PCSK9 inhibitors ameliorate arterial stiffness in ACS patients: evidences from mendelian randomization, cohort studies and basic experiments

PCSK9 inhibitors ameliorate arterial stiffness in ACS patients: evidences from mendelian randomization, cohort studies and basic experiments | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article PCSK9 inhibitors ameliorate arterial stiffness in ACS patients: evidences from mendelian randomization, cohort studies and basic experiments Linghao Xu, Liang Wang, Yuanqi Wang, Yiqiong Wang, Yuanzhen Jiang, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4008037/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Current evidences suggest that Proprotein Convertase Subtilisin/kexin Type 9 inhibitors (PCSK9i) exhibit a protective influence on acute coronary syndrome (ACS). Nevertheless, further investigation is required to comprehend the impact and mechanisms of these pharmaceutical agents on inflammatory factors and arterial stiffness (AS) in patients with ACS. Consequently, the objective of this study is to ascertain the influence of PCSK9i on arterial stiffness in ACS patients and elucidate the underlying mechanisms behind their actions. Methods This study employed Mendelian randomization (MR) analysis to examine the association between genetic prediction of PCSK9 inhibition and arterial stiffness. A total of 71 patients with ACS were randomly allocated into either a PCSK9i group or a control group. Blood lipid levels, inflammatory markers and pulse wave velocity (PWV) data were collected before treatment and at 1 and 6 months after treatment for analysis. Additionally, cell experiments were conducted to investigate the impact of PCSK9i on osteogenesis of vascular smooth muscle cells (VSMCs), utilizing western blot (WB), enzyme-linked immunosorbent assay (ELISA), and calcification index measurements. Results The results of the MR analysis suggest that genetic prediction of PCSK9 inhibition has potential to reduce the pulse wave reflection index (PWV). Following treatment of statins combined with PCSK9 inhibitors for 1 and 6 months, the PCSK9i group exhibited significantly lower levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), C-reactive protein (CRP), interleukin-6 (IL-6), fibrinogen (FIB) and procalcitonin (PCT) compared to the control group ( p < 0.05). Additionally, PWV in the PCSK9i group demonstrated significant reduction after 6 months of treatment and was found to be associated with the circulating CRP level. In cell experiments, PCSK9i pretreatment ameliorated osteogenesis of VSMCs through reducing the deposition of calcium ions, alkaline phosphatase (ALP) activity, and expression of runt-related transcription factor 2(RUNX2). Conclusion PCSK9i have potential to enhance arterial stiffness at various aspects, including the genetic, clinical, and cellular domains. Specifically, at the clinical level, this impact may be attributed to alterations in circulating CRP levels. At the cellular level, it is associated with the signaling pathway linked to RUNX2. Acute coronary syndrome PCSK9 inhibitors Arterial stiffness C-reactive protein Mendelian randomization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Acute coronary syndromes (ACS) encompass a collection of clinical syndromes characterized by the rupture or invasion of coronary atherosclerotic plaques, resulting in the formation of complete or incomplete occlusive thrombi [ 1 ] .ACS includes acute ST-segment elevation myocardial infarction(STEMI), acute non-ST-segment elevation myocardial infarction(NSTEMI), and unstable angina(UA) [ 1 ] .Several common contributing factors include the process of aging, smoking, dyslipidemia and glycemia disorders, as well as hypertension [ 2 ] .In clinical practice, various pharmacological treatments including antiplatelet therapy, lipid modulation, blood pressure control, and