Effect of Serum Carboxyl-Terminal Telopeptide of Type I Collagen on Clinical Outcomes in Patients With Coronary Artery Disease

Yoichiro Otaki; Tetsu Watanabe; Hiroe Ono; Takafumi Mito; Junya Sato; Tomonori Aono; Jun Goto; Taku Shikama; Daisuke Kinoshita; Masahiro Wanezaki; Shigehiko Kato; Harutoshi Tamura; Satoshi Nishiyama; Takanori Arimoto; Masafumi Watanabe

doi:10.1253/circj.CJ-25-0067

Abstract

Background: Coronary artery disease (CAD) is a major cause of mortality worldwide. Serum carboxyl-terminal telopeptide of type I collagen (CITP), a marker of collagen degradation in the heart and blood vessels, is associated with plaque vulnerability and cardiac remodeling in patients with acute myocardial infarction. However, the effect of CITP on the clinical outcomes of patients with CAD has not yet been elucidated.

Methods and Results: Serum CITP concentrations were measured in 621 consecutive patients with CAD. All patients were prospectively followed up for a median period of 1,554 days. The primary endpoint was a composite of hospitalization for heart failure or cardiovascular death; the secondary endpoints were all-cause death and heart failure rehospitalization. B-Type natriuretic peptide and the left ventricular mass index were higher in the highest CITP tertile group. Kaplan-Meier analysis demonstrated that the CAD patients in the highest CITP tertile group had the greatest risk of both primary and secondary endpoints, independent of acute or chronic coronary syndrome. Multivariate Cox proportional hazard regression analysis demonstrated that CITP was an independent predictor of both primary and secondary endpoints after adjusting for confounding risk factors, regardless of acute or chronic coronary syndrome.

Conclusions: The serum CITP concentration could be a feasible marker for clinical outcomes in patients with CAD.

Cardiovascular disease (CVD) is the leading cause of death worldwide. Coronary artery disease (CAD), which clinically manifests as acute coronary syndrome (ACS) and chronic coronary syndrome (CCS), is the most common cause of cardiovascular death, accounting for around 40% of all cardiovascular diseases.¹ Advances in percutaneous coronary intervention (PCI) procedures and medicine have improved clinical outcomes in CAD.²^,³ However, the mortality and incidence rate of heart failure (HF) in patients with CAD remain high.⁴ Thus, preventing future cardiovascular death and HF in patients with CAD undergoing PCI is of critical importance.

HF after cardiac injury develops through a complex mechanism.⁵ Cardiovascular fibrosis, a key feature of left ventricular (LV) remodeling in CAD, can have deleterious effects on cardiac structure and function, leading to HF.⁶ Markers of collagen turnover include markers of collagen synthesis and degradation. Thus, byproducts of collagen synthesis and degradation have been extensively investigated as markers of fibrosis.⁷ Serum carboxyl-terminal telopeptide of type I collagen (CITP) is a 12-kDa matrix metalloproteinase-induced collagen degradation product of type I collagen in the extracellular matrix of the heart, blood vessels, and bone. Therefore, CITP is a useful marker of collagen turnover and is representative of myocardial and vascular fibrosis. CITP levels reportedly do not differ between healthy controls and patients with stable angina, whereas CITP values in patients with ACS are higher than those in patients with stable angina and healthy controls.⁸ CITP levels have been reported to be positively related to the necrotic core area assessed by intravascular ultrasound in patients who underwent coronary angiography.⁹ Furthermore, serum CITP levels on admission have been shown to be related to extension of wall motion abnormality after acute myocardial infarction (AMI) independent of reperfusion.¹⁰ CITP levels have also been shown to be related to early and 6-month cardiac remodeling in patients with AMI undergoing reperfusion, indicating an association of CITP with plaque vulnerability and LV remodeling in patients with AMI.¹¹ One report indicated that CITP levels were associated with composite events and mortality at 1 year in patients with AMI.¹² However, the clinical significance of serum CITP levels has not yet been fully examined in patients with CAD.

This study examined whether serum CITP levels are associated with clinical outcomes in patients with CAD who underwent PCI.

Methods

Ethics Statement

All procedures were performed in accordance with the ethical, institutional, and/or national research committee guidelines of the centers at which the studies were conducted, and complied with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This study was approved by the Institutional Ethics Committee of Yamagata University School of Medicine. The first and updated IRB numbers are H20-62 and 2024-313, respectively.

Study Population

This prospective observational study is part of an ongoing Yamagata Cardiovascular and Cerebrovascular Prognosis Survey aimed at identifying the risk factors for poor clinical outcomes in patients with CAD. Starting in 2013, this survey examined the association between serum CITP levels and clinical outcomes. Serum CITP levels were measured early in the morning within 24 h of hospital admission after obtaining written informed consent. The exclusion criteria were malignant cancer with bone metastasis and active hepatic and lung diseases. All patients were prospectively followed up twice a year for 1,826 days, starting from the day after obtaining informed consent, using telephone or medical records.

The study population consisted of 621 patients with CAD who were admitted to Yamagata University Hospital for PCI. The sample size was estimated on the basis of the number of events required to adjust for confounding factors. ACS and CCS were diagnosed by 2 expert cardiologists according to the guidelines.²^,³^,¹³ PCI for CCS was performed in patients with angiographic stenosis >90% and in those showing angiographic stenosis >75% with evidence of ischemia assessed by myocardial scintigraphy or fractional flow reserve measurements. Successful revascularization was defined as Thrombolysis In Myocardial Infarction Grade 3 flow.

