ABSTRACT
Mucin‐1 was reported be correlated with organ fibrosis. Pulse pressure amplification (PPA) was a marker of arterial stiffness. We investigate the association of serum mucin‐1 (CA15‐3) concentration with peripheral and central blood pressure and PPA in untreated Chinese patients. The study participants were outpatients who were suspected of hypertension, but had not been treated with antihypertensive medication for at least two weeks. Serum mucin‐1 (CA15‐3) concentration was measured by the enzyme‐linked immunosorbent assay method. PPA was the brachial‐to‐aortic pulse pressure ratio. The 1761 participants included 916 (52.0%) women, and 578 (32.8%) participants with clinic hypertension. Mean (±standard deviation [SD]) age was 51.3±10.6 years. After adjustment for confounders, higher serum mucin‐1 (CA15‐3) concentration was significantly associated with higher peripheral and central systolic and diastolic blood pressure (p≤0.009) and lower PPA (p = 0.037). Among 428 participants with a PPA equal or greater than 130% at baseline, 185 progressed to be a lower PPA (<130%) during a median follow‐up of 4.65 years. Hazard ratio expressed the relative risk of lower PPA per 1 SD increment in the log transformed serum mucin‐1 (CA15‐3) concentration was 1.22 (p = 0.027). In women but not in men, the risk of lower PPA was significantly higher with increased baseline serum mucin‐1 (CA15‐3) concentration (p for interaction 0.015). Higher circulating mucin‐1 (CA15‐3) concentration was independently associated with higher peripheral and central blood pressure and lower PPA in untreated Chinese patients. It also correlated with the progression of arterial stiffness as indicated by a lower PPA, especially in women.
Keywords: blood pressure, CA15‐3, Mucin‐1, pulse pressure amplification, serum
1. Introduction
In the arterial system, due to the reflection characteristics of pressure waves, the pulse pressure (difference between systolic and diastolic blood pressure) increases from the central to the peripheral arteries, a phenomenon known as pulse pressure amplification (PPA) [1, 2, 3, 4, 5]. Typically quantified by the brachial‐to‐aortic pulse pressure ratio, PPA as a marker of arterial stiffness was well established. With the stiffening of the central elastic arteries, PPA decreases [1, 4]. Our previous prospective population study showed that lower PPA was a risk factor for fatal and nonfatal cardiovascular and coronary endpoints [5]. Arterial stiffening was associated with multiple conditions such as aging, hypertension, dyslipidemia, diabetes, and chronic kidney disease [3, 6]. Some certain biomarkers might involve in the progress of arterial stiffening.
Mucin‐1 (MUC1) is an integral membrane protein characterized by three key domains: a cytoplasmic tail, a transmembrane domain and an extracellular N‐terminal region containing a variable number of tandem repeats (VNTR), which can be shed into the circulation as a soluble form [7]. Circulating mucin‐1 also called CA15‐3 which is widely used to monitor breast cancer progression in clinical practice [8, 9] by detecting parts of the mucin‐1 within the VNTR region. While initially understood for its role in epithelial protection and lubrication, mucin‐1 is now recognized as a crucial multifunctional protein pivotal for cell signal transduction and intercellular communication [10]. Mucin‐1 was reported to be associated with organ fibrosis, such as the kidney and the lung fibrosis [7].
While mucin‐1 (CA15‐3) level is routinely used in breast cancer monitoring and might be correlated with organ fibrosis, its relationship with arterial stiffness remains underexplored. To address this issue, we investigated the association of serum mucin‐1 (CA15‐3) concentration with peripheral and central blood pressure and PPA in untreated Chinese patients.
2. Methods
2.1. Study Population
The study participants were untreated patients, referred to the Outpatient Clinic of the Department of Hypertension, Ruijin Hospital, Shanghai, China. At enrolment, they either had never been treated previously (∼90%) or stopped antihypertensive medication for at least two weeks (∼10%) [11, 12, 13, 14]. We adhered to the principles of the Declaration of Helsinki [15]. The Ethics Committee of Ruijin Hospital, Shanghai Jiaotong University School of Medicine approved the study. All participants gave written informed consent.
From March 2009 to June 2015, 1973 participants were enrolled in the study. We excluded from the present analysis 212 subjects, because PPA was not measured (n = 112), serum mucin‐1 (CA15‐3) concentration was not tested (n = 93) or out of the test range (n = 7). Thus, the total number of patients included in the analysis was 1761.