glucose therapy, alongside revascularization therapies such as percutaneous coronary intervention (PCI) and heart bypass surgery are commonly employed [ 3 ] , within 10 years, more than 20% of patients with ACS are at more than a 30% risk of recurrence which can lead to myocardial infarction, stroke, and other vascular-related fatal events [ 4 , 5 ] . Lipid-lowering agents are presently employed as one of the primary therapeutic intervention in clinical pharmacology for the majority of ACS patients [ 3 , 6 ] . Proprotein Convertase Subtilisin/kexin Type 9 inhibitors (PCSK9i) have primarily been employed for the purpose of reducing levels of low-density lipoprotein cholesterol (LDL-C) in the bloodstream, thereby exerting an anti-atherosclerotic impact [ 7 ] . The status of PCSK9i which possess robust lipid-lowering properties is progressively growing within the most recent clinical guidelines for ACS [ 8 ] . Numerous studies have elucidated that PCSK9 inhibitors possess potential broader physiological functions, beyond their established role in lipid level regulation [ 9 ] . Arterial stiffness (AS) serves as a significant predictor of cardiovascular disease (CVD) and cardiovascular adverse events. In patients with ACS, elevated AS emerges as a risk factor contributing to unfavorable prognosis. The primary features of AS encompass intravascular collagen deposition, calcium deposition, fibroblast proliferation, and diminished endothelial diastolic function [ 10 ] . The augmentation of AS may result in a decrease in myocardial afterload and coronary perfusion pressure, consequently precipitating a cascade of severe implications including hypertension, heart failure, and organic heart disease [ 11 ] . The methods of assessing AS include Pulse Wave Velocity (PWV), Ankle Brachial Index (ABI), Ambulatory arterial stiffness Index (AASI) and so on, among which the most widely used in clinical practice is PWV [ 12 ] . Recognizing the presence of AS in patients ACS and promptly intervening is considered a potential strategy to enhance the prognosis of ACS patients. While the efficacy of PCSK9i in improving AS has been demonstrated in individuals with familial hypercholesterolemia (HF) [ 13 ] , it remains uncertain whether these inhibitors can exert a similar effect in ACS patients. Given the extensive utilization of PCSK9i in ACS patients, our objective was to investigate the potential of these inhibitors in ameliorating AS in this specific population. Mendelian randomization (MR) is an analytical approach that employs genetic variations as instrumental variables (IVs) to investigate the potential association between exposures and outcomes [ 14 ] . Mendelian laws of inheritance randomly divide alleles among offspring, creating equal experimental and control groups. This minimizes confounding factors and makes MR studies a powerful tool for disease and clinical research [ 15 ] . We conducted a two-sample MR experiment to evaluate the genetic correlation between PCSK9 inhibition and AS. Additionally, we examined the clinical characteristics of ACS patients treated with PCSK9i and observed alterations in lipid levels, specific inflammatory markers and AS. Furthermore, we conducted cellular experiments to examine the impact of PCSK9 inhibitors on the extent of osteogenesis in vascular smooth muscle cells (VSMCs) of mice, thereby offering a comprehensive elucidation of the role played by PCSK9i in ameliorating AS. Materials and methods MR design Since the clinical effect of PCSK9i on LDL-C reduction is clear, we employed single nucleotide polymorphisms (SNPs) associated with LDL-C as IVs. To establish a causal relationship, it was necessary to satisfy the following criteria: 1.The IVs have no association with confounding factors; 2.The IVs are associated with exposures; 3.The IVs have no direct relationship with outcomes.