Transthoracic echocardiography was performed by physicians and sonographers who were blinded to biochemical data. LV ejection fraction (LVEF), LV end-diastolic diameter (LVEDD), LV mass index (LVMI), and the ratio of the mitral inflow E wave to the tissue Doppler e′ wave (E/e′ ratio) were measured. Clinical data, such as age, sex, traditional risk factors for CAD,¹⁴ medical history, and medication at discharge, were obtained from patients’ medical records and interviews

CITP and Cardiac Biomarker Measurement

Blood samples were collected in the early morning within 24 h of hospital admission. CITP levels were determined by radioimmunoassays, as reported previously,¹⁵ using a polyclonal antibody specifically directed against CITP (Orion Diagnostica, Finland).

B-Type natriuretic peptide (BNP) concentrations were measured in blood samples that were collected at the same time, preserved at 4℃, and centrifuged at 3200 r.p.m. for 7 min at 4℃. Plasma BNP concentrations were evaluated using a chemiluminescent immunoassay specific for human BNP (BNP-JP Abbott; Abbott Japan, Chiba, Japan).

High-sensitivity troponin T (hsTnT) and heart-type fatty acid-binding protein (H-FABP) concentrations were evaluated using the electrochemiluminescent immunoassay (ECLIA) method (Elecsystroponin-T; Roche Diagnostics, Tokyo, Japan) and a 2-step sandwich ELISA kit (MARKIT-M H-FABP; Dainippon Pharmaceutical Co. Ltd., Tokyo, Japan), respectively. High-sensitivity C-reactive protein (hsCRP) levels were measured simultaneously.

Cardiovascular Risk Factors

Hypertension was defined as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, or the use of antihypertensive medication. Diabetes was defined as fasting blood sugar levels ≥126 mg/dL, HbA1c levels ≥6.5%, or the use of antidiabetic medications. Dyslipidemia was defined as high-density lipoprotein cholesterol <40 mg/dL, low-density lipoprotein cholesterol ≥140 mg/dL, triglyceride ≥150 mg/dL, or the use of lipid-lowering medications.

The estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease equation with the Japanese coefficient, as reported previously.¹⁶ Chronic kidney disease (CKD) was defined as reduced eGFR (<60 mL/min/1.73 m²) or albuminuria. Severe CKD was defined as eGFR <30 mL/min/1.73 m² or hemodialysis. Hemoglobin levels were measured simultaneously, and anemia was defined as hemoglobin <13 g/dL in men and <12 g/dL in women, in accordance with the World Health Organization guidelines.

Thrombotic and Bleeding Risks

The components of the Coronary Revascularization Demonstrating Outcome Study in Kyoto Risk Score for thrombotic risk in patients who underwent PCI include age ≥75 years, chronic total coronary artery occlusion, diabetes, atrial fibrillation (AF), lower-extremity artery disease (LEAD), severe CKD, anemia, and HF.

Bleeding risk was assessed using the Japanese version of the high bleeding risk criteria according to the Japanese Circulation Society 2020 guideline recommendations.¹⁷ The primary criteria for the Japanese version of high bleeding risk include low body weight (men <55 kg, women <50 kg), LEAD, severe CKD, moderate-to-severe anemia (hemoglobin <11 g/dL), and HF.

Endpoints and Follow-up

All patients were prospectively followed up by telephone or by reviewing their medical records twice a year for a median period of 1,554 days (interquartile range [IQR] 695–1,826 days). The primary endpoints were HF-related events, defined as cardiovascular death and rehospitalization for HF. Secondary endpoints were all-cause death and rehospitalization for HF. In addition, we examined thrombotic events, such as target vessel revascularization, target vessel ACS, non-target vessel ACS, and bleeding events defined by the Bleeding Academic Research Consortiums 3 and 5.

Statistical Analysis

The normality of the distribution of continuous variables was confirmed using the Shapiro-Wilk test. Normally distributed continuous variables are presented as the mean±SD, whereas skewed variables are presented as the median with IQR. Categorical variables are presented as numbers and percentages. Continuous and categorical variables were compared using t-tests and the χ² test , respectively. The significance of differences among groups was analyzed using analysis of variance with Tukey’s post hoc test. Because CITP, BNP, hsTnT, H-FABP, and hsCRP data were not normally distributed, the significance of differences among groups was analyzed using the Steel-Dwass test.

Receiver operating characteristic curves for primary and secondary endpoints were plotted and used to measure the predictive accuracy of CITP, BNP, hsTnT, and H-FABP levels. C-indices for each cardiac biomarker were compared to the other biomarkers in all patients, patients with ACS, and those with CCS. Survival curves were constructed using the Kaplan-Meier method and compared using the log-rank test. Because of non-normal data distribution, we used log₁₀-transformed CITP, BNP, hsTnT, H-FABP, and hsCRP values for Cox proportional hazard regression analyses. Cox proportional hazard regression analysis was used to determine independent predictors of primary and secondary endpoints. Multicollinearity was assessed using the variance inflation factor. Multivariate Cox proportional hazard regression analysis of Models 1, 6, and 7 was performed in a stepwise manner. Multivariate Cox proportional hazard regression Models 2, 3, 4, and 5 were adjusted for cardiovascular risk factors, coronary status, thrombotic risk factors, and bleeding risk factors, respectively.

Statistical significance was set at P<0.05. All statistical analyses were performed using a standard software package (JMP Pro Version 16.1.0 [SAS Institute, Cary, NC, USA]; R 3.0.2, with additional packages, including Rcmdr, Epi, and pROC).

Results

Baseline Characteristics of CAD Patients and Comparisons of Clinical Characteristics According to CITP Tertile

Baseline characteristics of the 621 patients are presented in Table 1. The mean patient age was 70 years, and 78% of patients were men. The study population included 260 patients with ACS and 361 with CCS. Multivessel disease was identified in 236 (38%) patients. PCI was performed in all patients, with a success rate of 97%. Hypertension, diabetes, dyslipidemia, a family history of CAD, and current smoking status were identified in 449 (72%), 262 (42%), 318 (51%), 105 (17%), and 166 (27%) patients, respectively. The median serum CITP level was 5.4 ng/mL.

