信息编号11176001至11176050间共50条。
☉ 11176006:-Adrenergic Receptor–Stimulated Hypertrophy in Adu
the Cardiovascular Medicine Section Department of Medicine, and the Myocardial and Vascular Biology Units Boston University Medical Center, Boston, Mass. Abstract Background— -Adrenergic receptor (AR)–stimulated hypertrophy in adult rat ventricular myocytes is mediated by reactive oxygen species–dependent activation of the Ras-Raf-MEK1/2-ERK1/2 signaling pathway. Because Ras is known to have redox-sensitive cysteine residues, we tested the hypothesis that AR-stimulated hypertrophic signaling is mediated via oxidative modification of Ras thiols. Methods and Results— The effect of AR stimulation on the number of free thiols on Ras was measured with biotinylated iodoacetamide labeling. AR stimulation caused a 48% decrease in biotinylated iodoacetamide–labeled Ras that was reversed by dithiothreitol (10 mmol/L), indicating a decrease in the availability of free thiols on Ras as a result of an oxidative posttranslational modification. This effect was abolished by adenoviral overexpression of thioredoxin-1 (TRX1) and potentiated by the TRX reductase inhibitor azelaic acid. Likewise, AR-stimulated Ras activation was abolished by TRX1 overexpression and potentiated by azelaic acid. TRX1 overexpression inhibited the AR-stimulated phosphorylation of MEK1/2, ERK1/2, and p90RSK and prevented cellular hypertrophy, sarcomere reorganization, and protein synthesis (versus ;-galactosidase). Azelaic acid potentiated AR-stimulated protein synthesis. Although TRX1 can directly reduce thiols, it also can scavenge ROS by increasing peroxidase activity. To examine this possibility, peroxidase activity was increased by transfection with catalase, and intracellular reactive oxygen species were measured with dichlorofluorescein diacetate fluorescence. Although catalase increased peroxidase activity 20-fold, TRX1 had no effect. Likewise, the AR-stimulated increase in dichlorofluorescein diacetate fluorescence was abolished with catalase but retained with TRX1. Conclusions— AR-stimulated hypertrophic signaling in adult rat ventricular myocytes is mediated via a TRX1-sensitive posttranslational oxidative modification of thiols on Ras. Key Words: hypertrophy ; reactive oxygen species ; sulfhydryl compounds ; receptors, adrenergic, alpha ; thioredoxin Introduction In adult rat ventricular myocytes (ARVMs) in culture, -adrenergic receptor (AR)–stimulated hypertrophy is mediated via activation of the Ras-Raf-MEK1/2-ERK1/2 signaling pathway.1,2 We and others have shown that AR-mediated hypertrophic signaling and hypertrophy are mediated by reactive oxygen species (ROS).3–5 Nevertheless, little is known about the mechanism by which ROS initiate hypertrophic signaling. Ras activation is both necessary and sufficient for AR-stimulated protein synthesis in ARVMs.2 Ras has 4 cysteines with reactive thiol groups that can regulate its activity in response to oxidative modification.6,7 These observations suggest that ROS could mediate AR-stimulated hypertrophic signaling in ARVMs via the oxidative modification of thiols on Ras. Thioredoxin-1 (TRX1) is a cytosolic dithiol-disulfide oxidoreductase that plays an important role in maintaining intracellular thiols in a reduced state.8 TRX1 has been implicated in the regulation of cell growth in several cell types, including cardiac myocytes. In transgenic mice, myocyte-specific overexpression of TRX1 inhibits myocardial hypertrophy in response to pressure overload, whereas overexpression of a dominant negative mutant augments the hypertrophic response.9 Furthermore, in COS-7 cells, it was shown that TRX1 can regulate the basal level of Ras thiolation.9 It is not known whether a hypertrophic stimulus can cause oxidative posttranslational modification of Ras thiols in cardiac myocytes. Therefore, the goal of the present study was to test the hypothesis that AR-stimulated hypertrophy is mediated via the oxidative modification of thiols on Ras. The abundance of free thiols on Ras was measured by labeling with biotinylated iodoacetamide (BIAM). AR stimulation decreased the availability of free thiols on Ras; this effect was reversed by the reducing agent dithiothreitol (DTT), thus indicating that AR stimulation caused an oxidative posttranslational modification. The AR-stimulated decrease in free thiols was abolished by adenoviral overexpression of TRX1 and potentiated by the TRX reductase inhibitor azelaic acid, indicating that this effect was TRX1 sensitive. Finally, the functional importance of the TRX1-sensitive Ras thiol modification was assessed by measuring the effects of TRX1 and azelaic acid on AR-stimulated myocyte hypertrophy and hypertrophic signaling. Methods Cell Culture ARVMs were isolated from the hearts of adult (200 to 220 g) male Sprague-Dawley rats as described previously.10 Cells were plated at a nonconfluent density of 50 to 75 cells/mm2 on plastic culture dishes or glass coverslips precoated with laminin (1 μg/cm2) and kept at 37°C in ACCT medium (DMEM, BSA 2 mg/mL, L-carnitine 2 mmol/L, creatinine 5 mmol/L, taurine 5 mmol/L, penicillin 100 IU/mL, streptomycin 10 μg/mL) for 2 hours before adenoviral infection was performed. Cell Treatments L-Norepinephrine (1 μmol/L; Sigma) was added for 5 minutes (free Ras thiols, signaling), 48 hours (leucine incorporation, immunocytochemistry), or 30 minutes (intracellular ROS) before measurements. DL-Propranolol (2 μmol/L; Sigma) was added 30 minutes before L-norepinephrine. In some experiments, the TRX reductase inhibitor azelaic acid (10 μmol/L; Sigma)11 was added 16 hours before AR stimulation. All plates were supplemented with ascorbic acid (100 μmol/L; Sigma) to prevent oxidation of L-norepinephrine. Adenoviral Constructs An adenoviral plasmid expressing human TRX1 (ATCC, accession No. BC003377) was created by use of Gateway technology (Invitrogen). The TRX1 gene was transferred via BP and LR reactions to the adenoviral vector (Clontech) in which a Gateway Cassette (Invitrogen) had been inserted downstream of the cytomegalovirus promoter site. The ;-galactosidase (;-gal) and catalase (CAT) vectors were constructed as described by He et al.12 The adenoviral plaques were amplified in HEK 293 cells and purified with a double cesium chloride gradient. The viral titer was determined by the TCID50 method. Thirty-six hours before drug treatments, ARVMs were infected with the adenoviruses at a multiplicity of infection of 50/100. Ras Free Thiols Free reactive thiols were measured with BIAM (Molecular Probes) by a modification of the technique of Kim et al.13 Briefly, cells were lysed in buffer (1% NP 40, 0.25% DOC, 50 mmol/L PIPES, 100 μmol/L DTPA, 150 mmol/L NaCl, pH 6.5) containing 100 μmol/L BIAM. The lysates were separated by centrifugation at 14 000 rpm; ;-mercaptoethanol (50 mmol/L) was added to stop further thiol labeling; and the proteins were passed through a PD-10 Sephadex-G25 column to eliminate excess free BIAM. BIAM-labeled proteins were gathered with streptavidin-sepharose beads (50 μL) overnight, washed 4 times with lysis buffer, and separated from the beads by adding Laemmli buffer containing 5 mol/L urea. BIAM-labeled Ras was detected by Western blotting with a monoclonal anti-Ras antibody. In some experiments, DTT (10 mmol/L) was added to the lysis buffer before processing as described above. Ras Activation Assay Activated Ras was detected by a Ras activation assay kit (Upstate Biotechnology) according to the manufacturer’s instructions as previously described.4 Briefly, cell lysates (500 μg) were incubated at 4°C overnight with an agarose conjugate Ras-GTP affinity probe corresponding to the human Ras binding domain of Raf-1. The precipitates were resolved on a 4% to 20% SDS-PAGE and detected by Western blotting with an anti-Ras antibody. Western Blotting MEK1/2, ERK1/2, and p90RSK phosphorylation were assessed as previously described1 with anti–phospho-MEK1/2, anti-phospho-p44/42 MAP kinase, and anti–phospho-p90RSK antibodies (all from Cell Signaling). TRX1 was assessed with a polyclonal anti-human TRX1 antibody (BD Biosciences). Immunocytochemistry and Cell Size Cells were washed with PBS, fixed with 3.7% buffered formaldehyde for 30 minutes, and permeabilized with methanol at –20°C for 20 minutes. Cells were then treated with 5% BSA for 1 hour at room temperature and incubated with a monoclonal tetramethylrhodamine-5- (and 6)-isothiocyanate (TRITC)–conjugated (Pierce) anti–-sarcomeric actinin antibody for -sarcomeric actinin (clone EA-53, Sigma) at 37°C for another hour. Myocyte surface area was assessed with semiautomatic computer-assisted planimetry (Bioquant) from 2D images of unstained cells. Leucine Incorporation The cells were plated on 6-well laminin-coated dishes, and protein synthesis was measured as described previously.14 Peroxidase Activity Total cellular peroxidase activity was measured by spectrophotometry with 14 mmol/L H2O2 in a 15-mmol/L potassium phosphate buffer solution (pH 7) as described.15 Intracellular ROS Intracellular ROS were assessed with the ROS-sensitive fluorophore dichlorofluorescein diacetate (DCF) (Molecular Probes) as described previously.16 Briefly, cells were incubated with 20 μmol/L DCF for 30 minutes, and fluorescence was visualized and quantified with epifluorescent microscopy and video imaging (Bioquant, version 2.5). Statistical Analysis All data are presented as mean±SEM. Differences across multiple conditions were tested by 1-way ANOVA. Comparisons between conditions were tested by Student unpaired t test with Bonferroni correction for multiple comparisons. A value of P<0.05 was considered significant. Results AR Stimulation Decreases Free Ras Thiols To test the hypothesis that AR-stimulated hypertrophic signaling involves the modification of thiols on Ras, free thiols on Ras were measured by labeling with BIAM.13 AR stimulation (5 minutes) caused a 48% decrease in biotinylated Ras, indicating a decrease in the availability of free thiols resulting from a posttranslational modification. The AR-stimulated decrease in BIAM labeling was reversed by the addition of DTT to the lysis buffer, indicating that it is due to an oxidative modification (Figure 1A). The AR-Stimulated Decrease in Free Ras Thiols Is TRX1 Sensitive TRX1 was overexpressed by infection with an adenoviral vector for 36 hours. Under these conditions, TRX1 protein expression increased 6-fold, from 8±1 to 44±2 arbitrary units (P<0.0001 versus ;-gal). AR stimulation alone for up to 48 hours had no effect on TRX1 expression (data not shown). TRX1 overexpression abolished the AR-stimulated decrease in free Ras thiols (Figure 1B), suggesting that the decrease in free thiols is due to an oxidative modification that is sensitive to TRX1. To examine the role of endogenous TRX, TRX reductase was inhibited with azelaic acid.11 Azelaic acid decreased the abundance of both basal and AR-stimulated free Ras thiols (Figure 1C). Overexpression of TRX1 Inhibits AR-Stimulated Ras Activation AR stimulation (5 minutes) increased Ras activity by 2-fold (Figure 2). TRX1 overexpression had no effect on basal Ras activity but abolished the AR-stimulated increase (Figure 2A). Conversely, inhibition of TRX with azelaic acid tended to increase basal Ras activity and significantly potentiated the AR-stimulated increase (Figure 2B). Overexpression of TRX1 Inhibits AR-Stimulated Downstream Hypertrophic Signaling TRX1 overexpression abolished AR-stimulated phosphorylation of MEK1/2 and inhibited AR-stimulated phosphorylation of both ERK1/2 and its substrate, p90RSK (Figure 3). Overexpression of TRX1 Inhibits AR-Stimulated Hypertrophy in ARVMs We have previously shown that AR stimulation (48 hours) causes cellular hypertrophy that is associated with sarcomere reorganization and increased protein synthesis.3 TRX1 overexpression abolished both AR-stimulated sarcomere reorganization and hypertrophy (Figure 4A and 4B). Expression of ;-gal had no effect on basal or AR-stimulated hypertrophy or sarcomere reorganization compared with uninfected control cells (data not shown). Leucine incorporation was measured to assess protein synthesis. In ;-gal–expressing cells, AR stimulation increased leucine incorporation by 44±2%. TRX1 overexpression decreased basal leucine incorporation by 63±3% and abolished the response to AR stimulation (–95±9% versus ;-gal) (Figure 4C). The decrease in basal leucine incorporation was not due to cell loss because TRX1 overexpression had no effect on cell number (TRX1, 54±7 cells/mm2; ;-gal, 55±3 cells/mm2; P=NS; n=3). Likewise, TRX1 overexpression had no effect on total cellular protein, which was 104±3% of that in ;-gal–expressing cells (P=NS; n=4). In contrast, inhibition of TRX with azelaic acid caused a 49±3% augmentation of AR-stimulated leucine incorporation (P<0.05, n=3). TRX1 overexpression had no effect on leucine incorporation in response to either 3% or 10% serum (data not shown), indicating that inhibition of AR-stimulated protein synthesis is not due to a generalized effect on protein synthesis. Effect of TRX1 Overexpression on Peroxidase Activity and Intracellular ROS TRX1 might inhibit oxidative thiol modification directly via an interaction with the thiol group or indirectly by increasing peroxidase activity. TRX1 overexpression had no effect on peroxidase activity in ARVMs, whereas adenoviral overexpression of CAT increased peroxidase activity 20-fold (Figure 5). AR stimulation increased intracellular ROS, as assessed by DCF, by 117±15% (Figure 6A and 6B). Although both TRX1 and CAT overexpression decreased basal DCF, the AR-stimulated increase was prevented by CAT but not TRX1 overexpression. Discussion This study provides several new observations about the redox regulation of hypertrophic signaling in adult cardiomyocytes. First, AR stimulation decreased the availability of free thiols on Ras, and this effect was reversed by the reducing agent DTT. Second, the AR-stimulated decrease in Ras free thiols was prevented by overexpression of TRX1 and potentiated by inhibition of TRX with azelaic acid. Third, in parallel with the changes in free thiols, the AR-stimulated activation of Ras was prevented by overexpression of TRX1 and potentiated by azelaic acid. Finally, TRX1 inhibited AR-stimulated activation of the Ras-associated hypertrophic signaling pathway and myocyte hypertrophy, whereas azelaic acid potentiated AR-stimulated hypertrophy. We previously demonstrated in ARVMs that AR-stimulated hypertrophy is associated with ROS-mediated activation of Ras.1,4 Recently, Wang and Proud2 showed that Ras activation is both necessary and adequate for AR-stimulated protein synthesis in ARVMs. Ras has 4 cysteines with reactive thiol groups that can regulate its activity in response to oxidative modifications such as S-nitrosylation or S-glutathiolation.6,7 Free (ie, reduced) thiols react with iodoacetamide; therefore, the availability of free thiols can be quantified by use of BIAM to label and separate reduced thiols.13 AR stimulation caused a rapid (5 minutes) 50% decrease in the abundance of free Ras thiols, indicating a posttranslational modification. The AR-stimulated decrease was reversed by DTT, indicating that the modification was oxidative. To clarify the functional consequences of the AR-stimulated Ras modification, TRX1 was overexpressed. TRX1 is an oxidoreductase that plays an important role in maintaining intracellular thiols in a reduced state.8 TRX1 overexpression prevented the AR-stimulated decrease in free Ras thiols and the activation of Ras, indicating that both effects are mediated via a TRX1-sensitive