From June 2015, participants were invited to attend follow‐up examinations. Of these cross‐sectionally analyzed participants, 935 were followed up and had a repeated PPA measurement. Of these 935 patients, 428 had a PPA equal or greater than 130% at baseline and were included in the prospective analysis to investigate the incidence of lower PPA.
2.2. Clinical and Biochemical Data
An experienced physician measured each participant's clinic blood pressure three times consecutively by the use of the Omron HEM‐7051 device (Omron Healthcare, Kyoto, Japan), after the study subject had rested for at least five minutes in the sitting position. These three blood pressure readings were averaged for analysis. We defined clinic hypertension as a clinic blood pressure of at least 140 mmHg systolic or 90 mmHg diastolic.
The same physician administered a standardized questionnaire, inquiring into each subject's medical history, intake of medications, and smoking and drinking habits. Nurses measured body height to the nearest 0.5 cm. Participants wore light indoor clothing without shoes for body weight measurement. Body mass index was the body weight in kilograms divided by the body height in meters squared.
Venous blood samples were taken after overnight fasting for the measurement of plasma glucose, serum mucin‐1 (CA15‐3), cholesterol, triglycerides and creatinine. Estimated glomerular filtration rate (eGFR) was calculated from serum creatinine by the use of the Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI) [16] equation. We defined diabetes mellitus as a fasting plasma glucose of ≥7.0 mmol/L or as the use of antidiabetic treatment [17].
2.3. Serum Measurements of Mucin‐1 (CA15‐3)
Serum mucin‐1 (CA15‐3) concentration was measured by the enzyme‐linked immunosorbent assay (ELISA) method (mucin‐1 [CA15‐3] ELISA Kit, Fujirebio Diagnostics AB, Gothenburg, Sweden). The within‐assay and between‐assay coefficients of variation were 3.4% and 7.7%, respectively.
2.4. Pulse Wave Analysis
A trained technician performed pulse wave analysis after subjects had rested for 15 min in the supine position by the use of the applanation tonometry. Subjects were asked to refrain from rigorous exercise, cigarette smoking and drinking alcohol or caffeine‐containing beverages for at least 2 h before the examination. We used a high‐fidelity SPC‐301 micromanometer (Millar Instruments, Houston, TX, USA) interfaced with a laptop computer running the SphygmoCor software, version 7.1 (AtCor Medical, West Ryde, NSW, Australia) to record radial arterial waveforms. Recordings were discarded when the variability of consecutive waveforms exceeded 5% or when the amplitude of the pulse wave signal was below 80 mV. We calibrated the pulse wave by brachial blood pressure (the average of two consecutive readings) in the supine position immediately before the SphygmoCor recordings, using a validated Omron 705 CP oscillometric blood pressure monitor (Omron, Kyoto, Japan). From the radial signal, the SphygmoCor software calculates the aortic pulse wave by means of a validated generalized transfer function [18]. The central (aortic) systolic and diastolic blood pressures were derived from the aortic pulse wave. PPA was the brachial‐to‐aortic pulse pressure ratio. According to our previous study [5] on an outcome‐driven threshold for PPA, lower PPA was defined as <130%.
2.5. Statistical Analysis
For database management and statistical analysis, we used SAS software, version 9.4 (SAS Institute, Cary, NC, USA). Departure from normality was tested by the Shapiro–Wilk's statistic. Serum mucin‐1 (CA15‐3) concentration was not normally distributed and was, therefore, logarithmically transformed for statistical analysis. Means and proportions were compared with the Student t test and Fisher's exact test, respectively. We performed univariate and multivariate regression analysis to study cross‐sectional associations of serum mucin‐1 (CA15‐3) concentration with blood pressure and PPA. Multivariable‐adjusted Cox models were used to analyze the association of serum mucin‐1 (CA15‐3) concentration and the risk of lower PPA. Hazard ratios (HRs) relating lower PPA to serum mucin‐1 (CA15‐3) concentration were expressed per 1‐SD increment of log transformed serum mucin‐1 (CA15‐3) concentration. Statistical significance was an α level of 0.05 or less on two‐sided tests.
