Article ID: CJ-22-0750
Background: This study examined whether the severity of mitral valve stenosis (MVS) is associated with oxidative stress (OS) markers in the blood, and other hematological and clinicodemographic parameters.
Methods and Results: This prospective study was conducted between March and May 2022. Seventy-five patients with newly diagnosed MVS (25 mild, 25 moderate, 25 severe) were included. Mild, moderate, and severe MVS was defined as MV area >2, 1.5–2, and <1.5 cm2, respectively. Various OS markers and laboratory parameters were determined in venous blood samples. For predictive analyses, 2 different analyses were performed to detect patients with severe MVS and those with moderate or severe (moderate/severe) MVS. Age (P=0.388) and sex (P=0.372) distribution were similar in the 3 groups. Multiple logistic regression analysis revealed that a high white blood cell (WBC) count (P=0.023) and high malondialdehyde (P=0.010), superoxide dismutase (SOD; P=0.008), and advanced oxidation protein products (AOPP; P=0.007) levels were independently associated with severe MVS. A low platelet count (P=0.030) and high malondialdehyde (P=0.018), SOD (P=0.008), and AOPP (P=0.001) levels were independently associated with having moderate/severe MVS. The best discriminatory factors for severe MVS were SOD (cut-off >315.5 ng/mL) and glutathione (cut-off >4.7 μmol/L).
Conclusions: MVS severity seems to be affected by oxidant markers (malondialdehyde and AOPP), antioxidant enzymes (SOD), and inflammation-related cells (WBC and platelets). Future studies are needed to examine these relationships in larger populations.
Heart valve diseases (HVD) are an important public health problem that cause high morbidity and mortality. HVD are characterized by ineffective pumping functions.1,2 In patients aged ≥75 years, the incidence of both mitral valve (MV) and aortic valve (AV) disease is 6%; in contrast, the incidence of both MV and AV is less than 1% in patients aged <64 years.2 Congenital defects, degeneration of the valves with aging, calcification of the annulus, ischemia, rheumatic heart disease, functional anatomical abnormalities, and the obstruction of valves as a result of the accumulation of high levels of fats in the blood can damage the heart valves and cause valve stenosis or insufficiency.2,3
Reactive oxygen species (ROS) are a group of highly reactive chemical forms of molecular oxygen and some similar compounds.4 At physiological concentrations, ROS regulate cell growth, differentiation, senescence, migration, apoptosis, and autophagy, and modulate a number of metabolic functions including glycolysis, oxidative phosphorylation, and fatty acid synthesis.5–8 Many mechanisms, such as subcellular compartmentalization, antioxidant enzymes (e.g., catalase, glutathione peroxidase [GPx] and superoxide dismutase [SOD]), and non-enzymatic antioxidants (e.g., glutathione, vitamins C, E, and A, bilirubin, peroxiredoxins, and thioredoxin) contribute to the control of ROS concentrations.9–11 Oxidative stress (OS) is defined as ROS concentrations beyond physiologically tolerable limits resulting from increased expression and activity of ROS-producing enzymes and/or decreased expression and activity of antioxidant mechanisms.4 Many conditions associated with the cardiovascular system, such as endothelial dysfunction, hypertension, vascular calcification, HVD, atherosclerosis, stroke, and diabetes, have been associated with OS.12,13 OS markers may be associated with oxidative injury in the pathophysiology of HVD, and may allow for the prediction and monitoring of the possible efficacy of therapeutic strategies designed to control these pathologies.14 Although many studies have examined the relationship between AV stenosis (AVS) and OS and reported significant findings,15–17 there is only a limited number of studies on MV stenosis (MVS).16,17
The purpose of the present study was to examine whether MVS severity could be associated with various OS markers in the blood and some other hematological and clinicodemographic parameters.
This prospective study was conducted in the Cardiology Department of the Medicine Faculty of Yüzüncü Yıl University (Van, Turkey) from March 2022 to May 2022. The study protocol was approved by the Clinical Research Ethics Committee of Van Yüzüncü Yıl University (Decision no. 02; decision date: March 30, 2022). All procedures were conducted in accordance with the ethical standards of the institutional research committee and with the Declaration of Helsinki and its later amendments. Written informed consent was obtained from all participants.