mechanism. Likewise, TRX1 overexpression inhibited AR-stimulated activation of the MEK/ERK signaling cascade that plays a major role in mediating hypertrophy in adult rat cardiac myocytes.1 Although TRX1 overexpression abolished AR-stimulated Ras activation, inhibition of ERK was not complete. This observation is consistent with prior observations suggesting that there is a small amount of Ras-independent AR-stimulated ERK1/2 activation in adult rat cardiac myocytes.2 Conversely, inhibition of endogenous TRX with azelaic acid potentiated both the AR-stimulated decrease in free thiols and the AR-stimulated activation of Ras. These effects of TRX overexpression and inhibition, together with the effect of DTT, support our hypothesis that AR-stimulated activation of Ras requires an oxidative modification of thiols. This thesis is also consistent with our recent demonstration that the oxidative modification of Cyc118 of Ras via S-glutathiolation mediates angiotensin-induced hypertrophic signaling in vascular smooth muscle cells17 and the demonstration by Yamamoto et al9 that overexpression of dominant negative TRX1 increases the basal level of Ras thiolation in COS-7 cells. TRX can regulate the intracellular redox state by 2 mechanisms. First, TRX can directly catalyze the reduction of protein thiol groups.18–20 Second, the TRX system, consisting of TRX, TRX reductase, and NADPH, can scavenge ROS by supplying electrons for TRX peroxidase and other peroxidases, leading to increased peroxidase activity.21,22 Our data show that TRX1 overexpression had no measurable effect on cellular peroxidase activity. Likewise, although TRX1 decreased basal and AR-stimulated intracellular ROS levels, it had no effect on the AR-stimulated increase. The decrease in ROS with TRX1 likely reflects a direct chemical interaction between H2O2 and reduced sulfhydryl groups on TRX1 rather than increased peroxidase activity. Taken together, these observations suggest that TRX1 exerts its antihypertrophic effect by decreasing the oxidative posttranslational modification of Ras thiol groups. The data are consistent with the thesis that TRX1 inhibits AR-stimulated hypertrophy by protecting Ras thiols from oxidative modification. Although we cannot exclude the possibility that TRX1 also inhibits AR-stimulated signaling proximal to Ras, it seems unlikely because TRX1 did not inhibit the AR-stimulated increase in ROS as measured by DCF and because we have found no effect of TRX1 overexpression on AR-stimulated NADPH oxidase activity (data not shown). TRX1 overexpression decreased AR-stimulated myocyte hypertrophy, as evidenced by inhibition of the AR-stimulated increase in myocyte size, sarcomere reorganization, and protein synthesis. Conversely, inhibition of endogenous TRX with azelaic acid potentiated AR-stimulated protein synthesis. These observations are consistent with those of Yamamoto et al,9 who found that cardiac-specific transgenic overexpression of TRX1 in mice inhibited the hypertrophic effect of aortic banding and conversely that overexpression of a TRX1 dominant negative mutant potentiated the hypertrophic response. We found that TRX1 also decreased basal leucine incorporation in unstimulated myocytes: The decrease in leucine incorporation was not associated with a reduction in cell number, indicating that it was due to a decrease in basal protein synthesis rather than cell loss. The TRX1-induced decrease in basal protein synthesis was not associated with a decrease in cell size. This observation raises the possibility that TRX1 also decreased protein degradation and is consistent with the demonstration that oxidative thiol modifications can target proteins for degradation by the ubiquitin-proteasome pathway.23 In addition, we found that TRX1-overexpressing myocytes had a preserved protein synthetic response to serum, further indicating that the effects of TRX1 on both basal and AR-stimulated protein synthesis are not due to a generalized decrease in cellular synthetic function. It should be noted that the potent antihypertrophic effects of TRX1 found in our study in adult myocytes and by Yamamoto et al9 in mice differ from the findings of Yoshioka et al,24 who found that in vitro overexpression of TRX1 increased basal and AR-stimulated protein synthesis in neonatal rat cardiac myocytes, whereas overexpression of TRX-interacting protein, an endogenous inhibitor of TRX1, attenuated the hypertrophic response. They also found that in vivo inhibition of TRX1 with TRX-interacting protein decreased the hypertrophic response to pressure overload. Given the multiple actions of and substrates for TRX1, these disparate results may be due to differences related to cell type, cell species, and/or developmental stage. For example, although we have shown that TRX1 can inhibit Ras-mediated hypertrophic signaling, TRX1 can also activate transcription factors (eg, NF-B, AP-1), interact with signaling proteins (eg, ASK, PKC), and possibly bind to a cell surface receptor.25–32 Taken together, our findings indicate that AR stimulation causes the oxidative posttranslational modification of Ras in adult cardiac myocytes. Overexpression of TRX1 attenuated and inhibition of TRX potentiated the AR-stimulated decrease in free thiols, Ras activation, and myocyte hypertrophy, thus supporting the functional relevance of the posttranslational Ras modification. These observations identify a specific molecular site at which ROS act to mediate myocyte hypertrophy. Thus, modulation of intracellular thiol redox state may play a role in the pathophysiology and/or therapy of myocardial remodeling. Acknowledgments This work was supported by NIH National Heart, Lung and Blood Institute sponsoring of the Boston University Cardiovascular Proteomics Center (contract HHSN268200248178C) and grants HL-61639 and HL-20612 (Dr Colucci) and by grants from the American Heart Association (Drs Siwik, Pimentel, and Adachi), Swiss National Science Foundation (Dr Kuster), and Kilo Diabetes Research Foundation (Dr Ido). We thank Xinxin Guo, Kara Clemente, and Jing Wang for their expert technical assistance. Footnotes Guest Editor for this article was Roberto Bolli, MD. References Xiao L, Pimental DR, Amin JK, Singh K, Sawyer DB, Colucci WS. MEK1/2-ERK1/2 mediates alpha1-adrenergic receptor–stimulated hypertrophy in adult rat ventricular myocytes. 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A molecular redox switch on p21(ras): structural basis for the nitric oxide-p21(ras) interaction. J Biol Chem. 1997; 272: 4323–4326. Mallis RJ, Buss JE, Thomas JA. Oxidative modification of H-ras: S-thiolation and S-nitrosylation of reactive cysteines. Biochem J. 2001; 355: 145–153. Yamawaki H, Haendeler J, Berk BC. Thioredoxin: a key regulator of cardiovascular homeostasis. Circ Res. 2003; 93: 1029–1033. Yamamoto M, Yang G, Hong C, Liu J, Holle E, Yu X, Wagner T, Vatner SF, Sadoshima J. Inhibition of endogenous thioredoxin in the heart increases oxidative stress and cardiac hypertrophy. J Clin Invest. 2003; 112: 1395–1406. Communal C, Singh K, Pimentel DR, Colucci WS. Norepinephrine stimulates apoptosis in adult rat ventricular myocytes by activation of the ;-adrenergic pathway. Circulation. 1998; 98: 1329–1334. Hojo Y, Saito Y, Tanimoto T, Hoefen RJ, Baines CP, Yamamoto K, Haendeler J, Asmis R, Berk BC. 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Jain M, Brenner DA, Cui L, Lim CC, Wang B, Pimentel DR, Koh S, Sawyer DB, Leopold JA, Handy DE, Loscalzo J, Apstein CS, Liao R. Glucose-6-phosphate dehydrogenase modulates cytosolic redox status and contractile phenotype in adult cardiomyocytes. Circ Res. 2003; 93: e9–e16. Adachi T, Pimentel DR, Heibeck T, Hou X, Lee YJ, Jiang B, Ido Y, Cohen RA. S-glutathiolation of Ras mediates redox-sensitive signaling by angiotensin II in vascular smooth muscle cells. J Biol Chem. 2004; 279: 29857–29862. Holmgren A. Thioredoxin structure and mechanism: conformational changes on oxidation of the active-site sulfhydryls to a disulfide. Structure. 1995; 3: 239–243. Nakamura H, Nakamura K, Yodoi J. Redox regulation of cellular activation. Annu Rev Immunol. 1997; 15: 351–369. Arner ES, Holmgren A. Physiological functions of thioredoxin and thioredoxin reductase. Eur J Biochem. 2000; 267: 6102–6109. Spector A, Yan GZ, Huang RR, McDermott MJ, Gascoyne PR, Pigiet V. 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Mammalian thioredoxin is a direct inhibitor of apoptosis signal–regulating kinase (ASK) 1. EMBO J. 1998; 17: 2596–2606. Tanaka T, Nakamura H, Nishiyama A, Hosoi F, Masutani H, Wada H, Yodoi J. Redox regulation by thioredoxin superfamily: protection against oxidative stress and aging. Free Radic Res. 2001; 33: 851–855. Hirota K, Matsui M, Iwata S, Nishiyama A, Mori K, Yodoi J. AP-1 transcriptional activity is regulated by a direct association between thioredoxin and Ref-1. Proc Natl Acad Sci U S A. 1997; 94: 3633–3638. Matthews JR, Wakasugi N, Virelizier JL, Yodoi J, Hay RT. Thioredoxin regulates the DNA binding activity of NF-kappa B by reduction of a disulphide bond involving cysteine 62. Nucleic Acids Res. 1992; 20: 3821–3830. Schenk H, Klein M, Erdbrugger W, Droge W, Schulze-Osthoff K. Distinct effects of thioredoxin and antioxidants on the activation of transcription factors NF-kappa B and AP-1. Proc Natl Acad Sci U S A. 1994; 91: 1672–1676. Watson JA, Rumsby MG, Wolowacz RG. 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☉ 11176007:p38 Mitogen-Activated Protein Kinase Downregulates Endothelial Progenitor Cells
Molecular Cardiology, Department of Internal Medicine III, University of Frankfurt, Theodor-Stern-Kai 7, Frankfurt, Germany (F.H.S., J.H., D.H.W., U.R., J.R., C.U., L.R., A.M.Z., S.D.) Serono Pharmaceutical Research Institute, Geneva, Switzerland (A.C., Y.C.). Abstract Background— Transplantation of endothelial progenitor cells (EPCs) improves neovascularization after ischemia, but patients with coronary artery disease (CAD) or diabetes mellitus show a reduced number of EPCs and impaired functional activity. Therefore, we investigated the effects of risk factors, such as glucose and TNF-, on the number of EPCs in vitro to elucidate the underlying mechanisms. Methods and Results— EPCs of patients or healthy subjects were isolated from peripheral blood. Incubation with glucose or TNF- dose-dependently reduced the number of EPCs (79.9±1.3% and 74.3±8.1% of control; P<0.05, respectively). This reduction was not caused by apoptosis. TNF- and glucose induced a dose- and time-dependent activation of the p38 MAP kinase, the downstream kinase mitogen- and stress-activated kinase 1, and the transcription factor cAMP-responsive element–binding protein (CREB), in EPCs. Moreover, EPCs from CAD patients had significantly higher basal p38-phosphorylation levels (1.83±0.2-fold increase; P<0.05) compared with healthy subjects. The inhibition of the p38-kinase by SB203580 or infection with a dominant negative p38 kinase adenovirus significantly increased basal number of EPCs (136.7±6.3% and 142.9±18% versus control, respectively). Likewise, ex vivo cultivation of EPCs from patients with CAD with SB203580 significantly increased the number of EPCs and partially reversed the impaired capacity for neovascularization of EPCs in vivo (relative blood flow: 0.40±0.03 versus 0.64±0.08, P<0.05). The increased numbers of EPCs by SB203580 were associated with an augmentation of EPC proliferation and a reduction of cells expressing the monocytic marker proteins CD14 and CD64, suggesting that p38 regulates proliferation and differentiation events. Conclusions— These results demonstrate that p38 MAP kinase plays a pivotal role in the signal transduction pathways regulating the number of EPCs ex vivo. SB203580 can prevent the negative effects of TNF- and glucose on the number of EPCs and may be useful to improve the number of EPCs for potential cell therapy. Key Words: angiogenesis ; glucose ; mitogen-activated protein kinases ; stem cells ; tumor necrosis factor- Introduction Transplantation of endothelial progenitor cells (EPCs) successfully enhances neovascularization in animal experiments.1 Moreover, initial clinical pilot trials suggest that bone marrow–derived mononuclear cells or ex vivo expanded EPCs augment neovascularization after peripheral ischemia2 as well as in humans after myocardial infarction.3 Therefore, this beneficial property of EPCs is attractive for cell therapy targeting regeneration of ischemic tissue. Unfortunately, the functional activity of EPCs is impaired in patients with coronary artery disease (CAD).4 In vivo data revealed that the number of circulating progenitor cells inversely correlates with risk factors for CAD, such as diabetes, hypertension, or smoking.4 Endothelial progenitor cells derived from patients with type II diabetes exhibited impaired proliferation, adhesion, and incorporation into vascular structures.5 Moreover, EPCs are reduced in patients with type I diabetes.6 The molecular mechanisms underlying the reduced numbers of EPCs and function are not yet clearly defined and may involve a reduced mobilization.7 However, whereas the numbers of EPCs defined as CD133/KDR- or CD34/KDR-positive cells were lower in patients compared with healthy control subjects, the numbers of hematopoietic stem cells expressing CD45/CD34 or CD45/CD133 are not severely reduced in patients with CAD.4 Moreover, lower numbers of EPCs are obtained when equal numbers of mononuclear cells from patients with CAD are expanded ex vivo, suggesting that risk factors for CAD may affect proliferation and differentiation of EPCs.4 Mitogen-activated protein kinases (MAPKs) coordinately regulate cellular proliferation and differentiation induced by a variety of cellular stresses, such as TNF-, in different cell types.8 It has also been reported previously that high glucose levels can activate the p38 MAPK pathway in many cell types, including endothelial cells.9 MAPKs are a family of serine/threonine kinases that comprise 3 major subgroups, namely, extracellular signal–regulated kinase (ERK), p38 MAPK (p38), and c-Jun N-terminal kinases (JNK). Because TNF- and glucose have been reported to activate the p38, this could be a potential effector signaling mechanism impairing proliferation and differentiation of EPCs. Stimulation of the p38 results in phosphorylation of the downstream kinase mitogen- and stress-activated kinase (MSK) 1 and activation of transcription factors cAMP-responsive element–binding protein (CREB), ATF1, and ATF2, which are involved in the regulation of proliferation and differentiation of hematopoietic progenitor cells and other cell types.10,11 The aim of the present study was to examine the role of MAPK, particularly p38, in the regulation of numbers of EPCs by risk factors for CAD. Our results demonstrate that the reduction of numbers of EPCs induced by TNF- and glucose in vitro was associated with a profound upregulation of p38 phosphorylation and was completely blocked by p38 inhibitors. Furthermore, EPCs cultivated from patients with CAD showed an increased p38 phosphorylation compared with EPCs from healthy control subjects. TNF- and high glucose further augmented the phosphorylation of the p38 downstream kinase MSK1 and the transcription factor CREB, whereas ATF2 was not phosphorylated in EPCs, suggesting that MSK1/CREB mediate the p38-dependent effects. Indeed, the inhibitor H89, which inhibits MSK1, also increased numbers of EPCs. Methods Study Population and Patient Characteristics Mononuclear cells were isolated from the peripheral blood of 10 healthy human volunteers and 23 patients with stable CAD documented by angiographic