3. Results
3.1. Characteristics of Participants
The 1761 participants included 916 (52.0%) women, and 578 (32.8%) participants with clinic hypertension. Mean (±standard deviation [SD]) age was 51.3±10.6 years. They had either never been treated previously (n = 1604) or discontinued their antihypertensive medication for at least 2 weeks (n = 157). Table 1 shows the characteristics of the study participants according to the median of serum mucin‐1 (CA15‐3) concentration (≥11 vs. <11 U/mL). In comparison with the participants with lower serum mucin‐1 (CA15‐3) concentration, the participants with higher serum mucin‐1 (CA15‐3) concentration were older and had higher body mass index, higher peripheral and central systolic and diastolic blood pressure, higher serum total cholesterol, serum total/high‐density lipoprotein (HDL) cholesterol ratio, serum triglycerides and lower PPA, but similar plasma fasting glucose, female sex, current smoking and alcohol intake.
TABLE 1.
Characteristics of the study population.
| Characteristic | All (n = 1761) | Serum mucin‐1 (CA15‐3) ≥11 U/mL (n = 881) | Serum mucin‐1 (CA15‐3) <11 U/mL (n = 880) | p |
|---|---|---|---|---|
| Age, years | 51.3±10.6 | 52.1±10.7 | 50.4±10.4 | 0.0006 |
| Body mass index, kg/m2 | 24.5±3.1 | 24.7±3.2 | 24.3±3.1 | 0.008 |
| Female sex, n (%) | 916 (52.0) | 459 (52.1) | 457 (51.9) | 0.94 |
| Current smoking, n (%) | 303 (17.2) | 146 (16.6) | 157 (17.8) | 0.48 |
| Alcohol intake, n (%) | 334 (19.0) | 157 (17.8) | 177 (20.1) | 0.22 |
| Peripheral blood pressure, mm Hg | ||||
| Systolic | 137.5±14.1 | 138.7±13.4 | 136.2±14.8 | 0.0002 |
| Diastolic | 80.9±9.3 | 81.6±9.2 | 80.2±9.4 | 0.002 |
| Pulse pressure | 56.5±10.8 | 57.1±10.5 | 56.0±11.0 | 0.036 |
| Central blood pressure, mm Hg | ||||
| Systolic | 126.1±14.6 | 127.7±13.9 | 124.5±15.1 | <0.0001 |
| Diastolic | 82.3±9.5 | 83.0±9.3 | 81.6±9.6 | 0.003 |
| Pulse pressure | 43.8±11.0 | 44.8±10.7 | 42.9±11.2 | 0.0003 |
| Mean | 101.9±10.7 | 102.8±10.3 | 100.9±11.0 | 0.0002 |
| Pulse rate, beats/minute | 67.9±9.9 | 67.2±9.7 | 68.6±10.1 | 0.005 |
| Pulse pressure amplification, % | 131.7±17.5 | 130.0±16.8 | 133.4±18.0 | <0.0001 |
| Plasma fasting glucose, mmol/L | 5.06±0.81 | 5.08±0.79 | 5.05±0.83 | 0.44 |
| Serum total cholesterol, mmol/L | 5.11±0.93 | 5.22±0.97 | 5.01±0.89 | <0.0001 |
| Serum HDL cholesterol, mmol/L | 1.52±0.41 | 1.47±0.40 | 1.57±0.41 | <0.0001 |
| Serum total/HDL cholesterol ratio | 3.57±1.06 | 3.77±1.12 | 3.37±0.95 | <0.0001 |
| Serum triglycerides, mmol/L | 1.26 (0.91–1.77) | 1.32 (0.94–1.89) | 1.20 (0.87–1.68) | <0.0001 |
| eGFR, ml/min/1.73 m2 | 101.2±12.9 | 99.1±13.5 | 103.3±11.8 | <0.0001 |
| Serum mucin‐1 (CA15‐3), U/mL | 11.0 (6.05–21.2) | 21.2 (14.5–37.3) | 6.05 (3.82–8.30) | <0.0001 |
Note: Values are arithmetic (±SD) or geometric mean (interquartile range) or number of subjects (%).
Abbrevations: eGFR, estimated glomerular filtration rate; HDL, high density lipoprotein.