Study PopulationIn all, 160 newly diagnosed (i.e., those without prior prosthetic valve surgery) MVS patients aged between 18 and 90 years were examined as potential candidates, with 75 ultimately included in the study (Figure 1). The exclusion criteria were: presence of coronary artery disease, heart failure, atrial fibrillation, chronic kidney failure, chronic obstructive pulmonary disease, history of valve surgery, asthma, hypertension, diabetes, rheumatoid arthritis, cirrhosis, osteoporosis, malignancy and significant infections, the use of antioxidant and/or immunosuppressant medications within the previous 3 months, pregnancy, active smoking and alcohol usage, and a refusal to participate in the study.
Study flowchart.
Patients meeting the inclusion criteria were evaluated with a detailed medical history, complete physical and cardiological examination, and electrocardiographic and echocardiographic evaluation. All accessible and relevant clinical and demographic data were recorded. All echocardiographic measurements were performed by the same cardiologist while patients were at rest, according to American Society of Echocardiography guidelines18 and with using a General Electric Vivid E95 device and 2D M5Sc-D probe (GE Vingmed Ultrasound, Horten, Norway). M-Mode and Doppler echocardiographic measurements were made. Patients were classified based on MVS severity (mild, moderate, severe; see below) for comparisons, and further analyses were performed to detect parameters independently associated with having severe MVS. We also repeated regression analyses to assess factors associated with moderate or severe (moderate/severe) MVS by pooling these 2 (moderate and severe MVS) groups.
MVS, MV regurgitation (MVR), AV regurgitation (AVR), and tricuspid valve regurgitation (TVR) diagnosis and grading of patient were made by echocardiographic evaluation. MVS was defined as the presence of commissural fusion, thickening, and doming in the MV, and shortening and thickening of the chordae. The MV area (MVA) was measured using the planimetry method from the parasternal short axis. The diastolic maximal valve orifice was recorded. Continuous wave (CW) Doppler signals were registered parallel to mitral inflow in the apical 4-chamber view. Mean and maximum transmitral pressure gradient and MVA were calculated from the early diastolic flow pressure half-time.19 Mild MVS (n=25) was defined as MVA >2 cm2, moderate MVS (n=25) was defined as MVA 1.5–2 cm2, and severe MVS (n=25) was defined as MVA <1.5 cm2.20 MVR was assessed using color Doppler with the Nyquist limit set to 0.65 m/s. Either central or eccentric orientation of the regurgitation jet was recorded. MVR severity was roughly calculated by vena contracta and calculations of regurgitation fraction.19 AVR severity was established using the jet width to left ventricular outflow tract ratio, CW Doppler spectral volume, and pressure half-time of the AVR jet.19 Maximum velocity of the TVR jet was recorded with CW Doppler, and pulmonary artery pressure was calculated by adding anticipated right atrial pressure to the systolic pressure gradient across the tricuspid valve, calculated using the simplified Bernoulli equation (∆P=4V2, where ΔP is “pressure gradient” and V is “the peak continuous-wave doppler velocity”).19 A semiquantitative scale was used to grade valves regurgitation as follows: 0, none; 1+, trace; 2+, mild; 3+, moderate; and 4+, severe.21
In addition, using echocardiography, left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), systolic pulmonary artery pressure (SPAP), and left atrial conduit volume (LACV) were measured and/or calculated. Left atrial volume (LAV) and left ventricular volume (LVV) curves as a function of time were calculated simultaneously. Left atrial conduit volume (LACV), was calculated using following formula:22
LACV = (LVVmaximum − LVVminimum) − (LAVmaximum − LAVminimum)
Laboratory AnalysisBlood samples were obtained from the antecubital vein after patients had fasted for at least 8 h, and before echocardiographic evaluation. Blood was centrifuged at 1,500 g for 10 min at +4℃, after which serum samples were stored at −80℃ until biochemical analysis. All analyses were performed in the Clinical Chemistry Department of Yüzüncü Yıl University Faculty of Medicine.
Complete blood count (CBC), sodium, potassium, aspartate aminotransferase, alanine aminotransferase, and creatinine were measured using routine devices in accordance with routine protocols. Platelet, white blood cell (WBC), neutrophil, and lymphocyte counts, as well as platelet distribution width (PDW) and red blood cell distribution width (RDW), were obtained from routine CBC tests. The platelet-to-neutrophil ratio (PNR) was calculated by dividing the platelet count by the neutrophil count; the platelet-to-lymphocyte ratio (PLR) was calculated by dividing the platelet count by the lymphocyte count.