evidence of coronary lesions (Table). Patients with a history of myocardial ischemia documented by the classic symptoms of chest pain, ECG alterations, or elevation of creatine kinase or troponin T within the previous 3 months were excluded. Further exclusion criteria were the presence of active or chronic infection, surgical procedures or trauma within the last 3 months, or evidence for malignant diseases. All women included were in postmenopause and did not take hormone replacement therapy. The Ethics Review Board of the Hospital of the Johann Wolfgang Goethe University of Frankfurt, Germany, approved the protocol, and the study was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from each patient. The mononuclear cells of patients were used to measure number of cells (n=14 patients), phospho-p38 levels (n=10 patients), and relative blood flow (n=5 patients), dependent on the cell number obtained after isolation. The baseline patient characteristics were not different in the subgroups compared with the total patient population. Patient Characteristics Isolation, Cultivation, and Characterization of EPCs Mononuclear cells were isolated by density-gradient centrifugation with Biocoll separating solution from the peripheral blood of healthy human volunteers or patients with stable CAD (CAD patients) as described previously.4 Mononuclear cells (8x106 cells/mL medium) were plated on culture dishes coated with human fibronectin (Sigma) and maintained in endothelial basal medium (EBM; CellSystems) supplemented with 1 μg/mL hydrocortisone, 12 μg/mL bovine brain extract, 50 μg/mL gentamycin, 50 ng/mL amphotericin B, 10 ng/mL epidermal growth factor, and 20% FCS. Mononuclear cells of patients for Dil-Ac-LDL/Lectin staining were suspended in X vivo-15 medium (Biowhittaker) supplemented with 1 ng/mL carrier-free human recombinant vascular endothelial growth factor (VEGF) (R&D), 0.1 μmol/L atorvastatin (provided by Pfizer), and 20% human serum drawn from each individual patient.3 After 4 days of culture, more than 90% of the EPCs expressed the endothelial marker proteins KDR, VE-cadherin, and von Willebrand factor.4,12,13 Cells were incubated at the day of isolation (day 0), at day 3 (day 3), or repetitively at days 1, 2, and 3 (days 1 to 3) with TNF- or glucose without changing the medium. Murine Hindlimb Ischemia Model The incorporation of EPCs and their contribution to neovascularization were investigated in a murine model of hindlimb ischemia in 8- to 10-week-old athymic NMRI nude mice (The Jackson Laboratory) weighing 18 to 22 g. Ischemia was induced by ligation of the proximal femoral artery, including the superficial and the deep branches, with 7-0 silk suture. All arterial side branches were obliterated by use of an electrical coagulator (Erbe). The overlying skin was closed by use of surgical staples. After 24 hours, mice received an intravenous injection of 5x105 EPCs from healthy volunteers or patients with or without preincubation with the p38 inhibitor SB203580. Two weeks after induction of ischemia, blood flow of the ischemic (right) and normal (left) limb was measured by laser Doppler imager (MoorLDI-Mark 2, Moor Instruments). The perfusion of the ischemic and nonischemic limbs was calculated on the basis of colored histogram pixels (red = high perfusion, blue = low perfusion). Calculated perfusion was expressed as a ratio of right (ischemic) to left (nonischemic) limb. Dil-Ac-LDL/Lectin Staining Cells were incubated with 2.4 μg/mL 1,1'-dioctadecyl-3,3,3',3'-tetramethylindocarbocyanine–labeled acetylated LDL (Dil-Ac-LDL) (Harbor Bio-Products) for 1 hour. Cells were fixed in 4% paraformaldehyde and counterstained with FITC-labeled lectin from Ulex europaeus (Sigma). Then, 3 to 5 power fields were randomly counted using a computer-based program. Detection of Apoptosis by FACS Analysis The adherent cells were trypsinized for 2 minutes, then the reaction was stopped with PBS/10% FCS. Then, the cells were washed twice with annexin-binding buffer and incubated with 2.5 μL annexin-PE and 2.5 μL 7AAD for 20 minutes at room temperature according to the instructions of the manufacturer (Pharmingen, Annexin V-Pe Apoptosis Kit). Then, cells were analyzed by fluorescence-activated cell sorting (FACS) using a FACSCalibur flow cytometer and Cell Quest software (BD Biosciences). Proliferation Assay Living cells were incubated with bromodeoxyuridine (BrdU) labeling reagent for 3 days at 37°C. Cells were trypsinized for 2 minutes, the reaction was stopped with PBS/10% FCS, and cells were pelleted by centrifugation. Staining was performed according to the manufacturer’s protocol (Roche). Briefly, cells were fixed, digested for 1 hour with DNAse, and then incubated with an anti–BrdU-FITC antibody and thereafter with 1 μg/mL propidium iodide, and analyzed by FACS as previously described.14 Adenoviral Infection The dominant negative p38 adenovirus was provided by J. Han (The Scripps Research Institute). Antennapedia peptide (Antennapedia internalization sequence RQIAIWFQNRRMKWAA) at a concentration of 0.5 mmol/L, adenovirus (20 multiplicity of infection), and 100 μL of OptiMem (Gibco) were incubated for 30 minutes at room temperature. The mixture was then added to freshly isolated mononuclear cells in 2.5-mL volume and incubated with the cells until day 3. Western Blot Analysis Cells were washed and incubated in 75 μL lysis buffer as described previously.13 The nuclear and cytosolic fractions were separated by use of a commercially available kit according to the manufacturer’s protocol (Pierce) as described previously.14 The purity of the nuclear and cytosolic fractions was ensured by immunoblotting with topoisomerase-1. Proteins (30 to 50 μg/lane) were loaded onto SDS-polyacrylamide gels and blotted onto polyvinylidene difluoride membranes. Western blots were performed by use of antibodies directed against phospho-p38, phospho-CREB, phospho-ATF2, phospho-ERK1/2, phospho-MSK1, total p38, and total CREB (1:1000; Cell Signaling), ;-actin (1:10 000, Sigma), and topoisomerase-1 (1:250; Santa Cruz Biotechnology). Anti-rabbit and anti-mouse secondary antibodies (1:10 000) were from Amersham, and anti-goat antibody (1:6000) was from Santa Cruz Biotechnology. Enhanced chemiluminescence was performed according to the instructions of the manufacturer (Amersham). The autoradiographs were scanned and semiquantitatively analyzed, and the protein ratio was calculated (Scion Image). Protein/DNA–Binding Assay Protein/DNA arrays were performed according to the manufacturer’s protocol (Panomics). Briefly, 25 μg of nuclear extract was incubated with the TranSignal Probe Mix. DNA/protein complexes were washed. Then, DNA was separated from protein and hybridized on the membranes at 42°C. Signal was detected by use of ECL-Hyperfilm, and semiquantitative analysis was performed by use of Scion Image. VEGF-ELISA VEGF levels in the supernatants were measured by a high-sensitivity ELISA (R&D Systems) according to the manufacturer’s protocol. Samples were performed in duplicate. Flow Cytometry Analysis Mononuclear cells were incubated with SB203580 (1 μmol/L) after isolation. At day 3, the adherent EPCs were trypsinized and were pooled with the supernatant. A total number of 500 000 cells were incubated in the dark for 15 minutes with an APC-conjugated monoclonal mouse anti-CD14, a PE-conjugated mouse anti-CD64, or a FITC-conjugated anti–von Willebrand factor (BD Biosciences) antibody. Isotype-identical antibodies served as controls. Analysis was performed by use of a FACSCalibur flow cytometer and Cell Quest software (BD Biosciences). Statistical Analysis Data are expressed as mean±SEM from at least 3 independent experiments. For in vitro data, statistical analysis was performed by use of a 2-sided Student t test; comparisons between groups were analyzed by t test (2-sided) or ANOVA for experiments with more than 2 subgroups. Post hoc range tests and pairwise multiple comparisons were performed with Bonferroni adjustment. Probability values of P<0.05 were considered statistically significant. Results TNF- and Glucose Reduce EPC Number Human peripheral blood mononuclear cells were isolated and cultivated as described previously.4 EPCs were characterized as adherent cells after 4 days of cultivation that were double-positive for both lectin and Di-LDL uptake. In addition, the endothelial phenotype was confirmed by demonstrating the expression of the endothelial marker proteins KDR, vascular endothelium-cadherin, and von Willebrand factor by flow cytometry.4,13,15 Incubation of mononuclear cells at day 0 (day 0), at day 3 (day 3) or repetitively at days 1, 2, and 3 (days 1 to 3) with TNF- (10 ng/mL) induced a significant reduction of adherent EPCs (Figure 1A). This inhibitory effect of TNF- was dose dependent (Figure 1B). Incubation of mononuclear cells with high glucose levels, which are pathophysiologically relevant in patients with type II diabetes, at day 0 (data not shown) or at day 3 after isolation also revealed a dose-dependent reduction of EPCs, whereas an osmotic control with mannitol did not influence the number of EPCs (Figure 1C). The effect of TNF- (10 ng/mL) or glucose (15 mmol/L) was even more pronounced when the cells were cultured in serum-depleted medium, as shown in Figure 1D. TNF- and Glucose Activate p38 The p38-kinase has been shown to be involved in cell differentiation, proliferation, and apoptosis. Therefore, we investigated whether TNF- or glucose increases p38 phosphorylation. Incubation of EPCs with TNF- time- and dose-dependently increased p38-phosphorylation (Figure 2, A and B). The maximum of p38 activity (5-fold phosphorylation) was obtained at 10 minutes of incubation (Figure 2A). Preincubation of the cells for 20 minutes with the specific p38-inhibitor SB20358016–19 (1 μmol/L) prevented p38-phosphorylation by TNF- (Figure 2A). Similar results were obtained when EPCs were incubated with high levels of glucose (Figure 2, C and D). Moreover, long-term incubation of EPCs from day 0 with TNF- and glucose resulted in a significant increase of p38-phosphorylation (Figure 2E). In addition, TNF- activated the MAP kinase ERK1/2 (Figure 2F). Of note, SB203580 did not inhibit TNF-–induced ERK1/2 phosphorylation (Figure 2F). SB203580 Increases the Number of EPCs Having demonstrated that TNF- and glucose increase p38 and ERK1/2 activity, we next investigated the effect of specific p38 and ERK inhibitors on the number of EPCs. SB203580 significantly increased the number of EPCs under basal conditions and abolished TNF-– and glucose-induced reduction of the number of EPCs (Figure 3). Likewise, infection of EPCs at day 3 with a dominant negative p38 adenovirus also significantly increased the number of EPCs under basal conditions to an extent similar to that of blockade of p38 with SB203580 (142.9±18% compared with control). In contrast, the inhibitor of ERK activation PD98059 had no effect on the number of EPCs (Figure 3). SB203580 Increases the Number of EPCs in Healthy Control Subjects and in Patients With CAD To further elucidate a potential clinical relevance, we examined the effect of SB203580 on EPCs of patients with CAD. As reported previously,4 patients with CAD showed significantly lower levels of ex vivo–cultivated EPCs compared with healthy subjects. Incubation of EPCs with SB203580 at day 3 after isolation increased the number of EPCs of healthy control subjects as well as CAD patients. After incubation with SB203580, the number of cultivated EPCs from patients was similar to that of healthy untreated subjects’ EPCs (Figure 4A). Thus, we hypothesized that healthy subjects and CAD patients may have different basal p38 activity. Therefore, we measured the basal p38 activity in healthy subjects as well as in CAD patients. As shown in Figure 4B, p38 activity is increased almost 2-fold under basal conditions in CAD patients compared with healthy subjects. Because EPCs derived from patients with CAD demonstrated impaired neovascularization in the hindlimb ischemia compared with EPCs from healthy volunteers (Figure 4C), we next investigated whether pretreatment with SB203580 of EPCs derived from patients with CAD would improve recovery of blood flow of ischemic hindlimbs in nude mice. Indeed, infusion of SB203580-pretreated EPCs derived from patients with CAD significantly increased recovery of blood flow in the ischemic hindlimb model compared with untreated EPCs from CAD patients (Figure 4C). Effect of p38 on Apoptosis, Proliferation, and Differentiation The increased numbers of EPCs after ex vivo incubation of mononuclear cells with the p38 inhibitor could be a result of diverse effects, including the inhibition of apoptosis, stimulation of proliferation, or promotion of differentiation; however, apoptosis, as detected by annexin-FACS staining, was not affected (Figure 5A). In contrast, treatment of EPCs with the p38 inhibitor SB203580 significantly augmented EPC proliferation, as assessed by BrdU staining (Figure 5C). Next, we assessed the potential influence of p38 inhibition on the release of cytokines such as VEGF, which promotes EPC differentiation and proliferation. However, VEGF levels were similar in SB203580-treated and control cells (Figure 5B), excluding a potential effect of the p38 inhibitor on the expression of this cytokine. Finally, on the basis of the finding that the p38 kinase enhances the differentiation of macrophages,10 we investigated whether the p38 inhibitor affects the balance between monocytic and endothelial cell differentiation. Indeed, coincubation of SB203580 with the total mononuclear cells reduced the relative proportion of cells expressing CD14 and CD64 (Figure 5D). In contrast, p38 inhibition increased the relative proportion of cells expressing the endothelial marker von Willebrand factor (Figure 5E). Thus, these data support the concept that the increase in cell number seen after inhibition of p38 activation depends on increased proliferation as well as on differentiation toward the endothelial cell lineage. Downstream Mechanisms Next, we determined the downstream targets of p38 mediating the reduction of EPC numbers. After incubation of EPCs and mononuclear cells with TNF-, p38 is phosphorylated in the nucleus (Figure 6A). Likewise, the p38-downstream kinase MSK1 and the transcription factor CREB are phosphorylated in a p38-dependent manner in nuclear fractions of EPCs and mononuclear cells after TNF- or glucose treatment (Figure 6, A and B). However, ATF2, another p38-regulated transcription factor, is not phosphorylated by TNF- in EPCs and mononuclear cells (Figure 6A). To obtain additional data on the transcription factors regulated by p38 inhibition, we used a novel array technology to assess the DNA-binding activity of multiple transcription factors. Incubation of EPCs with glucose significantly increased the DNA-binding activity of CREB in a p38-dependent manner (Figure 6, C and D). In addition, glucose increased the DNA binding of activating protein (AP)-1 and AP-2, whereas a variety of other transcription factors were not affected (Figure 6, C and D). To finally determine the involvement of the downstream p38 targets involved in activation of CREB, we blocked MSK1. Incubation of EPCs and mononuclear cells with H89, a kinase inhibitor, which, in the concentration used (10 μmol/L), blocks MSK1 and partially blocks protein kinase A, did not affect TNF-–induced p38 phosphorylation but significantly inhibited MSK1 and CREB phosphorylation (Figure 7A). Moreover, incubation of total mononuclear cells with H89 enhanced the yield of adherent EPCs in the ex vivo culture