Abstract
Background
The oxidation of low-density lipoprotein cholesterol (LDL-C) plays a critical role in plaque inflammation and the subsequent high-risk plaque formation. However, the relationship between LDL-C oxidation and plaque morphology in patients with diabetes mellitus (DM) has not been systematically studied. The study aimed to investigate the association between LDL-C oxidation and plaque morphology assessed using optical coherence tomography (OCT).
Methods
A total of 138 patients with chronic coronary syndrome who underwent OCT were analyzed. Malondialdehyde-modified LDL-C (MDA-LDL), a representative form of oxidized LDL-C, was measured. Levels of LDL-C oxidation were assessed using the ratio of MDA-LDL to LDL-C ratio. Plaque morphology was assessed by OCT at the target lesions.
Results
Patients were divided into three groups according to the tertiles of LDL-C oxidation levels. Lipid index and macrophage grade were significantly higher in patients with higher levels of LDL-C oxidation in patients with DM (low vs. moderate vs. high; lipid index: 714 vs. 1226 vs. 2217, p for trend = 0.040; macrophage grade: 2 vs. 7 vs. 13, p for trend = 0.009). In contrast, no association was found in patients without DM (low vs. moderate vs. high; lipid index: 1109 vs. 1181 vs. 1436, p for trend = 0.633; macrophage grade: 8 vs. 5 vs. 8, p for trend = 0.748). Those associations remained significant even after adjusting for confounders in patients with DM but not in those without.
Conclusions
The levels of LDL-C oxidation were associated with plaque vulnerability, especially in patients with DM.
Keywords: Oxidized low-density lipoprotein cholesterol, Optical coherence tomography, Lipid-rich plaque, Macrophage, Diabetes mellitus
1. Introduction
The oxidative modification of low-density lipoprotein cholesterol (LDL-C) plays a key role in the progression of atherosclerosis [1]. Malondialdehyde (MDA), a product of oxidative fatty acid degeneration, is a marker for lipid peroxidation [2]. MDA modifies LDL-C particles, resulting in MDA-LDL formation, which is considered a representative form of oxidized LDL-C [3]. MDA-LDL is incorporated into macrophages by scavenger receptors, triggering atherosclerosis-related inflammation [1]. MDA-LDL is reportedly associated with coronary artery disease (CAD), particularly in acute coronary syndromes, indicating its role in developing plaque vulnerability [4,5]. Diabetes mellitus (DM) reportedly contributes to higher levels of oxidative stress and subsequent inflammation [6]. High blood glucose levels potentially promote monocyte adhesion to endothelial cells and the differentiation of monocytes into macrophages in subintimal space, facilitating macrophages to take up MDA-LDL [7]. Thus, MDA-LDL contributes to development of plaque vulnerability, particularly in patients with DM. Previously, hyperglycemia has been reported to be associated with plaque progression in patients with chronic coronary syndrome (CCS) [8]. However, the data on the relationship between levels of LDL-C oxidation and detailed plaque morphology remains scarce. Optical coherence tomography (OCT) has been recently used to evaluate plaque features at microscopic levels with high resolution [9]. Thus, the aim of this study was to investigate the association between LDL-C oxidation levels and plaque morphology with the help of OCT in patients with CCS, according to differences in diabetic status.
2. Methods
The data supporting this study's findings are available from the corresponding author upon reasonable request.
2.1. Study population
This study adopted an observational, single-center cohort design. Patients who underwent OCT-guided percutaneous coronary intervention (PCI) between January 2022 and October 2024 were enrolled in this study. All OCT imaging was performed at the operator's discretion. The culprit vessel was defined based on clinical and angiographic information and/or left ventricular regional wall motion abnormality. In cases of multivessel disease where the culprit vessel was not apparent, the choice was made based on the most severe lesion for patients with CCS or with residual stenotic lesions after PCI for ACS culprit lesions. A target lesion was defined as a lesion requiring PCI. When patients had multiple target lesions, the target lesion was identified as the lesion with the most severe stenosis. In cases where there was an inadequate antegrade coronary flow or if it was not possible to advance the OCT catheter, a predilatation could be performed using a small balloon with a diameter of 2 mm or less.