(Fig. 1 ) Exposure datasets selection and SNPs identification Genetically predicted inhibition of PCSK9 was used as an exposure. The gene sequence of PCSK9 was searched using the gene search function of the National Center for Biotechnology Information (NCBI) database [ 16 ] , and the gene region chr1: 55505221–55530525 was selected to identify SNPs that serve as proxies for PCSK9. Utilizing a similar approach for the selection of genetic variants as employed in prior research [ 17 ] , SNPs were identified within ± 100 kb regions of the corresponding gene sequences and were identified in the genome-wide association study(GWAS) LDL-C dataset (ieu-a-300, n = 173082) from Global Lipid Genetics Consortium (GLCC) [ 18 ] .SNPs that met the genome-wide significance threshold of p < 5×10 − 8 and a linkage disequilibrium (LD) threshold of R²< 0.2 were utilized as genetic tools. Additionally, the human genotype-phenotype association database PhenoScanner ( http://www.phenoscanner.medschl.cam.ac.uk/ ) was employed to identify traits that were directly linked to the SNPs used as IVs. This approach allowed us to exclude potential confounders from our analysis. Positive control and outcome dataset selection Based on previously researches [ 19 ] , we used coronary heart disease (CHD, ieu-a-7) data from the Consortium for the Genetics of Coronary Artery Disease (CARDIoGRAMplusC4D) [ 20 ] as a positive control dataset, comprising 60801 cases and 123504 controls. Using the pulse wave reflection index (PWRI, ukb-b-11598, n = 151546) from the UK Biobank (UKBB) as the primary outcome, the pulse wave peak to peak time (PWPPT, ukb-b-8778, n = 151466) and pulse wave arterial stiffness index (PWASI, ukb-b-11971, n = 151053) as secondary outcomes. All three parameters serve as indicators of AS, where elevated values correspond to increased levels of AS [ 21 ] . Datasets were chosen from European populations, although the sources of exposure and outcomes differed. Before the collection of the original database, informed consent was acquired from each participant and approved by the respective local ethics committees of GWAS. All datasets were procured via IEU OpenGWAS(Table.S1) [ 22 ] . MR analysis Heterogeneity among SNPs was assessed through the application of Cochran's Q test. A p -value > 0.05 was indicative of the absence of significant heterogeneity. The exposure-related drug-targeting instrument variables were aligned with the outcome dataset and subsequently subjected to analysis employing MR Egger, weighted median, and inverse variance weighted (IVW) methods. MR-PRESSO method was employed to detect potential outliers and address any horizontal polytomous outliers in the analyses. To mitigate the influence of individual SNPs on our findings, we employed the leave-one-out approach, systematically excluding each SNP to ascertain its lack of association with the outcome or presence of pleiotropy. All MR results are expressed as OR or beta, and statistical tests were two-sided. Analyses were completed using R language software (4.2.3), and the TwoSampleMR package was used throughout. p < 0.05 was considered a statistically significant difference. Clinical trial design The diagnosis of acute coronary syndrome (ACS) patients adheres to the ACS Emergency Rapid Diagnosis and Treatment Guidelines, which classify cases asSTEM, NSTEMI and UA [ 3 ] . A total of 76 ACS patients admitted between April 1, 2022, and June 31, 2022, and who underwent coronary angiography at Shanghai East Hospital were included in our evaluation. Inclusion criteria: 1. Age ≥ 18 years old. 2. Meets the ACS diagnostic criteria and is clearly diagnosed with ACS Exclusion criteria: 1. Clinical instability, defined as hemodynamic or electrocardiographic instability. 