assay (Figure 7B), suggesting that MSK-1 may be involved in p38-dependent activation of CREB. Discussion The present study demonstrates that p38 contributes to the reduction of numbers of EPCs induced by TNF- and high glucose levels in an ex vivo culture assay. Interestingly, although a related MAPK family member, ERK1/2, was activated by TNF-, its inhibition did not affect the number of EPCs, suggesting that p38 plays a rather specific role in affecting numbers of EPCs. The clinical relevance of these in vitro findings was further supported by the demonstration that EPCs isolated from patients with CAD exhibit an increased p38 phosphorylation. Moreover, the p38 inhibitor SB230580 increased the number of ex vivo–expanded EPCs isolated from patients with CAD. Of note, this effect was detected on top of optimal culture conditions used for clinical stem cell therapy, including statins,3 which were shown to augment the numbers and functions of EPCs when added to the culture medium.13,20 Moreover, pretreatment with SB203580 of EPCs isolated from patients with CAD led to a significant improvement of blood flow in the hindlimb ischemia model, underscoring the in vivo relevance of p38 activity blockade. p38 activation regulates a variety of downstream signaling cascades. In the present study, we demonstrate that TNF- and high glucose induced a p38–dependent phosphorylation of MSK1 in the cytosol and in the nucleus. MSK1 is a recently described nuclear CREB and histone H3 kinase that responds to both mitogen- and stress-activated kinases. Indeed, CREB is phosphorylated in EPCs when treated with TNF- and high glucose. MSK1 and subsequently CREB can be activated by the p38 kinase and by ERK1/2.21 Here, we show that the p38 kinase inhibition and MSK1 inhibition, but not ERK1/2 inhibition, had an effect on the number of EPCs, suggesting that the effects mediated by TNF- and high-glucose treatment are independent of ERK1/2. This is in line with findings by Han et al,22 who demonstrated that p38 kinase plays the predominant role in the activation of MSK1 and CREB but not ERK1/2. In contrast to CREB phosphorylation, the phosphorylation of ATF2 was unchanged on p38 inhibition or activation in EPCs, suggesting that ATF2 is not a target for p38 kinase under these experimental conditions. Similar findings were reported by Fuchs et al,23 who demonstrated that the activation of ATF2 in response to cellular stress requires the stress-activated protein kinase but is independent of p38. The p38 and its downstream targets critically regulate a variety of biological responses, including apoptosis, proliferation, and differentiation.21,24 The data of the present study demonstrate that p38 does not directly affect EPC apoptosis and does not interfere with the release of VEGF. In contrast, the proliferation of EPCs was significantly augmented after treatment of EPCs with the p38 inhibitor SB230580. p38 is known to regulate proliferation of myeloid and erythroid progenitor cells.11 The increased proliferation might be well explained by p38-dependent phosphorylation and inhibition of CREB. CREB is known to bind to the promoter region of cyclin D1 and thereby inhibits proliferation.25,26 Accordingly, we demonstrated that long-term incubation with SB203580 led to a significant increase in cyclin D1 expression (data not shown). Moreover, we identified 2 other transcription factors, namely, AP-1 and AP-2, which were regulated in a manner similar to CREB. Glucose-induced p38 activation has been shown to activate AP-1 in endothelial cells and regulate inflammatory cytokines.27 However, the biological function of AP-1 in EPCs is not yet clear. Therefore, further studies are necessary to elucidate the biological importance of AP-1 and AP-2 activation in EPCs. p38 is a critical regulator of cell differentiation. In particular, p38-dependent phosphorylation of CREB was shown to mediate the differentiation of macrophages induced by granulocyte colony–stimulating factor.10 Interestingly, the p38 inhibitor modulated the ratio of endothelial and monocyte committed cells in the culture assay in favor of the endothelial lineage. Whereas the yield of EPCs out of total peripheral blood mononuclear cells was significantly augmented, monocytes, which are characterized by expression of CD14 and CD64, were significantly reduced. Therefore, one may speculate that p38 inhibition prevents progenitor cell differentiation toward the macrophage lineage and thereby facilitates endothelial cell differentiation. p38 inhibitors have previously been shown to increase VEGF-induced angiogenesis.28 Interestingly, it was demonstrated that concomitantly, the p38 inhibitor blocked hyperpermeability induced by VEGF.28 The combination of improved angiogenesis and EPC levels but, on the other hand, reduced hyperpermeability and inflammation might be an attractive profile for a potential proangiogenic therapy. Taken together, the results of the present study demonstrate a critical role of p38 and its direct downstream kinase MSK1 and CREB for the regulation of numbers of EPCs. Inhibition of p38 increases proliferation and enhances endothelial differentiation ex vivo. Therefore, p38 inhibitors might be promising tools to augment the yield of ex vivo–expanded EPCs for cell therapy. Acknowledgments This study was supported by the Deutsche Forschungsgemeinschaft (FOR501, Di600/6-1). We thank Tina Rasper, Christine Goy, and Sarah Jainski for expert technical assistance. References Kalka C, Masuda H, Takahashi T, Kalka-Moll WM, Silver M, Kearney M, Li T, Isner JM, Asahara T. Transplantation of ex vivo expanded endothelial progenitor cells for therapeutic neovascularization. Proc Natl Acad Sci U S A. 2000; 97: 3422–3427. Tateishi-Yuyama E, Matsubara H, Murohara T, Ikeda U, Shintani S, Masaki H, Amano K, Kishimoto Y, Yoshimoto K, Akashi H, Shimada K, Iwasaka T, Imaizumi T. Therapeutic angiogenesis for patients with limb ischaemia by autologous transplantation of bone-marrow cells: a pilot study and a randomised controlled trial. Lancet. 2002; 360: 427–435. Assmus B, Schachinger V, Teupe C, Britten M, Lehmann R, Dobert N, Grunwald F, Aicher A, Urbich C, Martin H, Hoelzer D, Dimmeler S, Zeiher AM. Transplantation of Progenitor Cells and Regeneration Enhancement in Acute Myocardial Infarction (TOPCARE-AMI). Circulation. 2002; 106: 3009–3017. Vasa M, Fichtlscherer S, Aicher A, Adler K, Urbich C, Martin H, Zeiher AM, Dimmeler S. Number and migratory activity of circulating endothelial progenitor cells inversely correlate with risk factors for coronary artery disease. Circ Res. 2001; 89: e1–e7. Tepper OM, Galiano RD, Capla JM, Kalka C, Gagne PJ, Jacobowitz GR, Levine JP, Gurtner GC. Human endothelial progenitor cells from type II diabetics exhibit impaired proliferation, adhesion, and incorporation into vascular structures. Circulation. 2002; 106: 2781–2786. Loomans CJ, de Koning EJ, Staal FJ, Rookmaaker MB, Verseyden C, de Boer HC, Verhaar MC, Braam B, Rabelink TJ, van Zonneveld AJ. Endothelial progenitor cell dysfunction: a novel concept in the pathogenesis of vascular complications of type 1 diabetes. Diabetes. 2004; 53: 195–199. 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Role of p38 and ERK MAP kinase in proliferation of erythroid progenitors in response to stimulation by soluble and membrane isoforms of stem cell factor. Blood. 2002; 100: 1287–1293. Vasa M, Fichtlscherer S, Adler K, Aicher A, Martin H, Zeiher AM, Dimmeler S. Increase in circulating endothelial progenitor cells by statin therapy in patients with stable coronary artery disease. Circulation. 2001; 103: 2885–2890. Dimmeler S, Aicher A, Vasa M, Mildner-Rihm C, Adler K, Tiemann M, Rutten H, Fichtlscherer S, Martin H, Zeiher AM. HMG-CoA reductase inhibitors (statins) increase endothelial progenitor cells via the PI 3-kinase/Akt pathway. J Clin Invest. 2001; 108: 391–397. Haendeler J, Hoffmann J, Diehl JF, Vasa M, Spyridopoulos I, Zeiher AM, Dimmeler S. Antioxidants inhibit nuclear export of telomerase reverse transcriptase and delay replicative senescence of endothelial cells. Circ Res. 2004; 94: 768–775. Urbich C, Dernbach E, Zeiher AM, Dimmeler S. 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☉ 11176012:Cost-Effectiveness of Eplerenone Compared With Placebo in Patients With Myocardial Infarction Complicated by Left Ventricular Dysfunction an
Emory University, Atlanta, Ga (W.S.W., Z.Z., P.K.) New England Research Institutes, Watertown, Mass (E.M.M.) Mid America Heart Institute, Kansas City, Mo (J.A.S.) Caro Research, Inc., Boston, Mass (J.C., J.I.) University of Massachusetts, Worcester (R.G.) Prudential Equity Group, Deerfield, Ill (J.T.) Pfizer, Inc, New York, NY (R.W.) University of Michigan, Ann Arbor (B.P.). Abstract Background— In the Eplerenone Post-Acute Myocardial Infarction Heart Failure Efficacy and Survival Study (EPHESUS), aldosterone blockade with eplerenone decreased mortality in patients with left ventricular systolic dysfunction and heart failure after acute myocardial infarction. The present study was performed to evaluate the cost-effectiveness of eplerenone compared with placebo in these patients. Methods and Results— A total of 6632 patients with left ventricular systolic dysfunction and heart failure after acute myocardial infarction were randomized to eplerenone or placebo and followed up for a mean of 16 months. The coprimary end points were all-cause mortality and the composite of cardiovascular mortality/cardiovascular hospitalization. The evaluation of resource use included hospitalizations, outpatient services, and medications. Eplerenone was priced at the average wholesale price, $3.60 per day. Survival beyond the trial period was estimated from data from the Framingham Heart Study, the Saskatchewan Health database, and the Worcester Heart Attack Registry. The incremental cost-effectiveness of eplerenone in cost per life-year and quality-adjusted life-year gained compared with placebo was estimated. The number of life-years gained with eplerenone was 0.1014 based on Framingham (95% CI, 0.0306 to 0.1740), 0.0636 with Saskatchewan (95% CI, 0.0229 to 0.1038), and 0.1337 with Worcester (95% CI, 0.0438 to 0.2252) data. Cost was $1391 higher over the trial period in the eplerenone arm (95% CI, 656 to 2165) because of drug cost. The incremental cost-effectiveness ratio was $13 718 per life-year gained with Framingham (96.7% under $50 000 per life-year gained), $21 876 with Saskatchewan, and $10 402 with Worcester. Conclusions— Eplerenone compared with placebo in the treatment of heart failure after acute myocardial infarction is effective in reducing mortality and is cost-effective in increasing years of life by commonly used criteria. Key Words: cost-benefit analysis ; heart failure ; myocardial infarction Introduction One of the most serious and frequent consequences of acute myocardial infarction (AMI) is heart failure, which develops in 22% of men and 46% of women after an MI.1 The presence of heart failure in patients with AMI is associated with a 55% greater risk of dying and 2.15-times-greater risk of death or recurrent AMI at 30 days.2 Patients with AMI who present to the hospital with heart failure have longer hospital stays, higher readmission rates, and higher mortality rates during hospitalization and 6 months after discharge than those without heart failure.3,4 With estimated direct and indirect health expenditures for heart failure nearing $26 billion annually,1 cost-effective treatment strategies for this disease are needed. Multiple therapeutic strategies have been used to prolong life and to decrease hospitalizations for heart failure, including diuretics, ACE inhibitors or angiotensin receptor blockers (ARBs), ;-blockers, resynchronization therapy, implantable cardiac defibrillators, and heart transplantation. Additionally, nonselective aldosterone blockade has been shown to reduce mortality in patients with chronic, severe heart failure when used with ACE inhibitors, diuretics, and sometimes digoxin.5 Recently, the Eplerenone Post-Acute Myocardial Infarction Heart Failure Efficacy and Survival Study (EPHESUS)6 demonstrated that selective aldosterone blockade with eplerenone significantly reduced mortality and morbidity in patients with left ventricular systolic dysfunction (LVSD) and heart failure after AMI who were receiving optimal medical therapies. This trial was the first to demonstrate incremental benefit of a therapeutic agent in addition to standard therapy (including an ACE inhibitor or ARB and a ;-blocker) for improving outcomes in patients with heart failure after AMI. Although its clinical efficacy is clear, the question remains as to whether the added benefit of eplerenone is worth the added cost. This study presents a cost-effectiveness analysis to define the value of the use of eplerenone compared with placebo in patients with heart failure after an AMI. Methods EPHESUS Trial Design EPHESUS, a double-blind, multicenter, randomized, placebo-controlled trial, has previously been described in detail.6 Briefly, 6632 patients were recruited from December 1999 to December 2001 at 671 centers in 37 countries. Patients were randomized to eplerenone or placebo from 3 to 14 days after AMI. Inclusion criteria included LVSD (documented ejection fraction 40%) and heart failure documented by pulmonary rales, venous congestion on chest x-ray, or the presence of a third heart sound. Patients with diabetes were required to have LVSD but were not required to have documentation of heart failure. Patients were randomized to eplerenone (25 mg/d) or placebo for 4 weeks, after which the dosage of eplerenone was increased to a maximum of 50 mg/d. Patients received standard optimal medical therapy, which could include ACE inhibitors or ARBs, diuretics, ;-blockers, statin therapy, and coronary reperfusion. The 2 primary end points were time to death resulting from any cause and time to death caused by cardiovascular causes or first hospitalization for a cardiovascular event, including heart failure, recurrent AMI, stroke, or ventricular arrhythmia. The major secondary end points included death resulting from cardiovascular causes and death resulting from any cause or any hospitalization. Economic Analysis and Costs The economic analytic plan of EPHESUS was to compare the costs of the 2 treatment arms and, if the eplerenone arm was more costly and more effective, to perform an incremental cost-effectiveness analysis.7 Although not all sources of costs could be accounted for, the overall perspective was societal. Costs included in the analysis were direct medical care costs for hospitalizations, outpatient procedures, and drugs.8,9 No data were available from EPHESUS that could be used to calculate indirect costs resulting from lost productivity. All costs used 2001 as the base year, except the cost of eplerenone, which was not marketed until 2004. Costs and life expectancy differences were discounted 3% annually. The analysis used American unit costs but used resource use information and clinical outcomes for all 6632 patients. Cardiovascular healthcare resource use associated with the index and all follow-up hospitalizations, outpatient diagnostic tests and procedures, and medications were recorded prospectively. Using a predefined algorithm designed by the investigators from case report form resource use, an investigator blinded to treatment group assigned the initial and subsequent hospitalizations for patients enrolled in EPHESUS to a diagnosis-related group (DRG) as used in the Medicare program in the United States. Costs for each DRG were estimated from average Medicare