Among 549 patients, 190 patients underwent OCT imaging. Of those, 29 patients who underwent PCI for ACS culprit lesions, 17 patients with in-stent restenosis, and six patients with suboptimal image quality of OCT were excluded (Supplemental Fig. 1). Finally, 138 patients with 138 target lesions were included in the current study.
All participants provided written informed consent for the Yamagata OCT registry for potential future investigations, which was approved by the Ethics Committee of Yamagata University School of Medicine (approval no. no. 2022-17), in accordance with the Declaration of Helsinki and relevant national guidelines. The patient data were extracted from the Yamagata OCT registry database. Thus, the Yamagata University School of Medicine ethics committee granted a waiver of consent for this project. (approval no. 2024–299).
2.2. Cardiovascular risk factors
Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or antihypertensive medication use. DM was defined as a fasting blood sugar level of ≥126 mg/dL, glycosylated hemoglobin A1c ≥ 6.5 % (National Glycohemoglobin Standardization Program), or anti-diabetic medication use. Dyslipidemia was defined as high-density lipoprotein cholesterol <40 mg/dL, low-density lipoprotein cholesterol ≥140 mg/dL, triglyceride ≥150 mg/dL, or lipid-lowering medication use. The statin treatment was defined as statin treatment initiated more than a day before PCI.
2.3. OCT analysis
OCT was performed using a frequency domain (C7/C8, OCT Intravascular Imaging System, Abbott Laboratories Chicago, Illinois). All OCT images were analyzed by two independent investigators blinded to patient data using an offline review workstation (St. Jude Medical). Any disagreement was resolved by consensus with a third reviewer. Thin-cap fibroatheroma (TCFA) was defined as a plaque with a maximal lipid arc >90° and thinnest fibrous cap thickness < 65 μm [9]. Macrophage accumulation was defined as the presence of highly backscattering focal granular regions [9]. The degree of macrophage accumulation was graded as follows: grade 0, no macrophage; grade 1, localized macrophage accumulation; grade 2, clustered accumulation <1 quadrant; grade 3, clustered accumulation ≥1 quadrant but <3 quadrants; and grade 4, clustered accumulation ≥3 quadrants. Grading was performed every 1 mm along the entire target plaque, and the summation of 0 to 4 grades was calculated [10]. Lipid was defined as a signal-poor region with a diffuse border, and the degree of lipid arc was measured at 1 mm intervals [9]. Lipid length was obtained on the longitudinal view, and the lipid index was calculated as the product of the mean lipid arc and lipid length [11]. Lipid-rich plaque was defined as a plaque with a maximal lipid arc greater than 90° [9]. The definitions of other OCT features are provided in the Supplemental Methods. The intraclass correlation coefficients for intra-observer and inter-observer reproducibility were 0.944 and 0.899 for the lipid index, and 0.852 and 0.813 for the macrophage grade, respectively.
2.4. Measurement of LDL-C oxidation
Venous blood samples were obtained within 24 h before PCI during hospitalization. LDL-C levels were measured by enzymatic methods. MDA-LDL was measured as previously described [12]. MDA-LDL/LDL-C ratio was employed to evaluate LDL-C oxidation levels [13,14].
2.5. Statistical analysis
Continuous variables with a normal distribution were expressed as mean ± SD, while the median (interquartile range [25-75th percentile]) was used for nonnormally distributed variables. In comparing patient baseline characteristics, normally distributed variables were compared using the Student t-test, whereas nonnormally distributed variables were compared using the Mann-Whitney U test. Categorical data were expressed as absolute frequencies and percentages and compared using the χ2 test or Fisher exact test, as appropriate. The p for trend was calculated using the Jonckheere-Terpstra test for continuous dependent variables. Tukey's honestly significant difference test was used for multiple comparisons. Multiplicative interaction terms were used to calculate the statistical significance of the interaction between DM and LDL-C oxidation levels. In a multivariable regression analysis, the impacts of LDL-C oxidation levels on the OCT features of vulnerability was identified by a generalized linear model with identity link (continuous dependent variable) adjusting for confounders including age, gender, current smoker, high LDL-C (≥100 mg/dL), low HDL-C (<40 mg/dL for men and <50 mg/dL for women), high triglyceride (≥150 mg/dL), and eGFR, which were selected based on previous studies [[15], [16], [17]]. Subgroup analyses were conducted in patients without hemodialysis, those without PCI for ACS nonculprit lesions, those stratified by LDL-C level (<70 mg/dL or not), or by treatment with a sodium-glucose cotransporter 2 (SGLT2) inhibitor or not. For all tests, a two-sided p value < 0.05 was considered statistically significant. Statistical analyses were performed using R software, version 4.3.1 (R Foundation for Statistical Computing, Vienna, Austria).
