Abstract
The relationship between subclinical coronary atherosclerosis and lipoprotein(a) (Lp[a]) in asymptomatic people with and without diabetes mellitus (DM) is not well understood. We conducted a retrospective analysis of 7201 asymptomatic people (average age 54.4 ± 7.9 years; 65.3% male) who voluntarily had coronary computed tomography angiography (CCTA) as part of a general health evaluation and had no history of coronary artery disease (CAD). The severity and extent of subclinical coronary atherosclerosis were assessed using CCTA, with obstructive CAD defined as a diameter stenosis of at least 50%. Based on their Lp(a) levels, the study participants were divided into tertiles. To assess the relationship between Lp(a) levels and subclinical coronary atherosclerosis, logistic regression analysis was used. In participants without DM (n = 6252), after adjusting for cardiovascular risk factors, there were no statistically significant differences in the adjusted odds ratios (ORs) for calcified plaque, mixed plaque, non-calcified plaque, and obstructive CAD in the third Lp(a) tertile compared to the first tertile (p > 0.05 for all). On the other hand, in participants with DM (n = 949), there were no statistically significant differences in the ORs for calcified plaque (1.117, 95% confidence interval [CI] 0.794–1.572), mixed plaque (1.552, 95% CI 0.888–2.714), or non-calcified plaque (1.735, 95% CI 0.980–3.072) between the first and third Lp(a) tertiles. However, the adjusted ORs for obstructive CAD (2.051, 95% CI 1.248–3.372) were significantly higher in the third Lp(a) tertile compared to the first Lp(a) tertile. In asymptomatic individuals with DM, higher Lp(a) levels were associated with obstructive CAD, which may be linked to an increased risk of cardiac events.
Keywords: Lipoprotein(a), Diabetes mellitus, Coronary atherosclerosis, Coronary artery disease, Coronary computed tomography angiography
Subject terms: Cardiology, Cardiovascular diseases, Diabetes complications
Introduction
Coronary artery disease (CAD) is the primary cause of morbidity and mortality worldwide 1. Diabetes mellitus (DM) is a well-known risk factor for CAD and is also associated with high mortality 2. However, in patients with DM, CAD events are often asymptomatic until the onset of myocardial infarction or sudden cardiac death 3. Accordingly, it is important to identify and correct the residual risk factors to reduce the incidence of CAD-related events in these patients. Among the potential risk factors, the evolving role of lipoprotein(a) (Lp[a]) has been increasingly recognized4–6.
Lp(a) is composed of a low-density lipoprotein-like particle where apolipoprotein B is covalently bound to apolipoprotein A by a single disulfide bond 7. Through its proatherogenic, proinflammatory, and prothrombotic components, Lp(a) has been suggested to contribute to cardiovascular diseases 8. Several studies have shown that higher Lp(a) levels are related to CAD, stroke, peripheral artery disease, and even to coronary artery plaque progression 4–6,9–11. Furthermore, some studies have reported a link between Lp(a) levels and high-risk coronary plaque characteristics or accelerated progression of low-attenuation plaques, as assessed by CCTA 10,11. In addition, previous studies observed that effect of Lp(a) might be different in individuals with and without CAD according to the presence of DM 12,13. Therefore, the primary aim of this study was to assess the impact of Lp(a) on subclinical coronary atherosclerosis in relation to the presence of DM, using a large cohort of Korean patients without symptoms who willingly underwent CCTA to detect CAD early.
Methods
Study population
A total of 8,103 consecutive Koreans aged ≥ 20 who had received a general health examination at Ulsan University Hospital’s Health Promotion Center between March 2014 and March 2020 were retrospectively enrolled. Figure 1 describes the participant selection process in detail. After excluding ineligible participants, 7201 were evaluated in this study, as previously described14.
Fig. 1.
Overview of the study population. CCTA = coronary computed tomographic angiography; DM = diabetes mellitus; Lipoprotein(a) = Lp(a); MI = myocardial infarction; PCI = percutaneous coronary intervention.
