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Free vs total pregnancy-associated plasma protein a (PAPP-A) as a predictor of 1-year outcome in patients presenting with non-ST-elevation acute coronary syndrome.

Although the exact role of pregnancy-associated plasma protein A (PAPP-A) [5] in cardiac events is not fully understood, previous data imply that PAPP-A may play a role in the progression of atherosclerotic vascular disease. Increased PAPP-A in circulation correlates with poor outcome not only in acute coronary syndrome (ACS) (1-3) but also in stable coronary artery disease and hemodialysis (4, 5). PAPP-A is a metzincin metalloproteinase (6) that degrades insulin-like growth factor binding proteins 2, 4, and 5 (7-9). Although produced by cells in a noncomplexed form consisting of 2 PAPP-A subunits, in pregnancy and in the healthy population PAPP-A is found in blood predominantly as a covalent complex of 2 PAPP-A subunits and 2 proform of eosinophil major basic protein (proMBP) subunits (10,11). PAPP-A, when complexed with proMBP, is inactive (12).

Existing commercial assays for PAPP-A detect both complexed PAPP-A/proMBP and the noncomplexed free form of PAPP-A (FPAPP-A), and these total PAPP-A (TPAPP-A) assays are the only ones that have been used so far in published clinical reports on PAPP-A as a cardiac or ACS marker (1-4, 13, 14). Recently, FPAPP-A was reported to be the dominant molecular form released to the circulation during ACS (15). Measurement of FPAPP-A has therefore been suggested as a more specific and sensitive biomarker in ACS than TPAPP-A, which shows considerable intraindividual fluctuations not related to the acute event. Recently, it has been demonstrated that heparin treatment may increase circulating concentrations of PAPP-A. Heparin coinjection slowed the clearance of recombinant human PAPP-A in mice, and heparin injection 5 min after the PAPP-A injection led to a secondary increase in the PAPP-A concentration (16).In the same study, PAPP-A concentrations were found to be higher in heparin-treated vs heparin-naive patients with ST-elevation myocardial infarction. In another clinical study (17), the administration of a low molecular weight heparin bolus at the beginning of a hemodialysis session induced a dramatic increase in circulating PAPP-A concentrations, whereas this increase was not detected in patients with a heparin-free hemodialysis procedure.

Therefore, we analyzed the prognostic performance of FPAPP-A vs TPAPP-A using samples collected at the time of admission in patients hospitalized due to symptoms consistent with non-ST-elevation ACS but not treated with any heparin preparations before the first admission PAPP-A sample.

MATERIALS AND METHODS

SUBJECTS AND DESIGN

We recruited 360 consecutive patients hospitalized for at least 12 h owing to symptoms consistent with non-ST-elevation ACS. On the grounds of increased cardiac troponin I (cTnI), the diagnosis of non-ST-elevation myocardial infarction was made in 121 (45.3%) patients, and the rest were classified as unstable angina or other ACS. Individuals with acute ST elevation on electrocardiogram (ECG) (n = 62) or missing blood samples (n = 9) were excluded. Low molecular weight heparin was given to 136 patients during the hospitalization. Of these patients, 22 received low molecular weight heparin before the admission blood sampling and were excluded. Thus, the final study group consisted of 267 patients [136 men and 131 women, median (25th;75th percentile) age 70 (60;78) years] who were treated according to the routine clinical protocols of Turku University Hospital in 2000-2001. We collected data on the endpoints (the combination of death and the first episode of nonfatal myocardial infarction) during 12-month follow-up from hospital records and by interviewing the patients as described (1, 2).We obtained additional mortality data (including cause of death) from Statistics Finland (a registry that contains information on all deaths in Finland). The first and fourth authors (J. Lund, T. Ilva) retrospectively reviewed hospital records of all patients for the classification of nonfatal endpoints. Occasional discrepancies were settled by mutual consensus of all authors. The study was conducted in accordance with the Declaration of Helsinki as revised in 1996 and approved by the Ethics Committee of Turku University Hospital. All patients gave their written informed consent to participate.