3. Results
3.1. Baseline characteristics
Baseline characteristics are summarized in Table 1. The median age was 73 years, and 32 patients (23 %) were women. Of those, 126 patients (91.3 %) received the statin treatment before PCI. The median LDL-C levels were 76 and the median MDA-LDL levels were 71 U/L. The median MDA-LDL/LDL-C ratio, the LDL-C oxidation level, was 0.95.
Table 1.
Baseline characteristics.
| All (n = 138) | |
|---|---|
| Age, median (IQR), years | 73 (65–79) |
| Women, No (%) | 32 (23.2) |
| Body mass index, median (IQR), kg/m2 | 23.6 (22.1–26.5) |
| Risk factors, No (%) | |
| Hypertension | 108 (78.3) |
| Hyperlipidemia | 98 (71.0) |
| Diabetes mellitus | 66 (47.8) |
| Chronic kidney disease | 34 (24.6) |
| Current smoker | 19 (13.8) |
| Hemodialysis, No (%) | 18 (13.0) |
| AF, No (%) | 15 (10.9) |
| prior PCI, No (%) | 77 (55.8) |
| Prior CABG, No (%) | 10 (7.2) |
| History of ACS, No (%) | 48 (34.8) |
| Laboratory data | |
| MDA-LDL, median (IQR), U/L | 71 (55–91) |
| LDL-C, median (IQR), mg/dL | 76 (61–99) |
| LDL-C oxidation levels (MDA-LDL/LDL), median (IQR) | 0.95 (0.72–1.18) |
| HDL-C, median (IQR), mg/dL | 45 (38–53) |
| Triglyceride, median (IQR), mg/dL | 108 (82–147) |
| HbA1c, median (IQR), % | 6.2 (5.8–6.8) |
| eGFR, median (IQR), mL/min/1.73 m2 | 63 (49–76) |
| Target vessels | |
| LAD | 57 (41.3) |
| RCA | 49 (35.5) |
| LCX | 31 (22.5) |
| Other | 1 (0.7) |
| Medication before PCI, No (%) | |
| P2Y12 inhibitor | 130 (94.2) |
| Aspirin | 128 (92.8) |
| ACEi | 23 (16.7) |
| ARB | 55 (39.9) |
| ARNI | 24 (17.4) |
| β-blocker | 76 (55.1) |
| Statin | 126 (91.3) |
| SGLT2i | 44 (31.9) |
| Other anti-diabetic agents | 44 (31.9) |
| DOAC | 12 (8.7) |
| Warfarin | 2 (1.4) |
| Insulin | 7 (5.1) |
Data are given as n (%), mean ± SD or median (IQR). ACEi, angiotensin-converting enzyme inhibitor; AF, atrial fibrillation; ARB, angiotensin II receptor blocker; ARNI, angiotensin receptor neprilysin inhibitor; CABG, Coronary artery bypass grafting; DOAC, direct oral anticoagulant; eGFR, estimated glomerular filtration rate; HbA1c, glycosylated hemoglobin; HDL—C, high-density lipoprotein cholesterol; LAD, Left Anterior Descending artery; LCX, left circumflex artery; LDL-C, low-density lipoprotein cholesterol; MDA-LDL, Malondialdehyde-modified low-density lipoprotein; RCA, right coronary artery; SGLT2i, Sodium-Glucose Transport 2 inihibitor; PCI, percutaneous coronary intervention; P2Y12, purinergic receptor type Y, subtype 12.