2. Severe renal or hepatic insufficiency, indicated by an estimated glomerular filtration rate (EGFR) less than 30 ml/min or aspartate aminotransferase (AST) or alanine aminotransferase (ALT) levels exceeding 400 IU/L. 3. Patients who have previously been treated with PCSK9 inhibitors. 4. Recent use of systemic sex steroids or cytotoxic drugs within the past 3 months. 5. Active infection or significant hematological, metabolic, or endocrine dysfunction. 6. Patients with active malignant tumors requiring treatment. 7. Pregnancy. 8. Persistent atrial fibrillation. 9. Severe aortic valve insufficiency or aortic valve stenosis. 10. Peripheral arterial disease indicated by an ankle-brachial index (ABI) of 0.9 or lower, or a history of lower limb bypass grafting and/or endovascular treatment. The study involved the random allocation of patients into distinct treatment cohorts, including those receiving PCSK9 inhibitors (specifically, evolocumab 140 mg or alirocumab 75 mg) administered subcutaneously every 2 weeks in conjunction with statins (atorvastatin 20 mg or rosuvastatin 10 mg), as well as a control group receiving statins alone (atorvastatin 20 mg or rosuvastatin 10 mg). All participants were also administered a standard treatment regimen consisting of aspirin, clopidogrel/Tegrelo, angiotensin-converting enzyme inhibitor (ACEI) / adrenergic receptor binder (ARB), and β-blockers, unless contraindications were present for the use of these medications. Clinical data collection Patient demographics were gathered upon enrollment. Blood samples were obtained and AS indicators were evaluated before treatment initiation, as well as at 1 and 6 months post-treatment commencement. The blood samples were expeditiously transported to the laboratory at Shanghai East Hospital for analysis. The collected blood samples were promptly transported to the laboratory at Shanghai East Hospital for analysis. Various indicators including troponin T(Tnt), N-terminal brain natriuretic peptide (NT-pro-BNP), total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), high-density lipoprotein (HDL), small dense low-density lipoprotein (sdLDL), lipoprotein (a)[Lp (a)], C-reactive protein (CRP), Interleukin- 6 (IL-6), procalcitonin (PCT) and fibrinogen (FIB) were collected from all patients. To minimize bias, the same professional physician conducted measurements of PWV and ABI using the Omron Arteriosclerosis Tester (BP-203RPEIII) during a state of rest. Cell culture and treatment Mouse aortic smooth muscle cell lines (VSMCs, No. YC-A023) were purchased from Yuanjing Biotechnology (China,Guangzhou). The cells were cultured in DMEM/F12 (ShanghaiBasalmedia, China) medium containing 10% fetal bovine serum (Gibco, America) + 1% penicillin-streptomycin (NCMBiotech, China) in 5% CO 2 at 37℃. The medium was changed every two days. According to published methods, 10 mmol/L β-gp, 20ug/m dexamethasone and 50ug/mL L-ascorbic acid were added to the routine medium to induce osteogenesis of VSMCs for 7 days, the medium were changed every 2/3 days [ 23 – 28 ] . To mimic the effects of PCSK9i in vivo, 100 µg/mL of reagent-grade purified evolocumab (Selleck, America) was used to co-incubate with VSMCs for 7 days during osteogenesis induction [ 29 – 31 ] . To mimic the stimulation of VSMCs by PCSK9 protein in vivo, refer to previous research [ 32 ] , 0 µg/ml, 0.55 µg/ml, 1.1 µg/ml, 2.2 µg/ml, and 4.4 µg/ml of recombinant human PCSK9 (MedChemExpress, USA) were co-incubated with VSMCs for 7 days, and the concentration exhibiting the highest intracellular calcium content was chosen for subsequent experimental procedures. Detection of calcium content within VSMCs As per the guidelines provided by the Calcium Ion Assay Kit (Biyun Tian, China), the working solution for the assay was prepared by combining equal volumes of Solution A and Solution B. Subsequently, 50uL of VSMCs lysate was added to each well of the 96-well plate. Then 150uL of working solution per well was added to the 96-well plate and