BIOCHEMICAL MEASUREMENTS

Serum samples for PAPP-A were collected at the time of hospital admission. All samples were studied by investigational point-of-care time-resolved immunofluorometric assays for TPAPP-A and PAPP-A/proMBP complex, an approach specifically designed for the analysis of ACS patient samples and previously described (11). In TPAPP-A assay, the capture antibody and the detection antibody both specifically bind to the PAPP-A subunit of free PAPP-A and complexed PAPP-A molecules. In PAPP-A/proMBP assay, the same antibody is used for capture as in TPAPP-A assay; however, the detection antibody specifically binds to the proMBP subunit of PAPP-A/proMBP complex, enabling the exclusive detection of this complexed PAPP-A form. The analytical detection limits (zero calibrator + 3SD) and functional detection limits (imprecision <20%) were 0.18 mIU/L and 0.27 mIU/L for the TPAPP-A assay and 0.23 mIU/L and 0.70 mIU/L for the PAPP-A/proMBP assay, respectively (11). The total CV for TPAPP-A assay was 7.2% at 4.9 mIU/L and 9.7% at 3.1 mIU/L for PAPP-A/proMBP assay (11). The concentration of FPAPP-A was calculated from the difference of the results given by these 2 assays. Thus, the measured value of FPAPP-A is affected by the imprecision of both assays. The precision profiles of FPAPP-A, TPAPP-A, and PAPP-A/proMBP in the samples analyzed in this study are shown in Fig. 1. The 97.5th upper reference limit of the apparently healthy population was 1.29 mIU/L for FPAPP-A and 4.85 mIU/L for TPAPP-A (11).

For the purposes of this study, cTnI was analyzed at time points of 0 (admission cTnI), 6-12 h, and 24 h using the Innotrac Aio! second-generation assay (Innotrac Diagnostics Corp.), which has been classified as a level 1 contemporary clinically usable cTn assay (18). The minimum detectable concentration of the assay is 0.012 [micro]g/L, and the cutoff value for myocardial infarction defined as the concentration with a 10% CV is 0.06 [micro]g/L. The 99th percentile reference concentration was determined to be 0.025 [micro]g/L (19). Thus, a cTnI concentration >0.03 [micro]g/L was deemed to be increased in this study. Maximal cTnI was defined as the highest concentration detected during the first 24 h.

C-reactive protein (CRP) taken at admission was measured by an ultrasensitive Aio! assay [a high-sensitivity CRP assay according to US Food and Drug Administration (FDA) guidelines (20)] with an analytical detection limit of 0.003 mg/L and functional detection limit or 0.1 mg/L (21); 2.0 mg/L was used as a cutoff concentration in multivariate analysis. TPAPP-A, PAPP-A/proMBP, cTnI, and CRP measurements were performed using the Innotrac Aio! immunoanalyzer. All investigational samples were studied post hoc, and the results were not made available to the treating physicians.

[FIGURE 1 OMITTED]

ECG EVALUATIONS

The 12-lead admission ECG was manually coded by the fifth author (P. Porela). First, patients with left bundle branch block or nondiagnostic ECG were identified. ST-segment elevation [greater than or equal to] 0.1 mV (except V1-3 [greater than or equal to] 0.2 mV) at the J-point in 2 continuous leads was classified as ST elevation. Ischemic ST-segment depression [greater than or equal to] 0.05 mV at the J+ 80 ms point in at least 1 lead was coded as having ST depression. If the previous criteria were not fulfilled, then the T-wave was measured. T inversion was coded if it was present in [greater than or equal to] 2 contiguous leads. If none of these criteria were fulfilled, the ECG was coded as having no ischemic changes.

STATISTICAL METHODS

We compared categorical variables between groups with the [chi square] test and continuous variables with the Wilcoxon rank-sum test. We estimated survival curves by the Kaplan-Meier method and tested differences between curves with the log rank test. We tested correlations with Spearman correlation. We analyzed multivariate associations using Cox proportional-hazards modeling. Statistical analyses were performed using SAS statistical software (version 9.2, SAS Institute). P values <0.05 were considered significant.