Catalase activity was measured using hydrogen peroxide as a substrate, as described by Aebi.23 Potassium phosphate buffer, hydrogen peroxide, and serum samples were mixed, and the absorption of the sample was detected 3 times at 240 nm at 30-s intervals. Catalase activity (in units/mL) was calculated as follows:
Catalase activity = [(3.45 × slope) / 0.05] × (1,000 / 50 µL)
Blood malondialdehyde (MDA) levels (μmol/L) were measured using the thiobarbituric acid-reactive substances (TBARS) Assay. Absorbance was evaluated at 535 nm or fluorescence intensity was measured at 560 nm/585 nm, with values being proportional to the concentration of TBARS in the blood sample.24 Blood SOD levels (ng/mL) were determined using a commercially available ELISA kit, which used the competitive ELISA method. Color alterations were measured by spectrophotometry at a wavelength of 450 nm (±2 nm).24 Levels of AOPP in the blood were measured by using a biochemical autoanalyzer using commercially available kits. AOPP levels are expressed in terms of micromolar chloramine-T equivalents (μmol/L).25 Serum glutathione levels (μmol/L) were measured using HPLC-mass spectrometry, as described previously.26
Statistical AnalysisStatistical significance was set at the classical threshold of two-tailed P<0.05 and all analyses were performed using IBM SPSS Statistics for Windows, Version 25.0 (IBM Corp., Armonk, NY, USA). The normality of distribution was evaluated using the Shapiro-Wilk test. According to the normality results, data for continuous variables are presented as either the mean±SD or median with interquartile range. Categorical variables are presented as frequencies and percentage. Normally distributed variables were analyzed using 1-way analysis of variance (ANOVA). Non-normally distributed variables were analyzed using the Kruskal-Wallis test. The distribution of categorical variables was compared between groups using Chi-squared tests or the Fisher-Freeman-Halton test. For pairwise corrections of >2-group comparisons, the Bonferroni method was used.
Pearson and Spearman correlation coefficients were calculated to evaluate relationships between OS markers and gradient, MVA, and echocardiographic continuous metrics. The performance of the variables in predicting MVS severity was assessed by receiver operating characteristic (ROC) curve analysis. Optimal cut-off points were determined using the Youden index. Multiple logistic regression analysis (forward conditional) was used to determine variables independently associated with MVS severity.
The mean age of patients in the mild, moderate, and severe MVS groups was 62.36±17.12, 57.44±17.77, and 55.84±17.15 years, respectively (P=0.388). Twenty (80.0%), 21 (84.0%), and 17 (68.0%) patients in the mild, moderate, and severe MVS groups, respectively, were female (P=0.372). Patients’ demographic and clinical characteristics, as well as measurements, according to MVS severity are summarized in Table 1. In the severe MVS group, the frequency of patients with 4+ MVR (P=0.007) and 3+ TVR (P=0.016) was significantly higher than the other 2 groups. The mean WBC value was significantly (P=0.020) higher in the severe than moderate MVS group. PNR (P=0.048) and sodium (P=0.025) values were significantly lower in the severe than mild MVS group. Catalase (P=0.002) and MDA (P<0.001) levels were significantly higher in the severe than mild MVS group. SOD (P<0.001), AOPP (P<0.001), and glutathione (P<0.001) levels were significantly higher in the severe than moderate MVS group, and were significantly higher in the moderate than mild MVS group.