incubate for 10 min at room temperature, protected from light. Measure the absorbance at 575 nm to calculate the standard curve for calcium content. Analyze the remaining samples for BCA protein concentration. Express the Ca 2+ concentration as calcium content divided by protein content in ug/mg. Alizarin red staining According to the instructions of the Alizarin Red Staining Kit (Biyun Tian, China), VSMCs were fixed with 4% paraformaldehyde for 30 min at room temperature. The cells were then washed with sterile PBS three times and incubated with Alizarin Red Staining Solution for 30 min at 37°C. After that, the cells were washed with ddH 2 O three times and observed under a 10X light microscope. Alkaline phosphatase activity assay According to the instructions of the Alkaline Phosphatase Assay Kit (Biyun Tian, China), prepare the substrate working solution by diluting the color-developing substrate. Then add 25uL of VSMCs lysate, 25uL of detection buffer, and 50uL of the chromogenic substrate to the sample wells of a 96-well plate. Incubate at 37℃ for 10min and stop the reaction by adding 100uL of termination solution to each well. Measure the absorbance at 405 nm. Express the results as the ratio of enzyme activity unit to protein concentration. Western blot testing VSMCs were lysed using RIPA buffer (ShanghaiEpizyme, China) containing a protease inhibitor mixture (ShanghaiEpizyme, China). After centrifugation, the supernatant was extracted. BCA kit (ShanghaiEpizyme, China) was used for protein concentration measurements with appropriate loading buffer. Extracted proteins (30 µg per lane) were run on an SDS-PAGE gel and then transferred to a PVDF membrane (Merck, Germany). Primary antibodies with α-SMA (arigobio, America) and runt-related transcription factor 2(RUNX2, absin, China) were incubated overnight at 4°C. After careful washing with tween-containing triple-buffered saline (TBST), the membranes were incubated with horseradish peroxidase (HRP)-coupled secondary antibody (Biyun Tian, China, 1:2000) for 1 h at room temperature. The membranes were washed again three times for 10 min, and the signals were detected and quantified with Tanon 5200 multifunctional image analysis system (Tanon Technology, Shanghai, China). The average gray values of the bands were analyzed utilizing Image J (NIH, Bethesda, USA) with GAPDH serving as the internal reference protein. Statistical analysis Data were analyzed using SPSS 25.0. Count data were described as frequencies (%). Continuous variables were expressed as mean ± standard deviation (SD) when normally distributed or median and interquartile range (IQR) when not normally distributed. Comparisons between the two groups were performed using paired t-tests or Mann-Whitney U-tests for continuous variables, and chi-square or Fisher exact tests for dichotomous variables when appropriate. The Kolmogorov-Smirnov test was used to determine whether the distribution was normal or non-normal. The closeness test was analyzed using spearman correlation analysis. A p -value < 0.05 was considered statistically significant. Results Identification of drug target-associated SNPs We identified 10 independent SNPs from the GWAS database(Table S2 ). These SNPs are located within or near the PCSK9 gene, showing strong associations with PCSK9 and LDL-C levels in the GLCC dataset. Consequently, these SNPs can serve as genetic proxies for PCSK9 and imitate the effects of PCSK9i. To ensure the exclusion of confounding factors, we employed PhenoScanner, heterogeneity analyses, multiplicity analyses, MR-PRESSO and leave-one-out tests to establish the relationship between these SNPs and the outcomes (Table S3). Positive control analysis Given the widespread utilization of PCSK9i in the treatment of CHD, we employed aggregated data from the coronary GWAS as a means of confirming the reliability of the