3.2. Association of Serum Mucin‐1 (CA15‐3) Concentration With Blood Pressure and PPA
In univariate regression, serum mucin‐1 (CA15‐3) concentration was significantly associated with peripheral and central systolic and diastolic blood pressure, pulse pressure (0.51 to 1.57 mmHg increase per 1‐SD increase in log transformed serum mucin‐1 [CA15‐3] concentration, p ≤ 0.046) and PPA (1.64% decrease per 1‐SD increase in log transformed serum mucin‐1 [CA15‐3] concentration, p < 0.0001, Table 2). In multiple regression analyses, after adjustment for sex, age, body mass index, mean arterial pressure, pulse rate, current smoking and alcohol intake, serum fasting glucose, serum total‐to‐HDL cholesterol ratio, anti‐diabetic treatment and eGFR, serum mucin‐1 (CA15‐3) concentration was significantly associated with peripheral and central systolic and diastolic blood pressure (0.59 to 0.87 mmHg increase per 1‐SD increase in log transformed serum mucin‐1 [CA15‐3] concentration, p ≤ 0.009) and PPA (0.56% decrease per 1‐SD increase in log transformed serum mucin‐1 [CA15‐3] concentration, p = 0.037), but not with peripheral or central pulse pressure (p ≥ 0.18, Table 2). With increment of quartiles of serum mucin‐1 (CA15‐3) concentration, peripheral and central systolic blood pressure increased while PPA decreased (p for trend ≤0.027, Figure 1).
TABLE 2.
Association of serum mucin‐1 (CA15‐3) concentration with peripheral and central blood pressures and pulse pressure amplification.
| Variable | Unadjusted | Adjusted | ||
|---|---|---|---|---|
| Estimate (95% CI) | p | Estimate (95% CI) | p | |
| Peripheral blood pressure, mm Hg | ||||
| Systolic | 1.18 (0.52–1.84) | 0.0005 | 0.75 (0.18–1.32) | 0.009 |
| Diastolic | 0.67 (0.23–1.10) | 0.003 | 0.60 (0.28–0.92) | 0.0003 |
| Pulse pressure | 0.51 (0.01–1.02) | 0.046 | 0.15 (−0.34–0.64) | 0.54 |
| Central blood pressure, mm Hg | ||||
| Systolic | 1.57 (0.89–2.25) | <0.0001 | 0.87 (0.32–1.43) | 0.002 |
| Diastolic | 0.65 (0.21–1.09) | 0.004 | 0.59 (0.26–0.92) | 0.0004 |
| Pulse pressure | 0.92 (0.41–1.43) | 0.0004 | 0.28 (−0.13–0.70) | 0.18 |
| Pulse pressure amplification, % | −1.64 (−2.45–0.82) | <0.0001 | −0.56 (−1.08–−0.03) | 0.037 |
Note: Estimates express the association size for a 1‐SD increase in the log transformed serum mucin‐1 (CA15‐3) concentration. The adjusted variables included sex, age, body mass index, mean arterial pressure, pulse rate, current smoking and alcohol intake, plasma fasting glucose, serum total‐to‐high‐density lipoprotein cholesterol ratio, anti‐diabetic treatment and eGFR derived from serum creatinine by the CKD‐EPI formula with the unit of ml/min/1.73 m2.
FIGURE 1.
The association of systolic blood pressure and pulse pressure amplification with quartiles of serum mucin‐1 (CA15‐3) concentration. The analyses were adjusted for sex, age, body mass index, mean arterial pressure, pulse rate, current smoking and alcohol intake, plasma fasting glucose, serum total‐to‐high‐density lipoprotein cholesterol ratio, anti‐diabetic treatment and eGFR derived from serum creatinine by the CKD‐EPI formula with the unit of ml/min/1.73 m2. Vertical bars denote the standard errors. p trend indicates trend p value of quartiles.
3.3. Subgroup Analyses
Subgroup analyses showed that the association of serum mucin‐1 (CA15‐3) concentration with peripheral systolic blood pressure was significantly stronger in women, older subjects (≥60 years) and nonsmokers (p for interaction ≤0.021,Table 3). The associations of serum mucin‐1 (CA15‐3) concentration with central systolic blood pressure, peripheral and central diastolic blood pressure were also significant in nonsmokers but not in smokers (p for interaction ≤0.044,Table 3 and Table 4). The results were similar between peripheral and central diastolic blood pressure (Table 4) as a consequence of the consistent diastolic blood pressure between peripheral and central arteries (Table 1). The associations between serum mucin‐1 (CA15‐3) concentration and PPA did not statistically differ across sex, age, body mass index, hypertension, diabetes, serum total/HDL cholesterol ratio, current smoking and drinking (p for interaction ≥0.11, Table 3).