3.2. OCT findings
A total of 138 target lesions were imaged by OCT in 138 patients. Patients were divided into three groups based on the tertiles of LDL-C oxidation levels (MDA-LDL/LDL-C ratio) (low: < 0.80; moderate 0.80–1.09; high: ≥1.10). Lipid index and macrophage grade increased as LDL-C oxidation levels increased in whole patients (p for trend = 0.004 and 0.011, respectively) (Fig. 1). Other OCT findings are summarized in Table 2. The prevalence of TCFA is numerically higher as LDL-C oxidation levels increased, although that did not reach statistical significance. The results were similar in patients without ACS non-culprit lesions or without hemodialysis (Table S2 and S3).
Fig. 1.
The association between LDL-C oxidation levels and plaque vulnerability
Patients were divided into three groups based on the tertiles of LDL-C oxidation levels (low: <0.80; moderate: 0.80–1.09; high: ≥1.10). The p for trend was calculated using the Jonckheere-Terpstra test.
Table 2.
Other OCT findings.
| MDA/LDL-C ratio |
||||
|---|---|---|---|---|
| Low (n = 44) | Moderate (n = 54) | High (n = 40) | p value | |
| Qualitative analysis, No (%) | ||||
| TCFA | 6 (13.6) | 12 (22.2) | 11 (27.5) | 0.293 |
| Lipid-rich plaque | 31 (70.5) | 42 (77.8) | 32 (80.0) | 0.640 |
| Macrophage | 28 (63.6) | 39 (72.2) | 30 (75.0) | 0.531 |
| Microvessels | 22 (50.0) | 28 (51.9) | 19 (47.5) | 0.938 |
| Cholesterol crystal | 16 (36.4) | 18 (33.3) | 14 (35.0) | 0.976 |
| Layered plaque | 24 (54.5) | 30 (55.6) | 24 (60.0) | 0.888 |
| Multilayered plaque | 4 (9.1) | 7 (13.0) | 6 (15.0) | 0.724 |
| Thrombus | 1 (2.3) | 2 (3.7) | 1 (2.5) | >0.999 |
| Ruptured plaque | 4 (9.1) | 5 (9.3) | 4 (10.0) | >0.999 |
| Spotty calcification | 19 (43.2) | 22 (40.7) | 15 (37.5) | 0.862 |
| Quantitative analysis | ||||
| Maximal lipid arc, ° | 194 (35–295) | 208 (103−310) | 244 (126–296) | 0.253 |
| Maximal calcification arc, ° | 114 (67–293) | 98 (48–185) | 113 (51–319) | 0.959 |
| Maximal layer arc, ° | 102 (0−223) | 116 (0–247) | 136 (0−210) | 0.961 |
| Lipid index, | 854 (32–1806) | 1221 (171–2930) | 1964 (401–3158) | 0.024 |
| Calcium index | 535 (216–1864) | 304 (88–1657) | 894 (86–3028) | 0.268 |
| Layer index | 296 (0–1373) | 445 (0–1198) | 421 (0–1713) | 0.555 |
| Macrophage Grade | 4 (0−11) | 6 (0−13) | 11 (2–19) | 0.023 |
| MLA, mm2 | 1.3 (0.9–1.7) | 1.6 (1.2–1.9) | 1.5 (1.1–1.8) | 0.732 |
| Area stenosis, % | 75.4 (68.7–82.2) | 73.0 (67.9–82.6) | 76.2 (72.0–80.4) | 0.764 |
| Lesion length, mm | 21.0 (18.1–28.2) | 24.5 (18.4–32.0) | 28.4 (22.1–39.2)a | 0.024 |
Patients were divided into three groups based on the tertiles of MDA/LDL-C (low: <0.80; moderate 0.80–1.09; high: ≥1.10).
The p values were calculated by chi-square test for categorical variables or Mann-Whitney test for continuous variables.
Tukey's honestly significant difference test was used for multiple comparisons.
Indicates p < 0.05 vs Low group.
We compared baseline characteristics between subgroups with DM and those without. Baseline characteristics with and without DM are summarized in Supplemental Table 1. Patients with DM had higher BMI and lower LDL-C levels but higher LDL-C oxidation levels than those without. The median HbA1c of patients with DM was 6.8 %. Fig. 2 shows the association of LDL-C oxidation levels with lipid index and macrophage grade in patients with DM and those without. Lipid index and macrophage grade increased as LDL-C oxidation levels increased in DM patients, whereas no association was found in patients without DM. Furthermore, LDL-C oxidation levels were more profoundly associated with lesion length in patients with DM than in those without. Table 3 summarizes the results of the effect modification of DM on the association between LDL-C oxidation levels and OCT features of plaque vulnerability. Interaction p was significant for macrophage grade and lesion length. (Interaction p = 0.045 and 0.006, respectively) The results were consistent irrespective of LDL-C levels and the treatment with the SGLT2 inhibitor (Tables S4 and S5). The representative cases are shown in Fig. 3.
