Alterations in the balance of matrix metalloproteinase to tissue inhibitor of metalloproteinase (TIMP) are seen after acute myocardial infarction (AMI) and are associated with adverse left ventricular remodeling and prognosis in this setting. We aimed to investigate the association between TIMP levels and the occurrence of major adverse cardiac events (MACEs) after AMI. We measured plasma TIMP-1, -2, and -4 levels in 1,313 patients presenting with AMI. Subjects were followed over a median period of 520 days for the occurrence of MACEs. Clinical risk was assessed using the Global Registry of Acute Coronary Events (GRACE) score. All TIMP levels correlated with patient age and inversely with estimated glomerular filtration rate (all p values <0.001). Levels were higher in women versus men (p <0.001) and in subjects with a history of diabetes (TIMP-1, p <0.001; TIMP-2, p = 0.002; TIMP-4, p <0.001) or hypertension (TIMP-1, p = 0.031; TIMP-2, p <0.001; TIMP-4, p <0.001). TIMP-1 and TIMP-4 were higher in subjects with previous MI or angina (p <0.001). TIMP levels increased incrementally with quartiles of GRACE score (p <0.001). All TIMPs showed univariate association with the occurrence of MACEs (p <0.001). Areas under the receiver operator characteristic curve for prediction of MACE at 1 year were 0.61 for TIMP-1, 0.57 for TIMP-2, and 0.64 for TIMP-4. Combination of TIMPs with GRACE risk score revealed a greater area under the curve than GRACE score alone (0.72 vs 0.69, p = 0.0015). On multivariable Cox proportional hazards analysis, GRACE score (p <0.001) and plasma TIMPs (log TIMP-1, p = 0.017; log TIMP-2, p <0.001; log TIMP-4, p = 0.011) independently predicted MACEs. Using Kaplan-Meier analysis, the risk of MACEs increased incrementally with the number of TIMPs above their respective median (p <0.001 for all comparisons, log-rank test). In conclusion, higher plasma TIMP-1, -2, and -4 after AMI are associated with MACEs and provide additional prognostic information to that obtained from GRACE clinical risk scores alone.
Assessment of prognosis is a core part of the management of acute myocardial infarction (AMI). Current prognostic tools available to clinicians include assessment of clinical factors, which are incorporated into scoring systems such as the Global Registry of Acute Coronary Events (GRACE) risk score. Biochemical markers such as plasma natriuretic peptide concentrations are also useful and provide important prognostic information. Novel biochemical markers of prognosis may add additional information above and beyond that from those currently available. Tissue inhibitors of metalloproteinases (TIMPs) are low-molecular-weight proteins, the main biological action of which is to inhibit proteolytic activity of the matrix metalloproteinase (MMP) family of enzymes. Increased plasma TIMP levels have been demonstrated to be associated with adverse outcome in a variety of clinical settings including cardiovascular disease. On this background, the aim of the present study was to investigate the association between circulating concentrations of several TIMPs (TIMP-1, -2, and -4) and the occurrence of major adverse cardiac events (MACEs) after AMI.
