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. Author manuscript; available in PMC: 2015 Jun 24.
Published in final edited form as: Circ Heart Fail. 2012 Jun 8;5(4):406–413. doi: 10.1161/CIRCHEARTFAILURE.111.965327

Cardiac Micro-Injury Measured by Troponin T Predicts Collagen Metabolism in Adults Aged ≥ 65 Years with Heart Failure

Willem J Kop 1,2, John S Gottdiener 1, Christopher R deFilippi 1, Eddy Barasch 3, Stephen L Seliger 1, Nancy S Jenny 4, Robert H Christenson 5
PMCID: PMC4479498  NIHMSID: NIHMS392979  PMID: 22685114

Abstract

Background

Repeated myocardial micro-injuries lead to collagen deposition and fibrosis, thereby increasing the risk of clinical heart failure. Little is known about the longitudinal association between increases in myocardial injury and the biology of collagen synthesis and deposition.

Methods and Results

Repeated measures of highly sensitive cardiac troponin T (cTnT) were obtained in participants of the Cardiovascular Health Study (N-353; mean age=74±6 years, 52% women) at baseline and at three years follow-up. Biomarkers of collagen metabolism were obtained at follow-up and included carboxyterminal propeptide of procollagen type I (PIP), carboxyterminal telopeptide of type I collagen (CITP); and aminoterminal propeptide of procollagen III (PIIINP). Multivariable linear regression analyses were used to examine the association between baseline cTnT and changes in cTnT with collagen metabolism markers at follow-up, adjusting for demographics, heart failure status, and cardiovascular risk factors. Results indicated that cTnT increases over 3-years were significantly associated with higher levels of CITP (β=0.22, p<0.001) and PIIINP (β=0.12, p=0.035) at follow-up when adjusting for demographic, clinical and biochemical covariates including baseline cTnT. These associations were stronger in heart failure patients than in controls.

Conclusions

Increases in myocardial micro-injury measured by changes in cTnT adversely affect markers of collagen metabolism. These findings are important to the biology of myocardial fibrosis and tissue repair. Serial evaluation of cTnT combined with collagen metabolism markers may further elucidate the pathophysiology of heart failure.

Keywords: collagen metabolism, fibrosis, myocardial micro-injury, troponin T, heart failure, risk factors

Myocardial fibrosis plays an important role in increased left ventricular (LV) stiffness, elevated pulmonary venous pressure, and decreased LV stroke volume reserve (1–4). These conditions may result in clinical systolic heart failure (HF) or HF with preserved LV function. Myocardial infarction with necrosis of large amounts of myocardium leads to replacement fibrosis. The present study addresses the associations of myocardial micro-injury, reflecting injury or necrosis of few myocytes, with collagen metabolism markers. Biological processes related to micro-injury can lead to myocardial fibrosis in the absence of myocardial infarction and increase the risk of HF (5).

Myocardial micro-injury can now be accurately measured with a highly sensitive cardiac troponin T (cTnT) assay, with levels below those used to define an acute myocardial infarction (6;7). We recently demonstrated that high sensitivity cTnT can be detected in 66% of individuals aged ≥ 65 and that increases in cTnT over time are predictive of incident HF and cardiovascular mortality (8).

Micro-injury activates matrix metalloproteinase, thereby acting as a potent collagen turnover stimulating factor. Type I and III collagens are the predominant fibrillar collagens in normal and diseased myocardium (3;9–12). Biomarkers of collagen metabolism relevant to fibrosis include carboxyterminal propeptide of procollagen type I (PIP), a marker of type I collagen synthesis; carboxyterminal telopeptide of type I collagen (CITP), a marker of degradation of type I collagen; and aminoterminal propeptide of procollagen III (PIIINP), a marker of synthesis and degradation of type III collagen (13–15). Although markers of collagen metabolism derived from blood samples are not cardiac-specific (16), histological evidence indicates that serum PIP reflects myocardial fibrosis in heart failure and other cardiac conditions (17), whereas such evidence is still pending for CITP and PIIINP..