reimbursement rates obtained from the Medicare Part A data file,10 and professional costs were calculated by percent share by DRG according to the method of Mitchell et al.11 An investigator blinded to treatment group coded outpatient procedures by current procedural terminology and assigned a cost based on the Medicare fee schedule. All medications were assigned a cost based on Redbook average wholesale price (AWP).12 Specifically, the AWP for eplerenone was $3.60. All medications were assumed to continue for the duration of time that each patient was followed up. Utility was measured with the EQ-5D13,14 in a subset from English-speaking countries of 1792 patients at baseline, 1530 patients at 6 months, and 1123 patients at 12 months. Quality-adjusted life-years (QALYs) were then calculated by multiplying survival by utility. For patients with a missing utility score, the average utility for all patients with available scores by treatment arm was used to estimate utility. Utility after 12 months was carried forward by use of the 12-month value. Because utility was measured in only a minority of patients, the primary analysis of cost-effectiveness remained cost per life-year gained, with cost per QALY gained as a sensitivity analysis. Lifetime cost-effectiveness ratios in terms of cost per life-year gained and cost per QALY gained were predicted from in-trial estimates of incremental costs, event rates (death), and estimates of lost life expectancy associated with those in-trial deaths obtained from 3 sources: the Framingham Heart Study,12,15 the Saskatchewan Health database,16 and the Worcester Heart Attack Registry.17,18 These 3 sources were used to estimate survival because no single source perfectly met these criteria. For the Saskatchewan and Worcester databases, data on 2543 and 1094 patients, respectively, with heart failure after an AMI were analyzed with fractional polynomials and piecewise regression to obtain death hazard functions over time.19 These functions were adjusted according to patient characteristics through the use of separate Cox proportional-hazards models derived from the same data. For patients who died during the trial, life-years lost were obtained by subtracting the in-trial survival times from estimated age- and sex-specific life expectancy estimates.12 Patients were considered to have 0 life-years lost if they survived during the trial period. Average life-years lost for each treatment group were calculated across all patients who died and survived in each arm of the trial. The difference in average life-years lost because of deaths (placebo minus eplerenone) yields an estimate of the life-years gained with eplerenone. Life-years and QALYs were discounted at 3% annually.12 The additional healthcare costs attributed to life-years gained by treatment were estimated as a sensitivity analysis.20 Costs beyond the trial period were estimated by calculating the costs during the trial by year, carrying forward the average cost in years 2 and 3 of the trial, and discounting by 3% annually. Bootstrap methods were used to estimate the fraction of the joint distribution of the cost and effectiveness differences lying in different regions of the cost-effectiveness plane.21,22 In addition to applying these methods to the overall population, we also performed these cost-effectiveness analyses for certain demographic subgroups defined by age, sex, diabetes, and prior AMI. Results There were no differences in the baseline characteristics of age, gender, prior AMI, diabetes, hypertension, prior history of heart failure, and ejection fraction (Table 1). There was a 15% relative decrease in death from any cause with eplerenone compared with placebo. There was a 13% relative decrease in the other primary end point of death or hospitalization for cardiovascular events and significant decreases in the secondary end points of death from any cause or any hospitalization, sudden death from cardiac causes, and the number of episodes of hospitalization for heart failure. The average follow-up was 16 months. The incremental cost-effectiveness ratio (ICER) of eplerenone compared with placebo in the analysis with Framingham was $13 718 per life-year gained, with 96.7% of estimates falling below the threshold of $50 000 per life-year gained (Table 6). When the Saskatchewan estimates of life expectancy were used, the ICER was $21 876, with 93.8% of estimates under $50 000 per life-year gained. Based on Worcester estimates of life expectancy, the ICER was $10 402 per life-year gained, with 98.8% of observations falling below the threshold of $50 000 per life-year gained. The ICERs were systematically higher when calculated in cost per QALY gained. The ICERs were also systematically higher if the costs after the trial period were included. The joint bootstrap distribution of the difference in efficacy in life-years and cost is displayed in Figure 1, with the Framingham estimates for lost life expectancy used. Almost all estimates are in quadrant 1 of the cost-effectiveness plane, meaning that there was greater efficacy at increased cost with eplerenone. The diagonal line from the origin represents $50 000 per life-year gained. Estimates below this line in quadrant 1 or 2 would be cost-effective, if $50 000 represents society’s willingness-to-pay threshold. Discussion This analysis revealed that eplerenone in the setting of heart failure after an acute MI is a life-saving medication that is cost-effective compared with placebo by the common benchmark ceiling ratio of $50 000 per life-year gained. This conclusion was robust throughout a range of projections using 3 different sources for estimates of lost life expectancy resulting from in-trial deaths in a patient population in which the majority received both ;-blockers (75%) and ACE inhibitors or ARBs (87%).6 Furthermore, the bootstrap analysis revealed that with each method of costing, >90% of simulations were below the $50 000 benchmark. Previous reports from EPHESUS documented improved survival and fewer cardiovascular events in patients experiencing heart failure after an AMI who are treated with eplerenone compared with placebo.6 The results from EPHESUS complement previous results from the Randomized ALdactone (spironolactone) Evaluation Study for congestive heart failure (RALES), which showed improved survival in patients with severe chronic heart failure who were treated with spironolactone and in whom recent MI was excluded.5 EPHESUS is the first and only study to demonstrate the efficacy of aldosterone blockade for reducing mortality and morbidity in post-AMI patients with heart failure. It is important to note that eplerenone was effective in preventing events in these patients who were already treated optimally with ;-blockers and either ACE inhibitors or ARBs and that this is the only agent proven to add incremental benefit on mortality and morbidity above and beyond standard therapy in these patients;6 ;-blockers and ACE inhibitors have been shown to be clinically effective and cost-effective in the treatment of heart failure.23 The present study reveals that compared with placebo, eplerenone is cost-effective in the treatment of post-MI heart failure in a population of patients already receiving standard therapy. Study Limitations The follow-up period in EPHESUS was of variable length (range, 0 to 33 months). Thus, cost-effectiveness was calculated for the average follow-up period of 16 months, with therapy with eplerenone for that period of time but not thereafter. This study does not and realistically cannot address the issue of how long eplerenone should be taken. The estimation of life expectancy assumes that the survival curves remain parallel after the trial period. The in-trial results cannot give a full picture of the survival advantage of eplerenone. Thus, the estimation of survival was extended beyond the study period by using data from 3 separate sources. However, the degree to which the survival experience of patients from these observational studies yields accurate estimates of life expectancy for the EPHESUS population is uncertain. In both the Saskatchewan and Worcester databases, mortality within 1 year of MI was higher than in EPHESUS. This would mean a shorter projected life expectancy, rendering our results conservative. In addition, there was considerable variation between the estimates from these 3 sources, given variations in the populations. The Framingham Heart Study was used because it is a large, well-known, epidemiological database.15 The Worcester and Saskatchewan databases also were chosen because they included patients similar to those in EPHESUS (ie, post-AMI heart failure patients), and both databases included long-term data.16–18 Although the Worcester database had the greatest similarity to EPHESUS and the closest estimate of mortality hazard, the ICERs from these 3 databases were all in an acceptable range and provide a sensitivity analysis supporting the cost-effectiveness of eplerenone. The costing methodology was based on Medicare payments for hospitalization, the Medicare fee schedule for procedures, and AWPs for medications. Eplerenone was priced at the AWP of $3.60 a day. The extent to which these costs reflect resource use from a societal point of view is somewhat uncertain because there is no single source for costs that unequivocally represents societal costs. Thus, Medicare payments may appropriately reflect costs for the Centers for Medicare and Medicaid Services but may not adequately represent resource consumption by hospitals and physicians because Medicare costs tend to be lower than managed care costs. Therefore, the present analysis may provide a conservative representation of the cost-effectiveness of eplerenone. Costing beyond the trial period was based on projections of costs within the trial period. This approach, while reasonable, is not easily subject to empirical assessment. Indirect costs were not included, especially those reflecting return to work. To the extent that eplerenone permits return to work by preventing hospitalizations or deaths, this would lower costs in the eplerenone arm, again rendering the results conservative. Resource use and clinical outcomes were considered trial wide. Use of Medicare costing does not account for possible within-DRG differences in treatment practices and resource use across countries. With so many countries, it is not possible to adequately account for variation in DRGs across countries. Thus, the use of trial-wide data for costing in the United States may not perfectly reflect US resource utilization. In this respect, however, because the primary cause of the cost differential is the eplerenone cost, cost calculations using the unit resource use of other countries should have little effect on the results. The ability to generalize the EPHESUS data to the wider population of patients with post-AMI heart failure is also uncertain. Finally, EPHESUS cannot be used to compare the clinical outcomes or cost-effectiveness of eplerenone to spironolactone. In EPHESUS, eplerenone was compared with placebo; there is no direct comparison of eplerenone to spironolactone, making a comparison of the 2 aldosterone blockers speculative. The ICER in the subgroup of diabetic patients was higher than in other subgroups analyzed but still under the standard benchmark of $50 000. Diabetics were the only patients in EPHESUS who did not necessarily have to manifest evidence of heart failure to be enrolled in the trial. Approximately one third of EPHESUS subjects were diabetic, and about one third of this diabetic subgroup did not have evidence of heart failure. It is difficult to draw firm conclusions about the higher, but still acceptable, ICER in the relatively small diabetic subgroup compared with the overall trial population. Eplerenone compares well to other therapies in terms of cost-effectiveness. The ICER for eplerenone is slightly higher than the ICER for clopidogrel in acute coronary syndromes24,25 but is similar to that of medications such as ACE inhibitors and ;-blockers. The ICER for captopril therapy versus no captopril in post-AMI patients 50 to 80 years of age is $3700 to $10 400, depending on age,26 whereas ;-blocker treatment after AMI has an ICER ranging from $360 to $17 000, depending on patient status.27 Note that in all studies of ;-blockers and ACE inhibitors after AMI, the patients were not on an aldosterone blocker, and concomitant standard therapies were different. Higher ICERs have also been noted with life-saving interventions; an ICER of $40 000 was noted in a comparison of an implantable cardiac defibrillator with amiodarone in survivors of cardiac arrest.28 With ICERs from $10 402 to $21 876 in cost per life-year gained, eplerenone compares well to other therapies in terms of cost-effectiveness and is below the $50 000 threshold used to determine whether society will consider the medication a good value. Conclusions The cost-effectiveness of eplerenone compares favorably to that of many other well-known and well-accepted therapies. Eplerenone is the only pharmacological agent proven to add incremental benefit on mortality and morbidity above and beyond standard therapy, including ACE inhibition and ;-blockers, in patients with heart failure after AMI. Despite some limitations, EPHESUS provides strong support for both the efficacy and cost-effectiveness of eplerenone compared with placebo in patients with post-MI heart failure. Eplerenone therapy should be considered a cost-effective component of the current armamentarium to improve survival in patients with heart failure after AMI. Acknowledgments This analysis was financially supported by Pfizer Inc, New York, NY. References American Heart Association. Heart Disease and Stroke Statistics—2004 Update. Dallas, Tex: American Heart Association; 2003. Hasdai D, Topol EJ, Kilaru R, Battler A, Harrington RA, Vahanian A, Ohman EM, Granger CB, Van de Werf F, Simoons ML, O’Connor CM, Holmes DR Jr. Frequency, patient characteristics, and outcomes of mild-to-moderate heart failure complicating ST-segment elevation acute myocardial infarction: Lessons from 4 international fibrinolytic therapy trials. Am Heart J. 2003; 145: 73–79. Steg PG, Dabbous OH, Feldman LJ, Steg PG, Dabbous OH, Feldman LJ, Cohen-Solal A, Aumont MC, Lopez-Sendon J, Budaj A, Goldberg RJ, Klein W, Anderson FA Jr, for the Global Registry of Acute Coronary Events Investigators. Determinants and prognostic impact of heart failure complicating acute coronary syndromes. Circulation. 2004; 109: 494–499. Wu AH, Parsons L, Every NR, Bates ER, for the Second National Registry of Myocardial Infarction. Hospital outcomes in patients presenting with congestive heart failure complicating acute myocardial infarction: a report from the Second National Registry of Myocardial Infarction (NRMI-2). J Am Coll Cardiol. 2002; 40: 1389–1384. Pitt B, Zannad F, Remme WJ, Cody R, Castaigne A, Perez A, Palensky J, Wittes J. The effect of spironolactone on morbidity and mortality in patients with severe heart failure: Randomized Aldactone Evaluation Study Investigators. N Engl J Med. 1999; 341: 709–717. Pitt B, Remme W, Zannad F, Neaton J, Martinez F, Roniker B, Bittman R, Hurley S, Kleiman J, Gatlin M, for the Eplerenone Post-Acute Myocardial Infarction Heart Failure Efficacy and Survival Study Investigators. Eplerenone, a selective aldosterone blocker, in patients with left ventricular dysfunction after myocardial infarction. N Engl J Med. 2003; 348: 1309–1321. Spertus JA, Tooley J, Jones P, Poston C, Mahoney E, Deedwania P, Hurley S, Pitt B, Weintraub WS. Expanding the outcomes in clinical trials of heart failure: the quality of life and economic components of EPHESUS (Eplerenone’s Neurohormonal Efficacy and Survival Study). Am Heart J. 2002; 143: 636–642. Gold MR, Siegel JE, Russel LB, Weinstein MC. Cost-Effectiveness in Health and Medicine. New York, NY: Oxford University Press; 1996. Drummond MF, O’Brien B, Stoddart GL, Torrance G. Methods for the Economic Evaluation of Health Care Programmes. Oxford, UK: Oxford Medical Publications; 1987. Centers for Medicare and Medicaid Services. 