| Mitral stenosis | P value | |||
|---|---|---|---|---|
| Mild (n=25) | Moderate (n=25) | Severe (n=25) | ||
| Age (years) | 62.36±17.12 | 57.44±17.77 | 55.84±17.15 | 0.388 |
| Female sex | 20 (80.0) | 21 (84.0) | 17 (68.0) | 0.372 |
| Ejection fraction (%) | 60 [55–60] | 60 [60–60] | 60 [50–60] | 0.097 |
| AVR grade | ||||
| 0 | 10 (40.0) | 16 (64.0) | 12 (48.0) | 0.262 |
| 1+ | 8 (32.0) | 3 (12.0) | 4 (16.0) | |
| 2+ | 3 (12.0) | 4 (16.0) | 6 (24.0) | |
| 3+ | 4 (16.0) | 2 (8.0) | 1 (4.0) | |
| 4+ | 0 (0.0) | 0 (0.0) | 2 (8.0) | |
| MVR grade | ||||
| 0 | 5 (20.0) | 8 (32.0) | 9 (36.0) | 0.007 |
| 1+ | 8 (32.0) | 4 (16.0) | 2 (8.0) | |
| 2+ | 11 (44.0) | 5 (20.0) | 5 (20.0) | |
| 3+ | 1 (4.0) | 7 (28.0) | 3 (12.0) | |
| 4+ | 0 (0.0)a | 1 (4.0)a,b | 6 (24.0)b | |
| TVR grade | ||||
| 0 | 11 (44.0) | 7 (28.0) | 6 (24.0) | 0.016 |
| 1+ | 4 (16.0) | 8 (32.0) | 3 (12.0) | |
| 2+ | 5 (20.0) | 7 (28.0) | 3 (12.0) | |
| 3+ | 0 (0.0)a | 1 (4.0)a | 8 (32.0)b | |
| 4+ | 5 (20.0) | 2 (8.0) | 5 (20.0) | |
| Mean gradient (mmHg) | 4 [4–5]a | 7 [6–8]b | 11 [11–14]c | <0.001 |
| Maximum gradient (mmHg) | 11 [10–12]a | 14 [11–16]a | 24 [15–26]b | <0.001 |
| Mitral valve area (cm2) | 2.3 [2.0–2.5]a | 1.6 [1.5–1.8]b | 1.0 [0.9–1.1]c | <0.001 |
| LVEDD (mm) | 47.52±5.90 | 47.08±5.11 | 48.80±4.55 | 0.484 |
| LVESD (mm) | 28 [25–35] | 32 [27–34] | 32 [30–34] | 0.489 |
| LACV (%) | 39.60±3.44 | 42.00±4.49 | 41.96±3.37 | 0.086 |
| SPAP (mmHg) | 22 [18–30] | 24 [20–30] | 34 [21–40] | 0.051 |
| Hemoglobin (g/dL) | 12.60±2.27 | 12.93±2.00 | 13.81±2.44 | 0.149 |
| Hematocrit (%) | 38.22±6.31 | 39.61±6.05 | 42.40±7.28 | 0.080 |
| Platelets (×103/μL) | 237 [206–322]a | 200 [179–232]b | 197 [174–248]b | 0.007 |
| WBC (×103/μL) | 7.07±1.84a,b | 6.79±2.51a | 8.74±3.26b | 0.020 |
| Neutrophils (×103/μL) | 4.1 [3.6–6.0] | 4.1 [3.0–5.4] | 4.7 [4.0–7.2] | 0.257 |
| Lymphocytes (×103/μL) | 1.8 [1.0–2.0] | 1.5 [1.0–2.0] | 1.6 [1.1–2.0] | 0.464 |
| PNR | 57.41 [43.60–97.65]a | 43.86 [32.40–76.75]a,b | 42.61 [30.16–51.94]b | 0.048 |
| PLR | 185.33 [151.67–234.00] | 130.00 [97.37–180.00] | 125.33 [85.00–177.06] | 0.051 |
| Sodium (mEq/L) | 140 [139–142]a | 139 [136–141]a,b | 138 [136–141]b | 0.025 |
| Potassium (mEq/L) | 4.25±0.41 | 4.03±0.48 | 4.15±0.73 | 0.379 |
| AST (U/L) | 18 [16–24] | 22 [16–27.61] | 21 [18–35] | 0.126 |
| ALT (U/L) | 20 [16–26] | 25 [15–34] | 18 [14–25] | 0.358 |
| Creatinine (mg/dL) | 0.72 [0.65–0.84] | 0.72 [0.68–0.99] | 0.81 [0.63–1.1] | 0.490 |
| PDW (%) | 16.51±0.53 | 16.63±0.44 | 16.72±0.62 | 0.409 |
| RDW (%) | 13.3 [12.8–14.3] | 13.5 [12.9–14.4] | 13.7 [12.9–14.2] | 0.838 |
| Catalase activity (U/mL) | 361.34 [354.22–374.65]a | 371.4 [361.34–380.25]a,b | 384.71 [374.26–393.66]b | 0.002 |
| MDA (μmol/L) | 0.66 [0.64–0.69]a | 0.70 [0.65–0.77]a,b | 0.77 [0.69–0.83]b | <0.001 |
| SOD (ng/mL) | 290.92±17.22a | 306.90±15.26b | 325.08±15.14c | <0.001 |
| AOPP (μmol/L) | 28.22±3.14a | 31.36±3.26b | 34.11±3.61c | <0.001 |
| Glutathione (μmol/L) | 3.64 [3.26–4.25]a | 4.58 [4.12–4.86]b | 5.42 [4.92–6.24]c | <0.001 |
Data for continuous variables are given as the mean±SD or median (interquartile) depending on the normality of distribution. Data for categorical variables are presented as n (%). a,b,cWithin rows, values with the same superscript letter do not differ significantly. ALT, alanine aminotransferase; AOPP, advanced oxidation protein products; AST, aspartate aminotransferase; AVR, aortic valve regurgitation; LACV, left atrial conduit volume; LVEDD, left ventricular end-diastolic diameter; LVESD, left ventricular end-systolic diameter; MDA, malondialdehyde; MVR, mitral valve regurgitation; PDW, platelet distribution width; PLR, platelet to lymphocyte ratio; PNR, platelet to neutrophil ratio; RDW, red blood cell distribution width; SOD, superoxide dismutase; SPAP, systolic pulmonary artery pressure; TVR, tricuspid valve regurgitation; WBC, white blood cell count.