In a population-based sample of individuals aged ≥ 65 years, the present study investigates the hypotheses that: (1) myocardial micro-injury measured by high sensitivity cTnT is associated with elevated collagen metabolism markers and; (2) longitudinal increases in cTnT are predictive of elevated collagen metabolism markers. We also determined to what extent these associations are influenced by inflammation-related processes and whether HF-status plays a role in the association between cTnT and markers of dysregulated collagen metabolism.

Methods

Participants

The study included participants in the Cardiovascular Health Study (CHS) in whom collagen metabolism markers and serial cTnT levels were measured as part of a nested case-control study of heart failure. The associations between changes in cTnT and collagen metabolism markers were examined in individuals with HF, individuals with cardiovascular disease (CVD) risk factors (hypertension, diabetes, or hypercholesterolemia), and individuals without these CVD risk factors. The HF-free control groups were examined to determine whether changes in cTnT are associated with collagen metabolism markers prior to the onset of clinical HF and to minimize confounding by HF-related medications (e.g., ACE inhibition and beta-adrenergic blocking agents).

The CHS is a prospective, community-based, epidemiologic observational investigation designed to assess cardiovascular risk factors and outcomes in persons aged 65 and above. The design and examination of the CHS have been published previously (18). Briefly, 5,201 participants ≥ age 65 were enrolled in 1989–1990, with an additional cohort of 687 ethnic minority participants enrolled in 1992–1993. Exclusion criteria for the total CHS cohort were: hospice treatment, wheel-chair bound in the home, and radiation or chemotherapy for cancer. For purposes of the present study, history of chronic liver disease or pulmonary disease were used as additional exclusion criteria to minimize confounding effects of these diseases on the biochemical measures related to fibrosis, as described previously (19).

Figure 1 displays the inclusion flow chart of the 353 participants in this study. Using a case-control design based on HF status, collagen metabolism markers were assessed in a sub-cohort of the CHS (N=880; 638 in 1992–1993 and 242 in 1996–1997) (19;20). For this case-control study, controls were frequency-matched at a 1:1 ratio based on sex and age (19). The cTnT levels were obtained for the full CHS cohort with sufficient sample volume from samples collected in 1989–1990, 1992–1993, and 1994–1995 (minority cohort only). For the 1992–1993 collection, i.e., when cTnT and collagen metabolism markers were collected simultaneously, 153 participants did not have remaining samples for the concurrent assessment of collagen metabolism markers and cTnT. Of the 485 patients with concurrent data for collagen metabolism markers and cTnT, 11 did not have a preceding cTnT measure (these were enrolled as part of the minority cohort) and 121 did not have sufficient sample left for baseline assessments (1989–1990), leaving 353 participants for the present study. Patient characteristics are shown in Table 1.

Figure 1.

Figure 1

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Flow chart of participants included in this study.

Table 1.

