive protein (hsCRP) in patients undergoing angioplasty (7), and, using a potent and specific alpha/beta p38 MAPK inhibitor, losmapimod (5), improves vasoregulation in hypercholesterolemic patients (8), supporting translation of pre-clinical results into humans.
Cellular 18F-fluorodeoxyglucose (FDG) uptake, measured by positron emission tomography/computed tomography (PET/CT), correlates with macrophage glucose consumption (9), macrophage number (10,11), and is also influenced by the degree of hypoxia (12) in atherosclerosis, all potential markers of plaque vulnerability. FDG-PET/CT imaging has been successfully used to determine culprit plaques responsible for transient ischemic attack and stroke (13). In addition, FDG uptake is attenuated by statins, with reductions in FDG uptake observed in both animal and human models of atherosclerosis (10,14). Although FDG-PET/CT has not been validated for predicting cardiovascular events, it may serve to answer mechanistic questions about macrophage-focused effects on vascular inflammation when assessing novel anti-inflammatory compounds (13–16).
In this exploratory study, the primary objective was to test the hypothesis that selective p38 MAPK inhibition with losmapimod reduces vascular inflammation (as assessed with FDG-PET/CT imaging) in stable atherosclerotic patients on concurrent statin therapy. Pre-specified secondary objectives included safety, tolerability, and effects on serum inflammatory biomarkers. Finally, to determine effects on extravascular inflammation, FDG uptake in visceral and subcutaneous fat was also measured. Visceral fat is relevant to the metabolic risk associated with cardiovascular disease (17,18).
Methods
Study design
This was a phase II, randomized, double-blind, placebo-controlled study conducted at 4 sites in the United Kingdom (Cambridge University Hospitals National Health Service Foundation Trust; Bart's and The London School of Medicine and Dentistry; University of Oxford; and King's Health Partners, London). The protocol was approved by Oxfordshire Research Ethics Committee and registered with ClinicalTrials.gov (NCT00633022). The study complied with the Declaration of Helsinki and written informed consent was obtained from all participants.
Study population
Patients age 50 to 80 years with a history of atherosclerosis (clinically stable, at least 6 months after myocardial infarction, transient ischemic attack/stroke, or symptomatic peripheral vascular disease) and with a body mass index between 19 and 35 kg/m2 were eligible. Patients were on stable statin therapy. Prior to enrolment, eligible patients underwent a screening PET/CT to determine whether they had sufficient vascular inflammation for study entry, defined as an average arterial FDG whole vessel tissue-to-background ratio (TBR) of ≥1.6 (11) in either of the carotids or the ascending aorta. Patients with New York Heart Association functional class II to IV heart failure, atrial fibrillation, hepatic or renal disease, poorly controlled type II diabetes, insulin-dependent diabetics, and those with chronic inflammatory conditions and malignancy were excluded.
Intervention
Patients were randomized (1:1:1) to receive oral losmapimod 7.5 mg twice daily (higher dose [HD]), losmapimod 7.5 mg once daily (lower dose [LD]), or placebo for 84 days. Losmapimod and placebo tablets were indistinguishable and study personnel and patients were blinded to treatment allocation until the trial was complete. Study medication was manufactured by GlaxoSmithKline.
Vascular and fat PET/CT imaging
Vascular PET/CT imaging (19,20) was performed at study entry (pre-dose) and repeated at day 84. Vessels were identified and sectioned into 5-mm contiguous “segments.” Regions of interest were drawn around the arterial wall (in the axial plane) for every segment of the coregistered PET/CT images. The maximum standard uptake value (SUV) of FDG in each segment was recorded and normalized to background blood FDG activity, yielding a TBR. For each patient, the artery with the highest average maximum TBR at baseline was designated the “index vessel” (either carotid artery or aorta) and was used for further analyses. The index vessels were evaluated using a “whole vessel” approach and an “active segment” approach (Fig. 1). With the whole vessel approach, all segments composing the index vessel were analyzed, regardless of whether or not active inflammation was present at baseline. In the active segment approach, noninflamed segments were excluded, similar to previous work in which the effect of simvastatin was assessed only in locations with increased FDG uptake at baseline (14,21). Prior FDG-PET imaging studies with pathological correlations demonstrate that a TBR value <1.6 is associated with <5% inflammation within the atheroma (11,22–24). Therefore, segments with TBR ≥1.6 were defined as active. Measurements of visceral and subcutaneous fat were performed as previously described (25). See the supplementary methods in the Online Appendix for additional details.