Fig. 2.
The association between LDL-C oxidation levels and plaque vulnerability in patients with and without DM
Patients were divided into three groups based on the tertiles of LDL-C oxidation levels (low: <0.80; moderate: 0.80–1.09; high: ≥1.10). The p for trend was calculated using the Jonckheere-Terpstra test. A) in patients with diabetes mellitus (DM). B) in patients without DM.
Table 3.
The association between LDL-C oxidation levels and OCT features in patients with or without DM.
| DM |
Non-DM |
Interaction p | |||||
|---|---|---|---|---|---|---|---|
| Low (n = 19) | Moderate (n = 19) | High (n = 28) | Low (n = 25) | Moderate (n = 35) | High (n = 12) | ||
| Qualitative analysis, No (%) | |||||||
| TCFA | 2 (10.5) | 5 (26.3) | 9 (32.1) | 4 (16.0) | 7 (20.0) | 2 (16.7) | 0.314 |
| Lipid-rich plaque | 11 (57.9) | 15 (78.9) | 22 (78.6) | 20 (80.0) | 27 (77.1) | 10 (83.3) | 0.402 |
| Macrophage | 10 (52.6) | 16 (84.2) | 22 (78.6) | 18 (72.0) | 23 (65.7) | 8 (66.7) | 0.136 |
| Microvessels | 7 (36.8) | 10 (52.6) | 12 (42.9) | 15 (60.0) | 18 (51.4) | 7 (58.3) | 0.667 |
| Cholesterol crystal | 6 (31.6) | 7 (36.8) | 11 (39.3) | 10 (40.0) | 11 (31.4) | 3 (25.0) | 0.269 |
| Layered plaque | 9 (47.4) | 9 (47.4) | 16 (57.1) | 15 (60.0) | 21 (60.0) | 8 (66.7) | 0.835 |
| Multilayered plaque | 2 (10.5) | 4 (21.1) | 5 (17.9) | 2 (8.0) | 3 (8.6) | 1 (8.3) | 0.801 |
| Thrombus | 0 (0.0) | 1 (5.3) | 1 (3.6) | 1 (4.0) | 1 (2.9) | 0 (0.0) | 0.252 |
| Ruptured plaque | 1 (5.3) | 1 (5.3) | 4 (14.3) | 3 (12.0) | 4 (11.4) | 0 (0.0) | 0.112 |
| Spotty calcification | 7 (36.8) | 6 (31.6) | 9 (32.1) | 12 (48.0) | 16 (45.7) | 6 (50.0) | 0.807 |
| Quantitative analysis | |||||||
| Maximal lipid arc, ° | 158 (0–285) | 230 (135–360) | 254 (107–360) | 227 (132–328) | 186 (96–282) | 232 (208–267) | 0.298 |
| Maximal calcification arc, ° | 180 (80–360) | 120 (74–182) | 113 (52–316) | 90 (62–196) | 93 (0–214) | 106 (14–320) | 0.268 |
| Maximal layer arc, ° | 0 (0–236) | 0 (0–219) | 101 (0–229) | 115 (0−211) | 157 (0–247) | 165 (0–181) | 0.865 |
| Lipid index, | 714 (0–1565) | 1226 (177–2901) | 2217 (349–3484) a | 1109 (338–1798) | 1181 (175–2922) | 1436 (535–2689) | 0.051 |
| Calcium index | 752 (351–2130) | 719 (217–1707) | 1023 (155–3028) | 488 (88–1841) | 235 (0–1585) | 492 (11–2306) | 0.950 |
| Layer index | 0 (0–1565) | 0 (0−1010) | 421 (0–1875) | 334 (0−1221) | 612 (0–1363) | 504 (0–967) | 0.732 |
| Macrophage grade | 2 (0–9) | 7 (3−11) | 13 (4–21) a | 8 (0–14) | 5 (0−20) | 8 (0–13) | 0.045 |
| MLA, mm2 | 1.3 (1.1–1.8) | 1.4 (0.9–1.8) | 1.4 (1.1–1.9) | 1.3 (0.9–1.7) | 1.6 (1.3–2.0) | 1.6 (1.1–1.8) | 0.333 |
| Area stenosis, % | 73.2 (68.7–80.6) | 80.2 (68.8–84.2) | 76.2 (72.7–80.4) | 76.9 (68.8–83.0) | 71.2 (65.7–80.3) | 75.2 (71.4–79.4) | 0.202 |
| Lesion length, mm | 20.0 (15.6–26.8) | 23.2 (20.1–28.3) | 32.0 (24.5–39.8)a, b | 22.4 (19.0–29.6) | 24.8 (17.7–33.1) | 26.4 (15.1–29.3) | 0.006 |