Clinical and laboratory Assessments
We collected clinical and laboratory information from the electronic medical records and the clinical data warehouse platform of Ulsan University Hospital. Height, body weight, waist circumference, and blood pressure were measured in a standard manner during the general medical checkup as previously described 14. After overnight fasting, blood samples were analyzed for fasting blood glucose, hemoglobin A1c, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, creatinine, uric acid, and Lp(a) levels. Lp(a) levels were measured using a cobas® c 702 analyzer (Roche Diagnostics, Germany). 14 The corrected LDL-C level was determined by subtracting the Lp(a) mass multiplied by 0.3 from the LDL-C level 8. Each participant underwent a standard 12-lead electrocardiography. Transthoracic echocardiography was used to calculate the left ventricular ejection fraction.
DM was defined as fasting plasma glucose ≥ 126 mg/dL, hemoglobin A1c ≥ 6.5%, or a self-reported history of diabetes and/or treatment of diabetes with dietary modification or anti-diabetic medication. Prediabetes was defined as fasting plasma glucose 100–125 mg/dL or hemoglobin A1c 5.7–6.4%. Participants with normoglycemia or prediabetes were defined as being without diabetes. Body mass index ≥ 25 kg/m2 was adopted as the World Health Organization’s Asian-specific criterion for obesity. Hypertension was defined as a systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or a self-reported history of hypertension and/or the use of antihypertensive medication. Total cholesterol ≥ 240 mg/dL or a self-reported history of hyperlipidemia and/or usage of anti-hyperlipidemic medication were considered indicator of hyperlipidemia 14. A first-degree relative of any age with CAD was considered to have a family history of CAD15.
Coronary computed tomography angiography imaging and analysis
CCTA was conducted using single-source 256-slice CT (Brilliance iCT; Philips Healthcare, Best, Netherlands) or dual-source CT (Somatom Definition Flash; Siemens, Erlangen, Germany). The detailed CCTA protocol has been previously described 14. A proficient cardiovascular radiologist and cardiologist (S.H.C. and G.M.P., each with over 10 years of experience) used a specialized workstation (Syngo.via, Siemens or Aquarius iNtuition, Terarecon) to analyze all CCTA images and calcium score. Consensus was used to make final conclusions about the findings. The coronary artery calcium score (CACS) was quantified using the Agatston score and categorized as follows: 0, 1–10, 11–100, 101–400, and > 400 16. Plaques with more than 50% calcified tissue (density > 130 Hounsfield units) were categorized as calcified, those with less than 50% calcium as mixed, and those without calcium as non-calcified 17. Any coronary plaque was defined as the presence of at least one type of coronary plaque, including calcified plaque, mixed plaque, or non-calcified plaque. Obstructive CAD was defined as ≥ 50% diameter stenosis.
Statistical analysis
Continuous data are shown as means ± standard deviations, whereas categorical data are shown as numbers with percentages. Categorical variables were analyzed using the chi-square or Fisher’s exact test, and continuous variables were compared using one-way analysis of variance or the Kruskal − Wallis test for numerical variables, as appropriate. To assess potential correlations between Lp(a) levels and subclinical atherosclerosis on CCTA related to the presence of DM, logistic regression analyses were performed. Possible correlations between Lp(a) levels and subclinical coronary atherosclerosis on CCTA caused by presence of DM were assessed using logistic regression analyses. Unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were calculated by logistic regression. By referring to other related epidemiological studies 18–20, we selected clinically significant variables, including age, sex, obesity, hypertension, current smoking, family history of CAD, creatinine, corrected LDL-C, and HDL-C, to obtain the adjusted effect in the multivariable analyses. All reported p-values were 2-sided, and < 0.05 were considered statistically significant. R software (version 4.1.2) and SPSS (version 27.0; IBM Corp., Armonk, NY, USA) were used for all statistical analyses.
Ethics statement
This study was approved by the Institutional Review Board of Ulsan University Hospital, Ulsan, Korea. Due to the retrospective nature of the study, the Institutional Review Board of the Ulsan University Hospital, Ulsan, Korea (IRB No. UUH 2020-12-033) waived the need of obtaining informed consent. All methods were performed in accordance with relevant guidelines and regulations.
