Elevated serum lipoprotein(a) is significantly associated with angiographic progression of coronary artery disease

Abstract Background Lipoprotein(a)[Lp(a)] has been considered as an independent risk factor for coronary artery disease (CAD). The present study aimed to evaluate the association between baseline serum Lp(a) and CAD progression determined by angiographic score. Methods A total of 814 patients who had undergone two or more coronary computed tomography angiography at least 6 months apart were consecutively enrolled and the coronary severity was determined by the Gensini score system. Patients were stratified into two groups according to Lp(a)>300 mg/L and Lp(a) ≤ 300 mg/L or classified as “progressors” and “non‐progressors” based on the Gensini score rate of change per year. The association of continuous Lp(a) and Lp(a)>300 mg/L with CAD progression were respectively assessed by logistic regression analysis. Moreover, further evaluation of those association was performed in subgroups of the study population. Results Patients in the “progressors” group had significant higher Lp(a) levels. Furthermore, the multivariate logistic regression analysis showed that elevated Lp(a) (odds ratio [OR]: 1.451, 95% confidence interval [CI]: 1.177–1.789, p<.001) and Lp(a)>300 mg/L (OR:1.642, 95% CI:1.018–2.649, p = .042) were positively associated with CAD progression after adjusting for confounding factors. In addition, those relation seemed to be more prominent in subjects with lower body mass index (OR: 1.880, 95% CI: 1.224–2.888, p for interaction = .060). Conclusions Elevated baseline serum Lp(a) is positively and independently associated with angiographic progression of CAD, particularly in participants with relatively low body mass index. Therefore, Lp(a) could be a potent risk factor for CAD progression, assisting in early risk stratification in cardiovascular patients.


| INTRODUCTION
Coronary artery disease (CAD) is still a major cause of death worldwide. Despite great advances in its diagnosis, treatment, and prevention, adverse cardiovascular events do not seem to decline on the background of optimal medical therapy. 1 The importance of identifying residual risk and screening the coronary atherosclerotic progression for early prevention remains undisputed.
Lipoprotein(a)[Lp(a)] is composed of a low-density lipoprotein(LDL)like particle with its apolipoprotein (apo)B100, which covalently bound to a characteristic glycoprotein apolipoprotein a[apo(a)] by a disulfide bond. 2 Because of its proatherogenic, proinflammatory and prothrombotic properties, previous studies demonstrated that Lp(a) involved in the pathophysiological process of coronary atherosclerosis. [3][4][5] Meanwhile large amounts of evidence from epidemiological studies, 6 mendelian randomization analysis, 7 and genome-wide association studies 8 identified that Lp(a) was an independent risk factor for primary and secondary prevention of CAD. However, the correlation between Lp(a) and coronary atherosclerosis progression remains controversial. Previously, two study groups assessed the predictive utility of Lp(a) in coronary atherosclerosis progression by intravascular ultrasound, opposite results were obtained. 9,10 With the development of computed tomography technology, coronary computed tomography angiography (CTA) has been widely used for non-invasive assessment of coronary atherosclerosis at outpatient department. Compared with invasive coronary angiography, the predictive value of coronary artery stenosis by coronary CTA had high sensitivity and specificity. 11 Moreover, coronary CTA was more available and convenient for clinical application than invasive intravascular ultrasound.
Hence, in the present study, we aimed to analyze the association between baseline Lp(a) levels and angiographic progression of CAD by

| Clinical and laboratory parameters
Clinical parameters including age, sex, height, weight, systolic and diastolic blood pressure (DBP), heart rate, comorbidities, and medications were collected at outpatient or admission. Body mass index (BMI) was calculated from weight in kg divided by height in m 2 . Hypertension (HTN) was defined as systolic blood pressure (SBP) ≥ 140 mm Hg and/or diastolic blood pressure ≥90 mmHg or currently using antihypertensive agents. Diabetes (DM) was defined as fasting serum glucose≥7.0 mmol/L or random serum glucose≥11.1 mmol/L or the 2-h serum glucose of the oral glucose tolerance test≥11.1 mmol/L or using anti-diabetic medication. Smoking status was defined as a person who smoked at the time of initial coronary CTA or who had quit smoking within the year before initial coronary CTA. Obstructive CAD was defined as coronary stenosis of 50% or more in the epicardial coronary artery determined by initial coronary CTA.
Blood samples were obtained from each patient in the fasting state at outpatient or after admission and then tested in laboratory medicine as soon as possible. The serum lipid profiles including total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), apoA1, apoB100, and Lp(a) were determined by automatic biochemical analyzer (Hitachi 7600, Tokyo, Japan). In addition, in detail, TC and TG were measured with enzyme colorimetry method, while LDL-C and HDL-C were determined by the direct method. ApoA1 and apoB100 were measured with immunoturbidimetry method. The serum concentration of Lp(a) was analyzed using latex immunoturbidimetry method.
Due to racial differences, the optimal risk cutoffs for cardiovascular disease were still not clearly determined. The European Atherosclerosis Society proposed Lp(a) <50 mg/dl as the appropriate cutoffs, while China and the United States recommended Lp(a) <30 mg/dl as a desirable level. 12 According to Guidelines for the Prevention and Treatment of Dyslipidemia in Chinese Adult, 13 300 mg/L was selected as a cutoff value in our center. The normal range was 0-300 mg/L. Non-HDL-C levels were calculated as TC minus HDL-C levels.