Results

BASELINE

In the admission serum samples, median (25th; 75th percentile) FPAPP-A was 1.43 (1.13;1.95) mIU/L [1.49 (1.12;1.97) mIU/L in men and 1.43 (1.13;1.89) mIU/L in women, P = NS). The corresponding values for TPAPP-A were 2.41 (1.82, 3.26) mIU/L [2.53 (1.90; 3.39) mIU/L in men and 2.32 (1.80;3.18) mIU/L in women, NS). In 176 patients (65.9%), FPAPP-A was above the 97.5th percentile upper reference limit, whereas the concentrations of TPAPP-A exceeded the upper reference limit (4.85 mIU/L) in only 17 patients (6.4%). The patients were subdivided according to FPAPP-A (<1.27, 1.27-1.74, >1.74 mIU/L) and TPAPP-A (<1.98, 1.98 -2.99, >2.99 mIU/L) tertiles.

There were no statistically significant differences between the FPAPP-A and TPAPP-A tertiles with respect to age, sex, smoking habits, percentage of patients with previous myocardial infarction, previous revascularization, or duration of hospitalization, although diabetes was more frequent in the third tertile (Table 1). The frequency of revascularization during the follow-up was 18.0%, 22.5%, and 13.5%, respectively, in the FPAPP-A tertiles.

Table 2 shows the distribution of patients with increased maximal cTnI and ischemia on ECG, as well as median CRP, median admission cTnI, and median maximal cTnI concentrations according to FPAPP-A tertiles. The distribution of patients with increased maximal cTnI was equal between the groups, whereas admission cTnI and CRP were significantly higher in the third tertile compared with the lowest FPAPP-A tertile. There were only weak correlations between FPAPP-A and admission cTnI (r = 0.15, P = 0.012), maximal cTnI (r = 0.12, P = 0.043), and CRP (r = 0.17, P = 0.005). There was a significant correlation between TPAPP-A and FPAPP-A in the third tertile (r = 0.67, P < 0.001) that was weaker in the second (r = 0.23, P = 0.033) and first (r = 0.23, P = 0.03) tertiles.

OUTCOME AND FPAPP-A VS TPAPP-A

During follow-up, 57 patients (21.3%) met an endpoint (22 deaths and 35 nonfatal myocardial infarctions). Total mortality was 32 of 267 (12.0%), as 10 patients who had myocardial infarction as an endpoint died during the entire follow-up. Broken down by FPAPP-A and TPAPP-A tertiles, an endpoint was met by 12 (13.5%), 18 (20.2%), and 27 (30.3%) (P = 0.02) and 17 (19.1%), 17 (19.1%), and 23 (25.8%) (P = 0.54) subjects, respectively (Fig. 2). The Kaplan-Meier survival curves for the various FPAPP-A tertiles diverged early, but this was not the case for TPAPP-A (Fig. 2).

Fig. 3 shows the distribution of endpoints in FPAPP-A tertiles according to maximal cTnI status. The combination of normal maximal cTnI and FPAPP-A <1.27 mIU/L identified a subgroup at low risk for an endpoint (3 of 55pts, 5.5%). The highest risk (19 of 44 pts, 43.2%) was observed in patients with increased maximal cTnI and FPAPP-A > 1.74 mIU/L.