Results
Baseline characteristics
The study population’s average was 54.4 ± 7.9 years, and 4699 (65.3%) of the participants were men. Among the study participants, 949 (13.2%) had DM. Table 1 lists the study participants’ baseline characteristics based on DM and Lp(a) tertiles. In the non-DM group, the mean age, total cholesterol, LDL-C, HDL-C, and prevalence of hyperlipidemia significantly increased in the Lp(a) category. In contrast, the prevalence of men, obesity, and current smokers, as well as body mass index, waist circumference, fasting blood glucose, and triglyceride, significantly decreased across the Lp(a) tertiles. In the DM group, patients in the lower Lp(a) tertiles were younger and had a higher prevalence of male sex and higher levels of fasting blood glucose and triglycerides.
Table 1.
Baseline characteristics of the study population according to the tertiles of serum lipoprotein(a).
| Characteristics | Non-DM | DM | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Overall (n = 6,252) | Tertile 1 ≤ 5.6 mg/dl (n = 2,071) | Tertile 2 5.7 ~ 15.0 mg/dl (n = 2,101) | Tertile 3 ≥ 15.1 mg/dl (n = 2,080) | p-valueb | Overall (n = 949) | Tertile 1 ≤ 4.8 mg/dl (n = 317) | Tertile 2 4.9 ~ 13.4 mg/dl (n = 317) | Tertile 3 ≥ 13.5 mg/dl (n = 315) | p-valueb | |
| Age, years | 53.9 ± 7.9 | 52.9 ± 7.8 | 54.1 ± 7.9 | 54.7 ± 7.9 | < 0.001 | 57.2 ± 7.4 | 56.1 ± 7.4 | 57.4 ± 7.2 | 58.2 ± 7.6 | 0.001 |
| Men, no. (%) | 4,010 (64.1) | 1,414 (68.3) | 1,325 (63.1) | 1,271 (61.1) | < 0.001 | 689 (72.6) | 248 (78.2) | 224 (70.7) | 217 (68.9) | 0.020 |
| Systolic BP, mmHg | 125.6 ± 13.3 | 126.0 ± 13.0 | 125.3 ± 13.1 | 125.5 ± 13.8 | 0.173 | 129.0 ± 13.0 | 129.4 ± 12.7 | 128.6 ± 13.0 | 128.9 ± 13.4 | 0.730 |
| Diastolic BP, mmHg | 78.8 ± 9.4 | 79.1 ± 9.3 | 78.7 ± 9.6 | 78.7 ± 9.3 | 0.265 | 79.5 ± 9.0 | 79.9 ± 8.6 | 79.4 ± 8.9 | 79.3 ± 9.5 | 0.689 |
| BMI, kg/m2 | 24.1 ± 2.9 | 24.4 ± 3.0 | 24.1 ± 3.0 | 23.8 ± 2.8 | < 0.001 | 25.1 ± 3.1 | 25.4 ± 3.1 | 24.8 ± 3.1 | 25.0 ± 2.9 | 0.021 |
| Waist circumference, cm | 85.3 ± 7.8 | 86.1 ± 7.8 | 85.3 ± 7.9 | 84.7 ± 7.5 | < 0.001 | 88.3 ± 7.7 | 89.3 ± 7.8 | 87.7 ± 8.2 | 88.1 ± 7.2 | 0.027 |
| Obesity, no. (%) | 2,215 (35.4) | 825 (39.8) | 731 (34.8) | 659 (31.7) | < 0.001 | 448 (47.2) | 160 (50.5) | 138 (43.5) | 150 (47.6) | 0.213 |
| Hypertension, no. (%) | 1,984 (31.7) | 653 (31.5) | 676 (32.2) | 655 (31.5) | 0.867 | 487 (51.3) | 158 (49.8) | 172 (54.3) | 157 (49.8) | 0.439 |