Table 1.

Baseline Characteristics in All Patients and Comparisons of Baseline Clinical Characteristics Among CITP Tertiles in Patients With CAD

	All patients (n=621)	CITP tertile
	All patients (n=621)	T1 (CITP ≤4.5 ng/mL; n=212)	T2 (CITP 4.6–6.4 ng/mL; n=204)	T3 (CITP ≥6.5 ng/mL; n=205)
Age (years)	70±11	67±10	70±12*	73±10*^,†
Men/women (n)	483/138	170/42	162/42	151/54
ACS/CCS (n)	260/361	83/129	84/120	93/112
Multivessel disease	236 (38)	75 (35)	81 (40)	80 (39)
Main culprit lesion (n)
LMT/LAD/LCX/RCA/others	21/284/121/190/5	5/96/41/70/0	9/97/30/67/1	7/91/50/53/4
Lesion type (n)
A/B/C	137/335/149	59/105/48	40/117/47	38/113/54
Successful revascularization	605 (97)	208 (98)	197 (97)	200 (97)
Stent implantation	589 (95)	203 (96)	193 (95)	193 (94)
IVUS use	601 (97)	206 (97)	188 (97)	197 (96)
Prior PCI	130 (21)	36 (17)	48 (24)	46 (22)
Prior MI	97 (16)	25 (12)	35 (17)	37 (18)
Hypertension	449 (72)	136 (64)	152 (75)	161 (79)^‡
Diabetes	262 (42)	86 (41)	84 (41)	92 (45)
Dyslipidemia	318 (51)	114 (54)	118 (58)	86 (42)^‡
Family history of CAD	105 (17)	48 (23)	34 (17)	23 (11)^‡
Smoking (n)
Current/past/non-smoker	166/200/255	63/67/82	54/77/73	49/56/100
Low body weight	151 (24)	39 (18)	40 (20)	72 (35)^‡
Atrial fibrillation	101 (16)	28 (13)	27 (13)	46 (22)^‡
Prior LEAD	89 (14)	22 (10)	27 (13)	40 (20)^‡
Severe CKD	42 (6.8)	0 (0)	1 (0.5)	41 (20)^‡
CKD	232 (37)	38 (18)	70 (34)	124 (60)^‡
Anemia	294 (47)	91 (29)	88 (43)	145 (71)^‡
Prior HF	95 (15)	6 (3)	29 (14)	60 (29)^‡
Biochemical data
CITP (ng/mL)	5.4 [4.1–7.7]	3.7 [3.1–4.1]	5.4 [4.9–5.9]	9.7 [7.7–14.7]
BNP (pg/mL)	64 [25–186]	36 [17–87]	62 [23–148]*	134 [51–473]*^,†
hsTnT (ng/mL)	0.034 [0.012–1.105]	0.015 [0.008–0.846]	0.025 [0.013–1.130]*	0.091 [0.020–1.488]*^,†
H-FABP (ng/mL)	5.4 [3.4–12.4]	4.0 [2.7–8.25]	5.0 [3.3–8.9]*	7.3 [4.6–35.6]*^,†
eGFR (mL/min/1.73 m²)	72±24	87±19	74±20*	55±32*^,†
Hemoglobin (g/dL)	12.7±1.8	13.5±1.6	13.0±1.8*	11.6±2.0*^,†
hsCRP (pg/mL)	0.190 [0.055–1.020]	0.100 [0.039–0.542]	0.174 [0.052–0.844]*	0.527 [0.117–1.020]*^,†
Echocardiogram
Left atrial diameter (mm)	39±6	38±5	39±6	40±7*
LVEF (%)	60±13	62±12	60±13	59±15*
LVEDD (mm)	48±6	48±5	49±7	49±8
LVMI (g/m²)	153±41	146±34	152±40	163±48*^,†
E/e′ ratio	12.3±5.7	10.9±4.3	12.7±5.7*	13.6±6.7*
Medication at discharge
Aspirin	606 (98)	210 (99)	200 (98)	196 (96)
P2Y₁₂ inhibitors	596 (96)	205 (97)	201 (99)	190 (93)^‡
OACs or warfarin	108 (17)	29 (14)	38 (19)	41 (20)
Statins	519 (84)	194 (92)	170 (83)	155 (76)^‡
ACEi/ARBs	449 (72)	147 (69)	157 (77)	145 (71)
β-blockers	328 (53)	100 (47)	113 (55)	115 (56)
MRAs	54 (9)	5 (2)	21 (10)	28 (14)^‡
Diuretics	78 (13)	7 (3.3)	23 (11)	48 (23)^‡
Clinical outcomes
Target vessel revascularization	26 (4.2)	7 (3.3)	8 (3.9)	11 (5.4)
Target vessel ACS	5 (0.8)	2 (0.9)	1 (0.5)	2 (1)
Non-target vessel ACS	9 (1.5)	3 (1.4)	5 (2.5)	1 (0.5)
Bleeding events	24 (3.8)	7 (3.3)	9 (4.4)	8 (3.9)

Unless indicated otherwise, data are expressed as the mean±SD, n (%), or median [interquartile range]. *P<0.05 compared with Tertile (T) 1; ^†P<0.05 compared with T2 (analysis of variance with Tukey-Kramer test); ^‡P<0.05 compared with T1 (Chi-squared test). ACEi, angiotensin-converting enzyme inhibitor; ACS, acute coronary syndrome; ARBs, angiotensin II receptor blockers; BNP, B-type natriuretic peptide; CAD, coronary artery disease; CCS, chronic coronary syndrome; CITP, carboxyl-terminal telopeptide of type I collagen; CKD, chronic kidney disease; E/e′ ratio, the ratio of the mitral inflow E wave to the tissue Doppler e′ wave; eGFR, estimated glomerular filtration rate; H-FABP, heart-type fatty acid-binding protein; HF, heart failure; hsCRP, high-sensitivity C-reactive protein; hsTnT, high-sensitivity troponin T; IVUS, intravascular ultrasound; LAD, left anterior descending artery; LCX, left circumflex artery; LEAD, lower extremity artery disease; LMT, left main trunk; LVEDD, left ventricular end-diastolic dimension; LVEF, left ventricular ejection fraction; LVMI, left ventricular mass index; MI, myocardial infarction; MRA, mineralocorticoid receptor antagonists; OAC, oral anticoagulant; PCI, percutaneous coronary intervention; RCA, right coronary artery.