Analysis Methods Used To Quantify Vascular Inflammation in the Index Vessel
A series of contiguous segments from the index vessel are illustrated. Atherosclerotic plaques in the vessel wall are indicated in yellow. The value within each segment represents the maximum tissue-to-background ratio (TBR) for that segment. Active segments were pre-defined as segments with TBR ≥1.6.
Laboratory assessments
Blood samples were collected pre-dose on days 1, 7, 14, 28, 56, and 84 and 2 weeks post-cessation of drug for measurement of hsCRP and pre-dose on days 1, 28 or 42, and 84 for measurement of inflammatory biomarkers. All analyses were conducted centrally using standard laboratory methods.
Safety assessments
Adverse events, safety laboratory parameters, hemodynamic variables, and electrocardiograms were assessed throughout the study.
Statistical methods
A sample size of 30 patients per group provided 90% power to detect a 15% difference in change from baseline in TBR across all segments within the index vessel with a 5% level of significance (14).
The safety population included patients who received at least 1 dose of the investigational product. Change from baseline analyses for pharmacodynamics and FDG-PET/CT included patients with both baseline and post-baseline values.
We used 3 approaches to quantify vascular inflammation (Fig. 1): 1) the pre-specified whole vessel primary endpoint of change in the average maximum TBR for all segments within the index vessel (19), with a complementary post hoc analysis displaying the group distribution of TBR using a frequency histogram; 2) an analysis of change from baseline in average maximum TBR for active segments within the index vessel; and 3) an analysis of the probability of a segment being active within the index vessel.
Change from baseline in average maximum TBR was analyzed using analysis of covariance, fitting treatment as fixed effect, and including baseline value as a covariate. Point estimates and corresponding 95% confidence intervals (CI) were constructed for the relevant comparisons of interest.
TBR data were plotted to show the distribution from all segments from all index vessels within each treatment group (at pre-dose and post-dose). The Kolmogorov-Smirnov statistic was applied to these data to measure the effect of treatment on TBR distribution. The difference between losmapimod and placebo was calculated and tested using a nonparametric permutation test at the patient level. Baseline correction is not feasible with this analysis approach.
The number of active segments and the total number of segments were included in logistic regression analyses to model the probability of a segment being active. For baseline correction within each group, a model was fitted with terms for treatment and day. For placebo and baseline correction, a model was fitted with treatment term and including the baseline proportion of active segments as covariate. In the baseline correction within each group model, the generalized estimating equation method was used to adjust for the fact that multiple data points (day 1 and day 84) were from the same vessel (patient). Point estimates and corresponding 95% CI were constructed to establish the odds ratio for the relevant comparisons of interest.
Biomarker data were analyzed by analysis of covariance fitting terms for regimen, day, and interaction of day and regimen as fixed effects; patient as a random effect; and baseline biomarker at day 1 as a covariate.
Statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary, North Carolina). No multiplicity adjustment was made and p values <0.05 were considered statistically significant.
Results
The flow of participants through the study is shown in Figure 2: 159 patients were screened; 99 were randomized; 92 completed the 84-day dosing period; and 93 were included in FDG-PET/CT analyses. Demographic and baseline characteristics are summarized in Table 1. A summary of index vessel types for each group is shown in Online Table 1.
Flow of Patients Through the Trial
*Patients who withdrew after receiving ≥2 months of treatment had a post-dose positron emission tomography/computed tomography (PET/CT) scan at the time of withdrawal. These patients are included in the PET/CT analysis. AE = adverse event; HD = higher dose; LD = lower dose; SAE = serious adverse event; TBR = tissue-to-background ratio.