| Hyperlipidemia, no. (%) | 1,031 (16.5) | 291 (14.1) | 319 (15.2) | 421 (20.2) | < 0.001 | 161 (17.0) | 51 (16.1) | 54 (17.0) | 56 (17.8) | 0.851 |
| Current smoker, no. (%) | 1,211 (19.5) | 468 (22.8) | 382 (18.3) | 361 (17.5) | < 0.001 | 257 (27.5) | 98 (31.3) | 84 (27.1) | 75 (24.2) | 0.135 |
| Family history of CADa, no. (%) | 628 (10.0) | 213 (10.3) | 214 (10.2) | 201 (9.7) | 0.774 | 78 (8.2) | 28 (8.8) | 32 (10.1) | 18 (5.7) | 0.119 |
| FBG, mg/dL | 90.8 ± 11.0 | 92.1 ± 11.1 | 90.3 ± 10.9 | 90.1 ± 10.8 | < 0.001 | 136.6 ± 37.0 | 143.1 ± 38.7 | 133.9 ± 32.7 | 132.7 ± 38.4 | 0.001 |
| Hemoglobin A1c, % | 5.4 ± 0.3 | 5.4 ± 0.4 | 5.4 ± 0.3 | 5.4 ± 0.3 | 0.782 | 7.1 ± 1.2 | 7.2 ± 1.2 | 7.1 ± 1.1 | 7.1 ± 1.2 | 0.258 |
| Total cholesterol, mg/dL | 192.3 ± 35.7 | 187.3 ± 35.8 | 191.2 ± 35.3 | 198.4 ± 35.2 | < 0.001 | 174.6 ± 40.7 | 175.9 ± 39.8 | 176.4 ± 41.5 | 171.4 ± 40.7 | 0.237 |
| LDL cholesterol, mg/dL | 131.7 ± 33.8 | 126.1 ± 33.5 | 131.5 ± 33.3 | 137.6 ± 33.7 | < 0.001 | 116.2 ± 36.6 | 115.1 ± 34.8 | 119.5 ± 37.4 | 113.9 ± 37.3 | 0.131 |
| Corrected LDL cholesterol, mg/dL | 126.6 ± 33.6 | 124.9 ± 33.5 | 128.6 ± 33.3 | 126.3 ± 34.0 | 0.002 | 111.3 ± 37.1 | 114.1 ± 34.8 | 117.0 ± 37.4 | 102.7 ± 37.7 | < 0.001 |
| HDL cholesterol, mg/dL | 53.9 ± 15.3 | 52.5 ± 15.3 | 53.8 ± 14.6 | 55.4 ± 15.8 | < 0.001 | 48.2 ± 13.1 | 47.0 ± 12.6 | 48.3 ± 13.8 | 49.2 ± 12.7 | 0.098 |
| Triglyceride, mg/dL | 95.0 [66.0–140.0] | 107.0 [72.0–158.0] | 93.0 [65.0–135.0] | 90.0 [63.0–127.0] | < 0.001 | 114.0 [77.0–173.0] | 134.0 [87.5–213.5] | 109.0 [74.0–154.5] | 102.0 [70.0–146.0] | < 0.001 |
| Creatinine, mg/dL | 0.82 ± 0.17 | 0.82 ± 0.17 | 0.82 ± 0.17 | 0.82 ± 0.18 | 0.709 | 0.83 ± 0.18 | 0.83 ± 0.17 | 0.82 ± 0.18 | 0.83 ± 0.18 | 0.589 |
| Uric acid, mg/dL | 5.4 ± 1.3 | 5.4 ± 1.4 | 5.3 ± 1.3 | 5.3 ± 1.3 | 0.046 | 5.1 ± 1.3 | 5.1 ± 1.2 | 5.1 ± 1.3 | 5.1 ± 1.3 | 0.828 |
| Ejection fraction, % | 63.8 ± 4.4 | 63.7 ± 5.1 | 63.9 ± 4.0 | 63.9 ± 4.2 | 0.553 | 63.7 ± 4.2 | 63.7 ± 3.6 | 64.3 ± 4.5 | 63.2 ± 4.3 | 0.078 |
Values are shown as mean ± standard deviation or number (%).
Triglyceride values are presented as median [interquartile range].
aCoronary artery disease in a first-degree relative of any age.
bP-value is based on the comparison of the three groups.
BMI = body mass index; BP = blood pressure; CAD = coronary artery disease; DM = diabetes mellitus; FBG = fasting blood glucose; HDL = high density lipoprotein; LDL = low density lipoprotein.