Participant Characteristics

Total
(N=353)		 Healthy
Control
(N=153)		 CVD Risk
Control
(N=99)		 Heart
Failure
(N=101)		 p
overall		 p
HF vs
CV-Risk
Controld
Age (years) 74 ± 6 75 ± 5 74 ± 6 74 ± 6 a a
Sex (female) 185 (52%) 83 (54%) 51 (52%) 51 (51%) a a
Race
  European Am 332 (94%) 144 (94%) 93 (94%) 95 (94%) 0.99 0.97
  African Am/Other 21 (6%) 9 (6%) 6 (6%) 6 (6%)
CAD 73 (21%) 0 (0%) 18 (18%) 55 (55%) <0.0001 <0.0001
Stroke 9 (3%) 0 (0%) 1 (1%) 8 (8%) <0.0001 0.018
Atrial Fibrillation 11 (3%) 0 (0%) 3 (3%) 8 (8%) 0.0002 0.13
HF at screening 54 (15%) 0 (0%) 0 (0%) 54 (54%) b b
LVEF (screening)
  45–55% 21 (6%) 5 (3%) 5 (5%) 11 (11%) <0.0001 <0.0001
  < 45% 22 (6%) 0 (0%) 2 (2%) 20 (20%)
NT-proBNP (pg/mL)c 123 (58–245) 96 (49–156) 96 (53–185) 261 (117–783) < 0.0001 < 0.0001
Systolic BP (mmHg) 131 ± 19 125 ± 16 137 ± 19 135 ± 21 <0.0001 0.40
Diastolic BP (mmHg) 69 ± 10 67 ± 9 72 ± 10 68 ± 12 <0.0001 0.011
Diabetes Mellitus 32 (9%) 0 (0%) 13 (13%) 19 (19%) <0.0001 0.27
Cholesterol (mg/dL) 207 ± 37 214 ± 37 207 ± 37 197 ± 36 0.0002 0.054
BMI (kg/m2) 26.1 ± 4.4 24.9 ± 3.7 26.8 ± 4.9 27.1 ± 4.7 <0.0001 0.62
Smoking status (current) 28 (8%) 12 (8%) 6 (6%) 10 (10%) 0.60 0.32
GFR (mL/min/1.73 m2) 78 ± 25 80 ± 23 78 ± 22 73 ± 29 <0.0001 0.15
CRP (mg/L)c 2.19 (0.96–4.01) 1.55 (0.78–3.18) 2.46 (1.11–4.01) 3.25 (1.65–6.00) <0.0001 0.013
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a

= no p-value, matching variable

b

= no p-value, selection variable

c

= median and IQR; statistical analyses based on ln-transformed data

d

= p based on t-test or Chi as appropriate

Data are values obtained at baseline (1989–1990).

All clinical and biochemistry measures were obtained at the same evaluation visit for each patient when collagen metabolism markers and cTnT were assessed (i.e., 1992–1993) to ensure simultaneous assessments of collagen metabolism markers, cTnT and covariates. Issues concerning the stability of the collagen metabolism markers and cTnT related to long-duration sample storage are described below (see also (21) (22)).

The presence of HF was determined by expert adjudication of clinical records as described previously (23). In brief, self-report of a physician diagnosis of HF was followed by confirmational review of the participant’s medical records. HF was defined as present if a diagnosis of congestive HF by a physician and treatment of HF were documented (i.e., current prescription for a diuretic agent and either digitalis or a vasodilator). In addition, symptoms, signs and chest X-ray findings of congestive HF were reviewed by the CHS Events Committee. Congestive HF was termed “definite” if the medical record data were complete or non-ambiguous. Patients who had an adjudicated HF diagnosis and with available biochemistry data for fibrosis markers and repeated cTnT (N=101) were compared to two control groups: (1) controls with cardiovascular disease risk factors but without HF (N=99); and (2) healthy controls without HF, coronary heart disease (CHD), hypertension, diabetes mellitus, or hypercholesterolemia in 1992–1993 (N=153)..

Blood chemistry

Phlebotomy methods, blood processing, and handling of samples have been described previously (24;25). Aliquots were frozen at −70°C until analysis for collagen metabolism, cTnT and other biological measures. Collagen metabolism markers were analyzed in 2005 at the University of Vermont (19) and cTnT assays were conducted in 2010 at the University of Maryland (8). Technologists were blind to participants’ clinical status and other biochemical data.

Collagen metabolism markers

Serum CITP was measured using a radioimmunoassay from Orion Diagnostica. Inter-assay and intra-assay variability are 3.5–9.5% and 5.6–9.0%, respectively, and the lower detection limit is 0.4 µg/L.

Serum PIIINP was determined by a coated-tube radioimmunoassay, as described previously by Risteli and colleagues (26), using commercial antisera specifically directed against the terminal amino terminal peptide (Orion Diagnostica, Finland). The inter-assay and intra-assay variations for determining PIIIP are < 6%, and the lower detection limit is 1.5 ng/mL.

Procollagen type 1 terminal peptide (PIP) was measured using enzyme immunoassay (Takara Mirus Bio Inc., Madison, WI). The assay range is 10 – 640 ng/ml with a lower detection limit of 10 ng/ml. Intra-assay and inter-assay CVs range from 4.5–7.4% and 4.3–6.3%, respectively.