| Coronary computed tomography angiography and Gensini score assessment
The 320-slice coronary CTA was performed by a predefined standard operating procedure as previously described. 14  All coronary CTA images were reconstructed and analyzed using a dedicated workstation (VitreafX Version 2.1, TOSHIBA) by experienced radiologists, which in accordance with the Society of Cardiovascular Computed Tomography guidelines. 15 The severity of coronary artery was assessed by angiographic scoring system: the Gensini score system, which were calculated by three experienced interventional cardiologists. Based on the degree of luminal narrowing, severity scores indicated angiographic stenosis of coronary artery segment were 1, 2, 4, 8, 16, and 32 for 0%-25%, 26%-50%, 51%-75%, 76%-90%, 91%-99%, and 100%, respectively. 16 Given the variation in time during the coronary CTAs, the Gensini score rate of change per year was used to define angiographic CAD progression as detailed elsewhere. 17 In brief, subjects were arbitrarily categorized as "progressors" and "non-progressors" based on a Gensini score rate of change of >1 or ≤ 0.5 points/year, respectively. Subject with a Gensini score rate of change between 0.5< and ≤ 1 points/year were excluded as "gray area" in the present study.   Table 1 shows the baseline clinical characteristics of the study subjects.

| Statistical analysis
Patients were stratified into two groups according to Lp(a)>300 mg/L and Lp(a) ≤ 300 mg/L. Several baseline clinical and biochemical characteristics were compared between groups. Serum TC, HDL-C, Non-HDL-C, and LDL-C levels increased in the higher Lp(a) group. However, no significant difference was observed in demographic characteristics, clinical comorbidities, medications, as well as serum levels of TG, ApoA1, ApoB100, FPG, HbA1c, creatinine, eGFR, UA, and WBC.

| Impact of clinical variables on coronary artery disease progression
Subjects were divided into two groups on the basis of the presence of angiographic CAD progression(a Gensini rate of change of >1 or ≤ 0.5 points/year was considered as "progressors" or "non-progressors," respectively). As is shown in Table S1, patients in "progressors" group were older; more often men and smoking; more likely to have history of HTN and initially obstructive CAD; and more likely to have elevated baseline serum Lp(a), ApoB100, HbA1c and decreased HDL-C and ApoA1. In addition, the incidence of Lp(a)>300 mg/L was significantly higher in progressors group (25.6% vs. 18.3%, p = .018).
3.3 | Gensini score at baseline and follow-up according to baseline serum Lp(a) levels      Furthermore, it was found that the prognostic utility of Lp(a) as a marker of risk in the setting of primary and secondary prevention was apparently only in the population with higher cholesterol levels. 26 However, a single-center cross-sectional study was recently conducted to investigate the association between Lp(a) and coronary atherosclerotic lesion using Gensini score, Li et al. found the association was influenced by LDL-C levels. They revealed that Lp(a) was the risk factors of coronary atherosclerotic heart disease in patients with LDL-C<100 mg/dl. 27 Therefore, the evaluation of Lp(a) in patients with well controlled cholesterol remained to be further studied.

| Subgroup analysis for the relation of Lp(a) with CAD progression
Another interesting finding of the present study was that the association of baseline Lp(a) and CAD progression seemed to be more prominent in subjects with relatively lower BMI, even after controlling for conventional covariates. In prior studies, obesity has been considered as an independent risk factor for CAD, as well as increased rates of adverse cardiovascular events. 28 Current guidelines recommend weight control to be a fundamental life style changes strategy in management of CAD. 29 Previously, Troy et al.
conducted a prospective multicenter observational study to confirm that increased BMI had a strong and consistent relationship with the prevalence, extent, and severity of CAD. 30 Afterward, Cho et al. analyzed the association between obesity type and CAD in stable symptomatic postmenopausal women. The authors revealed that central obesity but not overall obesity was related to obstructive CAD. 31 As we know obesity usually accompanies with several clinical comorbidities, such as HTN, DM, and hyperlipidemia, which may categorize to the high risk individuals. Nowadays, many guidelines recommend to screen the Lp(a) level mostly in high-risk individuals. 32 However, the present study showed the association of baseline Lp(a) and CAD progression was more prominent in patients with relatively lower BMI rather than obesity, one possible explanation was that Lp(a) may play a significant role as an overlooked "residual risk factor," which implying the importance of routine Lp(a) measurement to assist in early risk stratification in seemingly normal-sized populations. Further studies are needed to confirm the relationship and reveal the underlying mechanism.
In the present study, there were several limitations.  33 In the present study, we mainly aimed to analyze the correlation between baseline Lp(a) and coronary artery progression. In addition, 85% subjects received statins treatment in our study. Currently, statins effect on Lp(a) metabolism was still not well understood, resulting in controversial results by different statins. 5,34 Whether changes in Lp(a) levels over time could affect the result will need additional study. Thus, further studies are required in multicenter and larger populations to confirm our findings, especially therapeutic strategies of Antisense oligonucleotide (ASO) technology.

| CONCLUSION
In conclusion, the current study found that baseline serum Lp(a) concentration was significantly associated with angiographic progression of CAD, particularly in those with relatively low BMI. Therefore, Lp(a) could be a potent risk factor for progression of CAD, assisting in early risk stratification in cardiovascular patients. Further studies will clearly be required to confirm our findings.

ACKNOWLEDGMENTS
The authors express sincere thanks to Dr. Zhuoshan Huang for his help in statistics.

CONFLICT OF INTEREST
No conflict of interest was declared.

AUTHOR CONTRIBUTIONS
Conceived and designed the study: Lin Chen and Zhen Wu; clinical data acquisition: Binghan Zheng and Yongxia Wu; data analysis: Xujing Xie, Zefeng Chen and Zhen Wu; statistical analysis: Xing Shui and Zheqi Wen; Manuscript drafting: Xing Shui, Zheqi Wen and Zefeng Chen; Each author contributed important intellectual content during manuscript writing or revision.

DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.