Demographic and Baseline Characteristics
Vascular PET/CT imaging
All Segments
Figure 3 illustrates the patchy nature of vascular inflammation in atherosclerosis. The magnitude of reduction in average maximum TBR of all segments within the index vessel was larger in the losmapimod groups, but there was no significant difference when compared with placebo (Table 2). There was, however, a significant leftward shift in TBR distribution from baseline to day 84 in the losmapimod groups (HD vs. placebo: p = 0.007; LD vs. placebo: p = 0.031), with no significant change in the placebo group (Fig. 4).
Typical FDG-PET/CT Images
(A) From left to right, sagittal CT, PET, and combined CT and PET images from a patient at pre-dose (baseline) are shown. (B) Matching images from the same patient after 84 days of treatment with losmapimod HD. The arrows highlight the descending aorta, demonstrating heterogeneous atherosclerotic fluorine 18F-fluorodeoxyglucose (FDG) uptake, which is lowered post-dose. Other abbreviations as in Figure 2.
Frequency Histograms of All Segments From the Index Vessel
Frequency histograms of all segments from the index vessel histograms show tissue-to-background ratio (TBR) data from all patients in the placebo group (A) at pre-dose baseline (black dashed line) and after 84 days (black solid line), in the losmapimod LD group (B) at pre-dose baseline (green dashed line) and after 84 days (green solid line), and in the losmapimod HD group (C) at pre-dose baseline (pink dashed line) and after 84 days (pink solid line).
Change from Baseline in FDG Uptake in the Index Vessel
Active Segments
When only active segments were considered, there was a statistically significant reduction in average maximum TBR in these inflamed areas for both HD and LD losmapimod compared with placebo (p = 0.0125 and p = 0.0194, respectively) (Table 2).
The odds of having an active segment on day 84 was significantly lower than on day 1 for the HD group (p < 0.001) and the LD group (p = 0.001), without significant change in the placebo group (p = 0.736) (Table 2, Fig. 5). After adjusting for baseline and correcting for placebo, the odds of having an active segment on day 84 were significantly lower in the HD group than in the placebo group (p = 0.002), but no significant difference was observed for the LD group versus the placebo group (p = 0.429). This result was maintained irrespective of the TBR cutoff used to define significant inflammation (Online Table 2).
Change in Probability of a Segment Being Active
This figure depicts the odds ratio (OR) and associated 95% confidence intervals for having an inflamed arterial segment (TBR ≥1.6) in the index vessel on day 84 versus baseline in the placebo, losmapimod LD, and losmapimod HD groups. The p values above each bar denote the comparison within each group on day 84 compared with baseline (based on logistic regression model with baseline correction within each group); p values above the horizontal parentheses denote the comparison for LD or HD groups versus placebo, after baseline adjustment (based on logistic regression model with both baseline and placebo correction). The numbers underneath the x-axis show the mean (SD) of proportion of active segments at baseline and day 84 for each group. Abbreviations as in Figures 1 and 2.
Biomarkers
There was a statistically significant decrease from baseline in average hsCRP over the 84-day treatment period in the HD group compared with the placebo group, and there was a nonsignificant trend for a decrease in the LD group (Table 3,Fig. 6). There was a rebound in hsCRP above baseline levels 2 weeks after cessation of losmapimod treatment (Fig. 6). In the HD group, compared with the placebo group, statistically significant reductions from baseline were also observed at day 84 for interleukin 8, matrix metalloproteinase 9-neutrophil gelatinase associated lipocalin dimer, and monocyte chemotactic protein-1. No reductions were observed for other biomarkers (Table 3).
Percentage Change From Baseline in hsCRP
Percentage change from baseline in high-sensitivity C-reactive protein (hsCRP) percentage change (95% confidence intervals) from baseline in hsCRP in the placebo group (black dashed line), losmapimod LD group (green solid line), and losmapimod HD group (pink solid line). Day 7 data includes a subset of the total population (HD: n = 15; LD: n = 13; placebo: n = 14). Abbreviations as in Figure 2.