Stability of the collagen metabolism assays was determined by comparing levels of controls obtained in 1992–1993 versus controls assessed in 1996–1997, adjusting for age. Analysis of covariance indicated that the age-adjusted mean levels were stable for all three markers (PIP = 406.06 ± 14.44 ng/mL vs. 419.34 ± 15.59 ng/mL p = 0.24; CITP 5.09 ± 0.25 µg/L vs. 5.02 ± 0.30 µg/L, p = 0.79; and PIIINP 3.93 ± 0.15 µg/mL vs. 4.35 ± 0.18 µg/mL, p = 0.11, for 1992–1993 vs. 1996–1997, respectively).

Cardiac Troponin

Measurements were performed on serum using highly sensitive cTnT reagents on an Elecsys 2010 analyzer (Roche Diagnostics, Indianapolis, Indiana) as described previously (8). The analytical measurement range is 3 to 10 000 pg/mL, with the 99th percentile cut-off from a healthy reference population (n=616) is 13.5 pg/mL and the 10% inter-assay coefficient of variation concentration close to or less than the 99th percentile of the reference population (7). The assay is stable over time, with an estimated degradation rate of 0.36 ng/L per year (22). In the present study, we compared the cTnT levels at baseline (1989–1990) and three years later (1992–1993) in the subgroup of healthy participants (N=153; time delays of 20–21 and 17–18 years, respectively). There was no significant difference in cTnT levels over this three-year period (median change = 0.00, IQR = −1.12 – 2.66 pg/mL; age-adjusted cTnT levels were 6.90, 95% CI = 5.63–8.16 pg/mL and 7.07, 95% CI = 6.23–7.91 pg/mL, p = 0.847 based on analysis of covariance).

Inflammation

High sensitivity C-reactive protein (CRP) was assessed with an ultra-sensitive enzyme-linked immunosorbent assay using purified protein and polyclonal anti-CRP antibodies (27) with a inter-assay coefficient of variation of < 5%.

Covariates

Clinical variables included cardiovascular risk factors (hypertension, diabetes mellitus, smoking status, physical activity levels, and body mass index), history of coronary heart disease (CHD, defined as myocardial infarction, history of revascularization, or angina), and echocardiographically determined left ventricular ejection fraction (LVEF) and LV mass. Other disease-related covariates included osteoarthritis and arthritis, history of stroke and obstructive peripheral artery disease because these conditions are associated with elevated collagen metabolism markers (clinically significant liver and pulmonary disease were used as exclusion criteria because these conditions substantially influence collagen metabolism marker assays). Prevalent disease status was updated for the 1992–1993 visit based on adjudicated incident events throughout the study.

Echocardiograms were used to determine systolic and diastolic measures and were analyzed at a central core echocardiography laboratory (JSG). Qualitative LVEF was estimated based on echocardiographic data obtained either at the baseline CHS examination or at the point of care as abstracted from clinical records.

Co-variates based on blood chemistry included total cholesterol, HDL and LDL, creatinine (to calculate eGFR), and N-terminal pro-type B natriuretic peptide (NT-proBNP) as described previously (24;25) (28).

Statistical analyses

Data are presented as mean ± standard deviation for continuous variables, median and inter-quartile range (IQR) for biochemistry measures, and percentages for categorical variables. The three groups of participants (healthy controls, controls with cardiovascular disease risk factors and HF patients) were compared using analysis of variance for continuous data with logarithmic transformations for non-normally distributed variables, non-parametric Kruskal-Wallis test for cTnT (to handle the participants with below-detection rate values, set at 2.99 pg/mL), or Chi-square tests for categorical variables.