TABLE 3.
Association of serum mucin‐1 (CA15‐3) concentration with peripheral and central systolic blood pressure and pulse pressure amplification according to various characteristics of the study population.
| Peripheral systolic blood pressure, mm Hg | Central systolic blood pressure, mm Hg | Pulse pressure amplification | ||||
|---|---|---|---|---|---|---|
| Estimate (95% CI) | pint | Estimate (95% CI) | pint | Estimate (95% CI) | pint | |
| All subjects (n = 1761) | 0.75 (0.18–1.32) | 0.87 (0.32–1.43) | −0.56 (−1.08–−0.03) | |||
| Men (n = 845) | 0.13 (−0.60–0.87) | 0.009 | 0.40 (−0.30–1.10) | 0.052 | −0.78 (−1.63–0.07) | 0.11 |
| Women (n = 916) | 1.32 (0.47–2.17) | 1.35 (0.51–2.19) | −0.48 (−1.06–0.10) | |||
| Age ≥60 years (n = 383) | 1.79 (0.46–3.11) | 0.021 | 1.61 (0.32–2.90) | 0.10 | −0.28 (−1.23–0.67) | 0.24 |
| Age <60 years (n = 1378) | 0.45 (−0.18–1.07) | 0.67 (0.05–1.29) | −0.65 (−1.29–−0.01) | |||
| Body mass index ≥24 kg/m2 (n = 953) | 0.73 (−0.04–1.50) | 0.71 | 0.99 (0.26–1.73) | 0.80 | −0.86 (−1.59–−0.14) | 0.12 |
| Body mass index <24 kg/m2 (n = 808) | 0.84 (0.00–1.69) | 0.83 (0.00–1.67) | −0.23 (−1.00–0.54) | |||
| Hypertension (n = 578) | 0.37 (−0.65–1.39) | 0.93 | 0.61 (−0.41–1.64) | 0.86 | −0.57 (−1.48–0.34) | 0.96 |
| Normotensive (n = 1183) | 0.74 (0.09–1.38) | 0.79 (0.17–1.41) | −0.48 (−1.12–0.16) | |||
| Diabetes (n = 82) | 0.73 (−2.36–3.83) | 0.69 | 0.34 (−2.70–3.38) | 0.38 | 0.31 (−3.00–3.62) | 0.33 |
| Non‐diabetes (n = 1679) | 0.77 (0.19–1.34) | 0.91 (0.35–1.47) | −0.60 (−1.13–‐0.07) | |||
| Higher serum total/HDL cholesterol ratio (n = 868) | 0.46 (−0.28–1.21) | 0.23 | 0.67 (−0.04–1.39) | 0.36 | −0.73 (−1.46–0.00) | 0.51 |
| Lower serum total/HDL cholesterol ratio (n = 893) | 1.12 (0.28–1.96) | 1.19 (0.36–2.02) | −0.44 (−1.18–0.30) | |||
| Current smoking (n = 303) | −1.01 (−2.17–0.14) | 0.004 | −0.74 (−1.86–0.37) | 0.010 | −0.54 (−1.96–0.87) | 0.65 |
| Nonsmokers (n = 1458) | 1.13 (0.49–1.77) | 1.22 (0.59–1.84) | −0.55 (−1.10–0.01) | |||
| Current drinking (n = 334) | −0.22 (−1.32–0.89) | 0.081 | 0.07 (−1.01–1.15) | 0.19 | −0.71 (−1.96–0.54) | 0.45 |
| Nondrinkers (n = 1427) | 1.00 (0.35–1.65) | 1.08 (0.45–1.71) | −0.52 (−1.10–0.05) | |||
Note: Estimates express the association size for a 1‐SD increase in the log transformed serum mucin‐1 (CA15‐3) concentration. The adjusted variables included sex, age, body mass index, mean arterial pressure, pulse rate, current smoking and alcohol intake, plasma fasting glucose, serum total‐to‐high‐density lipoprotein cholesterol ratio, anti‐diabetic treatment and eGFR derived from serum creatinine by the CKD‐EPI formula with the unit of ml/min/1.73 m2. pint indicates p value for interaction.
TABLE 4.