As shown in Figure 1, patients were divided into 3 CITP tertiles: T1, CITP ≤4.5 ng/mL (n=212); T2, CITP, 4.6–6.4 ng/mL (n=204); and T3, CITP ≥6.5 ng/mL (n=205). As indicated in Table 1, patients in T3 were older, had a higher prevalence of hypertension, low body weight, AF, prior LEAD, severe CKD, anemia, and prior HF, and a lower prevalence of dyslipidemia and a family history of CAD than patients in T1 and T2. Patients in T3 had higher BNP, hsTnT, H-FABP, hsCRP, and LVMI concentrations, and lower eGFR and hemoglobin levels than patients in T1 and T2. Echocardiograms showed higher left atrial diameter, LVEDD, and E/e′ ratio and lower LVEF in T3 compared with T1. There were no significant differences in target vessel revascularization, target vessel ACS, non-target ACS, and bleeding events among the 3 groups. Patients in T3 had significantly higher BNP and LVMI independent of clinical presentation. Notably, BNP, hsTnT, and H-FABP levels increased with increasing CITP tertile in patients with CCS (Figure 2).

Figure 1.

Flowchart of the study selection process. After patients had been grouped according to carboxyl-terminal telopeptide of type I collagen (CITP) tertile (T1–T3), they were followed up for a median of 1,554 days (interquartile range 695–1,826 days). ACS, acute coronary syndrome; BNP, B-type natriuretic peptide; CCS, chronic coronary syndrome; H-FABP, heart-type fatty acid-binding protein; hsTnT, high-sensitivity troponin T; PCI, percutaneous coronary intervention.

Figure 2.

Differences in cardiac biomarker levels and the left ventricular mass index (LVMI) according to carboxyl-terminal telopeptide of type I collagen (CITP) tertile (T1–T3) in patients with (A–D) acute coronary syndrome and (E–H) chronic coronary syndrome. For cardiac biomarkers, the boxes show the interquartile range, with the median value indicated by the horizontal line; whiskers show the range. LVMI data are given as the mean±SD. *P<0.05 compared with T1; ^†P<0.05 compared with T2. BNP, B-type natriuretic peptide; H-FABP, heart-type fatty acid-binding protein; hsTnT, high-sensitivity troponin T.

Because CITP levels reportedly differ by clinical presentation,⁸ we compared the levels of cardiac biomarkers between patients with ACS and those with CCS. BNP, hsTnT, and H-FABP levels were significantly higher in patients with ACS than in those with CCS (Supplementary Figure 1A–C). In contrast, CITP levels did not differ significantly between patients with ACS and those with CCS (Supplementary Figure 1D). Serum CITP levels were significantly higher in patients with than without myocardial injury (Supplementary Figure 1E,F). We also compared serum CITP concentrations according to the presence of hypertension, AF, LEAD, severe CKD, and prior HF. Serum CITP concentrations increased in the presence of these conditions (Supplementary Figure 2).

CITP and Clinical Outcomes

During the study period, there were 81 HF-related events, 45 all-cause deaths, and 69 HF rehospitalizations. To compare the prognostic capacity of CITP levels with that of cardiac biomarkers, we created receiver operating characteristic curves for HF-related events. As shown in Supplementary Figure 3 and Table 2, the C-indices of CITP levels for predicting the primary and HF rehospitalization endpoints were significantly greater than those of hsTnT levels, but not those of BNP or H-FABP levels, in all patients and in those with ACS. Interestingly, abnormal cut-off values in cardiac biomarkers differed according to setting, such as ACS and CCS, and the cut-off CITP values were similar between patients with ACS and those with CCS (Table 2).

Table 2.

C-Indices for Primary and Secondary Endpoints in Patients With CAD

	All patients		ACS		CCS
	C index	Cut-off value	C index	Cut-off value	C index	Cut-off value
Primary endpoint^A
CITP	0.759* (0.709–8.110)	6.4 ng/mL	0.764* (0.683–0.846)	6.4 ng/mL	0.759 (0.694–0.824)	5.2 ng/mL
BNP	0.774* (0.717–0.829)	265 pg/mL	0.764* (0.675–0.852)	147 pg/mL	0.782 (0.709–0.855)	99.5 pg/mL
hsTnT	0.614 (0.558–0.675)	0.015 ng/mL	0.544 (0.451–0.636)	0.679 ng/mL	0.699 (0.615–0.778)	0.012 ng/mL
H-FABP	0.693* (0.635–0.752)	4.9 ng/mL	0.691* (0.601–0.783)	34.4 ng/mL	0.707 (0.627–0.788)	4.7 ng/mL
Secondary endpoints
All-cause death
CITP	0.669 (0.583–0.756)	6.4 ng/mL	0.692* (0.565–0.819)	8.4 ng/mL	0.646 (0.528–0.764)	6.4 ng/mL
BNP	0.646 (0.562–0.728)	79.8 pg/mL	0.643 (0.521–0.764)	133.2 pg/mL	0.623 (0.500–0.746)	46 pg/mL
hsTnT	0.622 (0.555–0.700)	0.025 ng/mL	0.516 (0.407–0.625)	0.202 ng/mL	0.684 (0.565–0.802)	0.025 ng/mL
H-FABP	0.621 (0.535–0.708)	7.8 ng/mL	0.569 (0.570–0.698)	18.7 ng/mL	0.643 (0.512–0.773)	7.3 ng/mL
HF rehospitalization
CITP	0.761*^,† (0.709–0.814)	5.1 ng/mL	0.770*^,† (0.687–0.852)	6.3 ng/mL	0.758 (0.689–0.827)	5.1 ng/mL
BNP	0.784*^,† (0.726–0.843)	263 pg/mL	0.786*^,† (0.696–0.877)	273 pg/mL	0.793 (0.718–0.868)	261 pg/mL
hsTnT	0.589 (0.527–0.650)	0.014 ng/mL	0.515 (0.419–0.612)	2.39 ng/mL	0.691 (0.603–0.779)	0.011 ng/mL
H-FABP	0.655* (0.592–0.718)	4.8 ng/mL	0.610 (0.509–0.710)	4.8 ng/mL	0.695 (0.608–0.782)	4.6 ng/mL