100% MEDPAR Inpatient Hospital National Data for Fiscal Year 2001. Short Stay Inpatient by Diagnosis Related Groups. Available at: www.cms.gov/statistics/medpar/shtstay01drg.pdf. Accessed 2004. Mitchell J, Burge RT, Lee AJ, McCall NT. Per Case Prospective Payment for Episodes of Hospital Care. Springfield, Va: US Department of Commerce National Technical Information Service; 1995. Mahoney EM, Jurkovitz CT, Chu H, Becker ER, Culler S, Kosinski AS, Robertson DH, Alexander C, Nag S, Cook JR, Demopoulos LA, DiBattiste PM, Cannon CP, Weintraub WS, for the TACTICS-TIMI 18 Investigators. Treat Angina with Aggrastat and Determine Cost of Therapy With an Invasive or Conservative Strategy-Thrombolysis in Myocardial Infarction: cost and cost-effectiveness of an early invasive vs conservative strategy for the treatment of unstable angina and non-ST-segment elevation myocardial infarction. JAMA. 2002; 288: 1851–1858. Rabin R, De Charro F. EQ-5D: a measure of health status from the EuroQoL group. Ann Med. 2001; 33: 337–343. Weintraub WS, Mahoney EM, Zhang Z, Chu H, Hutton J, Buxton M, Booth J, Nugara F, Stables RH, Dooley P, Collinson J, Stuteville M, Delahunty N, Wright A, Flather MD. De Cock E. One year comparison of costs of coronary surgery versus percutaneous coronary intervention in the stent or surgery trial. Heart (Br Card Soc). 2004; 90: 782–788. 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The decomposition of time-varying hazard into phases, each incorporating a separate stream of concomitant information. J Am Stat Assn. 1986; 81: 615–624. Meltzer D. Accounting for future costs in medical cost-effectiveness analysis. J Health Econ. 1997; 16: 33–64. Efron B, Tibshirani R. An Introduction to the Bootstrap. New York, NY: Chapman and Hall; 1993. Mahoney EM, Chu H. Cost-Effectiveness analysis alongside clinical trials: statistical and methodologic issues. In: Weintraub WS, ed. Cardiovascular Health Care Economics. Totowa, NJ: Humana Press, Inc.; 2003: 123–156. Weintraub WS, Cole J, Tooley JF. Cost and cost-effectiveness studies in heart failure research. Am Heart J. 2002; 143: 565–576. Latour-Perez J, Navarro-Ruiz A, Ridao-Lopez M, Cervera-Montes M. Using clopidogrel in non-ST-segment elevation acute coronary syndrome patients: a cost-utility analysis in Spain. Value Health. 2004; 7: 52–60. Lindgren P, Jonsson B, Yusuf S. 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☉ 11176029:State of Disparities in Cardiovascular Health in t
the Office of the Director (G.A.M.) and Behavioral Surveillance Branch (A.H.M., E.S.F.) and Cardiovascular Health Branch (K.J.G., J.B.C.) Division of Adult and Community Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control, Atlanta, Ga. Abstract Background— Reducing health disparities remains a major public health challenge in the United States. Having timely access to current data on disparities is important for policy and program development. Accordingly, we assessed the current magnitude of disparities in cardiovascular disease (CVD) and its risk factors in the United States. Methods and Results— Using national surveys, we determined CVD and risk factor prevalence and indexes of morbidity, mortality, and overall quality of life in adults 18 years of age by race/ethnicity, sex, education level, socioeconomic status, and geographic location. Disparities were common in all risk factors examined. In men, the highest prevalence of obesity (29.2%) was found in Mexican Americans who had completed a high school education. Black women with or without a high school education had a high prevalence of obesity (47.3%). Hypertension prevalence was high among blacks (39.8%) regardless of sex or educational status. Hypercholesterolemia was high among white and Mexican American men and white women in both groups of educational status. Ischemic heart disease and stroke were inversely related to education, income, and poverty status. Hospitalization was greater in men for total heart disease and acute myocardial infarction but greater in women for congestive heart failure and stroke. Among Medicare enrollees, congestive heart failure hospitalization was higher in blacks, Hispanics, and American Indians/Alaska Natives than among whites, and stroke hospitalization was highest in blacks. Hospitalizations for congestive heart failure and stroke were highest in the southeastern United States. Life expectancy remains higher in women than men and higher in whites than blacks by 5 years. CVD mortality at all ages tended to be highest in blacks. Conclusions— Disparities in CVD and related risk factors remain pervasive. The data presented here can be invaluable for policy development and in the planning, implementation, and evaluation of interventions designed to eliminate health disparities. Key Words: ethnic groups ; life expectancy ; mortality ; quality of life ; continental population groups Introduction In its broadest sense, the term "health disparities" refers to preventable differences in the indicators of health of different population groups, often defined by race, ethnicity, sex, educational level, socioeconomic status, and geographic location of residence. The first National Institutes of Health Working Group on Health Disparities defined disparities as including "differences in the incidence, prevalence, mortality, and burden of diseases and other adverse health conditions."1 These disparities have been documented in the United States throughout most of the past 2 centuries.2–4 More recently, the National Healthcare Disparities Report5 and an Institute of Medicine report6 confirmed that disparities are pervasive and that improvements are possible. Elimination of these disparities is one of the 2 overarching goals of the Healthy People 2010 national public health agenda.7 Up-to-date surveillance data at the national, state, and local levels are important for the design, implementation, and evaluation of programs designed to reduce these disparities. Accordingly, we present in this report the most recently available population-based data on disparities in cardiovascular disease (CVD) and related risk factors. Indicators examined include prevalences of major and emerging CVD risk factors, morbidity and mortality for major CVD, overall life expectancy and quality of life, and the prevalence of social and environmental determinants of health. Specific strategies for eliminating CVD-related health disparities are not addressed in this report. Methods Self-Reported Behavioral Risk Factors The Behavioral Risk Factor Surveillance System (BRFSS) is a cross-sectional telephone survey conducted by state health departments with assistance from the Centers for Disease Control and Prevention (CDC). BRFSS questionnaires consist primarily of questions about personal behaviors that increase one’s risks for illness and death. The BRFSS uses a multistage cluster design based on random-digit dialing to select a representative sample from each state’s noninstitutionalized civilian residents 18 years of age. Data from each state are pooled to produce nationally representative estimates. A detailed description of the survey methods is available elsewhere.8 Because all BRFSS questionnaires, reports, and data also are available elsewhere,9 they are not discussed here. We used self-reported weight and height to calculate body mass index (BMI) as weight (kg) divided by height (m2). A participant was classified as obese if his or her BMI was 30 kg/m2. Diagnosed diabetes was assessed by asking, "Have you ever been told by a doctor that you have diabetes;" The type of diabetes was not assessed. Results from the 2003 BRFSS module on fruit and vegetable consumption were used to classify participants into 4 groups based on their daily fruit and vegetable consumption: (1) 102 cm in men, >88 cm in women), hypertension (see definition below), elevated concentrations of total cholesterol (200 mg/dL), LDL cholesterol (130 mg/dL), triglycerides (150 mg/dL), C-reactive protein (>3 mg/L), fibrinogen (>3 g/L), glycosylated hemoglobin (>7%), homocysteine (>10 μmol/L), and low concentrations of HDL cholesterol (<40 mg/dL in men, <50 mg/dL in women). Albuminuria was defined as a urinary albumin-to-creatinine ratio of 30 mg/g (microalbuminuria 30 to <300 mg/g; macroalbuminuria 300 mg/g). Obesity was calculated from measured height and weight. Waist circumference was measured at the high point of the iliac crest at minimal respiration to the nearest 0.1 cm at the end of normal expiration. Hypertension was defined as the presence of a systolic blood pressure 140 mm Hg or a diastolic blood pressure 90 mm Hg; the self-reported, current use of antihypertensive medication; or having been told on 2 different visits by a doctor or other health professional that the participant had hypertension. We used the average of the last 2 blood pressure measurements for participants who had 3 or 4 measurements, the second one for participants with only 2 measurements, and the only one for participants who had 1 measurement to establish hypertension status. For most risk factors for CVD, we used all available participants regardless of fasting status. Concentrations of fibrinogen were measured only in participants 40 years of age. For concentrations of HDL cholesterol, LDL cholesterol, and triglycerides, only data for 1999 to 2000 were available. For concentrations of triglycerides and LDL cholesterol, we limited the analyses to participants who attended the morning examination and who had fasted 10 hours. We calculated the percentage of participants who had a risk factor stratified by race or ethnicity (white, black, and Mexican American), sex, and educational status (less than a high school education versus high school graduate, recipient of a general equivalency diploma, or higher education). To account for the complex sampling design of the survey, we calculated prevalences of risk factors using SUDAAN software (Research Triangle Institute, release 8.0.2, January 2003). Morbidity Morbidity data on self-reported heart disease, stroke, and congestive heart failure (CHF) are from the National Health Interview Survey (NHIS).12 The NHIS, initiated in 1957, is a continuing nationwide sample survey of the civilian noninstitutionalized population. Data are collected through household interviews. Medicare (part A) hospital claims from the Medicare Provider Analysis and Review files and beneficiary enrollment records for 2000 were obtained from the Centers for Medicare and Medicaid Services. Hospitalizations among Medicare enrollees 65 years of age include those for the principal (first-listed) diagnosis on hospital claims between January 1 and December 31, 2000. The denominators were US residents living in the 50 states, District of Columbia, and US territories who were 65 years of age and entitled to Medicare part A benefits on July 1, 2000 (excluding members of health maintenance organizations). Acute myocardial infarction was defined as a diagnosis with International Classification of Diseases, ninth revision, clinical modification (ICD-9-CM) code 410. Heart failure was defined as ICD-9-CM code 428, and stroke was defined as ICD-9-CM codes 430 to 434 or 436 to 438. Age-adjusted prevalences of hospitalizations were directly age standardized to the 2000 US standard population 65 years of age.13,14 Mortality Mortality data for 2001 are presented as summarized in several CDC publications.15 In cooperation with state vital statistics offices, mortality data are compiled by the CDC National Center for Health Statistics and processed in accordance with regulations from the World Health Organization. Demographic data on death certificates were reported by funeral directors or provided by family members of the decedent. Heart disease–related deaths are those for which the underlying cause listed on the death certificate by a physician or a coroner is classified according to the ICD-10 codes I00 through I09, I11, I13, and I20 through I51. Stroke deaths were those classified as ICD-10 codes I60 through I69. For the years 1980 to 1995, heart disease deaths were categorized as ICD-9 codes 390 to 398, 402, and 404 to 429; stroke deaths, as codes 430 to 438. Death rates for the total population and by sex and race/ethnicity were age adjusted to the 2000 US standard population.13,14,16 Years of potential life lost, a measure of premature mortality, is presented for persons <75 years of age because the average life expectancy in the United States is 75 years.16 Results Self-Reported Risk Factors Self-reported measures of obesity are not presented in Table 1 because of the availability of BMI calculated from measured heights and weights from NHANES (shown in Table 2). However, BMI calculated from self-reported height and weight in BRFSS is used to demonstrate state-based geographic disparities in obesity and overweight (Figure 1) because state-based data are not available from NHANES. Comparisons of 1990 with 1996 show the gradual and continued increase in the prevalence of obesity throughout the United States (Figure 1). People with higher education were more likely to have health insurance. Among the racial groups, Hispanics were least likely to have health insurance. Hispanics were also least likely to receive a flu or pneumonia vaccination. Those with less than a high school education were most likely to report limitation of activities and the highest number of days with physical and mental health problems. Hispanics had the highest prevalence of poor or fair health (data not presented). Measured Risk Factors Generally, the prevalence of hypertension was high among blacks regardless of sex or educational status. The prevalence of hypercholesterolemia was generally high among white and Mexican American men and white women in both education groups. The prevalence of low concentrations of HDL cholesterol and hypertriglyceridemia was most favorable among black participants, although among the most educated women, whites and blacks had a similar prevalence of low concentration of HDL cholesterol. The prevalence of measured levels of glycosylated hemoglobin 7% was highest in black men (except among the most educated men and women; Table 2). Morbidity In 2002, 11.2% of people reported having heart disease and 2.4% reported ever having had a stroke.12,16 In the NHIS, reported heart disease, ischemic heart disease, hypertension, and stroke were inversely related to poverty status, education, and income (Table 4).12 Discharges from short-stay hospitals in 2002 were greater in men than women for total heart disease and for acute myocardial infarction but greater for women for CHF and stroke (data not shown).12 Among Medicare enrollees 65 years of age, the prevalence rates of hospitalizations with acute myocardial infarction, CHF, and stroke were higher in men than women12,16 (data not presented). Whites had the highest prevalence rate of hospitalization for acute myocardial infarction, but the prevalence rate of hospitalization for CHF was higher in blacks, Hispanics, and American Indians/Alaska Natives than among whites. Blacks