Data are given as n (%), mean ± SD, or median (IQR). Patients were divided into three groups based on the tertiles of LDL-C oxidation levels (low: <0.80; moderate 0.80–1.09; high: ≥1.10). The p values were calculated by the chi-square test for categorical variables or the Mann-Whitney test for continuous variables. Tukey's honestly significant difference test was used for multiple comparisons. Multiplicative interaction terms were used to calculate the statistical significance of the interaction between DM and LDL-C oxidation levels. a indicates p < 0.05 vs Low group. b indicates p < 0.05 vs the Moderate group. DM, diabetes mellitus.
Fig. 3.
Representative cases
A case of a 74-year-old man with low LDL-C oxidation levels is shown in the left panel. He dominantly presents calcified plaque (white arrowhead) without lipid accumulation (white arrow) and macrophage infiltration (white arrowhead). A case of a 76-year-old man with high LDL-C oxidation levels is shown in the right panel. His target plaque is characterized by a significant accumulation of lipids and macrophage infiltration throughout the plaque.
3.3. Multivariable analyses
Multivariable analyse for the lipid index was conducted to adjust for confounders (Table 4). LDL-C oxidation levels remained significant in all patients after adjusting confounders. However, the association was more pronounced in subgroups with DM, while no association was found in those without. Similarly, the LDL-C oxidation levels were significantly associated with macrophage grade in all patients after adjusting confounders. LDL-C oxidation levels were associated with macrophage grade in subgroups with DM, while there was no association in those without DM (Table 5).
Table 4.
Multivariable analyses for factors related to lipid index.
| Variables | Univariable |
Multivariable |
||||
|---|---|---|---|---|---|---|
| β | 95 % CI | p value | β | 95 % CI | p value | |
| All | ||||||
| LDL-C oxidation levels | 0.553 | −0.078, 1.184 | 0.086 | 0.781 | 0.112, 1.449 | 0.022 |
| DM | ||||||
| LDL-C oxidation levels | 0.925 | 0.010, 1.839 | 0.047 | 1.136 | 0.117, 2.154 | 0.029 |
| Non-DM | ||||||
| LDL-C oxidation levels | 0.220 | −0.613, 1.054 | 0.605 | 0.218 | −0.554, 0.989 | 0.580 |
The dependent variable is transformed: log(1 + analyte). Multivariable analyses were conducted in whole populations and subgroups stratified by diabetes mellitus (DM). Confounders include age, gender, current smoker, high LDL-C (≥100 mg/dL), low HDL-C (<40 mg/dL for men and < 50 mg/dL for women), high triglyceride (≥150 mg/dL), and eGFR.
Table 5.
Multivariable analyses for factors related to macrophage grade.
| Variables | Univariable |
Multivariable |
||||
|---|---|---|---|---|---|---|
| β | 95 % CI | p value | β | 95 % CI | p value | |
| All | ||||||
| LDL-C oxidation levels | 0.285 | 0.004, 0.566 | 0.047 | 0.330 | 0.016, 0.644 | 0.039 |
| DM | ||||||
| LDL-C oxidation levels | 0.558 | 0.212, 0.904 | 0.002 | 0.532 | 0.122, 0.943 | 0.011 |
| Non-DM | ||||||
| LDL-C oxidation levels | −0.077 | −0.526, 0.373 | 0.738 | −0.074 | −0.513, 0.365 | 0.741 |
The dependent variable is transformed: log(1 + analyte). Multivariable analyses were conducted in whole populations and subgroups stratified by diabetes mellitus (DM). Confounders include age, gender, current smoker, high LDL-C (≥100 mg/dL), low HDL-C (<40 mg/dL for men and <50 mg/dL for women), high triglyceride (≥150 mg/dL), and eGFR.