Association of serum mucin‐1 (CA15‐3) concentration with peripheral and central diastolic blood pressure according to various characteristics of the study population.
| Peripheral diastolic blood pressure, mm Hg | Central diastolic blood pressure, mm Hg | |||
|---|---|---|---|---|
| Estimate (95% CI) | pint | Estimate (95% CI) | pint | |
| All subjects (n = 1761) | 0.60 (0.28–0.92) | 0.59 (0.26–0.92) | ||
| Men (n = 845) | 0.46 (‐0.01–0.93) | 0.67 | 0.46 (−0.01–0.94) | 0.73 |
| Women (n = 916) | 0.77 (0.33–1.21) | 0.76 (0.31–1.21) | ||
| Age ≥60 years (n = 383) | 0.83 (0.20–1.46) | 0.48 | 0.76 (0.12–1.40) | 0.60 |
| Age <60 years (n = 1378) | 0.58 (0.21–0.95) | 0.59 (0.21–0.97) | ||
| Body mass index ≥24 kg/m2 (n = 953) | 0.66 (0.21–1.12) | 0.77 | 0.66 (0.20–1.11) | 0.77 |
| Body mass index <24 kg/m2 (n = 808) | 0.60 (0.13–1.06) | 0.59 (0.12–1.06) | ||
| Hypertension (n = 578) | 0.76 (0.13–1.40) | 0.20 | 0.76 (0.12–1.40) | 0.19 |
| Normotensive (n = 1183) | 0.39 (0.03–0.74) | 0.38 (0.01–0.74) | ||
| Diabetes (n = 82) | −0.16 (−1.73–1.42) | 0.055 | −0.19 (−1.81–1.44) | 0.052 |
| Non‐diabetes (n = 1679) | 0.64 (0.31–0.97) | 0.64 (0.30–0.97) | ||
| Higher serum total/HDL cholesterol ratio (n = 868) | 0.53 (0.09–0.96) | 0.39 | 0.52 (0.08–0.96) | 0.38 |
| Lower serum total/HDL cholesterol ratio (n = 893) | 0.76 (0.29–1.24) | 0.77 (0.29–1.24) | ||
| Current smoking (n = 303) | −0.17 (−0.93–0.59) | 0.043 | −0.19 (−0.96–0.59) | 0.044 |
| Nonsmokers (n = 1458) | 0.76 (0.40–1.11) | 0.75 (0.39–1.11) | ||
| Current drinking (n = 334) | 0.40 (−0.29–1.08) | 0.91 | 0.40 (−0.29–1.09) | 0.92 |
| Nondrinkers (n = 1427) | 0.64 (0.28–1.01) | 0.63 (0.26–1.01) |
Note: Estimates express the association size for a 1‐SD increase in the log transformed serum mucin‐1 (CA15‐3) concentration. The adjusted variables included sex, age, body mass index, mean arterial pressure, pulse rate, current smoking and alcohol intake, plasma fasting glucose, serum total‐to‐high‐density lipoprotein cholesterol ratio, anti‐diabetic treatment and eGFR derived from serum creatinine by the CKD‐EPI formula with the unit of ml/min/1.73 m2. pint indicates p value for interaction.
3.4. Risk of Lower PPA in Relation to Serum Mucin‐1 (CA15‐3) Concentration
Among 428 participants with a PPA equal or greater than 130% at baseline, 185 progressed to be a lower PPA (<130%) during follow‐up with the median follow‐up of 4.65 years (fifth‐95th percentile interval, 4.0–5.8 years). Figure 2 shows the hazard ratios (HRs) relating the risk of lower PPA to serum mucin‐1 (CA15‐3) concentration analyzed as continuous variables. The analyses were adjusted for sex, age, body mass index, mean arterial pressure, pulse rate, current smoking and alcohol intake, serum fasting glucose, serum total‐to‐HDL cholesterol ratio, use of antihypertensive drugs and eGFR. Hazard ratio expressed the relative risk of an endpoint per 1 SD increment in the log transformed serum mucin‐1 (CA15‐3) concentration in all participants was 1.22 (95% confidence interval (CI): 1.02‐1.45, p = 0.027).
FIGURE 2.