had the highest prevalence rate of hospitalization for stroke in the Medicare population. Among Medicare enrollees 65 years of age, the prevalence rate of hospitalizations for acute myocardial infarction varied between states, with some clustering along the Appalachians. The highest prevalence rates of hospitalizations for acute myocardial infarction, heart failure, and stroke were clustered primarily in the southeastern United States (Figure 2). Life Expectancy and Mortality In 2001, overall US life expectancy at birth was 77.2 years. Life expectancy was higher in women than men by 5.4 years and higher in whites than blacks by 5.5 years.15 Age-adjusted death rates for both diseases of the heart and stroke in 2001 were higher among men than women and higher among blacks than whites (Figure 3). Men and blacks also had more premature mortality compared with women and whites, as measured by years of potential life lost before 75 years of age, because of these conditions (Figure 4). Age-specific death rates for diseases of the heart (Figure 5) suggest that black adults had higher death rates at all ages compared with whites. Asians/Pacific Islanders tended to have lower heart disease death rates in all age groups (Figure 5A) but higher stroke death rates, particularly at young ages (Figure 5B). Age-adjusted heart disease death rates since 1980 did not decline as rapidly for blacks, particularly men, compared with whites (Figure 6). Stroke death rates for American Indians/Alaska Natives, Asians and Pacific Islanders, and Hispanics have not declined as rapidly as for whites and blacks (Figure 6). Coding of race/ethnicity on death certificates is known to be imprecise, particularly for American Indians/Alaska natives and Asians/Pacific Islanders.17 In general, age-adjusted mortality for stroke and heart disease tended to be higher in the southeastern United States than the rest of the country (Figure 7). Discussion These surveillance data suggest that marked disparities exist in the prevalence, morbidity, and mortality associated with CVD and their major risk factors. The disparities are found in both self-reported and measured risk factors. Both biological risk factors and social and environmental determinants of CVD demonstrate important disparities in the population subgroups examined. These disparities appear to play a key role in the observed differences in the overall life expectancy and quality of life of population subgroups. In general, population subgroups most significantly and adversely affected include blacks, Hispanics/Mexican Americans, persons with low socioeconomic status, and residents of the southeastern United States and the Appalachians. Similarly, persons with less than a high school education tend to have a higher burden of CVD and related risk factors regardless of race/ethnicity. The limited data available from the national and state-based surveillance system presented here on American Indian/Alaska Natives obscure the burden of CVD and risk factors in this population group. However, data from the Racial and Ethnic Approaches to Community Health (REACH) 2010 Risk Factor Survey18 demonstrate a high prevalence of self-reported CVD, hypertension, high blood cholesterol, and diabetes. For example, in that survey, the median prevalence of obesity was 39.2% and 37.5% of American Indian men and women, respectively, compared with only 2.9% and 3.6% of Asian/Pacific Islander men and women, respectively.18 Similarly, cigarette smoking was common in American Indian communities, with a median of 42.2% for men and 36.7% for women.18 Data on the disparities in the prevalence, awareness, treatment, and control of high blood pressure are not presented here because of the recent CDC publication of the 1999 to 2002 analysis of the NHANES data.19 In that report, the age-adjusted prevalence of hypertension was highest in non-Hispanic blacks (40.5%) compared with 27.4% and 25.1% in non-Hispanic whites and Mexican Americans, respectively.19 The age adjusted proportion of persons who reported current treatment was also highest in non-Hispanic blacks (55.4%) compared with 48.6% and 34.9% in non-Hispanic whites and Mexican Americans, respectively. The proportion with controlled blood pressure was similar among non-Hispanic blacks (29.8%) and non-Hispanic whites (29.8%) but substantially lower among Mexican Americans (17.3%).19 Blood pressure control increased with increasing age and was substantially higher in women (35.5%) than in men (27.5%).19 No data are presented here on access to care, disease management, or indicators of the delivery of quality cardiac care. However, several recent publications,20–26 an Institute of Medicine summary of the literature,6 and one review that focused specifically on cardiac care, conducted jointly by the American College of Cardiology Foundation and Kaiser Family Foundation,27 concluded—after examining the most rigorous studies investigating racial/ethnic differences in angiography, angioplasty, CABG surgery, and thrombolytic therapy—that disparities in the quality of medical care are pervasive and that they persist even after adjustment for potentially confounding factors. The primary purpose of this report was to assess current epidemiology of the disparities in CVD and its risk factors in the United States, not to determine the reason for the differences. The causes of these disparities are complex and are not identified or discussed in this report. The lack of complete information on all population subgroups is also an important limitation. Although the most recent national and state-level population-based surveillance data are reported, sample size limitations preclude reporting of several important disparities data. Several emerging risk factors are also not reported for all age groups and some nonwhite racial/ethnic groups. Finally, trend data are not presented for most of the indicators examined here or for the disparities found. However, several recent publications show that despite multiple national calls to action for aggressive prevention and control of cardiovascular risk factors, little progress has been made in reducing physical inactivity, poor nutrition, and hypertension prevalence, and adverse trends in epidemic obesity and diagnosed diabetes continue. Most importantly, although some significant improvements such as reductions in gender disparities in CVD mortality have been noted,28 disparities in CVD mortality based on race/ethnicity have remained largely unchanged,25 and disparities in the morbidity of major CVD appear to be increasing.29 In conclusion, disparities in cardiovascular health remain pervasive. The data presented here can be invaluable for policy development and in the planning, implementation, and evaluation of programs and interventions designed to eliminate health disparities. Continued collection of epidemiological data stratified by race/ethnicity, sex, education level, socioeconomic status, and geographic location of residence is necessary. References National Institutes of Health. Addressing health disparities: the NIH program of action. Available at: http://healthdisparities.nih.gov/whatare.html. Accessed on March 31, 2004. Ewbank DC. History of black mortality and health before 1940. Milbank Q. 1987; 65 (suppl 1): 100–128. Krieger N. Shades of difference: theoretical underpinnings of the medical controversy on black/white differences in the United States, 1830–1870. Int J Health Serv. 1987; 17: 259–278. Kochanek KD, Maurer JD, Rosenberg HM. Why did black life expectancy decline from 1984 through 1989 in the United States; Am J Public Health. 1994; 84: 938–944. US Department of Health and Human Services. National healthcare disparities report. Available at: http://www.qualitytools.ahrq.gov/disparitiesreport/documents/Report%207.pdf. Accessed on July 1, 2003. Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 2003. US Department of Health and Human Services. Healthy People 2010. 2nd ed. Washington, DC: US Government Printing Office; 2000. Mokdad AH, Stroup DF, Giles WH. Public health surveillance for behavioral risk factors in a changing environment: recommendations from the Behavioral Risk Factor Surveillance Team. MMWR Recomm Rep. 2003; 52: 1–12. Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System: turning information into action. Available at: http://www.cdc.gov/brfss/. Accessed on October 11, 2004. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey (NHANES 1999–2004). Available at: http://www.cdc.gov/nchs/about/major/nhanes/nhanes99–02.htm. Accessed on October 5, 2004. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey: Laboratory Procedures Manual. Available at: http://www.cdc.gov/nchs/data/nhanes/LAB7–11.pdf. Accessed on October 5, 2004. Lethbridge-;ejku M, Schiller JS, Bernadel L. Summary health statistics for U.S. adults: National Health Interview Survey, 2002. Hyattsville, MD: National Center for Health Statistics. Vital Health Stat 10. 2004; 2: 1–160. Klein RJ, Schoenborn CA. Age adjustment using the 2000 projected US population. Healthy People 2010 Statistical Notes. No. 20. Hyattsville, Md: National Center for Health Statistics; 2001. Anderson RN, Rosenberg HM. Age-Standardization of Death Rates: Implementation of the Year 2000 Standard. Hyattsville, Md: National Center for Health Statistics; 1998. Anderson RN, Smith BL. Deaths: leading causes for 2001. Natl Vital Stat Rep. 2003; 52: 1–85. National Center for Health Statistics. Health, United States, 2003. In: Chartbook on Trends in the Health of Americans. Hyattsville, Md: National Center for Health Statistics; 2003. Rosenberg HM, Maurer JD, Sorlie PD, Johnson NJ, MacDorman MF, Hoyert DL, Spitler JF, Scott C. Quality of death rates by race and Hispanic origin: a summary of current research, 1999. Vital Health Stat 2. 1999; Sept: 1–13. Liao Y, Tucker P, Okoro CA, Giles WH, Mokdad AH, Harris VB. REACH 2010 Surveillance for Health Status in Minority Communities: United States, 2001–2002. MMWR Surveill Summ. 2004; 53: 1–36. Centers for Disease Control and Prevention. Racial/ethnic disparities in prevalence, treatment, and control of hypertension: United States, 1999–2002. MMWR Morb Mortal Wkly Rep. 2005; 54: 7–9. Gordon HS, Paterniti DA, Wray NP. Race and patient refusal of invasive cardiac procedures. J Gen Intern Med. 2004; 19: 962–966. Martin R, Lemos C, Rothrock N, Bellman SB, Russell D, Tripp-Reimer T, Lounsbury P, Gordon E. Gender disparities in common sense models of illness among myocardial infarction victims. Health Psychol. 2004; 23: 345–353. Rothenberg BM, Pearson T, Zwanziger J, Mukamel D. Explaining disparities in access to high-quality cardiac surgeons. Ann Thorac Surg. 2004; 78: 18–24. Walker DR, Stern PM, Landis DL. Examining healthcare disparities in a disease management population. Am J Manag Care. 2004; 10: 81–88. Grace SL, Abbey SE, Bisaillon S, Shnek ZM, Irvine J, Stewart DE. Presentation, delay, and contraindication to thrombolytic treatment in females and males with myocardial infarction. Womens Health Issues. 2003; 13: 214–221. O’Connell L, Brown SL. Do nonprofit HMOs eliminate racial disparities in cardiac care; J Health Care Finance. 2003; 30: 84–94. Litaker D, Koroukian SM. Racial differences in lipid-lowering agent use in Medicaid patients with cardiovascular disease. Med Care. 2004; 42: 1009–1018. Lillie-Blanton M, Maddox TM, Rushing O, Mensah GA. Disparities in cardiac care: rising to the challenge of Healthy People 2010. J Am Coll Cardiol. 2004; 44: 503–508. Pearcy JN, Keppel KG. A summary measure of health disparity. Public Health Rep. 2002; 117: 273–280. Davis SK, Liu Y, Gibbons GH. Disparities in trends of hospitalization for potentially preventable chronic conditions among African Americans during the 1990s: implications and benchmarks. Am J Public Health. 2003; 93: 447–455....查看详细 (26102字节)
☉ 11176034:Racial Misclassification and Disparities in Cardio
the Division of American Indian and Alaska Native Programs, University of Colorado Health Sciences Center, Denver. Abstract Background— National vital event data suggest that cardiovascular disease (CVD) mortality rates are lower for American Indians and Alaska Natives (AIAN) than for the general US population, but these data are disproportionately flawed for AIAN because of racial misclassification. Methods and Results— Vital event data adjusted for racial misclassification and published by the Indian Health Service were used to compare trends in CVD mortality from 1989 to 1991 to 1996 to 1998 between AIAN, US all-races, and US white populations. Without misclassification accounted for, AIAN initially had the lowest mortality rates from major CVD, but by the end of the study, their rates were the highest. Adjustment for misclassification revealed an early and rapidly growing disparity between CVD mortality rates among AIAN compared with rates in the US all-races and white populations. By 1996 to 1998, the age- and misclassification-adjusted number of CVD deaths per 100 000 among AIAN was 195.9 compared with age-adjusted rates of 166.1 and 159.1 for US all races and whites, respectively. The annual percent change in CVD mortality for AIAN was 0.5 compared with –1.8 in the other groups. Regardless of racial misclassification, the most striking and widening disparities were found for middle-aged AIAN, but CVD mortality among AIAN 65 years of age was lower than in the other populations. Conclusions— A previously underrecognized disparity in CVD mortality exists for AIAN, particularly among middle-aged adults. Moreover, these disparities are increasing. Efforts to reduce CVD mortality in AIAN must begin before the onset of middle age. Key Words: cardiovascular disease ; epidemiology ; Indians, North American ; Inuits Introduction Several racial disparities in cardiovascular disease (CVD) mortality and health care have been documented in the United States.1,2 The Institute of Medicine reports that racial and ethnic disparities in health care are widespread, are associated with worse health outcomes, and occur independently of socioeconomic status.1 Nevertheless, national vital event data suggest that CVD mortality for American Indians and Alaska Natives (AIAN) is lower than in the general US population and has been for decades.2,3 Similar findings have been reported in other AIAN population-based studies using vital event data.4,5 These findings are somewhat puzzling because American Indians have for years had some of the nation’s highest prevalence rates of major CVD risk factors6 such as smoking,7,8 diabetes,9,10 and obesity.11,12 CVD is also the leading cause of death among AIAN and has been for decades. Furthermore, AIAN are among the most disadvantaged populations in the United States. Despite improvements in life expectancy and total mortality over the past century, disparities in these health status indicators remain for this population compared with the general population. Also, AIAN death rates for several major diseases, including cerebrovascular disease, increased during the 1990s, unlike rates in other racial and ethnic groups.3 Data from the nation’s only longitudinal epidemiological study of CVD and its risk factors among a diverse group of American Indians, the Strong Heart Study (SHS),13 suggest that CVD incidence and mortality rates are as bad as or worse than those in comparable general populations.14,15 The seemingly disparate findings between national data and the SHS may be explained by errors in national data resulting from racial misclassification and population estimates. These errors disproportionately affect AIAN16 and likely contribute to falsely low