4. Discussion
The current study demonstrated the following: 1) LDL-C oxidation levels were significantly associated with degrees of lipid accumulation and macrophage infiltration assessed by OCT; 2) those associations were more pronounced in patients with DM.
4.1. LDL-C oxidation and CAD
Numerous reports have shown that oxidized LDL-C has a causative role in the development of high-risk plaques, leading to acute coronary syndromes [5,[18], [19], [20], [21]]. Tsimikas et al. reported that serum oxidized LDL-C levels were associated with the presence of obstructive CAD [18,19], especially in patients who presented with acute coronary syndromes compared with those without [5,20,21]. The LDL-C oxidation levels, assessed by MDA-LDL, have been reported to be associated with worse clinical outcomes [12,22]. Furthermore, OCT studies have demonstrated that MDA-LDL is associated with the presence of TCFA and more significant macrophage infiltration [10,23]. The mechanics and kinetics of oxidized LDL-C in the bloodstream remain unclear. Oxidized LDL-C might accumulate in high-risk plaques and be partly released from them into the bloodstream [19]. Unlike serum levels of oxidized LDL-C, the MDA-LDL / LDL-C ratio may indicate LDL-C's susceptibility or extent to lipid peroxidation, an essential process believed to occur when a plaque becomes vulnerable. MDA-LDL is a reliable biomarker for systemic oxidative stress [14]. MDA-LDL is formed when the lysine residues of apolipoprotein B-100 are modified by MDA, leading to structural and functional changes in LDL-C [24]. MDA-LDL/LDL-C ratio is employed as one of the LDL-C oxidation, indicating a proportion of MDA-modified LDL-C among total LDL-C [25]. Since LDL-C levels can fluctuate due to various factors, using a ratio of MDA-LDL/LDL-C ratio can reflect the extent of LDL-C oxidation relative to total LDL-C, offering an adequate measure of lipid peroxidation. Beyond the positive correlation between MDA-LDL and lipoproteins, MDA-LDL/LDL-C ratio is reportedly associated with obstructive CAD [19]. Toshima et al. reported a significant correlation between CAD and MDA-LDL/apolipoprotein B ratio but not serum levels of MDA-LDL [26]. These findings indicate the key role of LDL-C oxidation in developing high-risk plaques rather than circulating oxidized LDL-C.
However, the relationship between LDL-C oxidation and plaque morphology has not been fully investigated, especially in vivo. The current study demonstrated that levels of LDL-C oxidation were associated with lipid accumulation and macrophage infiltration, especially in patients with DM. Hiraya et al. demonstrated that circulating MDA-LDL levels were associated with the presence of high-intensity plaque in T1-weighted magnetic resonance imaging [12], indicating the association between MDA-LDL and intraplaque hemorrhage, which is considered to be involved in developing high-risk plaque through ferroptosis, regulated cell death driven by iron-dependent lipid peroxidation [27].
4.2. LDL-C oxidation and plaque morphology
The LDL-C oxidation levels reportedly increase both in circulation and within plaques with macrophage infiltration [28]. The results also showed that the LDL-C oxidation levels were nearly 70 times higher than in plasma from the same patient [28]. Oxidized LDL-C is absorbed by macrophages, triggering inflammatory responses. These responses are essential for forming foam cells, which can be observed on OCT. [9,29] Due to the low prevalence of TCFA in patients with CCS, the current study did not find an association between LDL-C oxidation levels and TCFA, unlike the previous research [23]. Komukai et al. demonstrated that reducing MDA-LDL levels was parallel with thicker fibrous-cap thickness [10]. They also showed that the changes in MDA-LDL levels were not associated with macrophage grade assessed by OCT. Thus, the association between serum levels of MDA-LDL and plaque vulnerability remains controversial. The current study found that MDA-LDL was associated with lipid index and macrophage grades when converted to the MDA-LDL/LDL-C ratio in patients with CCS, especially those with DM. This finding indicates that lipid peroxidation plays a critical role in forming high-risk plaques under environments where reactive oxygen species (ROS) are actively produced, such as DM [30].