Coronary computed tomography angiography findings
Table 2 shows CCTA findings according to the Lp(a) tertiles and the presence of DM. Study participants with DM had a higher mean CACS (99.2 versus 33.4) and a higher prevalence of any coronary plaques (56.0% versus 32.4%), calcified plaques (52.6% versus 30.6%), mixed plaques (8.7% versus 2.7%), non-calcified plaques (9.3% versus 4.4%), and obstructive CAD (13.1% versus 5.1%) than those without DM (p-values < 0.05 for all). However, regardless of DM, the mean CACS and prevalence of any coronary plaques, calcified plaques, mixed plaques, and non-calcified plaques did not differ according to the Lp(a) category. On the other hand, obstructive CAD did not differ according to Lp(a) categories in non-DM participants, but in DM patients, higher Lp(a) levels were associated with an increased prevalence of obstructive CAD.
Table 2.
Comparison of coronary computed tomography angiographic findings according to the tertiles of serum lipoprotein(a).
| Characteristics | Non-DM | DM | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Overall (n = 6,252) | Tertile 1 ≤ 5.6 mg/dl (n = 2,071) | Tertile 2 5.7 ~ 15.0 mg/dl (n = 2,101) | Tertile 3 ≥ 15.1 mg/dl (n = 2,080) | p-valuea | Overall (n = 949) | Tertile 1 ≤ 4.8 mg/dl (n = 317) | Tertile 2 4.9 ~ 13.4 mg/dl (n = 317) | Tertile 3 ≥ 13.5 mg/dl (n = 315) | p-valuea | |
| Mean CACS | 33.4 ± 136.8 | 33.7 ± 127.7 | 31.8 ± 139.7 | 34.9 ± 142.7 | 0.756 | 99.2 ± 284.4 | 100.2 ± 297.2 | 80.3 ± 262.2 | 117.3 ± 292.1 | 0.261 |
| CACS, no. (%) | 0.297 | 0.417 | ||||||||
| 0 | 4,309 (68.9) | 1,456 (70.3) | 1,442 (68.6) | 1,411 (67.8) | 439 (46.3) | 151 (47.6) | 155 (48.9) | 133 (42.2) | ||
| 1–10 | 603 (9.6) | 180 (8.7) | 218 (10.4) | 205 (9.9) | 94 (9.9) | 30 (9.5) | 30 (9.5) | 34 (10.8) | ||
| 11–100 | 847 (13.5) | 278 (13.4) | 287 (13.7) | 282 (13.6) | 216 (22.8) | 70 (22.1) | 78 (24.6) | 68 (21.6) | ||
| 101–400 | 366 (5.9) | 114 (5.5) | 110 (5.2) | 142 (6.8) | 140 (14.8) | 47 (14.8) | 37 (11.7) | 56 (17.8) | ||
| > 400 | 127 (2.0) | 43 (2.1) | 44 (2.1) | 40 (1.9) | 60 (6.3) | 19 (6.0) | 17 (5.4) | 24 (7.6) | ||
| Any coronary plaque, no. (%) | 2,026 (32.4) | 637 (30.8) | 688 (32.7) | 701 (33.7) | 0.118 | 531 (56.0) | 175 (55.2) | 171 (53.9) | 185 (58.7) | 0.454 |
| Plaque characteristics, no. (%) | ||||||||||
| Calcified plaque | 1,912 (30.6) | 601 (29.0) | 653 (31.1) | 658 (31.6) | 0.156 | 499 (52.6) | 162 (51.1) | 160 (50.5) | 177 (56.2) | 0.288 |
| Mixed plaque | 166 (2.7) | 55 (2.7) | 47 (2.2) | 64 (3.1) | 0.240 | 83 (8.7) | 27 (8.5) | 23 (7.3) | 33 (10.5) | 0.353 |
| Non-calcified plaque | 275 (4.4) | 79 (3.8) | 88 (4.2) | 108 (5.2) | 0.081 | 88 (9.3) | 23 (7.3) | 32 (10.1) | 33 (10.5) | 0.312 |
| Obstructive coronary artery disease , no. (%) | 318 (5.1) | 93 (4.5) | 106 (5.0) | 119 (5.7) | 0.195 | 124 (13.1) | 32 (10.1) | 39 (12.3) | 53 (16.8) | 0.038 |
Values are shown as mean ± standard deviation or number (%).
aP-value is based on the comparison of the three groups.
CACS = coronary artery calcium score; DM = diabetes mellitus.