Subgroup analysis of the incidence of lower pulse pressure amplification in relation to the serum mucin‐1 (CA15‐3) concentration. The strata are categorized by sex, age, body mass index, hypertension, current smoking or drinking. Hazard ratios (HR), given with 95% confidence interval, are adjusted for sex, age, body mass index, mean arterial pressure, pulse rate, current smoking and alcohol intake, plasma fasting glucose, serum total‐to‐high‐density lipoprotein cholesterol ratio, use of antihypertensive drugs and eGFR derived from serum creatinine by the CKD‐EPI formula with the unit of ml/min/1.73 m2. In the adjustment, the covariable used to categorize the subgroups was excluded. n/N indicates the number of endpoints per number of participants at risk. pint refers to the significance of the difference in hazard ratios between categories in each subgroup. BMI: body mass index.
Subgroup analyses with stratification for sex, age (<60 versus ≥60 years), body mass index, hypertension, current smoking or alcohol intake did not reveal subgroup differences in the aforementioned fully adjusted HRs relating the lower PPA with serum mucin‐1 (CA15‐3) concentration, except for sex. In women but not in men, the risk of lower PPA was significantly higher with increased baseline serum mucin‐1 (CA15‐3) concentration (p for interaction 0.015, Figure 2).
4. Discussion
Our current study indicated that circulating mucin‐1 (CA15‐3) concentration was independently associated with peripheral and central blood pressure and PPA in untreated Chinese patients. Circulating mucin‐1 (CA15‐3) level was increased with higher peripheral and central blood pressure and lower PPA. Higher circulating mucin‐1 (CA15‐3) concentration was associated with the progression of arterial stiffness as indicated by a lower PPA, especially in women.
From the central aorta to peripheral arteries, systolic blood pressure and pulse pressure amplify, whereas diastolic blood pressure remains relatively constant, attributable to the arrival time difference of the reflection wave between the central and peripheral arteries. Stiffening of the central elastic arteries leads to the earlier return of backward waves from peripheral reflection sites [1, 4], thereby increasing central systolic pressure and pulse pressure, so that the ratio of brachial‐to‐aortic pulse pressure decreases. Arterial stiffening was associated with aging as well as age‐related morbid conditions such as hypertension, dyslipidemia, diabetes, and chronic kidney disease [3, 6]. Exaggerated blood pressure amplification from the central to the peripheral arteries might also appear in adolescents and young adults with isolated systolic hypertension, who had increased stroke volume, normal central blood pressure but exaggerated blood pressure amplification from the central to the peripheral arteries. The risk of cardiovascular events in such patients was reported to be lower than those with combined systolic‐diastolic hypertension [19, 20, 21]. In these young patients with isolated systolic hypertension, assessing both arterial stiffness index PPA and central blood pressure was helpful to differentiate real arterial stiffness or increased stroke volume with normal central blood pressure which has lower cardiovascular risk [22].
To our knowledge, our study first demonstrates that higher levels of circulating mucin‐1 (CA15‐3) are linked to higher peripheral and central blood pressure as well as lower PPA. Certain biomarkers, such as transforming growth factor‐beta 1 (TGF‐β1) [23], Protein 6‐lysyl oxidase (LOX) [24], matrix metalloproteinase‐3 (MMP‐3) [25] and osteoglycin (OGN) [26], were reported to be associated with fibrosis or aging. Therefore, functional biomarkers might be involved in the progression of age‐related arterial stiffening. Mucin‐1 is a high‐molecular weight (400 kDa) membrane‐tethered glycoprotein [7] existing in many organs and can be cleaved into circulation. Mucin‐1 relating to organ fibrosis, such as the lung and the kidney fibrosis was reported previously [7]. Javier Milara et al. found mucin‐1 intracellular bioactivation is enhanced in idiopathic pulmonary fibrosis (IPF) and promotes fibrotic processes [27]. A retrospective study in seventy patients with IPF receiving pirfenidone treatment demonstrated that patients with baseline mucin‐1 levels ≥2.5 ng/mL had enhanced risks of acute exacerbation of IPF (adjusted hazard ratio, 14.07; 95% CI, 4.26–46.49) within 2 years [28]. A Japanese cohort study with 52 patients from 40 families identified the variants of MUC1 in patients with autosomal dominant tubulointerstitial kidney disease (ADTKD) characterized by tubular atrophy and interstitial fibrosis [29]. Our previous study does demonstrated that circulating mucin‐1 (CA15‐3) together with its ligand galectin‐3 levels were significantly associated with renal function [14]. Nevertheless, although mucin‐1 was proved to be a multifunctional protein, it's association with arterial stiffness was rarely reported. Circulating mucin‐1 (CA15‐3) is widely used to monitor breast cancer progression in clinical practice [8, 9]. In this study, we measure it in untreated outpatients suspected of hypertension rather than patients with malignancy. Serum mucin‐1 (CA15‐3) concentrations were within the conventional reference range in most participants with the median (interquartile range) of 11.0 (6.05‐21.2) U/mL. Therefore, our current study reviling the potential link between serum mucin‐1 (CA15‐3) and PPA position mucin‐1 as a promising biomarker of arterial stiffening. Basic researches on the molecular mechanism of mucin‐1 on arterial stiffness are essential, which might provide basis for the possible promising targeted therapeutic strategy of antifibrotic agents to control fibrosis progression efficiently and improve patient outcomes [30].