Associations between cTnT and myocardial collagen metabolism markers were examined using non-parametric correlation coefficients (Spearman’s rho). Multivariable models were then used to examine whether association between cTnT and collagen metabolism markers remained significant when adjusting for covariates obtained at the same time-point (1992–1993). A hierarchical approach was used, examining the role of three covariate sets: (1) demographics (age, sex, race [black vs. other] and group status (HF, control with traditional cardiovascular risk factors, healthy control)); (2) traditional cardiovascular risk factors were selected from validated risk scores for cardiovascular mortality (29): history of coronary heart disease, systolic and diastolic blood pressure, use of antihypertensive medications, diabetes, smoking, and total and high density lipoprotein cholesterol; and (3) inflammation (CRP). Participants were divided into three categories of incremental cTnT concentration based on tertiles, (<3.00 – 4.75 pg/mL; ≥4.75 – <11.10 pg/mL; and ≥ 11.10 pg/mL) and analysis of variance were then used to compare cTnT-based groups on collagen metabolism markers. The group (HF, control with CV risk factors, healthy control) × cTnT level (per tertile) interaction term was used to determine whether associations between cTnT with collagen metabolism markers differed across groups.

Change in cTnT concentration was considered using continuous scores and based on a ≥ 50% increase in cTnT from baseline (1989–1990) to follow-up (1992–1993). Those with ≥ 50% relative increase in cTnT were compared with those with longitudinal change of < 50% with regard to collagen metabolism markers levels, adjusting for baseline cTnT and for the risk factors described above. The choice of a ≥ 50% relative change threshold was specified a priori based on a prior study of short-term change in cardiac troponin I (measured with a highly sensitive assay) in healthy adults (30). At baseline 94/353 had cTnT values below detection (<3.0 pg/mL); for change scores these were set at 2.99 pg/mL. Analyses were repeated while excluding participants with undetectable levels, which revealed the same results (data not shown).

Because biological correlates of systolic HF may differ from HF with preserved ejection fraction (HF-PEF), subgroup analyses were performed for these two subgroups. Data were analyzed using STATA and SPSS/PASW. A p-value of < 0.05 was used to indicate statistical significance.

Results

Participant characteristics

Table 1 presents participant characteristics. Age and sex distributions were comparable across the HF and control groups, reflecting successful matching procedures. HF patients differed from the control group with cardiovascular risk factors on the following measures: history of coronary artery disease, stroke, LV ejection fraction, NT-proBNP and CRP. Among patients with HF, 54/101 (54%) had HF at study entry and 57 (56%) developed HF between baseline assessment (1989–1990) and measurement of collagen metabolism at follow-up (1992–1993).

Patients with HF had significantly higher CITP, PIIINP but not PIP levels than controls, as documented previously (19). The cTnT levels were also higher in HF patients than controls. The two control groups did not differ on collagen metabolism markers (p-values > 0.20), whereas cTnT levels were higher in controls with risk factors vs. healthy controls (p=0.004).

Associations between cTnT and collagen metabolism markers

Significant cross-sectional associations (collected in 1992–1993) were found between cTnT and the collagen metabolism markers CITP and PIIINP, but not PIP (Table 2).

Table 2.

Association between baseline cTnT and collagen metabolism markers

Total Healthy
Control		 CVD Risk
Control		 HF
CITP 0.35** 0.15 0.32** 0.48**
PIIINP 0.31** 0.17* 0.25* 0.34**
PIP −0.03 −0.04 0.05 −0.03
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*

= p < 0.05;

**

= p < 0.01.

Correlations are Spearman non-parametric correlations

Collagen metabolism and cTnT data were derived from samples obtained at the same blood collection time-point (1992–1993)

The collagen metabolism markers (CITP and PIIINP) were correlated with selected demographic and clinical measures (most consistently with older age, lower total cholesterol, lower HDL, and higher CRP) and cTnT with older age, male sex, diabetes, lower cholesterol and lower HDL). Multivariable regression analyses showed that cTnT was significantly associated with CITP (β=0.35, p<0.001) and PIIINP (β=0.22, p=0.003), but not PIP (β=−0.03, p=0.73), adjusting for age, sex, race, HF/control status, coronary heart disease, systolic and diastolic blood pressure, antihypertensive medication use, diabetes, smoking status, total cholesterol, HDL, and CRP (overall model R2 = 0.23, 0.15, and 0.09, respectively).