MULTIVARIATE ANALYSIS

Increased admission cTnI [risk ratio (RR) 1.9; 95% CI 1.1-3.5, P = 0.024) and CRP >2.0 mg/L (rR 2.4; 95% CI 1.2-4.7, P < 0.01) were found to be independent early-phase predictors of adverse outcome after adjusting for age in 10-year subgroups, sex, diabetes (dietary or drug treated), previous acute myocardial infarction, and ischemic ECG findings, FPAPP-A >1.74 mIU/L (RR 2.0; 95% CI 1.0-4.2, P = 0.048). Replacing admission with maximal cTnI gave comparable results, as the independent predictors were FPAPP-A >1.74 mIU/L (RR 2.0; 95% CI 1.0-4.1, P = 0.053), increased maximal cTnI (RR 2.4; 95% CI 1.3- 4.4, P = 0.01), and CRP 2.0 mg/L (RR 2.3; 95% CI 1.2- 4.6, P = 0.014). In the same setting, however, TPAPP-A did not reach significance as an independent predictor of an endpoint (RR 1.1-1.2, P = 0.49-0.88).

Discussion

This is the first study to show the independent prognostic significance of the free form of PAPP-A measured in ACS patients in the earliest available blood sample. FPAPP-A was found to be an independent predictor of death and myocardial infarction in patients with ACS without ST elevation on ECG. These results are in line with our previous study, where we showed the correlation of increased TPAPP-A with poor prognosis in ACS patients who remained cTnI negative (1) and in patients with ST-elevation myocardial infarction and late PAPP-A increases (2). Notably, the population in the present study included ACS patients with both normal and increased cTnI.

In contrast to all previously published clinical PAPP-A studies using an assay for TPAPP-A (measuring both FPAPP-A and complexed PAPP-A), this study used the specific determination of FPAPP-A for prognostication of ACS. Complexed PAPP-A is variably found in all individuals without ACS, whereas FPAPP-A predominantly represents the PAPP-A fraction that changes dynamically in ACS (11, 15). As we have previously argued (11), the measured concentrations of circulating TPAPP-A in ACS are variably affected by interindividual variations in complexed PAPP-A. Therefore it is reasonable to assume that FPAPP-A should be a more accurate marker for ACS and risk for adverse cardiac events than TPAPP-A, especially when TPAPP-A concentrations are low, as is the case in admission samples of patients with non-ST-elevation ACS. When TPAPP-A is high, FPAPP-A is also high, giving similar information; when TPAPP-A is low, FPAPP-A more clearly shows disease-related increases, giving more information. We expect this to be true also in other patient groups such as hemodialysis patients, but it remains to be confirmed in further studies. In this study, FPAPP-A, but not TPAPP-A, measured in the admission sample reached statistical significance as an independent predictor of the endpoint. In agreement with this, we showed that TPAPP-A and FPAPP-A concentrations were correlated in the highest tertile, but not in the lowest tertile owing to the more pronounced baseline variations of TPAPP-A levels.

[FIGURE 2 OMITTED]

As recently shown, heparin treatment may significantly increase the PAPP-A concentration in the circulation (16, 17). This has possibly affected the results of some earlier studies, including our own (1, 2),in which heparin administration was not taken into account and could explain some discrepancies in the results obtained. This may also partly explain the discrepancy of the prognostic performance of TPAPP-A in comparison to our previous studies, although the patient material and PAPP-A sampling protocols were not identical. We have previously reported that maximal TPAPP-A within 24 h predicts adverse cardiac events in 6 months in ACS patients without cTnI increases (2). However, many patients received heparin medication within the first 24 h after admission, which may have had a substantial effect on the results, i.e., the inclusion of higher-risk patients on heparin treatment led to higher observed increases of PAPP-A in these patients. To avoid the confounding effect of heparin, in this study only admission FPAPP-A and TPAPP-A were analyzed, and patients receiving heparin or low molecular weight heparin treatment before the first blood sampling were excluded. The use of admission samples may also explain the difference between our present and previous studies (2): admission TPAPP-A concentrations are lower than 24-h maximal values, creating a situation where FPAPP-A works better than TPAPP-A as described above.

[FIGURE 3 OMITTED]

FPAPP-A in the admission sample was increased in a majority of the patients of this study compared to the normal population. The exact mechanism of PAPP-A increases in ACS is unknown. There were more patients with diabetes in the third tertile, indicating that more complex or advanced atherosclerosis could be 1 explanation. Notably, because neither the concentration of maximal cTnI nor the distribution of the patients with increased cTnI during the hospitalization differed between the FPAPP-A tertiles, the extent of myocardial damage does not appear to explain the FPAPP-A increases. Furthermore, FPAPP-A correlated only weakly with admission cTnI, maximal cTnI, and CRP.