^AThe primary endpoint was a composite of hospitalization for HF or cardiovascular death. *P<0.05 compared with hsTnT; ^†P<0.05 compared with H-FABP. Abbreviations as in Table 1.

Kaplan-Meier analysis revealed that among the CITP tertiles, T3 had the greatest risk of primary and secondary endpoints (Figure 3A–C). Similar results were obtained in subgroup analyses of patients with ACS (Figure 3D–F) and CCS (Figure 3G–I).

Figure 3.

Kaplan-Meier analysis for primary and secondary endpoints according to carboxyl-terminal telopeptide of type I collagen (CITP) tertile (T1–T3) in all patients (A–C) and in patients with acute coronary syndrome (D–F) and chronic coronary syndrome (G–I) separately. The primary endpoint was a composite of hospitalization for heart failure (HF) or cardiovascular death.

Univariate and multivariate Cox proportional hazard regression analyses were performed to determine the risk of the primary event. Univariate Cox proportional hazard regression analysis revealed that CITP level was significantly associated with HF-related events. Furthermore, age, multivessel disease, left main trunk and left anterior descending artery lesion, diabetes, low body weight, AF, prior LEAD, severe CKD, anemia, prior HF, BNP, hsTnT, H-FABP, hsCRP, eGFR, hemoglobin, left atrial diameter, LVEF, LVEDD, LVMI, and the E/e′ ratio were associated with the primary event (Table 3). Multivariate Cox proportional hazards regression analysis demonstrated that CITP level was an independent predictor of the primary event after adjusting for confounding factors (Table 4). Similarly, among the CITP tertiles, T3 had the greatest risk for the primary endpoint in the multivariate Cox proportional hazard regression analysis (Table 4). This association was maintained in the subgroups analyses of patients with ACS or CCS (Figure 4).

Table 3.

Univariate Cox Proportional Hazard Regression Analyses for Primary and Secondary Endpoints in Patients With CAD