The addition of CRP did not significantly change the model (ΔR2 < 0.05; p > 0.10). The correlations between CRP levels with collagen metabolism markers or cTnT were also non-significant (r-values < 0.10), suggesting that inflammation does not play a primary role in the association between cTnT and collagen metabolism markers.

When examining tertiles of cTnT, the pattern of results was similar with significant main effects for CITP (p<0.001) and PIIINP (p<0.001), but not PIP (p=0.40). Consistent with the analyses of continuous collagen metabolism marker levels, associations with cTnT tended to be stronger in HF patients than controls as shown in Figure 2 (pinteraction=0.061 for CITP and pinteraction=0.092 for PIIINP).

Figure 2.

Figure 2

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Association between level of cTnT (in tertiles) and concurrent levels of collagen metabolism markers. Data are presented separately for healthy controls, controls with cardiovascular risk factors, and patients with heart failure. Panel A = CITP, Panel B = PIIINP and Panel C = PIP. * = p < 0.05 compared to lowest tertile.

Longitudinal changes in cTnT over three years as predictor of collagen metabolism markers

The median cTnT increase (Δ) from baseline (1989–1990) to follow-up (1992–1993) was 1.16 (IQR=−0.85 – 4.24 pg/mL) for the complete sample. Increases were higher in HF patients (Δ=3.10 (IQR=0.23–13.05; p<0.001) than controls (healthy controls Δ=0.00 (IQR=−1.12 – 2.66 pg/mL); controls with cardiovascular risk factors Δ=1.22 (IQR=−1.30 – 4.33 pg/mL)). Of the 94 participants with below-detectable cTnT levels (< 3.00 pg/mL) at baseline, 43 (46%) continued to have undetectable levels at follow-up, an increase in cTnT > 50% was observed in 120 (34%) of the participants, of whom 51 (43%) had initially undetectable cTnT levels. The prevalence of ≥ 50% increase in cTnT was more common in HF than controls (healthy controls 28%, controls with cardiovascular risk factors 33%, and HF 44%; p=0.039).

As shown in Table 3, the increase in cTnT from baseline to 3 years follow-up was significantly associated with higher levels of collagen metabolism markers at follow-up. Furthermore, an increase of 50% or more was associated with higher CITP and PIIINP levels at follow-up (CITP p=0.006; PIIINP p=0.029; PIP p=0.75). As shown in Figure 3, the predictive value of a ≥ 50% increase in cTnT was stronger in HF patients then in controls for CITP (pinteraction=0.050) and PIIINP (pinteraction=0.011), but not PIP (pinteraction=0.61).

Table 3.

Associations between increases in cTnT with collagen metabolism markers

Total Healthy
Control		 CVD Risk
Control		 HF
CITP 0.21** −0.04 0.11 0.42**
PIIINP 0.14** −0.11 0.11 0.27**
PIP 0.07 0.12 −0.04 0.14
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*

= p < 0.05;

**

= p < 0.01.

Correlations are Spearman non-parametric correlations

Collagen metabolism markers from samples collected at follow-up (1992–1993)

Δ cTnT from samples collected at baseline (1989–1990) and follow-up (1992–1993). Positive correlations indicate that an increase in cTnT was associated with higher collagen metabolism marker levels.

Figure 3.

Figure 3

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Association between increases in cTnT over 3 years and collagen metabolism marker levels at follow-up. Data are presented separately for healthy controls, controls with cardiovascular risk factors, and patients with heart failure. * = p < 0.05 comparison between individuals with a ≥ 50% increase in cTnT vs. < 50% increase in cTnT.

Multivariable analyses indicated that increases in cTnT were independently predictive of CITP (β=0.23, p<0.001) adjusting for demographic and biomedical covariates including baseline cTnT (multivariable model R2 = 0.23). Increases in cTnT were also independently predictive of PIIINP in multivariable analyses (β=0.12, p=0.030), adjusting for covariates (multivariable model R2 = 0.17), whereas adjusted models for PIP did not show significant associations with Δ cTnT (β=0.03, p=0.67; multivariable model R2 = 0.15).