Association between Lp(a) and subclinical coronary atherosclerosis based on the presence of DM
The relationship between Lp(a) levels and subclinical coronary atherosclerosis is displayed in Table 3. In univariable analyses of the non-DM group, increasing tertiles of Lp(a) were significantly associated with an increased risk of any coronary plaque and non-calcified plaque. In the DM group, the third tertile of Lp(a) had a higher risk of obstructive CAD than the first tertile.
Table 3.
Association between serum lipoprotein(a) levels and coronary computed tomography angiographic findings accoding to the presence of diabetes mellitus.
| Variables | Non-DM | DM | ||||||
|---|---|---|---|---|---|---|---|---|
| Univariable | Multivariable | Univariable | Multivariable | |||||
| Odds ratio (95% CI) | p-value | Odds ratio (95% CI) | p-value | Odds ratio (95% CI) | p-value | Odds ratio (95% CI) | p-value | |
| Any coronary plaque | ||||||||
| Tertile 1 (reference) | 1 | 1 | 1 | 1 | ||||
| Tertile 2 | 1.096 (0.962–1.249) | 0.168 | 1.076 (0.929–1.245) | 0.328 | 0.950 (0.695–1.299) | 0.750 | 0.912 (0.651–1.277) | 0.593 |
| Tertile 3 | 1.144 (1.005–1.304) | 0.043 | 1.153 (0.995–1.336) | 0.058 | 1.155 (0.843–1.583) | 0.371 | 1.058 (0.752–1.489) | 0.745 |
| Calcified plaque | ||||||||
| Tertile 1 (reference) | 1 | 1 | 1 | 1 | ||||
| Tertile 2 | 1.103 (0.966–1.259) | 0.147 | 1.083 (0.934–1.256) | 0.289 | 0.975 (0.714–1.331) | 0.874 | 0.930 (0.664–1.303) | 0.675 |
| Tertile 3 | 1.132 (0.991–1.292) | 0.067 | 1.134 (0.977–1.316) | 0.098 | 1.227 (0.897–1.678) | 0.200 | 1.117 (0.794–1.572) | 0.525 |
| Mixed plaque | ||||||||
| Tertile 1 (reference) | 1 | 1 | 1 | 1 | ||||
| Tertile 2 | 0.839 (0.566–1.244) | 0.382 | 0.872 (0.580–1.310) | 0.509 | 0.840 (0.471–1.500) | 0.556 | 0.909 (0.500–1.651) | 0.754 |
| Tertile 3 | 1.164 (0.807–1.677) | 0.417 | 1.227 (0.835–1.804) | 0.298 | 1.257 (0.737–2.145) | 0.402 | 1.552 (0.888–2.714) | 0.123 |
| Non-calcified plaque | ||||||||
| Tertile 1 (reference) | 1 | 1 | 1 | 1 | ||||
| Tertile 2 | 1.102 (0.808–1.503) | 0.538 | 1.048 (0.764–1.439) | 0.771 | 1.435 (0.820–2.513) | 0.206 | 1.495 (0.845–2.645) | 0.168 |
| Tertile 3 | 1.381 (1.026–1.858) | 0.033 | 1.348 (0.993–1.830) | 0.056 | 1.496 (0.857–2.611) | 0.156 | 1.735 (0.980–3.072) | 0.059 |
| Obstructive coronary artery disease | ||||||||
| Tertile 1 (reference) | 1 | 1 | 1 | 1 | ||||
| Tertile 2 | 1.130 (0.850–1.503) | 0.401 | 1.098 (0.815–1.480) | 0.537 | 1.249 (0.761–2.051) | 0.379 | 1.360 (0.811–2.283) | 0.244 |
| Tertile 3 | 1.291 (0.977–1.705) | 0.072 | 1.254 (0.934–1.682) | 0.132 | 1.802 (1.126–2.882) | 0.014 | 2.051 (1.248–3.372) | 0.005 |
CI = confidence interval; DM = diabetes mellitus.
Covariates in the multivariable model include age, sex, obesity, hypertension, current smoking, family history of coronary artery disease, creatinine, corrected low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol.