This study has several limitations, and the results must be interpreted with caution. First, the only available means of analyzing FPAPP-A is to measure TPAPP-A and PAPP-A/proMBP complex separately and calculate FPAPP-A as the difference. To improve assay sensitivity and simplify the method for possible clinical use, a direct FPAPP-A assay should be developed to minimize interassay variation. Second, in this cohort study performed in 2000-2001, the patients were treated according to local routine protocols and received less invasive treatment in comparison to the current guidelines. Therefore, although this study allowed observations in a relatively high-risk group treated conservatively, the prognostic performance of FPAPP-A should be investigated across the current clinical and therapeutic continuum of ACS. Third, the proportion of cTn-positive patients was quite low, and by using a more robust high-sensitivity cTn assay (22,23), the proportion of cTn-positive patients would likely be higher. It is conceivable that a proportion of the so-called low-risk cTn-negative patients, in fact, had minimal cTn leakages that remained below the recommended cutoff threshold of the assay used. The use of a more robust cTn assay might have had an impact on the prognostic value of FPAPP-A in this subgroup. However, to further explore the added value of FPAPP-A vs cTn, future studies need to be done using not only a high-sensitivity cTn assay but also a direct FPAPP-A assay to replace the 2-assay approach of this study. Fourth, the clinical applicability of FPAPP-A as a prognostic marker is currently restricted by the fact that most non-ST-elevation ACS patients are treated with heparin before admission.

Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements:

(a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.

Authors' Disclosures of Potential Conflicts of Interest: No authors declared any potential conflicts of interest.

Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of manuscript.

Acknowledgments: Noora Ristiniemi is thanked for excellent technical assistance.

References

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Juha Lund, [1] * Saara Wittfooth, [2] Qiu-Ping Qin, [2] Tuomo Ilva, [1] Pekka Porela, [1] Kari Pulkki, [3] Kim Pettersson, [2] and Liisa-Maria Voipio-Pulkki [1,4]

[1] Department of Medicine and [2] Department of Biotechnology, University of Turku, Turku, Finland; [3] Department of Clinical Chemistry, University of Eastern Finland and ISLAB, Kuopio, Finland; [4] Department of Medicine, Helsinki University Hospital, Helsinki, Finland.

* Address correspondence to this author at: Department of Medicine, University of Turku, FIN-20520 Turku, Finland. Fax +358-2-3132030; e-mail juha.lund@tyks.fi.

Received September 11, 2009; accepted April 19, 2010.

Previously published online at DOI: 10.1373/clinchem.2009.136960

[5] Nonstandard abbreviations: PAPP-A, pregnancy-associated plasma protein A; ACS, acute coronary syndrome; proMBP, proform of eosinophil major basic protein; FPAPP-A, free form of PAPP-A; TPAPP-A, total PAPP-A; cTnI, cardiac troponin I; ECG, electrocardiogram; CRP, C-reactive protein; FDA, US Food and Drug Administration; RR, risk ratio.
Table 1. Baseline characteristics of the patients in PAPP-A
tertiles. (a)

 FPAPP-A, mIU/L

 < 1.27 1.27-1.74 >1.74 p(b) p(c)

n 89 89 89

Age, years 64 (57;74) 70 (62;78) 73 (64;79) NS(d) NS

Male sex 46 (51.7) 43 (48.3) 47 (52.8) NS NS

Diabetes 12 (13.5) 19(21.3) 27 (30.3) NS 0.012

Smoking 23 (23.6) 21 (25.8) 23 (23.6) NS NS

Previous myocar-
dial infarction 24 (27.0) 35 (39.3) 32 (36.0) NS NS

Previous
reperfusion 17(19.1) 22 (24.7) 12 (13.5) NS NS

Hospitalization 4 (2;6) 5 (3;7) 5 (2;7) NS NS
time, days

 TPAPP-A, mIU/L

 <1.98 1.98-2.99 > 2.99 p(b) P(c)