Subgroup analyses based on HF status revealed similar results for patients with systolic HF vs. HF-PEF, with significant correlations for concurrent cTnT as well as changes in cTnT as related to CITP (p values < 0.01). PIIINP was associated with concurrent cTnT (p=0.033) and Δ cTnT (p=0.015) in HF-PEF and only with concurrent cTnT (p=0.033) but not Δ cTnT (p=0.48) in systolic HF. Associations for PIP remained non-significant in these subgroup analyses.

Discussion

This study shows that myocardial injury at the micro level are associated with pathophysiological processes that are critically involved in tissue repair and fibrosis. Specifically, higher levels of cTnT, a high-sensitive marker of myocardial damage, were associated with collagen deposition. Moreover, increases in cTnT over time are related to higher levels of two primary collagen metabolism markers, CITP and PIIIINP, and these associations were independent of cardiovascular risk factors. This study also indicates that associations between myocardial tissue damage at the micro level and dysregulated collagen metabolism are stronger in patients with HF than in controls without HF.

Myocardial injury from ischemia, physical damage, infections, or biochemical origins may result in cell death and scar. Serum measures of cTnT reflect these micro-injury-related processes and previous research from our group has demonstrated that longitudinal increases in cTnT are predictive of incident HF and mortality in individuals aged ≥ 65 and above (8). The biological processes involved in tissue repair involve collagen production and collagen deposition. These processes play an essential role in myocardial fibrosis and subsequent cardiac remodelling leading to HF (9–12). Recent studies also report the prognostic value of myocardial fibrosis identified by cardiac magnetic resonance imaging in both ischemic and non-ischemic cardiomyopathy (31;32). The present study showed that cTnT is cross-sectionally associated with elevated CITP and PIIINP levels, and in addition that increases in cTnT over a three-year period independently predict higher levels of these collagen metabolism markers at follow-up.

Associations between cTnT and collagen metabolism markers were significant for CITP and PIIINP, but not PIP. This finding seems at variance with studies demonstrating a specific association between PIP and HF (11;16;33;34). Although, histological evidence suggests that serum PIP reflects myocardial fibrosis in heart failure (16), evidence also indicates that PIP is also elevated in other clinical conditions such as liver disease (35) and osteoporosis (36). Furthermore,, other studies have not found significant associations between PIP with prevalent HF (12;15) and a prior report based on this cohort have also indicated that PIP was not significantly related to HF (19). PIP is a marker of type I collagen synthesis and plays an essential role in the balance between collagen deposition and degradation. One explanation of the lack of association between cTnT with PIP is that CITP and PIIINP are better indicators of dysregulation of the collagen deposition process, whereas PIP reflects the initial synthesis process that may not be dysfunctional in HF. It is possible that type I collagen destruction exceeds its synthesis or that a shift from type I to type III collagen synthesis develops over time, Other possible explanations include assay-related issues or a plateau of collagen type I synthesis in this particular study sample (all participants were ≥ 65 years of age).

Myocardial ischemia and neurohormonal activation (including the renin-agiotensin-aldosterone axis dysregulation and sympathetic nervous system activation) may lead to clinical HF (1–4). In addition, inflammation acts as a collagen synthesis stimulating factor and also results in excess deposition of collagen in the extracellular matrix of the myocardium and other tissues (37). The present data did not find significant correlations between elevated CRP levels with collagen metabolism markers or cTnT in cross-sectional and longitudinal analyses (r-values < 0.10). Metalloprotease activation can lead to fibrosis, both in chronic (9) as well as acute (38) conditions. However, CITP can also be released in response to collagen formation, and the net effect on interstitial collagen remains unknown. While MMPs are proteolytic enzymes that degrade collagen in extracellular matrix, MMP-9 also activates profibrotic pathways. Moreover, inflammation upregulates MMPs, and the remodelling of interstitium likely involves both collagen degradation and synthesis (37). The present paper indicates that it is likely that micro-injury plays a contributing role in the collagen metabolism and possibly fibrosis processes. Basic science, epidemiological and clinical intervention studies are needed to disentangle the relative importance of micro-injury on cardiac fibrosis, particularly as related to the pathophysiology of heart failure. Future longitudinal studies are also needed to identify the biological pathways including serial assessments of metalloproteases and TIMPs to identify the biological processes that precede myocardial dysfunction and clinical HF.