Correlations between echocardiographic continuous metrics and OS markers are presented in Table 2. There were moderately significant positive correlations between the MV mean gradient and SOD (r=0.660, P<0.001), AOPP (r=0.537, P<0.001), and glutathione (r=0.598, P<0.001), as well as between MV maximum gradient and SOD (r=0.475, P<0.001) and AOPP (r=0.457, P<0.001). In addition, there was a moderately significant negative correlation between MVA and MDA (r=−0.445, P<0.001), SOD (r=−0.643, P<0.001), AOPP (r=−0.538, P<0.001) and glutathione (r=−0.619, P<0.001). No significant correlations (except for a few weak correlations) were found between LVEDD, LVESD, LACV, SPAP, and OS markers.
| Catalase | MDA | SOD | AOPP | Glutathione | |
|---|---|---|---|---|---|
| Mean gradient | |||||
| r | 0.368 | 0.415 | 0.660 | 0.537 | 0.598 |
| P | 0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
| Maximum gradient | |||||
| r | 0.336 | 0.343 | 0.475 | 0.457 | 0.396 |
| P | 0.003 | 0.003 | <0.001 | <0.001 | <0.001 |
| Mitral valve area | |||||
| r | −0.355 | −0.445 | −0.643 | −0.538 | −0.619 |
| P | 0.002 | <0.001 | <0.001 | <0.001 | <0.001 |
| LVEDD | |||||
| r | −0.110 | 0.224 | 0.155 | −0.231 | 0.059 |
| P | 0.349 | 0.053 | 0.185 | 0.046 | 0.615 |
| LVESD | |||||
| r | 0.255 | 0.167 | 0.076 | 0.041 | −0.050 |
| P | 0.027 | 0.152 | 0.517 | 0.726 | 0.667 |
| LACV | |||||
| r | 0.164 | 0.072 | 0.349 | 0.110 | −0.058 |
| P | 0.160 | 0.541 | 0.002 | 0.346 | 0.623 |
| SPAP | |||||
| r | 0.087 | 0.082 | 0.076 | 0.146 | 0.212 |
| P | 0.458 | 0.487 | 0.515 | 0.210 | 0.068 |
AOPP, advanced oxidation protein products; LACV, left atrial conduit volume; LVEDD, left ventricular end-diastolic diameter; LVESD, left ventricular end-systolic diameter; MDA, malondialdehyde; SOD, superoxide dismutase; SPAP, systolic pulmonary artery pressure.
The predictive performance of OS markers for severe MVS is summarized in Table 3 and shown in Figure 2. SOD in particular, with a cut-off value of >315.5 ng/mL for the detection of severe MVS, demonstrated high sensitivity (80.0%), specificity (88.0%), accuracy (85.3%), positive predictive value (PPV; 76.9%), and negative predictive value (NPV; 89.8%). Glutathione, with a cut-off value of >4.7 μmol/L, also showed good results (sensitivity 84.0%, specificity 80.0%, accuracy 81.3%, PPV 67.7%, NPV 90.9%). We also evaluated the performance of these markers in predicting moderate/severe MVS (Table 3; Figure 3). All parameters investigated demonstrated significant discriminatory value; however, despite high percentages for specificity and PPV, the sensitivity, accuracy, and NPV were generally low.