An interesting finding was that higher circulating mucin‐1 (CA15‐3) concentration was associated with the progress of arterial stiffness indicated by a lower PPA especially in women. The mechanism was not understood. In aortic stenosis patients, aorta histopathology showed sex differences (males more calcified, females more fibrotic) [31]. Basic researches on smooth muscle cell specific mineralocorticoid receptors knockout (SMC‐MR‐KO) mice revealed that in males, SMC‐MR‐KO prevented arterial fibrosis by downregulating expression of a pro‐fibrotic gene program and collagen genes, while these gene expression changes did not occur in female mice [32]. Moreover, PPA was an index with sex difference which was lower in women [33]. Indeed, in the cross‐sectional analysis of our current study, based on the outcome‐driven threshold of 130% which being unified in both sexes [5], 939 (53.3%) has a lower PPA (<130%) at baseline, among whom 265 (28.2%) and 674 (71.8%) were men and women respectively. In the prospective analysis, among all the 428 participants with a higher PPA (≥130%) at baseline, only 124 (29.0%) were women. Further studies are expected to investigate the mechanism of mucin‐1 on arterial stiffness among different genders.
Our study had several limitations. First, we measured circulating mucin‐1 (CA15‐3) as a fragment of mucin‐1 instead of the integral membrane protein which could not be measured in a population sample. Second, the sample size was relatively small (n = 428) when analyzing the progress of PPA. Further studies in larger prospective studies were expected. Finally, we measured central blood pressure by using noninvasive SphygmoCor technology to reconstruct the aortic pulse wave from the radial pulse wave. While noninvasive method helps the measurements of the central hemodynamic indices easier in population studies, measuring central blood pressure directly by invasive catheter still considered to be a gold standard.
In conclusion, higher circulating mucin‐1 (CA15‐3) concentration was independently associated with higher peripheral and central blood pressure and lower PPA in untreated Chinese patients. It also correlated with the progression of arterial stiffness as indicated by a lower PPA, especially in women. Our findings position mucin‐1 as a promising biomarker of arterial stiffening. Further researches are expected to validate its clinical utility in risk stratification and investigate the underlying mechanisms responsible for the sex‐specific differences of arterial stiffness.
Funding
This study was financially supported by grants from the National Natural Science Foundation of China (grants 81970353, 82070432, 82070435, 82100445, 82270469, and 82370426), the National Health Commission of China (Noncommunicable Chronic Diseases‐National Science and Technology Major Project, grants 2024ZD0538700 and 2024ZD0527304), the Ministry of Science and Technology (2022YFC3601302), Beijing, China, and by the Shanghai Municipal Health Commission (grants 202340035, 201940297, 20234Y0036, 2024ZZ1028, and Leading Academics 2022LJ022), the Shanghai Municipal Commission of Science and Technology (grants 22ZR1452900), and the Shanghai Talent Work Bureau (Oriental Talent Program BJWS2024086 and QNWS2024013), Shanghai, China.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgments
The authors gratefully acknowledge the voluntary participation of all patients and the expert technical support of Junwei Li, Beiwen Lv, Jiaye Qian, Yuzhong Shi, Qian Yu, Jie Zhou, Yi Zhou, Yini Zhou, and Jiajun Zong (The Shanghai Institute of Hypertension, Shanghai).
Data Availability Statement
Consent given by study participants did not include data sharing with third parties. Anonymized data can be made available to investigators for targeted research based on a motivated request to be addressed to the corresponding author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Consent given by study participants did not include data sharing with third parties. Anonymized data can be made available to investigators for targeted research based on a motivated request to be addressed to the corresponding author.