Percentage Change From Baseline in Blood Biomarkers
Visceral and subcutaneous fat imaging
At baseline, there were no significant differences between groups in SUV for FDG for either subcutaneous or visceral fat (Table 4). At day 84, there was a significant reduction from baseline in the HD (but not LD) group in maximum SUV for visceral fat (p = 0.002) that remained statistically significant when compared with placebo (p = 0.018) (Table 4). There were no changes from baseline in maximum SUV for subcutaneous fat in any of the groups. There were no changes in glucose, adiponectin, or insulin levels or body mass index over the course of the study (data not shown).
Change From Baseline in FDG Uptake in Subcutaneous and Visceral Fat
Safety
Losmapimod was well-tolerated in this study. There were no clinically meaningful changes in laboratory parameters, vital signs, or electrocardiograms over time in any of the groups. Adverse events were reported by a similar proportion of patients in each group (Online Table 3).
Discussion
We conducted an experimental study to assess the effect of a novel anti-inflammatory agent on vascular inflammation, over 3 months, in stable atherosclerotic patients receiving statin therapy. Despite a negative primary endpoint, we demonstrated that losmapimod reduced arterial inflammation, as measured by FDG-PET/CT imaging in the most active discrete segments (pre-defined as a TBR of ≥1.6) of selected arteries, suggesting influence predominantly in the most inflamed areas. Complementing this finding, there was a shift in the distribution of active segments using our frequency analysis. The modest vascular effects were accompanied by significant reductions in circulating inflammatory biomarkers, in line with previous results using this compound (8), and in visceral fat FDG uptake.
A linear correlation in a previous small study between TBR vessel average (which ranged from approximately 1.0 to 4.0) and the tissue level of macrophage marker CD68 (11) drove the decision on our primary endpoint. However, a dearth of segments in our study with baseline TBR substantially >2.0, observed within a narrow range, in addition to the modest effect size, encouraged a more thorough analytic review of the data. FDG-PET/CT imaging is a relatively new, noninvasive method to assess arterial inflammation (26). To date, most interventional FDG-PET/CT studies in cardiovascular patients have been small (14,15) and without clear consensus on the most relevant method of analysis (27). Whereas tests of reproducibility can reasonably employ averaging strategies (20), interventional therapeutic studies often target pre-identified lesions (14,28). We used a variety of methods to examine vascular inflammation across the whole vessel and a more specific focus on active segments of the vascular tree, emulating the evolution of analytic techniques for imaging plaques using coronary intravascular ultrasound (29).
FDG uptake and macrophage activation are closely related in humans (11). The reduction in FDG uptake with therapy in the current study could be due to an attenuation of cellular glucose uptake (30), reduction in macrophage number, or reductions in macrophage hypoxia (12). Although this study cannot determine the precise mechanisms, the original hypothesis for macrophage reduction was based on the correlation between FDG-PET/CT in-vivo and macrophage cell number ex vivo (11).
We also found a significant differential reduction in uptake of FDG in visceral versus subcutaneous adipose tissue following HD losmapimod. FDG-PET imaging of fat to detect its glucose usage is a promising technique in understanding metabolic differences between adipose tissue compartments (31). The fact that this change only occurred in visceral fat implies that there was not a generalized reduction in FDG uptake in all fat cells. Consistent with this notion, serum glucose levels were not influenced by losmapimod treatment (data not shown). It has previously been shown that visceral fat has a relatively greater FDG uptake than subcutaneous fat does, which was attributed to differential stromal macrophage activity (17). However, adipose cells express p38 MAPK, with glucose uptake thought to be related to tumor necrosis factor alpha expression (a p38 MAPK-mediated cytokine) (32,33). Whereas our findings suggest a selective reduction in macrophage activity with p38 MAPK inhibition, we did not perform adipose tissue biopsies to confirm this hypothesis. In future work, more specific biological imaging agents might help determine whether the effect of losmapimod is due to a reduction in glucose consumption in macrophages or within the adipocytes themselves.