n 89 89 89

Age, years 67 (58;76) 68 (59;78) 73 (66;78) NS NS

Male sex 37 (41.6) 49 (55.1) 50 (56.2) NS NS

Diabetes 13(14.6) 19(21.3) 26 (29.2) NS 0.02

Smoking 22 (24.7) 23 (25.8) 22 (24.7) NS NS

Previous myocar-
dial infarction 32 (36.0) 26 (29.2) 33 (37.1) NS NS

Previous
reperfusion 18(20.2) 17(19.1) 16(18.0) NS NS

Hospitalization 4 (2;6) 5 (2;7) 5 (2;7) NS NS
time, days

 All

n 267

Age, years 70 (60;78)

Male sex 136 (50.9)

Diabetes 58 (21.7)

Smoking 67 (25.1)

Previous myocar-
dial infarction 91 (32.9)

Previous
reperfusion 51 (19,1)

Hospitalization 5 (2;7)
time, days

(a) Data are median (25th; 75th percentile) or n (%).
(b) First vs second tertile
(c) First vs third tertile.
(d) NS, nonsignificant.

Table 2. Other markers in PAPP-A tertiles. (a)

 FPAPP-A, mIU/L

 <1.27 1.27-1.74 >1.74 P(b) P(c)

n 89 89 89
Increased cTnI 34 (38.2) 43 (48.3) 44 (49.4) NSd NS
Ischemia on ECG 35 (39.3) 43 (48.3) 43 (48.3) NS NS
Admission cTnI, 0.01 (0; 0.02 (0; 0.02 (0; NS 0.002
 [micro]g/L 0.04) 0.09) 0.12)
Maximal cTnI, 0.02 (0; 0.03 0.03 (0.01; NS NS
 [micro]g/L 0.20) 0.71)
CRP mg/L 2.5 (1.3; 2.2 (1.0; 5.1 (1.3; NS 0.034
 6.1) 7.0) 10.8)
TPAPP-A, mIU/L 1.6(0.2, 2.3 (1.4, 3.0 (2.1;
 3.5) 4.8) 5.9)

 TPAPP-A, mIU/L

 <1.98 1.98-2.99 >2.99 P(b) P(c)

n 89 89 89 89 89
Increased cTnI 41 (38.2) 35 (48.3) 45 (49.4) NS NS
Ischemia on ECG 36 (39.3) 39 (48.3) 46 (48.3) NS NS
Admission cTnI, 0.01 (0; 0.02 (0; 0.02 (0; NS NS
 [micro]g/L 0.08) 0.06) 0.11)
Maximal cTnI, 0.03 (0,01; 0.02 (0; 0.05 (0.01; NS NS
 [micro]g/L 0.20) 0.98) 0.63)
CRP mg/L 2.8 (1.4; 2.6 (0.95; 3.2 (1.3; NS NS
 8.2) 8.2) 8.9)
TPAPP-A, mIU/L

 All

n 267
Increased cTnI 121 (45.3)
Ischemia on ECG 121 (45.3)
Admission cTnI, 0.01 (0;
 [micro]g/L 0.08)
Maximal cTnI, 0.03 (0.01;
 [micro]g/L
CRP mg/L 2.8 (1.3;
 8.2)
TPAPP-A, mIU/L 2.4 (1.8;
 3.3)

(a) Data are median (25th; 75th percentile) or n (%).
(b) First vs second tertile.
(c) First vs third tertile.
(d) NS, nonsignificant.
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Title Annotation:Proteomics and Protein Markers
Author:Lund, Juha; Wittfooth, Saara; Qin, Qiu-Ping; Ilva, Tuomo; Porela, Pekka; Pulkki, Kari; Pettersson, K
Publication:Clinical Chemistry
Date:Jul 1, 2010
Words:4649
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