SNPs. The implementation of the IVW method yielded statistically significant evidence (OR [95%] = 0.605 [0.516 ~ 0.709], p = 0.001) showcasing a noteworthy decrease in the risk of CHD through the use of PCSK9i (Fig. 2 ),. This outcome was consistently observed across both the weighted median and MR Egger approaches. The validation of the positive control further substantiates credibility of the SNPs. The effect of genetic prediction of PCSK9 inhibition on arterial stiffness In our study, we utilized the IVW method to conduct correlation analysis. Our findings indicate a negative correlation between genetic prediction of PCSK9 inhibition and PWRI (beta [95% CI] =-0.058 [-0.094~-0.023], p = 0.001). However, we did not observe significant correlations with PWPPT and PWASI(Fig. 2 ). Sensitivity analysis revealed no evidence of heterogeneity or horizontal pleiotropy across all outcomes ( p > 0.05). Additionally, the retention method demonstrated that removing SNPs did not significantly impact the results. Cochran's Q-test did not identify any indications of heterogeneity (Table S3). The leave-one-out method demonstrated no statistically significant variance in the results following the exclusion of SNPs(Supplementary PDF). Baseline information for clinical studies A total of 88 patients with ACS after PCI were screened. Ultimately, 71 eligible patients were included and randomly divided into the PCSK9i group (n = 36) and the control group (n = 35) at a ratio of 1:1(Fig. 3 ). There were no notable disparities observed in the overall data of the two groups, encompassing fundamental information, medical history, and medication history(Table.1, p > 0.05). However, discrepancies were identified solely in smoking history(Table.1, p = 0.013) and the administration of β-blocker(Table.1, p = 0.001). Moreover, no statistically significant variances were found in baseline data, CRP, FIB, IL-6, PCT, or lipid levels between the two groups(Table.2, p > 0.05). Table.1 Clinical Characteristics for ACS Study Group (n = 71) Clinical feature total(n = 71) the treatment group (n = 36) the control group (n = 35) p -value Age (years) 66.8 ± 11.2 66(36–91) 71(49–88) 0.247 Men, n (%) 52(73.2) 28(77.8) 24(68.6) 0.43 BMI(kg×m − 2 ) 25.02 24.6(19.3–31.2) 25.1(19-30.8) 0.739 Coronary heart disease, n (%) 12 (16.9%) 7(19.4) 5(14.3) 0.562 Diabetes mellitus, n (%) 18 (25.4%) 6(16.7) 12(34.3%) 0.088 Heart failure, n (%) 4 (5.6%) 2(5.6) 2(5.7) 0.977 Stroke history, n (%) 2 (2.8%) 1(2.8) 1(2.9) 0.984 Hypertension, n (%) 40 (56.3%) 23(63.9) 17(48.6) 0.193 Smoking history, n (%) 35 (49.3%) 23(63.9) 12(34.3) 0.013** STEMI, n (%) 46 (64.8%) 27(75) 19(54.3) 0.08 NSTEMI, n (%) 15 (21.1%) 7(19.4) 8(22.9) 0.08 Unstable angina, n (%) 10 (14.1%) 2(5.6) 8(22.9) 0.08 ARB, n (%) 58(81.7) 31(81.6) 27(73) 0.329 ACEI, n (%) 3(4.2) 2(5.3) 1(2.7) 0.572 β-blocker, n (%) 61(85.9) 36(94.7) 25 (67.6) 0.001** CCB, n (%) 18(25.4) 7(18.4) 11(29.7) 0.246 diuretic, n (%) 34(47.9) 18(47.4) 16(43.2) 0.718 Hypoglycemic drugs, n (%) 11(15.5) 7(18.4) 4 (10.8) 0.351 Anticoagulation, n (%) 41(57.7) 22(57.9) 19(51.4) 0.561 * p < 0.05 ** p < 0.01 Table.2 Clinical feature of the study population at baseline Clinical feature the treatment group (n = 36) the control group (n = 35) p -value Tnt(ng/ml) 1.23(0.005-10) 1.38(0.006-10) 0.284 FBG(mmol/L) 5.7(3.74–18.97) 6.33(3.97–16.4) 0.252 TC(mmol/L) 4.46(3.13–9.05) 4.38(2.05–8.23) 0.243 TG(mmol/L) 1.41(0.65–3.82) 1.53(0.65–3.5) 0.421 HDL(mmol/L) 1.02(0.63-2) 1.01(0.67–1.74) 0.904 LDL(mmol/L) 2.96(1.56–6.91) 2.76(1.76–5.69) 0.476 sdLDL(mmol/L) 0.84(0.33–1.98) 0.63(0.2–1.98) 0.531 Lp(a) (nmol/L) 37(1-257) 25(4-235) 0.272 WBC(*10^9/L) 10.09(6-17.86) 9.12(5.77–17.39) 0.178 N(*10^9/L) 7.91(3.11–12.19) 6.99(3.09–12.45) 0.501 CRP(mg/L) 2.03(1.6-85.53) 2.3(1.6-104.05) 0.218 FIB(g/L) 3.13(1.77–6.77) 3.61(2.06–7.54) 0.051 IL-6(pg/ml) 14.68(1.73–91.94) 15.71(3.22–50.01) 