estimates of CVD. The Indian Health Service (IHS), the nation’s leading source of health care for AIAN, has compiled data since the 1950s on mortality rates for 60% of the US AIAN population. These rates are derived from the vital event and census data and are reported in the IHS Trends in Indian Health (Trends) series of publications. The IHS began to adjust for racial misclassification beginning with data from the early 1990s. The present article uses data from the IHS to report trends in CVD mortality and to assess the impact of racial misclassification on an underrecognized CVD disparity among AIAN. Methods Data were obtained from the IHS as published in the Trends series for the periods of 1989 to 1991,17 1991 to 1993,18 1992 to 1994,19 1994 to 1996,20 and 1996 to 1998.21 Population Estimates IHS obtains population estimates from the US Bureau of the Census and defines its service population as those persons who identified themselves as American Indian, Eskimo, or Aleut on the 1990 census and who resided in geographic areas "on or near" reservations or trust lands. Estimates of the IHS service population are census based, not "user" or clinic based. This population is also characterized by marked geographic and cultural diversity. The IHS service population from the 1990 census consisted of 1.21 million AIAN, 60% of the total AIAN population. CVD mortality rates for the IHS service population from 1989 to 1991 on have been corrected by the IHS for revisions in the census counts made by the US Bureau of the Census. Rates before 1989 to 1991 were not adjusted for changes in census estimates and therefore are not included in the present study. Population estimates for subsequent periods used consistent assumptions and projections obtained with linear regression techniques.21 By 1998, the IHS service population was estimated at 1.46 million.21 Vital Event Data Vital event statistics as reported in Trends were derived by the IHS from the National Center for Health Statistics (NCHS) publications and from unpublished data supplied by the NCHS.20 The NCHS compiles vital event data for all US residents on the basis of information reported on official birth and death certificates from state departments of health. Causes of death were identified by the NCHS from death certificates and coded with the International Classification of Diseases, ninth revision, definitions. The codes for categories of CVD were consistent throughout the study period and included the following: 390 to 448 for major CVD; 390 to 398, 402, and 404 to 429 for diseases of the heart; and 430 to 438 for cerebrovascular diseases. The IHS uses 3-year averages to minimize the random fluctuations that may result from uncommon events. Rates for the US all-races and US white populations represent single years corresponding to the "center" year for the IHS period. For example, the US all-races and white rates corresponding to the AIAN rates for 1989 to 1991 were obtained from 1990 data. Age group data for those 45 to 54 and 55 to 64 years of age are reported in Trends from 1991 to 1993 on. Age-adjusted total CVD, heart disease, and cerebrovascular disease mortality rates were not available by sex in the Trends publications. Although data were stratified by sex within age groups, they were available for 1 million AIAN residing on or near reservations and trust lands. Findings suggest that total CVD mortality for AIAN is higher, not lower, than in the rest of the nation and may have been higher for more than a decade. Furthermore, CVD mortality is increasing in this population but decreasing in the general population, widening a previously unrecognized disparity. National vital event data had consistently suggested that CVD mortality rates among AIAN compared favorably to the general population, even to the present2,4,5,23–25; however, prior studies did not account for the effect of racial misclassification. This study also reveals differences in CVD mortality among adults by age groups. The marked disparity in CVD mortality between middle-aged AIAN and the US all-races and white populations is striking and is increasing. Other studies have also recently demonstrated a higher burden of premature heart disease mortality for AIAN.26,27 In contrast, lower rates of heart disease and cerebrovascular disease mortality occurred among AIAN compared with US all-races and white populations 65 years of age, even after adjustment for racial misclassification. This finding is also consistent with some other studies27,28 but not all.14,15 In addition, heart disease mortality rates for AIAN 65 years of age decreased and cerebrovascular mortality rates increased. Although it is tempting to speculate that the lower mortality from diseases of the heart, coupled with a rising prevalence of hypertension,29 increased the number of AIAN elders at risk for dying of stroke, reasons for this pattern are not clear. Similarly, the increasing trend in mortality from diseases of the heart among middle-aged AIAN compared with the decreasing trend in older AIAN cannot be explained by this study. This may reflect the birth cohort effects of diabetes and smoking, which have increased markedly in prevalence among younger AIAN in recent decades. Additional evidence that the burden of CVD among AIAN was not as low as suggested by national vital event data can be found in previous studies. The 1987 Survey of American Indians and Alaska Natives found that the self-reported percent prevalence of CVD was nearly equal to that reported for the general US population.28 Among AIAN in Washington State, heart disease and cerebrovascular mortality did not differ significantly between urban AIAN and urban whites, but rural AIAN had significantly higher mortality than either of these 2 groups.10 Other smaller, tribally based studies in the late 1980s also suggested that AIAN heart disease rates rivaled or exceeded rates in the general population or were rising rapidly.6 Findings from the largest study of CVD among American Indians provide even stronger support for a growing burden of CVD. The SHS is an epidemiological study of CVD among a well-defined but culturally diverse population of American Indians 45 to 74 years of age residing in Arizona, Oklahoma, and North and South Dakota.13 The SHS included a population-based survey to estimate CVD mortality rates in these communities for 1984 to 1988.14 Major CVD mortality rates were determined from death certificate data and confirmed by independent review of medical records. In contrast to studies using national event data, the SHS found that CVD mortality rates were close to the US averages in Arizona and Oklahoma and >2 times higher in North and South Dakota for persons between 45 and 64 years of age. Furthermore, American Indian CVD mortality rates were often higher than the respective state rates for most age and sex groups. The SHS also longitudinally ascertained CVD morbidity and mortality from medical record review, clinical history, and physical examinations in a cohort of 4549 American Indians 45 to 74 years of age in the 3 regions described above. Lists of tribal rolls were used to identify eligible persons, thus eliminating racial misclassification.13 Medical records and death certificates were independently reviewed by 2 physicians to determine whether the deaths were due to CVD. After 7 years of follow-up, combined coronary heart disease incidence rates were nearly twice as high as those reported in the national Atherosclerosis Risk in Communities study cohort.15 This finding suggests that rates of coronary disease in this cohort exceed those of other US populations. Racial Miscoding and CVD Several studies support the use of adjustment for racial miscoding in reporting AIAN mortality rates. The National Center for Health Statistics evaluated the quality of the national death rates and found a markedly disproportionate underestimation of AIAN total mortality rates compared with other races.16 Specifically, the study found that death rates for AIAN were underestimated by nearly 21% compared with 11% for Asians and 2% for Hispanics. In contrast, death rates for black and white populations were overestimated by 5% and 1%, respectively. In the misclassification study of death certificate data for the IHS user population, AIAN race was misidentified an average of 10.9%, with rates varying widely from 1.2% to 30.4% across the different service units and age groups.22 Also, in Washington State, nearly 15% of AIAN were misclassified as a different race.30 Racial misclassification among AIAN has resulted in substantial underestimation of cancer mortality,31 injury rates,32 and prevalence of end-stage renal disease.33 Furthermore, mortality from "signs, symptoms, and ill-defined conditions" was a disproportionately leading cause of death among American Indians in New Mexico,34 likely leading to underestimation in rates of death from CVD. Study Limitations The adjustment factors developed by IHS were based on racial misclassification of deaths from all causes in the IHS user population from 1986 to 1988. Although overlap exists between the IHS user-defined population and the census-defined IHS service population, misclassification may be greater in the wider service population. Because adjustment factors by both age group and IHS area could not be determined,22 only the area-specific adjustment factors were applied, forcing the assumption that rates of misclassification across age groups were uniform. Also, rates of misclassification of AIAN race may be increasing.30 Finally, disease-specific misclassification rates have not been determined for the IHS populations. Still, misclassification might vary by cause of death, with racial misclassification occurring less often for conditions well known to affect AIAN such as alcoholism than for conditions such as cancer.35 Because CVD has not been widely recognized as disproportionately affecting AIAN, it may be subject to greater rates of misclassification. Mortality from ill-defined causes is also markedly disproportionate for some American Indians,34 leading to undercounting of CVD as a cause of death. The combined effect of these biases may result in conservative estimates of CVD mortality among AIAN; therefore, the disparities in the present study may be greater than demonstrated. Data were not available for a sensitivity analysis of CVD-specific adjustment factors. The adjustment for misclassification led to a 16% increase in total CVD mortality rates, which, as discussed above, may be conservative. If the overall correction of the misclassification of CVD deaths had resulted in only a 10% increase in mortality rates, the disparity would be apparent only 2 years later. Another limitation in the IHS data is the use of the standard 1940 population rather than a more recent standard population for age adjustment. It is unlikely, though, that the observed disparities would be substantially affected by use of a different standard population. The lack of sex-specific age-adjusted CVD mortality rates is another limitation of the IHS data. Such information would contribute to a better understanding of the disparities demonstrated in this study, especially if the disparities affect men and women differentially. Despite these limitations, the data clearly show an enlarging disparity in CVD mortality among AIAN compared with the US white and all-races populations. These disparities are particularly marked among middle-aged AIAN even without adjustment for racial misclassification. Reasons for the widening disparities in CVD mortality cannot be determined from the present study. One factor may be the severe epidemic of diabetes mellitus, which is markedly disproportionate among AIAN9,36,37 and may be exacting its toll. Diabetes mellitus is the most common modifiable CVD risk factor for many AIAN populations38,39 and is one of the strongest risk factors for incident CVD among participants in the SHS.15 Indeed, diabetes is a stronger risk factor among the SHS cohort than among the Framingham cohort.40 The role of socioeconomic status and access to specialty care cannot be assessed with these data but could also account for some of the disparities found here. For instance, in the 1990 census, 31.6% of the AIAN living in states with reservations lived below the poverty level compared with 13.1% of the US all-races population.20 Also, in 2000, the IHS annual per capita healthcare spending was $1430, less than one half that for the general US population ($3766),41 raising the specter that some of the observed disparities could be due to underfunding of the IHS. Although >1.2 million AIAN were included in this study, the extent to which these data can be generalized to other AIAN populations is unknown. Many AIAN may have different access to health care or different risk profiles compared with the IHS service population. Furthermore, marked heterogeneity in CVD risk factors,29 mortality,42 and racial misclassification exists among AIAN.42 The present report cannot provide region- or tribe-specific information. Conclusions and Future Directions Unfavorable and widening disparities in CVD mortality for AIAN have been largely unrecognized because of errors in national vital event data that disproportionately affect AIAN. Even without misclassification accounted for, disparities in CVD are most marked among middle-aged AIAN, which in turn suggests an even higher burden of chronic disease among younger AIAN. Rigorous data collection efforts to ensure accurate and adequate representation of AIAN in national data sets are required. Reassessments of national rates of racial misclassification should be conducted periodically to help ensure the accuracy of CVD mortality data. IHS should be commended because it is the only federal healthcare agency to routinely account for misclassification of AIAN in its health status reports. Researchers using national event data to assess trends in the health of AIAN should follow its lead. This study shows an alarming increase in CVD mortality among middle-aged AIAN and a growing disparity in CVD mortality for AIAN compared with the general population. Further research is needed to discover the root causes of these disparities and to identify persons at high risk. Although the premature CVD deaths may be attributable in part to the disproportionate and rising scourge of diabetes among younger AIAN, this hypothesis has not been tested. How AIAN men and women are affected differently by CVD mortality needs further elucidation. Also, manifestations of CVD among AIAN may differ from the general population or may be less recognized. To best address these questions, future research should include longitudinal comparative epidemiological studies of AIAN and non-AIAN men and women before the onset of middle age. Finally, AIAN communities should be alerted to the increased risk of early CVD mortality so that they can develop programs targeted at decreasing this risk. Acknowledgments This work was supported by grants 1P30AG/NE15292 from the National Institute of Aging and P01 HS10854 from the Agency for Healthcare Research and Quality. I thank Mark P. Doescher, MD, MSPH, for his critical reviews of the manuscript. References Institute of Medicine of the National Academies. Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare. Washington, DC: National Academies Press; 2003. Cooper R, Cutler J, Desvigne-Nickens P, Fortmann SP, Friedman L, Havlik R, Hogelin G, Marler J, McGovern P, Morosco G, Mosca L, Pearson T, Stamler J, Stryer D, Thom T. 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