| Cut-off | Sensitivity (%) | Specificity (%) | Accuracy (%) | PPV (%) | NPV (%) | AUC (95% CI) | P value | |
|---|---|---|---|---|---|---|---|---|
| Severe mitral stenosis | ||||||||
| Catalase activity (U/mL) |
>381 | 64.0 | 82.0 | 76.0 | 64.0 | 82.0 | 0.722 (0.600–0.844) |
0.002 |
| MDA (μmol/L) | >0.72 | 72.0 | 78.0 | 76.0 | 62.1 | 84.8 | 0.741 (0.624–0.859) |
0.001 |
| SOD (ng/mL) | >315.5 | 80.0 | 88.0 | 85.3 | 76.9 | 89.8 | 0.885 (0.807–0.963) |
<0.001 |
| AOPP (μmol/L) | >34.5 | 56.0 | 92.0 | 80.0 | 77.8 | 80.7 | 0.802 (0.695–0.908) |
<0.001 |
| Glutathione (μmol/L) |
>4.7 | 84.0 | 80.0 | 81.3 | 67.7 | 90.9 | 0.864 (0.777–0.951) |
<0.001 |
| Moderate and severe mitral stenosis | ||||||||
| Catalase activity (U/mL) |
>366 | 76.0 | 72.0 | 74.7 | 84.4 | 60.0 | 0.708 (0.576–0.839) |
0.004 |
| MDA (μmol/L) | >0.72 | 54.0 | 92.0 | 66.7 | 93.1 | 50.0 | 0.742 (0.627–0.857) |
0.001 |
| SOD (ng/mL) | >307.6 | 68.0 | 92.0 | 76.0 | 94.4 | 59.0 | 0.852 (0.759–0.945) |
<0.001 |
| AOPP (μmol/L) | >30.8 | 74.0 | 76.0 | 74.7 | 86.0 | 59.4 | 0.823 (0.730–0.916) |
<0.001 |
| Glutathione (μmol/L) |
>4.5 | 70.0 | 88.0 | 76.0 | 92.1 | 59.5 | 0.839 (0.746–0.932) |
<0.001 |
AOPP, advanced oxidation protein products; AUC, area under the curve; CI, confidence interval; MDA, malondialdehyde; NPV, negative predictive value; PPV, positive predictive value; SOD, superoxide dismutase.
Receiver operating characteristic (ROC) curve for oxidative stress markers to predict severe mitral valve stenosis.
Receiver operating characteristic (ROC) curve for oxidative stress markers to predict moderate and severe mitral valve stenosis.
Multiple logistic regression analysis revealed that high WBC (P=0.023), high MDA (P=0.010), high SOD (P=0.008), and high AOPP (P=0.007) were independently associated with severe MVS. Other variables included in the analysis, namely age (P=0.329), sex (P=0.648), MVR (P=0.989), TVR (P=0.193), platelet count (P=0.981), PLR (P=0.821), sodium (P=0.542), catalase (P=0.590), and glutathione (P=0.313), were not significantly associated with severe MVS (Table 4).
| OR | 95% CI for Exp(β) | P value | Nagelkerke’s R2 | |
|---|---|---|---|---|
| Severe mitral stenosis | ||||
| WBC (×103) | 2.088 | 1.105–3.946 | 0.023 | 0.847 |
| MDA | 3.452×1013 | 1,610.969–7.398×1023 | 0.010 | |
| SOD | 1.242 | 1.059–1.456 | 0.008 | |
| AOPP | 1.963 | 1.205–3.195 | 0.007 | |
| Moderate and severe mitral stenosis | ||||
| Platelets (×103) | 0.977 | 0.957–0.998 | 0.030 | 0.844 |
| MDA | 3.669×1010 | 65.946–2.041×1019 | 0.018 | |
| SOD | 1.119 | 1.029–1.216 | 0.008 | |
| AOPP | 1.828 | 1.263–2.648 | 0.001 | |
AOPP, advanced oxidation protein products; CI, confidence interval; MDA, malondialdehyde; OR, odds ratio; SOD, superoxide dismutase; WBC, white blood cell.
When multiple logistic regression analysis was used to assess factors independently associated with moderate/severe MVS, the significant parameters were low platelet count (P=0.030), high MDA (P=0.018), high SOD (P=0.008), and high AOPP (P=0.001). Other variables included in the analysis, namely age (P=0.612), sex (P=0.254), MVR (P=0.912), TVR (P=0.693), WBC count (P=0.616), PNR (P=0.522), sodium (P=0.362), catalase (P=0.966), and glutathione (P=0.054), were not significantly associated with moderate/severe MVS (Table 4).