The prospective nature of this study is unique and a major strength of the design. However, a few limitations need to be considered. Collagen metabolism markers were obtained in a subset of the CHS cohort, with a focus on patients with HF. Controls were selected using frequency-based matching for age, sex, and race. This is a potential strength when comparing HF patients with controls, but this selection strategy may have introduced a biased control group which potentially interferes with generalizability. Examining myocardial injury and collagen metabolism markers in control groups without myocardial disease may need to a restriction of range related to the low-grade nature or absence of the target fibrosis-related pathophysiological processes. The study also did not use biopsies or MRI to directly measure cardiac fibrosis, which was not feasible in this population-based study. Another limitation is that the baseline assessments in the CHS do not include collagen metabolism markers, and simultaneous assessments of cTnT and collagen metabolism markers were only feasible in the 1992–1993 examination year. This study could therefore only examine whether changes in cTnT preceded increases in collagen metabolism markers whereas the possibility of ruling out a reverse pattern of associations remains to be examined.

The clinical implications of this study include the potential benefits of serial assessments of multiple biomarkers that reflect different components of the multifactorial disease processes in HF and other cardiovascular diseases. Assessments of cTnT may identify patients in whom the biology of collagen metabolism is dysregulated resulting in increased myocardial fibrosis. Myocardial fibrosis precedes increased ventricular stiffness which in turn may lead to poor cardiac contractility and clinical HF. Trials examining aldosterone antagonists support the role of fibrosis in HF as these agents in decrease collagen formation and improve clinical outcomes (39–41). Thus, serial assessments of cTnT combined with collagen metabolism markers may increase our understanding of the pathophysiological fibrotic processes involved in HF. Prospective studies are needed to determine whether the combined use of serial micro-injury and collagen metabolism markers are useful for patient risk stratification and future guidance for treatment strategies in targeted populations at risk of heart failure.

Clinical Impact.

Myocardial fibrosis results from dysregulated collagen metabolism and plays an important role in clinical systolic heart failure as well as heart failure with preserved left ventricular function. Micro-injury of the myocardium may predispose patients to developing myocardial fibrosis and subsequent clinical heart failure. Myocardial microinjury can now be accurately measured with high-sensitive troponin T (cTnT) assays. This study shows that increases in myocardial micro-injury are associated with subsequent dysregulated collagen metabolism during three years of follow-up. The findings further indicate that myocardial micro-injury is associated with elevated collagen metabolism in the absence of myocardial infarction. Serial assessments of cTnT and other biomarkers of heart failure biology are important to understand the underlying pathophysiological processes of this life threatening disease. Such serial assessments may also identify patients at risk of increased myocardial fibrosis and subsequent heart failure.

Interventions such as aldosterone antagonists may reduce collagen formation and hence reduce fibrosis and improve clinical heart failure outcomes.

Acknowledgments

Sources of Funding

The research reported in this article was supported by contracts N01-HC-85239, N01-HC-85079 through N01-HC-85086, N01-HC-35129, N01 HC-15103, N01 HC-55222, N01-HC-75150, N01-HC-45133, and grant R0-1 HL079376 and HL080295 from the National Heart, Lung, and Blood Institute (NHLBI), with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG-023629, AG-15928, AG-20098, and AG-027058 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm

Disclosures

There are no relationships with industry for Drs. Kop, Gottdiener, Barasch and Jenny. Dr. deFilippi receives research grant support (>$10,000) and honorarium/consulting fees (>$10,000) from Siemens, Roche Diagnostics, BG Medicine, and Critical Diagnostics. Dr. Seliger received a research grant from Roche, Inc.

Dr. Christenson reports that funding from Roche Diagnostics, Siemens Medical Diagnostics and Response Biomedical.

Footnotes

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