In participants without DM, after adjusting for cardiovascular risk factors (age, sex, obesity, hypertension, current smoking, family history of CAD, creatinine, corrected LDL-C, and HDL-C), no statistically significant differences in the adjusted ORs for any coronary plaque, calcified plaque, mixed plaque, non-calcified plaque, and obstructive CAD in the third Lp(a) tertile compared to the first tertile (p-values > 0.05 for all) were found. However, in DM participants, both the first and third Lp(a) tertiles did not differ statistically significantly in the ORs for any coronary plaque (1.058, 95% confidence interval [CI] 0.752–1.489), calcified plaque (1.117, 95% CI 0.794–1.572), mixed plaque (1.552, 95% CI 0.888–2.714), or non-calcified plaque (1.735, 95% CI 0.980–3.072). However, the adjusted ORs for obstructive CAD (2.051, 95% CI 1.248–3.372) were significantly higher in the third Lp(a) tertile compared to the first Lp(a) tertile.
Subgroup analysis in participants without DM (normoglycemia and prediabetes)
We also examined the relationship between Lp(a) and subclinical coronary atherosclerosis in individuals with prediabetes and normoglycemia, respectively. Baseline characteristics and CCTA findings of individuals with normoglycemia and prediabetes were shown in Supplementary Table 1 and 2. On multivariable logistic regression analyses, in participants with normoglycemia, the ORs of subclinical coronary atherosclerosis did not differ between the first and third Lp(a) tertiles, except for any coronary plaque (1.215, 95% CI 1.004–1.470). In participants with prediabetes, none of subclinical coronary atherosclerosis were statistically significantly associated with Lp(a) tertiles (p-values > 0.05 for all) (Supplementary Table 3).
Discussion
The main finding of this study was that asymptomatic individuals with DM and elevated Lp(a) levels were linked to obstructive CAD, which may be linked to an increased risk of cardiac events, after adjusting for cardiovascular risk factors.
The risk of CAD is high in patients with DM 2, and approximately 20% of these patients are asymptomatic 21. Therefore, guidelines recommend that patients with DM should manage modifiable cardiovascular risk factors, including glycemia, blood pressure, lipid control, and lifestyle modifications, such as weight reduction, diet control, increased physical activity, and smoking cessation 22,23. However, despite efforts to control modifiable risk factors, CAD risk remains higher in patients with DM than in those without DM 24. These findings suggest that there may be unrecognized risk factors other than the traditional cardiovascular risk factors. Recently, the role of Lp(a) as a new risk factor is increasingly being recognized 4–6. Kaiser et al. observed that elevated Lp(a) level in patients with CAD was associated with accelerated progression of low-attenuation plaque (necrotic core) assessed by CCTA, suggesting the importance of Lp(a) in secondary prevention 11. In addition, previous studies showed that effect of Lp(a) might be different in individuals with and without CAD according to the presence of DM 12,13. Based on previous findings, we hypothesized that the effect of Lp(a) on subclinical coronary atherosclerosis might be different in asymptomatic individuals according to the presence of DM.
In this study, we observed an association between higher Lp(a) levels and obstructive CAD on CCTA in asymptomatic patients with DM. According to earlier research using different diagnostic modalities, such as stress echocardiography or nuclear imaging, patients with DM with normal test results have a higher rate of cardiac events than the general population 25. However, unlike other test modalities, obstructive CAD detected by CCTA is an excellent predictor of all-cause and cardiovascular mortality, regardless of the presence or absence of DM 26,27. Even in asymptomatic populations with and without DM, obstructive CAD on CCTA has long-term prognostic value for predicting cardiac events 28,29. A recent study also reported that asymptomatic patients with DM with obstructive CAD had high rates of cardiac events during a 10-year follow-up, irrespective of the baseline UKPDS (U.K. Prospective Diabetes Study) risk category 30. On the other hand, in the current study, the cutoff values of the third Lp(a) tertile were 13.5 mg/dL and 15.1 mg/dL in diabetic and non-diabetic participants, respectively. Although the Lp(a) level in the third tertile was lower in the DM group, it was significantly associated with obstructive CAD, which was not observed in the non-DM group. Accordingly, these findings suggest that Lp(a) may have a relatively worse effect in diabetic than in non-diabetic individuals. Therefore, efforts to control Lp (a) levels may be more important to prevent future cardiac events in individuals with DM.