HVDs represent an important cause of loss of physical functionality, quality of life, and longevity.1 After the AV, the MV is the second most common valve affected by HVD.27 There is substantial evidence for the critical roles of OS in the initiation and progression of HVD.4 In the present study, high blood levels of MDA, SOD, and AOPP were independently associated with both severe MVS and moderate/severe MVS. In terms of discriminatory capability with a single variable, SOD and glutathione were determined as the strongest predictors of severe MVS.
MDA is an end product of the lipid peroxidation process that emerges by ROS attack on polyunsaturated fatty acids. Increased OS causes lipid peroxidation, and thus cellular damage. Measuring MDA levels also provides information about the presence and severity of OS.28 MDA is one of the most frequently used OS biomarkers in cardiovascular diseases (CVD).1 The reliability of high levels of MDA as an indicator of increased OS in CVD such as myocardial infarction and atherosclerosis has been reported.29,30 Although MDA is a marker of OS, few studies have investigated the relationship between MDA and HVD, especially in MVD. The present study showed that high blood MDA levels were associated with greater MVS severity. In a previous study, patients were divided into 3 groups: AV disease, MV disease, and controls.1 In that study, MDA levels in both the AV and MV disease groups were significantly higher than in the control group, but there was no significant difference between the AV and MV disease groups.1 In another study, MDA was identified as the most promising predictor of adverse outcomes during 30-day and 1-year follow-up in high-risk patients with symptomatic severe AVS treated with transcatheter AV implantation.15
AOPP, which are primarily formed by chlorinated oxidants resulting from myeloperoxidase activity, have been identified as another biomarker of OS.14 AOPP can provoke oxidative bursts of neutrophils, monocytes, and phagocytic cells, increase ROS production, and stimulate the secretion of cytokines, causing endothelial injury.31 They are also recognized as a new class of inflammatory mediators.31 Therefore, AOPP are used as an important marker in monitoring the progression of diseases such as atherosclerosis, in which OS and inflammation are critical.31,32 As for MDA, only a limited number of studies have investigated the relationship between AOPP and HVD. In the present study, high AOPP levels were also identified as an independent factor associated with both severe and moderate/severe MVS. In one study, blood AOPP levels was higher in patients with chronic rheumatic valvular disease than in healthy control patients, but there was no significant relationship between MVS severity and AOPP levels.16 However, the authors of that study suggested that one of the reasons for the high AOPP levels in patients who underwent valve surgery may have been more severe MVS.16 Although the specific pathophysiological effects of AOPP and MDA on MVS onset and progression are not yet known, it is important to understand that high AOPP and MDA levels are associated with MVS severity. In patients with mild MVS, MVS progression may be monitored by following AOPP and MDA levels, and, potentially, it may be possible to slow progression by administering antioxidants such as vitamin E (which can stabilize AOPP levels).32 However, for an accurate conclusion, randomized controlled trials are required.
OS occurs when the physiological balance between antioxidant mechanisms and ROS concentration is disrupted, resulting in increased ROS.1 Antioxidant enzymes and non-enzymatic antioxidants contribute to ROS control.9,10 Although in the present study blood catalase, SOD, and glutathione levels increased with MVS severity, a significant independent relationship was only detected for SOD. In addition, SOD and glutathione were found to have the best predictive values for the detection of severe MVS. A study of MV prolapse reported that catalase activity decreased significantly, whereas the activity of SOD and glutathione reductase increased, compared with controls.33 The authors of that study concluded that these parameters reflect an imbalance in ROS and the antioxidant defense system in MVP patients with low compensatory and adaptive reserves.33 Normally, an increase in oxidant factors and a decrease in antioxidants are expected in HVD, and numerous studies have demonstrated such findings in AV and MV diseases.16,17 Earlier studies have reported that patients with CVD have lower plasma glutathione levels.34,35 In fact, OS typically stimulates antioxidant mechanisms, so OS in most tissues often causes a compensatory and protective increase in SOD levels.36,37 However, in different CVD, the role of SOD may vary and there may be fundamental differences in the mechanisms leading to increased OS in AV disease and atherosclerotic vascular lesions.37,38 In the present study, the relationship between MVS severity and higher antioxidant enzyme activities may be explained as follows. First, previous studies largely focused on AVS and compared healthy controls to patients, whereas MVS severity has not been adequately studied. Second, depending on the degree of MVS severity, antioxidant enzymes may play different roles. Third, an