0.565 PCT(ng/ml) 0.207(0.02–0.677) 0.32(0.013–4.65) 0.242 Changes in lipids and inflammatory factors after treatment in both groups In comparison to the baseline data, the PCSK9i group exhibited a statistically significant and persistent reduction in the levels of inflammatory markers WBC, N, CRP, IL-6 and PCT at both 1 and 6 months. Additionally, the levels of TC, LDL, Lp(a), and sdLDL continued to decrease significantly. However, there was no significant decrease in TG levels at 1 month, with the results lacking statistical significance. Nevertheless, a statistically significant decrease was observed at 6 months. Furthermore, the patients' HDL levels displayed a tendency to increase at both 1 month and 6 months, with statistically significant results (Table.3). Table.3 Indicators of the PCSK9i group after 1-mo and 6-mo Indicators baseline 1month 6month p -value (1month vs. Baseline) p -value (6month vs. 1month) TC(mmol/L) 4.46(3.13–9.05) 3.47(1.79–4.9) 2.778(1.64–4.21) 0.000** 0.000** TG(mmol/L) 1.41(0.65–3.82) 1.31(0.72–2.89) 1.38(0.70–2.32) 0.060 0.003** HDL(mmol/L) 1.02(0.63-2) 1.07(0.83–1.92) 1.21(0.73–1.82) 0.000** 0.000** LDL(mmol/L) 2.96(1.56–6.91) 1.89(0.34–3.12) 1.4(0.43–2.27) 0.000** 0.000** sdLDL(mmol/L) 0.84(0.33–1.98) 0.77(0.28–1.99) 0.72(0.13–1.76) 0.017* 0.003** Lp(a) (nmol/L) 37(1-257) 32(2-162) 31.5(4–87) 0.003** 0.231 WBC(*10^9/L) 10.09(6-17.86) 8.29(5.12–11.17) 7.88(5.83–9.67) 0.000** 0.157 N(*10^9/L) 7.91(3.11–12.19) 5.33(2.91–8.23) 5.35(3.14–6.95) 0.000** 0.610 CRP(mg/L) 2.03(1.6-85.53) 1.6(1.6–7.92) 1.6(1.21–5.1) 0.000** 0.968 FIB(g/L) 3.13(1.77–6.77) 2.23(1.17–4.27) 1.99(1.21–3.32) 0.000** 0.003** IL-6(pg/ml) 14.68(1.73–91.94) 7.3(1.71–21.77) 4.18(1.17–7.3) 0.000** 0.000** PCT(ng/ml) 0.207(0.020–0.677) 0.095(0.010–0.350) 0.160(0.010–0.320) 0.000** 0.030* * p < 0.05 ** p < 0.01 In comparison to the baseline data, the control group exhibited a statistically significant reduction in inflammatory factors WBC, N, CRP, IL-6, and PCT following 1 month of treatment. Nonetheless, the extended duration of treatment to 6 months did not yield any additional improvements in the remaining markers, including IL-6. Lp(a) and sdLDL did not exhibit significant changes, and the observed results did not demonstrate statistical significance. Conversely, the patients' TC and LDL continued to decrease in a statistically significant manner. Notably, HDL did not display significant changes at the 1-month checkpoint, and these findings also lacked statistical significance. However, a noteworthy increase was observed at the conclusion of the 6-month follow-up period, with the results demonstrating statistical significance(Table.4). Table.4 Indicators of the control group after 1-mo and 6-mo Indicators baseline 1month 6month p -value (1month vs. Baseline) p -value (6month vs. 1month) TC(mmol/L) 4.38(2.05–8.23) 3.92(2.15–5.95) 3.76(2.56–5.13) 0.002** 0.035* TG(mmol/L) 1.53(0.65–3.5) 1.40(0.49–3.2) 1.38(0.57–3.06) 0.027* 0.147 HDL(mmol/L) 1.01(0.67–1.74) 1.09(0.73–1.75) 1.12(0.72–1.68) 1.000 0.001** LDL(mmol/L) 2.76(1.76–5.69) 2.10(1.33–3.66) 1.99(0.76–3.17) 0.000** 0.012* sdLDL(mmol/L) 0.63(0.2–1.98) 0.75(0.32–1.85) 0.77(0.29–1.82) 0.161 0.539 Lp(a) (nmol/L) 25(4-235) 36(7-217) 33(7-116) 0.752 0.959 WBC(*10^9/L) 9.12(5.77–17.39) 8.01(4.27–9.82) 7.99(5.23–9.79) 0.000** 0.164 N(*10^9/L) 6.99(3.09–12.45) 5.71(2.16–7.36) 5.87(3.34–7.55) 0.000** 0.408 CRP(mg/L) 2.3(1.6-104.05) 4.99(1.6–68.8) 5.47(1.6–29.4) 0.050 0.265 FIB(g/L) 3.61(2.06–7.54) 3.07(1.97–7.32) 3.01(1.66–5.79) 0.013* 0.322 IL-6(pg/ml) 15.71(3.22–50.01) 9.76(2.2–99) 5.89(1.65–20.1) 0.001** 0.001** PCT(ng/ml) 0.32(0.013–4.65) 0.178(0.010–0.83) 0.170(0.010–1.35) 0.012* 0.459 * p < 0.05 ** p < 0.01 In comparison to the control group, the PCSK9i group exhibited statistically significant enhancements in CRP, FIB, IL-6 and PCT following a 1-month intervention. Nevertheless, there