The LDL-C oxidation levels are reportedly increased in patients with DM, reflecting the systemic increase of ROS [30]. The expression of LOX-1, a scavenger receptor for oxidized LDL-C, is reportedly upregulated in patients with DM [31]. Lipid peroxidation induced by MDA has been observed to occur at an increased rate in smaller LDL-C particles, which tend to be reduced in size in patients with DM [13,32]. Moreover, high glucose levels facilitate the migration of monocytes treated with oxidized LDL-C to the endothelial cell monolayer, triggering the pro-inflammatory response [33]. In addition to increased ROS production, endogenous antioxidant mechanisms are impaired in DM patients. This condition exacerbates lipid peroxidation that leads to ferroptosis, eventually forming rupture-prone plaques with large necrotic cores in patients with DM, which aligns with our findings.
Statins and ezetimibe have been demonstrated to lower MDA-LDL in parallel with LDL-C [34,35]. The current study highlights that lipid peroxidation may play a significant role in the formation of high-risk plaques, particularly in patients with DM. These findings may advocate for more aggressive interventions targeting lipid peroxidation mechanisms to mitigate plaque vulnerability, especially in patients with DM.
5. Limitations
There are some limitations to our study. First, this study was a cross-sectional, single-center study and included only the Japanese population. Consequently, the generalizability of the present results to other populations with different ethnic backgrounds may be limited. Furthermore, among the 549 patients treated with PCI, OCT imaging was performed in 190 cases, representing a relatively limited subset. This selection bias constitutes an important limitation of the study and warrants consideration when interpreting the findings. Second, we used MDA-LDL which is one of oxidized LDL-C type and did not measure others, which may provide additional insight. Various oxidation-modified substances serve as biomarkers for measuring oxidation of LDL-C, including 4-hydroxy-nonenal-modified LDL-C, carboxymethyl lysine-modified LDL-C, and oxidized phospholipid-modified LDL-C besides MDA-LDL [33]. Thus, in this study, we did not demonstrate the association between the full range of oxidation of LDL-C and plaque vulnerability in patients with DM. However, MDA-LDL is reportedly a stable marker of lipid peroxidation, which is widely used in clinical practices. Third, the sample size in this study was relatively small. Therefore, the current study could not adapt the study design to investigate the association between MDA-LDL and clinical outcomes. Lastly, OCT was conducted only in a target vessel requiring PCI, which limited the ability to assess the relationship between LDL-C oxidation and plaque vulnerability across the entire coronary artery tree.
6. Conclusions
The levels of LDL-C oxidation were associated with high-risk plaque formation, such as lipid accumulation and macrophage infiltration, especially in patients with DM. Integrating lipid peroxidation markers such as the MDA-LDL/LDL-C ratio into risk stratification strategies may enhance the early identification of high-risk patients, particularly those with DM, and inform tailored interventions to prevent plaque progression.
CRediT authorship contribution statement
Jun Goto: Writing – original draft, Investigation, Data curation. Daisuke Kinoshita: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Yoichiro Otaki: Writing – review & editing, Visualization, Project administration, Methodology, Funding acquisition. Seisei Ra: Validation, Methodology. Hiroe Ono: Formal analysis, Data curation. Takafumi Mito: Methodology, Investigation, Formal analysis. Taku Shikama: Methodology, Investigation, Data curation. Shingo Tachibana: Methodology, Investigation, Formal analysis. Shigehiko Kato: Supervision, Software, Methodology, Investigation. Tetsu Watanabe: Writing – review & editing, Visualization, Supervision, Software. Ik-Kyung Jang: Writing – review & editing, Supervision, Methodology, Investigation. Masafumi Watanabe: Writing – review & editing, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization.
Source of funding
This study did not receive any specific funding.
Declaration of competing interest
All authors declare no conflicts of interest for this contribution.
Acknowledgments
None.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.ahjo.2025.100691.
Appendix A. Supplementary data
Supplementary material
References
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