Study limitations
A limitation of our exploratory study is that a stable patient group was enrolled with well-controlled risk factors, low levels of systemic inflammation, and background statin therapy, likely making any apparent change more difficult to determine. It is possible that the effect would have been greater in patients with higher inflammatory burden. We also excluded patients with chronic disease without active vessel inflammation in whom plaques may be particularly quiescent; therefore, the effect of losmapimod in these especially stable patients is unknown. Finally, we accept the exploratory nature of our approach including the imaging technique and analyses we used to determine vascular effect. The 10% change in FDG-PET/CT observed in a previous statin study (15) suggests that the additional changes reported herein could have clinical relevance.
Conclusions
In summary, we demonstrate that losmapimod modestly reduced FDG-PET/CT associated vascular inflammation in actively inflamed segments, in conjunction with significant reductions in circulating inflammatory biomarkers as well as FDG uptake in visceral adipose tissue. Inflammation is an important predictor of future cardiovascular events (34,35). We suggest that the role of p38 MAPK inhibition requires further evaluation as a novel therapeutic intervention for atherosclerosis.
Acknowledgments
The authors would like to thank the participating patients, clinical site personnel, Dr. Yasmin for biomarker assays, and Alliance Medical Group for performing the imaging protocols. Editorial assistance was provided by Julie Taylor (funded by GlaxoSmithKline).
Appendix
For supplementary methods and tables, please see the online version of this paper.
Appendix
Effects of p38 Mitogen-Activated Protein Kinase Inhibition on Vascular and Systemic Inflammation in Patients With Atherosclerosis: Results From a Randomized Controlled Study
[S1936878X12005281_mmc1.docx]Footnotes
This study was funded by GlaxoSmithKline. Ms. Elkhawad, and Drs. Rudd, Wilkinson, and Cheriyan, as well as the Cambridge University Hospitals PET/CT Unit, have received funding support from National Institute for Health Research (NIHR) Cambridge Comprehensive Biomedical Research Centre. Ms. Elkhawad has received funding support from the Raymond and Beverly Sackler Foundation. Drs. Rudd and Wilkinson are consultants for GlaxoSmithKline. Drs. Sarov-Blat, Cai, Lepore, Davis, Willette, and Sprecher are employees of and own stock in GlaxoSmithKline. Mr. Wells has reported that he has no relationships relevant to the contents of this paper to disclose. Drs. Davies and Collier have received funding from NIHR Cardiovascular Biomedical Research Unit, Bart's and the London School of Medicine and Dentistry. Dr. Collier has received a research grant from GlaxoSmithKline for this study. Dr. Marber has received funding from the NIHR Comprehensive Biomedical Research Centre, Guy's and St Thomas's National Health Service Foundation Trust in partnership with the British Heart Foundation Centre, King's College, London. He has received a research grant from and is a consultant for GlaxoSmithKline for this compound. Drs. Choudhury and Gleeson have received funding from the NIHR Oxford Comprehensive Biomedical Research Centre. Dr. Choudhury is a Wellcome Trust Senior Research fellow and is supported by the British Heart Foundation Centre for Research Excellence, Oxford. He has received a research grant for this study and is on the advisory board of AstraZeneca and Roche. Dr. Fayad has received research grants from GlaxoSmithKline, AstraZeneca, Roche, Bristol-Myers Squibb Merck & Co. Inc., VBL Therapeutics, Philips, Siemens, Novartis, and the National Institute of Health. Dr. Tawakol has received research grants from Bristol-Myers Squibb, GlaxoSmithKline, Merck & Co. Inc., Genentech/Roche, VBL Therapeutics, Siemens, Novartis, and the National Institute of Health. He consults for Bristol-Myers Squibb, GlaxoSmithKline, Merck & Co. Inc., Novartis, and Roche. Dr. Wilkinson has received funding support from the British Heart Foundation as a funded post holder; he has also received educational grants from GlaxoSmithKline for current clinical trials. Dr. Cheriyan is employed by Cambridge University Hospitals National Health Service Foundation Trust and is obligated to spend 50% of his time on GlaxoSmithKline clinical trial research, representing a significant relationship; however, he receives no other benefits or compensations from GlaxoSmithKline. Ms. Elkhawad and Dr. Rudd contributed equally to this paper. H. William Strauss, MD, served as Guest Editor for this paper.