	Primary endpoint^A		All-cause death		HF rehospitalization
	HR (95% CI)	P value	HR (95% CI)	P value	HR (95% CI)	P value
Age	1.03 (1.01–1.05)	0.0084	1.05 (1.02–1.08)	0.0024	1.04 (1.01–1.06)	0.0025
Male vs. female sex	1.23 (0.72–2.22)	0.4676	0.68 (0.37–1.38)	0.2626	1.10 (0.63–2.05)	0.7595
ACS/CCS	1.29 (0.83–1.99)	0.2608	1.81 (1.01–3.29)	0.0484	1.12 (0.69–1.80)	0.6239
Multivessel disease	1.67 (1.08–2.58)	0.0225	1.22 (0.66–2.21)	0.5094	1.48 (0.91–2.37)	0.1113
Main culprit lesion
LMT and LAD vs. LCX, RCA, and others	1.59 (1.03–2.50)	0.0392	1.05 (0.58–1.89)	0.8624	1.61 (1.00–2.63)	0.0494
Revascularization	0.41 (0.18–1.17)	0.0553	1.24 (0.27–21.95)	0.8267	0.60 (0.22–2.40)	0.4184
Stent implantation	0.49 (0.25–1.12)	0.0868	1.18 (0.36–7.24)	0.8131	0.57 (0.27–1.47)	0.2220
IVUS use	0.48 (0.21–1.36)	0.1492	1.38 (0.30–24.41)	0.7381	0.40 (0.18–1.15)	0.0832
Prior PCI	1.33 (0.78–2.16)	0.2838	1.19 (0.56–2.32)	0.6278	1.23 (0.68–2.10)	0.4793
Prior MI	1.48 (0.83–2.44)	0.1764	0.86 (0.33–1.88)	0.7236	1.28 (0.67–2.27)	0.4287
Hypertension	1.49 (0.89–2.63)	0.1293	1.30 (0.64–2.54)	0.5441	1.56 (0.89–2.91)	0.1236
Diabetes	1.70 (1.10–2.64)	0.0177	1.14 (0.63–2.06)	0.6474	1.39 (0.86–2.23)	0.1736
Dyslipidemia	0.66 (0.42–1.03)	0.0670	0.66 (0.36–1.19)	0.1699	0.66 (0.41–1.07)	0.0910
Family history of CAD	1.05 (0.58–1.79)	0.8663	0.57 (0.20–1.32)	0.2066	0.97 (0.50–1.74)	0.9252
Smoking
Current vs. non-smoker	0.79 (0.45–1.33)	0.3722	0.38 (0.14–0.88)	0.0233	0.77 (0.43–1.35)	0.3740
Past vs. non-smoker	0.73 (0.43–1.23)	0.2377	0.99 (0.52–1.86)	0.9719	0.69 (0.39–1.20)	0.1922
Low body weight	1.86 (1.16–2.92)	0.0107	3.21 (1.77–5.78)	0.0002	2.14 (1.30–3.46)	0.0033
Atrial fibrillation	3.61 (2.28–5.64)	<0.0001	1.37 (0.59–2.80)	0.4309	4.49 (2.76–7.22)	<0.0001
Prior LEAD	2.30 (1.35–3.74)	0.0028	1.58 (0.68–3.22)	0.2631	2.50 (1.42–4.20)	0.0021
Severe CKD	4.35 (2.39–7.43)	<0.0001	3.75 (1.53–7.91)	0.0060	4.55 (2.38–8.08)	<0.0001
CKD	3.62 (2.30–5.79)	<0.0001	2.03 (1.13–3.67)	0.0182	3.18 (1.97–5.24)	<0.0001
Anemia	3.45 (2.15–5.76)	<0.0001	4.11 (2.15–8.52)	<0.0001	3.69 (2.20–6.49)	<0.0001
Prior HF	4.75 (3.03–7.37)	<0.0001	1.25 (0.52–2.64)	0.5938	6.07 (3.76–9.74)	<0.0001
Log₁₀[CITP]^B	1.89 (1.61–2.19)	<0.0001	1.72 (1.36–2.12)	<0.0001	1.94 (1.63–2.27)	<0.0001
CITP tertile
T3 vs. T1	11.35 (5.30–29.50)	<0.0001	4.92 (2.27–12.28)	<0.0001	14.40 (5.85–47.77)	<0.0001
T2 vs. T1	3.74 (1.59–10.23)	0.0019	1.78 (0.70–4.84)	0.2255	5.36 (2.01–48.48)	0.0004
Log₁₀[BNP]^B	2.77 (2.20–3.50)	<0.0001	1.81 (1.35–2.44)	<0.0001	2.96 (2.31–3.83)	<0.0001
Log₁₀[hsTnT]^B	1.35 (1.09–1.67)	0.0049	1.39 (1.04–1.85)	0.0246	2.33 (0.98–1.56)	0.0696
Log₁₀[H-FABP]^B	1.73 (1.45–2.04)	<0.0001	1.50 (1.15–1.91)	0.0015	1.52 (1.24–1.85)	<0.0001
eGFR^B	0.54 (0.45–0.65)	<0.0001	0.85 (0.65–1.13)	0.2682	0.55 (0.45–0.68)	<0.0001
Hemoglobin^B	0.53 (0.44–0.65)	<0.0001	0.49 (0.37–0.64)	<0.0001	0.49 (0.39–0.61)	<0.0001
Log₁₀[hsCRP]^B	1.68 (1.32–2.18)	<0.0001	1.66 (1.21–2.36)	0.0028	1.54 (1.19–2.02)	0.0012
Left atrial diameter^B	1.84 (1.47–2.27)	<0.0001	1.07 (0.76–1.49)	0.7135	1.88 (1.49–2.34)	<0.0001
LVEF^B	0.62 (0.50–0.76)	<0.0001	0.98 (0.72–1.37)	0.8815	0.64 (0.52–0.81)	<0.0001
LVEDD^B	1.39 (1.12–1.71)	0.0021	0.67 (0.46–0.98)	0.0434	1.36 (1.07–1.69)	0.0087
LVMI^B	1.41 (1.14–1.73)	0.0011	1.01 (0.71–1.38)	0.9620	1.44 (1.15–1.78)	0.0011
E/e′ ratio^B	1.50 (1.25–1.75)	<0.0001	1.38 (1.03–1.74)	0.0160	1.52 (1.27–1.79)	<0.0001
ACEi or ARBs	0.82 (0.52–1.35)	0.4221	0.61 (0.33–1.15)	0.1212	0.91 (0.54–1.58)	0.7216
β-blockers	2.10 (1.33–3.42)	0.0014	0.69 (0.38–1.24)	0.2169	2.47 (1.48–4.29)	0.0008
MRAs	1.39 (0.68–2.58)	0.3445	0.45 (0.08–1.46)	0.2131	1.68 (0.81–3.13)	0.1554
Diuretics	3.98 (2.49–6.24)	<0.0001	0.75 (0.23–1.86)	0.5694	4.86 (2.96–7.84)	<0.0001

^AThe primary endpoint was a composite of hospitalization for HF or cardiovascular death. ^BPer 1-SD increase. CI, confidence interval; HR, hazard ratio. Other abbreviations as in Table 1.

Table 4.

HRs for CITP in the Multivariate Cox Proportional Hazard Regression Analysis for Primary and Secondary Endpoints in Patients With CAD

	CITP tertile			Log₁₀CITP^A	P value
	T1	T2	T3	Log₁₀CITP^A	P value
Primary endpoint^B
Model 1	1.00	3.14 (1.31–8.69)*	5.57 (2.40–15.20)*^,†	1.61 (1.22–2.11)	0.0007
Model 2	1.00	3.75 (1.59–10.31)*	10.44 (4.77–27.53)*^,†	1.55 (1.28–1.89)	<0.0001
Model 3	1.00	3.42 (1.45–9.37)*	10.86 (5.01–28.42)*^,†	1.89 (1.59–2.22)	<0.0001
Model 4	1.00	2.89 (1.22–7.98)*	5.70 (2.49–15.45)*^,†	1.68 (1.26–2.25)	0.0004
Model 5	1.00	3.20 (1.34–8.84)*	5.70 (2.46–15.59)*^,†	1.66 (1.23–2.24)	0.0008
Secondary endpoints
All-cause death
Model 6	1.00	1.42 (0.55–3.93)	2.87 (1.23–7.55)*^,†	1.59 (1.20–2.05)	0.0007
HF rehospitalization
Model 7	1.00	4.10 (1.52–14.22)*	4.97 (1.86–17.29)*	1.30 (1.04–1.63)	0.0222