increased ROS load may stimulate the release of antioxidant enzymes through positive feedback, similar to the effects in atherosclerotic vascular lesions. Of note, as demonstrated in the study of Rabus et al,39 there may be differences in favor of atrial fibrillation in terms of OS markers between MVS patients with atrial fibrillation and MVS patients without atrial fibrillation. Therefore, we excluded patients with atrial fibrillation from the present study because our aim was to explore the pure relationship between MVS with OS. Uncovering these potential relationships may be critical to ensuring better management of patients with MVS, and may prevent dangerous treatments, because surgery is recommended for patients with severe and/or symptomatic valve diseases,40 and it has been established by a recent meta-analysis (involving 5,572 elderly patients) that these surgeries carry a mortality risk of 15%.41 Addressing and countering OS as an important unifying mechanism involved in the initiation and propagation of heart valve degeneration and calcification may contribute to major and effective innovations in targeted therapy.27
We also investigated the relationship between various heart failure-related echocardiographic parameters and OS markers to demonstrate how the significant results obtained regarding the relationship between OS markers and MVS severity were affected by the previously reported relationship between heart failure and OS.42 However, we did not find any significant correlation (except for a few weak correlations) between LVEDD, LVESD, LACV, SPAP, and OS markers.
Various other blood parameters, indirectly related or unrelated to OS, have also been shown to be associated with HVD.43,44 Among these, inflammatory markers stand out. Inflammatory activation of the endothelium is proportionally associated with calcification in the heart valve.45 We determined that there was a significant association between elevated WBC and severe MVS, and the low number of platelets and moderate/severe MVS disease. There is leukocyte infiltration in regions with cardiac valve calcification, leading to valve stenosis.43 Leukocytes in inflammatory conditions may also contribute to increases in superoxide.38 Increased platelet aggregation plays a role in the pathophysiology of AVS in the early stages, similar to that in acute coronary syndrome.44 Thrombus formation may occur as a result of increased thrombotic activity in the calcified and stenotic AV.46,47 However, there is no clarified relationship between the platelet count and HVD. In previous studies, MPV, PDW, and PLR were found to be independently associated with MV annular calcification.48,49 Sucu et al reported that platelet indices, including MPV and PDW, were significantly higher in patients with AVS, but that the platelet count itself was similar to that in the control group.44 In another study, PLR, platelet count, and MPV were higher in severe AVS patients compared with a group with mild-moderate disease.50 Due to limited evidence on this topic, elucidating these pathophysiological mechanisms with further research may allow the development of new treatment strategies to prevent the progression of MVS.
Study LimitationsBecause this was a single-center study, the results cannot be generalized to the whole population. Using broad exclusion criteria was necessary to minimize the factors that may affect the level of OS markers, but this also limited the number of subjects that could be included in the study. There was no healthy control group in this study; only the severity of MVS was investigated. In addition, rheumatic and degenerative MVS patients were not evaluated separately. The reason for this was because we thought that the cause of MVS in our population was mostly rheumatic. Because the main purpose of the study was to investigate the factors associated with MVS severity and the duration of the study was short, treatment details and follow-up information of the patients were not included.
In conclusion, we found high blood MDA, SOD, and AOPP levels, as well as the WBC count, were independently associated with severe MVS. In addition, high levels of MDA, SOD, and AOPP, and a lower platelet count were independent variables associated with moderate/severe MVS. In particular, SOD (cut-off >315.5 ng/mL) and glutathione (cut-off >4.7 μmol/L) were found to be the strongest predictors of severe MVS. MVS severity seems to be affected by oxidant markers (MDA and AOPP), antioxidant enzymes (SOD), and inflammatory cells (WBC and platelets). If the precise roles of these markers in the pathogenesis of MVS can be determined by further comprehensive studies, new markers can be developed to predict MVS occurrence and progression. These can be used to monitor treatment response and prognosis.
The authors received no financial support for the research, authorship, and/or publication of this article.
The authors declare that they have no conflicts of interest.
The protocol for this study was approved by the Clinical Research Ethics Committee of Van Yüzüncü Yıl University (Decision no. 02; decision date March 30, 2022). All procedures were conducted in accordance with the ethical standards of the institutional research committee and with the Declaration of Helsinki and its later amendments.