- Abbreviations and Acronyms
- CI
- confidence interval
- FDG
- fluorodeoxyglucose
- HD
- higher dose
- hsCRP
- high-sensitivity C-reactive protein
- LD
- lower dose
- MAPK
- mitogen-activated protein kinase
- PET/CT
- positron emission tomography/computed tomography
- SUV
- standard uptake value
- TBR
- tissue-to-background ratio
- Received September 10, 2011.
- Revision received January 13, 2012.
- Accepted February 29, 2012.
- American College of Cardiology Foundation
References
- ↵
- ↵
- ↵
- ↵
- Willette R.N.,
- Eybye M.E.,
- Olzinski A.R.,
- et al.
- ↵
- Morris J.B.,
- Olzinski A.R.,
- Bernard R.E.,
- et al.
- ↵
- Sarov-Blat L.,
- Morgan J.M.,
- Fernandez P.,
- et al.
- ↵
- Cheriyan J.,
- Webb A.J.,
- Sarov-Blat L.,
- et al.
- ↵
- Kubota R.,
- Yamada S.,
- Kubota K.,
- Ishiwata K.,
- Tamahashi N.,
- Ido T.
- ↵
- Ogawa M.,
- Magata Y.,
- Kato T.,
- et al.
- ↵
- Tawakol A.,
- Migrino R.Q.,
- Bashian G.G.,
- et al.
- ↵
- Folco E.J.,
- Sheikine Y.,
- Rocha V.Z.,
- et al.
- ↵
- Rudd J.H.,
- Warburton E.A.,
- Fryer T.D.,
- et al.
- ↵
- Tahara N.,
- Kai H.,
- Ishibashi M.,
- Nakaura H.,
- et al.
- ↵
- Lee S.J.,
- On Y.K.,
- Lee E.J.,
- Choi J.Y.,
- Kim B.T.,
- Lee K.H.
- Tahara N.,
- Kai H.,
- Yamagishi S.,
- et al.
- ↵
- Rosito G.A.,
- Massaro J.M.,
- Hoffmann U.,
- et al.
- Christen T.,
- Sheikine Y.,
- Rocha V.Z.,
- et al.
- ↵
- Rudd J.H.,
- Myers K.S.,
- Bansilal S.,
- et al.
- ↵
- Rudd J.H.,
- Myers K.S.,
- Bansilal S.,
- et al.
- Fayad Z.A.,
- Mani V.,
- Woodward M.,
- et al.
- Graebe M.,
- Pedersen S.F.,
- Højgaard L.,
- Kjaer A.,
- Sillesen H.
- Martin-Ventura J.L.,
- Blanco-Colio L.M.,
- Gomez-Hernandez A.,
- et al.
- ↵
- ↵
- ↵
- Menezes L.J.,
- Kotze C.W.,
- Hutton B.F.,
- et al.
- ↵
- ↵
- ↵
- Gropler R.J.,
- Peterson L.R.
- ↵
- Sweeney G.,
- Somwar R.,
- Ramlal T.,
- Volchuk A.,
- Ueyama A.,
- Klip A.
- ↵
- Wilson P.W.,
- Pencina M.,
- Jacques P.,
- Selhub J.,
- D'Agostino R. Sr..,
- O'Donnell C.J.
- Ridker P.M.
Toolbox
Citation Manager Formats
Article Outline
Figures in Article
Supplementary Materials
- Online Appendix and Online Tables 1 to 3
Effects of p38 Mitogen-Activated Protein Kinase Inhibition on Vascular and Systemic Inflammation in Patients With Atherosclerosis: Results From a Randomized Controlled Study
[S1936878X12005281_mmc1.docx]