Methods
We conducted a prospective cohort study in 1,313 patients with AMI admitted to the 2 coronary care units of the University Hospitals of Leicester NHS Trust (Leicester, United Kingdom) from March 1, 2000 to April 31, 2007. The hospitals provide emergency and elective care for a catchment population of approximately 940,000. Diagnosis was based on presenting symptoms consistent with AMI in conjunction with new dynamic electrocardiographic changes (ST-segment MI, n = 733, 55.8%) or ST-segment/T-wave changes (non–ST-segment MI, n = 580, 44.2%) and increase in plasma markers of myocardial necrosis (creatine kinase or troponin I to 2 times the upper limit of normal). Of the 733 patients presenting with ST-segment MI, 486 (66.3%) received thrombolytic therapy. No patients were treated with primary percutaneous coronary intervention, which was not available in our unit at that time. We excluded patients with coexisting illness likely to influence TIMP levels or prognosis, such as known malignancy or sepsis. Venous blood samples were taken in the convalescent phase of the acute coronary syndrome, within 4 days after admission, for determination of plasma levels of TIMP-1, TIMP-2, and TIMP-4. After 15 minutes of bed rest 20 ml of blood was collected into tubes containing ethylenediaminetetra-acetic acid and aprotinin. All plasma was stored at −70°C until assayed in a single batch, blind to patient details. For each patient, the GRACE score, a measurement of risk of adverse outcome based on clinical variables was calculated. Factors included in the GRACE score are patient age, heart rate, and systolic blood pressure at presentation, creatinine, Killip class, cardiac arrest at admission, ST-segment deviation, and increase of cardiac enzymes. The predefined primary outcome measurement was the composite of all-cause mortality, recurrent nonfatal MI, or heart failure episode (MACEs) during follow-up. Heart failure episode was defined as an unplanned hospital admission (>12 hours) for which the primary reason was clinical heart failure requiring high-dose diuretic (furosemide >40 mg intravenously), intravenous nitrate, or inotropic support. Secondary outcomes were the individual components of the primary outcome. Clinical end points were identified through the hospital patient-tracking system, with review of medical records for each end point. Checks were made by telephone contact with all surviving patients on a single occasion at the end of the study to ensure complete capture of all events. The local research ethics review committee approved the study and all patients gave written consent to participation. The conduct of the study was in keeping with the Declaration of Helsinki.
The TIMP assay used was based on a noncompetitive assay. All antibodies were obtained from R&D Systems (Abingdon, United Kingdom). Assays for TIMPs were constructed using specific monoclonal mouse antibodies for capturing the TIMPs, coating 200 ng/well of the respective specific monoclonal antibody in wells of enzyme-linked immunosorbent assay plates. After overnight incubation, plates were washed and then blocked with 10% fetal calf serum. Samples and standards were pipetted into the wells using dilution series of recombinant standards (TIMP-1 400 pg/well downward, TIMP-2 200 pg/well downward, TIMP-4 100 pg/well downward). After overnight incubation, plates were washed, and then biotinylated goat polyclonal antibodies specific for each TIMP were pipetted into the wells (50 ng/well). Plates were washed after 2-hour incubation at room temperature. Detection was with methyl-acridinium ester–labeled streptavidin on an MLX plate luminometer (Dynex Technologies, Ltd., Worthing, United Kingdom) using sequential injections of hydrogen peroxide in nitric acid followed 4 seconds later by sodium hydroxide in cetyl-ammonium bromide. There was no cross-reactivity between TIMPs in the different assays.
For all variables with non-Gaussian distribution (TIMPs, creatine kinase, troponin I), log-transformed values were used in analyses. Associations of TIMP levels with categorical variables were assessed using paired t test or Mann-Whitney U test for non-normally distributed variables and with continuous variables using Pearson correlation coefficient. Differences in TIMPs between quartiles of GRACE risk score were compared using between-group analysis of variance. Factors with univariate association with each end point at a significance level of a p value <0.1 were entered into multivariable Cox proportional hazards models. For each TIMP, the strength of association with end points is expressed as hazard ratio (HR) per log-transformed unit increase in plasma concentration of that TIMP. When considering the primary end point of MACEs, we assessed time to first event. Median values of each TIMP were calculated for the entire population and used as cut-off points to predict adverse outcome using Kaplan-Meier assessment; we compared outcome between groups with 0, 1, 2, or 3 TIMPs above their respective median. Receiver operator characteristic curves were constructed for the predictive ability of each of our markers and for GRACE risk score. Comparison between c-statistics of receiver operator characteristic curves was performed using the method of DeLong et al. For all analyses, a p value <0.05 was regarded statistically significant and 2-sided tests were used where appropriate. Statistical analyses were carried out using SPSS 14 (SPSS, Inc., Chicago, Illinois) and Analyse-it (Analyse-it software, Ltd., Leeds, United Kingdom) for Excel. The authors had full access to the data, accept responsibility for their validity, and have read and agreed to the report as submitted.