Unless indicated otherwise, data are given as hazard ratios with 95% confidence intervals in parentheses. *P<0.05 compared with Tertile (T) 1; ^†P<0.05 compared with T2. ^APer 1-SD increase. ^BThe primary endpoint was a composite of hospitalization for HF or cardiovascular death. Model 1 includes sex, left main trunk and left anterior descending artery lesion, atrial fibrillation, severe CKD, prior HF, BNP, and heart-type fatty acid-binding protein, which were selected in a stepwise manner. Model 2 includes age, sex, and cardiovascular risk factors, such as hypertension, diabetes, dyslipidemia, family history of CAD, and smoking. Model 3 includes age, sex, and coronary status, such as ACS, multivessel disease, culprit lesion, lesion type, and revascularization. Model 4 includes age, sex, and major components of the Japanese version of high bleeding risk, such as low body weight, prior LEAD, severe CKD, anemia, and prior HF. Model 5 includes thrombotic risk factors such as high age, ACS, lesion type, prior PCI, diabetes, smoking, atrial fibrillation, prior LEAD, severe CKD, anemia, and prior HF. Model 6 includes low body weight, anemia, prior HF, and hsCRP, which were selected in a stepwise manner. Model 7 includes sex, atrial fibrillation, prior LEAD, prior HF, BNP, and hemoglobin, which were selected in a stepwise manner. Abbreviations as in Table 1.

Figure 4.

Unadjusted and adjusted hazard ratios (HRs) of carboxyl-terminal telopeptide of type I collagen (CITP) tertiles (T1–T3) in the univariate and multivariate Cox proportional hazards regression analysis. Variables were selected by the stepwise method. The model for the primary endpoint (a composite of hospitalization for heart failure [HF] or cardiovascular death) includes left main trunk and left anterior descending artery lesion, prior HF, and B-type natriuretic peptide (BNP). The model for all-cause death includes low body weight. The model for HF rehospitalization includes prior HF and BNP. *P<0.05 compared with T1; ^†P<0.05 compared with T2. CI, confidence interval.

Univariate and multivariate Cox proportional hazard regression analyses were performed to determine the risk of the secondary endpoints. Univariate Cox proportional hazard regression analysis revealed that CITP levels were significantly associated with the secondary endpoints. Furthermore, age, low body weight, severe CKD, anemia, BNP, H-FABP, hemoglobin, and hsCRP levels, and the E/e′ ratio were associated with the secondary endpoints (Table 3). Multivariate Cox proportional hazard regression analysis demonstrated that CITP was an independent predictor of secondary endpoints after adjusting for confounding risk factors (Table 4). Similarly, among the CITP tertiles, T3 had the greatest risk for the secondary endpoints in the multivariate Cox proportional hazard regression analysis (Table 4).

Discussion

The novel findings of the present study are that: (1) the T3 group had higher BNP levels and LVMI than the T1 and T2 groups; (2) the C-index of CITP for the primary and secondary endpoints was comparable to those of BNP and H-FABP in patients with CAD; (3) unlike other cardiac biomarkers, abnormal cut-off CITP values were equivalent between patients with ACS and those with CCS; (4) Kaplan-Meier analysis demonstrated that CAD patients in T3 had the greatest risk of both the primary and secondary endpoints, independent of ACS or CCS; and (5) multivariate Cox proportional hazard regression analysis demonstrated that CAD patients in T3 had the highest hazard ratios for both the primary and secondary endpoints . Our results raise the possibility that CITP is a feasible marker of clinical outcomes in patients with CAD, regardless of ACS or CCS.

CITP in CAD

Because CITP is a collagen degradation marker in the heart and blood vessels, elevated CITP levels reflect pre-existing fibrosis in patients with CAD. In the present study, the T3 group showed persistently elevated CITP levels at follow-up coronary angiography (Supplementary Figure 4) and a higher prevalence of hypertension, AF, prior LEAD, severe CKD, and prior HF, despite similar coronary artery disease severity. Conversely, serum CITP levels were elevated in these settings (Supplementary Figure 2). These findings indicate the possibility that serum CITP is derived from atrial, ventricular, and vascular fibrosis and atherosclerotic lesions from peripheral arteries, not merely from coronary atherosclerosis. Several studies have investigated the clinical importance of CITP levels in the setting of hypertension, AF, LEAD, CKD, and HF.

Hypertension generally induces fibrosis of the heart and vasculature. CITP levels have been reported to increase in relation to collagen type I synthesis in patients with hypertension and stiffer arteries, as assessed by aortic pulse wave velocity and the augmentation index.¹⁸ Among patients with hypertension, serological evidence of an active fibrotic process was frequently observed in patients with more severe diastolic dysfunction.¹⁹ The changes in collagen I turnover favoring its increased degradation reportedly contribute to the LV radial and global systolic dysfunction seen in advanced hypertensive heart disease.²⁰ Therefore, CITP reflects vascular and heart collagen degradation in patients with hypertension, which is potentially involved in cardiac and vascular remodeling and function.

AF is associated with fibrotic processes in both atria and ventricles.²¹ CITP levels were higher in patients with persistent AF than in control participants.²² In the Multi-Ethnic Study of Atherosclerosis (MESA), elevated CITP levels were associated with the incidence of AF.²³ CITP levels have been shown to be proportional to pulmonary capillary wedge pressure and C-reactive protein levels in patients with chronic HF and AF.²⁴ Recent reports defined collagen cross-linking, which stiffens the fibrils, as a decreased CITP/matrix metalloproteinase-1 ratio and related it to the onset of AF and AF recurrence after ablation.²⁵ These findings suggest that CITP participates in the pathophysiology of AF.

LEAD is characterized by atherosclerosis of the peripheral arteries. We have reported that CITP levels are significantly associated with the severity and clinical outcomes of LEAD.¹⁵ Serum CITP levels have been reported to be independently associated with peripheral pulse wave velocity in patients with chronic HF.²⁶ These reports indicate a possible link between altered collagen metabolism and peripheral vascular stiffness. Thus, prior LEAD may be a cause of elevated CITP levels.