Evidence suggests that elevated Lp(a) levels might be a potential therapeutic target to further reduce cardiovascular risk beyond statin-mediated LDL-C regulation 31,32. The present study also indicates that Lp(a) could be an attractive therapeutic target for preventing subsequent cardiac events in asymptomatic individuals with DM. Recent pro-protein convertase subtilisin/kexin 9 (PCSK9) inhibitor studies have suggested its potential clinical benefits for Lp(a) lowering 33,34. In the FOURIER (Further Cardiovascular Outcomes Research with PCSK9 Inhibition in Subjects with Elevated Risk) trial, higher baseline levels of Lp(a) were associated with an increased risk of cardiovascular events, irrespective of LDL-C levels. Lp(a) levels were dramatically lowered with evolocumab, with a median decrease of 26.9%. Patients with higher baseline Lp(a) levels experienced greater absolute reductions in Lp(a) levels and tended to have greater coronary benefits 33. Alirocumab decreased Lp(a) by 5 mg/dL in a pre-specified analysis of the ODYSSEY Outcomes (ODYSSEY Outcomes: Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) trial. The reduction of Lp(a) by alirocumab independently contributed to the decrease in major adverse cardiovascular events 34. A meta-analysis of patients with DM also reported that a significant reduction in Lp(a) with PCSK9 inhibitors was effective in reducing the risk of major cardiovascular events in patients with DM 35. So far, the cardiovascular benefits of Lp(a)-lowering therapy for primary prevention in asymptomatic diabetic individuals have not been definitely established. However, our findings along with insights from previous studies, suggest that Lp(a) could be a potential therapeutic target for reducing cardiovascular risk in asymptomatic individuals with diabetes, which warrants further investigation in future studies.
There were several limitations in our study. First, since the study was conducted with participants who visited the hospital independently for general health examinations, selection bias was a potential concern. In addition, our study design is a retrospective cohort study. Therefore, large-scale prospective studies are required to validate our findings. Second, the study only included Korean participants, which may limit the generalizability of our findings to other ethnic groups may be limited. Third, obstructive CAD on CCTA may have been overestimated because of calcified plaques and a higher CACS. Fourth, high-risk plaque features, such as positive remodeling, low attenuation plaque, spotty calcium, and napkin ring sign, were an important issue. However, since our study did not perform an analysis of these high-risk characteristics, additional studies are required to elucidate the impact of Lp(a) on these high-risk plaques in asymptomatic individuals with and without DM. Finally, the systemized self-report questionnaire distributed before the general health examination did not contain information on medical history of statin, which may be an important potential confounder. Despite these limitations, our findings may have significant clinical implications for identifying the differential impact of Lp(a) level on subclinical coronary atherosclerosis based on the presence of DM in asymptomatic individuals.
Conclusions
This study showed that higher Lp(a) levels were associated with obstructive CAD in asymptomatic individuals with DM. These findings indicate that appropriate strategies for the primary prevention of CAD are necessary in patients with DM and elevated Lp(a) levels.
Supplementary Information
Author contributions
MH Jang, S Han, and GM Park were involved in the conception, design, or planning of the study. MH Jang, S Park, YJ Jeon, S Lim, WJ Kwon, SH Choi, and GM Park were involved in the acquisition of data. MH Jang, S Han, and GM Park were involved in the analysis of data. MH Jang, S Park, SH Ann, YG Kim, S Han, and GM Park were involved in the interpretation of results. MH Jang, S Han, and GM Park substantially contributed to drafting of the manuscript.
Funding
This research was supported by grants from the Ulsan University Hospital Research Grant (UUH-2024-11) and the Medical data-driven hospital support project, through the Korea Health Information Service (KHIS), funded by the Ministry of Health & Welfare, Republic of Korea. Additional support was provided by the National Research Foundation of Korea grant funded by the Korean government (MSIT) (2022R1F1A1063027). The funders were not involved in the study design, data collection and analysis, decision to publish, or manuscript preparation.
Data availability
The data utilized and examined in this study can be obtained from the corresponding author upon reasonable request.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Seungbong Han, Email: hanseungbong@gmail.com.
Gyung-Min Park, Email: gmpark@uuh.ulsan.kr.
Supplementary Information
The online version contains supplementary material available at 10.1038/s41598-025-04964-8.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data utilized and examined in this study can be obtained from the corresponding author upon reasonable request.