Results
Admission demographic features, medications at discharge, and differences in demographic factors between those admitted with ST-elevation versus non–ST-elevation MI of the study population are listed in Table 1 . Seven hundred thirty-three (55.8%) presented with ST-segment MI, of whom 484 (66%) received thrombolytic therapy. No patient received primary percutaneous revascularization. Follow-up was obtained in all 1,313 patients over a median of 520 days (range 1 to 2,825). For patients alive at the end of the study, minimum follow-up was 125 days.
| Variable | All Patients | STEMI | NSTEMI | p Value ⁎ |
|---|---|---|---|---|
| (n = 1,313) | (n = 733) | (n = 580) | ||
| Age (years) | 67 (24–97) | 64 (24–95) | 70 (37–97) | <0.001 |
| Men | 948 (72.2%) | 550 (75.0%) | 398 (68.6%) | 0.008 |
| Medical history | ||||
| Diabetes | 309 (23.5%) | 142 (19.4%) | 167 (28.8%) | <0.001 |
| Hypertension | 644 (49.0%) | 298 (40.7%) | 346 (59.7%) | <0.001 |
| Ischemic heart disease | 447 (34.0%) | 176 (24.0%) | 271 (46.7%) | <0.001 |
| Left ventricular failure | 51 (3.9%) | 38 (5.2%) | 13 (2.2%) | 0.006 |
| Current smoker | 609 (46.4%) | 453 (61.8%) | 156 (26.9%) | <0.001 |
| Index admission | ||||
| Anterior territory | 480 (36.6%) | 286 (39.0%) | 194 (33.4%) | 0.033 |
| Thrombolysis | 486 (37.0%) | 486 (66.3%) | — | — |
| Peak creatine kinase (IU/L, normal range 0–200) | 838 (4.5–9,523) | 939 (4.5–9,523) | 243 (35–7,264) | <0.001 |
| Troponin I (mg/L) | 3.5 (0.06–150) | 11.0 (0.06–150.0) | 2.0 (0.06–67.0) | <0.001 |
| Estimated glomerular filtration rate (ml/min) | 66.4 (12.0–184.3) | 68.6 (17.8–177.3) | 62.6 (12.0–184.3) | <0.001 |
| Global Registry of Acute Coronary Events score | 152 (31–299) | 155 (31–299) | 146 (55–284) | 0.001 |
| Admission Killip class | ||||
| I | 692 (52.7%) | 328 (44.7%) | 364 (62.8%) | — |
| II | 409 (30.7%) | 270 (36.8%) | 139 (24.0%) | — |
| III | 127 (9.7%) | 53 (7.2%) | 74 (12.8%) | — |
| IV | 4 (0.3%) | 2 (0.3%) | 2 (0.3%) | — |
| Medications | ||||
| Aspirin | 1,129 (86.0%) | 662 (90.3%) | 467 (80.5%) | <0.001 |
| β Blocker | 1,048 (79.8%) | 609 (83.1%) | 439 (75.7%) | <0.001 |
| Angiotensin-converting enzyme inhibitor/angiotensin receptor blocker | 1,034 (78.8%) | 585 (79.8%) | 449 (77.4%) | 0.292 |
| Statin | 1,089 (82.9%) | 598 (81.6%) | 491 (84.7%) | 0.142 |
| Furosemide | 384 (29.2%) | 210 (28.6%) | 174 (30.0%) | 0.604 |
Figure 1 shows the incremental increase in TIMP-1 levels divided by clinical risk as assessed by GRACE risk score (quartiles) at admission (p <0.001, analysis of variance). Similar changes in plasma concentrations of TIMP-2 and TIMP-4 were also seen (all p values <0.001, analysis of variance).
Factors associated with individual plasma TIMP levels are listed in Table 2 . All TIMPs were directly correlated to age and inversely to estimated glomerular filtration rate. All TIMPs were lower in men compared to women and were higher in subjects with previous diabetes mellitus or hypertension. TIMP-1 and TIMP-4 were higher in subjects with previous ischemic heart disease. TIMP-2 and TIMP-4 were lower in smokers. There was weak correlation between levels of each TIMP and troponin I, but not creatine kinase. TIMP-1 was higher and TIMP-4 lower in ST-segment MI compared to non–ST-segment MI. Factors with univariable association with each TIMP were entered into a multivariable regression model for prediction of plasma TIMP concentrations. Factors demonstrating an independent association with TIMP-1 were age (p <0.001), estimated glomerular filtration rate (p <0.001), history of diabetes (p <0.001), and ST-segment MI (p <0.001). Factors demonstrating an independent association with TIMP-2 were age (p <0.001), estimated glomerular filtration rate (p <0.001), and nonsmoking history (p = 0.032). Factors with an independent association with TIMP-4 were age (p <0.001) and previous ischemic heart disease (p = 0.001).