Circulating CITP is excreted by glomerular filtration in the kidney.²⁷^,²⁸ Thus, we could not exclude the possibility that renal excretion may have affected serum CITP levels in the present study. In patients with IgA nephropathy, CITP levels were similar between CKD stages 1–2 and stages 3–5. However, carotid-femoral pulse wave velocity, aortic pulse pressure, and LVMI showed strong positive correlations with CITP.²⁹ In patients with CKD and HF with preserved ejection fraction (HFpEF), CKD facilitates malignant myocardial fibrosis associated with severe diastolic dysfunction as assessed by the CITP/matrix metalloproteinase-1 ratio.³⁰ These reports indicate that high CITP levels are related to vascular stiffness and LV remodeling in patients with CKD.

The failing heart exhibits cardiac fibrosis. Repeated micro myocardial injury generally leads to collagen deposition and fibrosis, which increase the risk of HF. An increase in cardiac TnT levels over 3 years was significantly associated with CITP elevation at follow-up.³¹ In MESA, elevated circulating CITP levels appeared to be associated with incident HFpEF.³² The Cardiovascular Health Study also indicated that elevated circulating CITP levels were associated with incident HF in elderly subjects with cardiovascular risk factors and no previous HF.³³ A report showed CITP had good predictive value for diastolic dysfunction and HFpEF in patients with HT.³⁴ These findings raise the possibility that CITP could be useful in the diagnosis of HFpEF. A predominance of collagen degradation over synthesis results in matrix tensile strength that can be responsible for ventricular dilatation and systolic dysfunction in patients with chronic HF.³⁵ Thus, collagen biomarkers may be correlated with the incidence of HF. In outpatients with chronic HF, increased CITP levels were associated with self-assessed health status.³⁶ In patients with acute decompensation of chronic HF, CITP levels were significantly higher at discharge than at admission.³⁷ Thus, HF exacerbation may cause CITP elevation.

Collectively, CITP levels increased in response to collagen degradation in the heart and vasculature in the setting of hypertension, AF, LEAD, CKD, and HF. The T3 group also exhibited severe LV remodeling. CITP elevation in CAD may be plausibly augmented by comorbidities resulting from collagen degradation in the heart and vasculature, as well as atherosclerosis in the coronary artery.

Importantly, the CITP level was independently associated with HF-related events after adjusting for these covariates. One report showed an association between CITP levels and short-term cardiovascular events in patients with AMI.¹² CITP levels predicted cardiac events in patients with HFpEF.³⁸ In the OPTIMAL project study, CITP levels were reportedly an independent prognostic factor for all-cause and cardiovascular mortality in elderly patients with HF with reduced ejection fraction.³⁹ Serum CITP concentrations have been suggested to be an additional prognostic indicator of N-terminal pro BNP levels and an independent and strong prognostic marker for survival in patients with chronic HF.⁴⁰ These findings support our hypothesis that CITP could be a prognostic marker for HF-related events in patients with CAD who undergo PCI.

CITP and Medications

Several studies have investigated the effects of medications on circulating CITP levels. Bisoprolol has been reported to reduce circulating CITP levels, but not levels of collagen synthesis markers, and is related to reverse remodeling in patients with chronic HF, suggesting that β-blockers gradually inhibit collagen degradation.⁴¹ Intriguingly, an improvement in LVEF after β-blocker administration was proportional to the reduction in CITP levels. Conversely, angiotensin AT₁ receptor blockers and aldosterone blockers reportedly failed to decrease serum CITP levels.⁴²^–⁴⁴ No changes in CITP levels were observed in patients with moderate-to-severe chronic HF receiving diuretic therapy, indicating that loop diuretics did not affect serum CITP levels.²⁸ Beta-blockers are the Class I recommended drugs in patients with CAD. CITP may help identify β-blocker responders among patients with CAD. Further studies are required to determine whether CITP levels can provide additional information for the treatment and management of patients with CAD.

Study Limitations

First, because this was a single-center study, the sample size was relatively small. Second, the pathology of ACS could not be identified because intravascular ultrasound-guided PCI was performed. Generally, intravascular ultrasound cannot identify the precise pathology of ACS owing to its low resolution. Patients with ACS caused by plaque rupture may have higher CITP levels than those without this form of ACS. Third, we did not measure the levels of collagen synthesis markers and matrix metalloproteinases in this study. Therefore, we could not determine the mechanisms related to collagen metabolism and cross-linking in patients with CAD. Due to the lack of the autopsy or biopsy samples, we could not determine the association between serum CITP levels and the degree of cardiac fibrosis in patients with CAD. Fourth, the thrombotic and bleeding event rates were relatively low. Follow-up coronary angiography was performed in 81% of patients at 6–12 months. The duration of dual-antiplatelet therapy was determined after follow-up coronary angiography. This may have contributed to the low rates of thrombotic and bleeding events. Fifth, the optimal cut-off value for CITP remains unclear. Further studies with larger sample sizes are required to establish this value. Finally, the normal ranges of fibrosis markers, including CITP, were not confirmed. However, CITP levels ranged from 1.8 to 9.7 ng/mL in previous studies. Thus, our results are almost consistent with those of previous reports.⁷

Conclusions

We demonstrated that CITP levels are associated with clinical outcomes in patients with CAD. Further clinical and experimental studies are required to determine the precise role of collagen degradation markers in the development and progression of CAD.

Acknowledgments

None.

Sources of Funding

This study did not receive any specific funding.

Disclosures

All authors declare no conflicts of interest for this contribution.

IRB Information

This study was approved by the Institutional Ethics Committee of Yamagata University School of Medicine (first and updated IRB numbers: H20-62 and 2024-313).

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circj.CJ-25-0067

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