| Factor | TIMP-1 | p Value ⁎ | TIMP-2 | p Value ⁎ | TIMP-4 | p Value ⁎ |
|---|---|---|---|---|---|---|
| Age (years) | r = 0.287 | <0.001 | r = 0.271 | <0.001 | r = 0.449 | <0.001 |
| Estimated glomerular filtration rate (ml/min) | r = −0.270 | <0.001 | r = −0.237 | <0.001 | r = −0.366 | <0.001 |
| Creatine kinase (IU/L) | r = 0.042 | 0.248 | r = 0.046 | 0.201 | r = −0.040 | 0.266 |
| Troponin (mg/L) | r = 0.069 | 0.041 | r = 0.066 | 0.049 | r = −0.074 | 0.028 |
| Gender | ||||||
| Men | 222.0 (0.3–826.2) | <0.001 | 88.2 (33.1–361.1) | <0.001 | 4.2 (1.1–67.4) | <0.001 |
| Women | 247.5 (5.2–963.2) | 94.8 (94.8–465.3) | 5.7 (1.0–83.8) | |||
| Diabetes | ||||||
| Yes | 256.2 (0.3–963.2) | <0.001 | 93.3 (47.0–164.0) | 0.002 | 5.3 (1.2–52.5) | <0.001 |
| No | 219.4 (0.3–720.9) | 88.6 (33.1–465.3) | 4.3 (1.0–83.8) | |||
| Hypertension | ||||||
| Yes | 232.4 (5.2–826.2) | 0.031 | 92.7 (33.1–361.2) | <0.001 | 4.9 (1.3–67.4) | <0.001 |
| No | 221.4 (0.3–963.2) | 86.5 (33.6–465.3) | 4.2 (1.0–83.8) | |||
| Ischemic heart disease | ||||||
| Yes | 252.0 (0.3–963.2) | <0.001 | 90.7 (33.1–465.2) | 0.061 | 5.6 (1.4–61.2) | <0.001 |
| No | 215.3 (0.3–720.9) | 89.1 (33.6–325.2) | 4.1 (1.0–83.8) | |||
| Left ventricular failure | ||||||
| Yes | 274.7 (80.8–610.5) | 0.012 | 83.7 (59.2–211.3) | 0.138 | 5.14 (2.2–17.5) | 0.079 |
| No | 223.5 (0.3–963.2) | 89.7 (33.1–465.3) | 4.5 (1.01–83.8) | |||
| Anterior territory | ||||||
| Yes | 230.7 (0.3–720.9) | 0.227 | 89.0 (33.1–313.8) | 0.564 | 4.6 (1.2–83.8) | 0.894 |
| No | 222.5 (5.2–963.1) | 89.6 (41.7–465.3) | 4.5 (1.0–65.4) | |||
| Thrombolysis (ST-elevation myocardial infarction only) | ||||||
| Yes | 235.4 (35.8–963.2) | 0.200 | 89.1 (33.6–361.1) | 0.117 | 3.9 (1.2–83.8) | 0.113 |
| No | 227.9 (0.3–720.9) | 93.1 (52.7–221.6) | 4.4 (1.0–65.5) | |||
| Smoker | ||||||
| Yes | 223.6 (0.3–664.7) | 0.518 | 86.6 (33.1–211.3) | <0.001 | 3.8 (1.1–65.4) | <0.001 |
| No | 226.9 (0.31–963.2) | 92.9 (47.0–465.3) | 5.0 (1.0–83.8) | |||
| ST-elevation myocardial infarction | 233.4 (0.3–963.2) | <0.001 | 90.4 (33.6–361.2) | 0.082 | 4.2 (1.0–83.8) | <0.001 |
| Non–ST-elevation myocardial infarction | 217.4 (5.2–826.2) | 88.7 (33.1–465.3) | 5.1 (1.1–60.5) |
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