was no notable disparity in lipid levels between the two groups. Subsequent to 6 months of treatment, there was a statistically significant reduction in TC, LDL-C, CRP, FIB, IL-6 and PCT levels(Fig. 4 ). Alterations in PWV in both groups of patients At the baseline level, there was no statistically significant difference between bilateral PWV and bilateral ABI between the two groups ( p > 0.05). After 1 month of treatment, RPWV ( p < 0.05) and bilateral ABI ( p 0.05), and no significant changes in bilateral PWV and bilateral ABI were observed in the control group ( p > 0.05). After 6 months of treatment, there was a significant decrease in both bilateral PWV and ABI in the PCSK9i group ( p 0.05) (Table.5). Comparing the AS parameters between the two groups of patients after 6 months of treatment, there was no significant difference in bilateral ABI ( p > 0.05), but bilateral PWV in the PCSK9i group was significantly lower than that in the control group ( p < 0.05) (Table.5). Table.5 PWV of the two groups after 1 month and 6 months Group Indicators Baseline 1 month 6 month p -Value (1month vs. Baseline) p -Value (6month vs. 1month) PCSK9i group LPWV (cm/s) 1448.5(1106–1796) 1467(1098–1791) 1320(1021–1543) 0.219 < 0.001** RPWV (cm/s) 1497.5(1133–1912) 1488.5(1103–1882) 1350(1032–1679) 0.026* < 0.001** LABI 1.07(1-1.11) 1.04(1.01–1.1) 1.02(0.99–1.06) 0.001** < 0.001** RABI 1.03(0.99–1.1) 1.03(1-1.07) 1.01(0.98–1.03) 0.002** < 0.001** Control group LPWV (cm/s) 1405(1128–2013) 1405(1138–1987) 1407(1138–1980) 0.849 0.850 RPWV (cm/s) 1451(1176–1873) 1461(1185–1882) 1465(1196–1890) 0.238 0.702 LABI 1.03(0.9–1.1) 1.04(0.92–1.09) 1.06(0.94–1.09) 0.358 0.680 RABI 1.02(0.91–1.1) 1.04(0.91–1.09) 1.04(0.95–1.09) 0.888 0.158 p -Value (PCSK9i vs. Control) LPWV (cm/s) 0.792 0.980 < 0.001** —— —— RPWV (cm/s) 0.413 0.423 0.012* —— —— LABI 0.775 0.629 0.152 —— —— RABI 0.580 0.791 0.089 —— —— * p < 0.05 ** p < 0.01 A correlation analysis was conducted between the changes in blood lipids and inflammatory factors in the PCSK9i group after 6 months of treatment and the changes in PWV. Only ΔCRP and ΔPWV were correlated(Table.6, r = 0.343, p = 0.043). Table.6 The relationship between ΔPWV and changes in inflammatory factors and blood lipids Indicators r - Value p - Value ΔTC 0.088 0.615 ΔTG 0.026 0.883 ΔHDL 0.289 0.093 ΔLDL 0.152 0.382 ΔsdLDL 0.198 0.255 ΔLp(a) 0.190 0.275 ΔWBC 0.110 0.528 ΔN 0.194 0.265 ΔCRP 0.343 0.043* ΔFIB 0.281 0.103 ΔIL-6 0.125 0.473 ΔPCT 0.240 0.164 * p < 0.05 Detection of calcium content in VSMCs In the pre-experiment we found that the intracellular calcium content showed a concentration-dependent increase with increasing PCSK9 concentration. The highest intracellular calcium content of 2.2 µg/ml PCSK9 was selected for subsequent experiments(Fig. 5 A). The intracellular calcium content increased significantly in the osteogenic group(OS) compared to the control group(NC) and decreased after treatment with PCSK9i compared to OS. After stimulating the cells with PCSK9, the intracellular calcium content increased compared to NC. After treatment with PCSK9i, the intracellular calcium content decreased compared to the PCSK9 group(Fig. 5 B). Alizarin Red stain In this experiment, an increase in the intensity of red hues correlates with a higher concentration of calcium salt deposition. Calcium salt deposition was significantly increased in OS compared to NC and was significantly decreased after treatment with PCSK9i compared to OS. After stimulation of cells with PCSK9, calcium salt deposition increased compared to NC. After treatment with PCSK9i, calcium salt deposition was decreased compared to PCSK9 group (Fig. 6 ). Alkaline phosphatase activity assay ALP activity was significantly increased in OS compared to NC and significantly decreased after treatment with PCSK9i compared to OS. After stimulation of cells with PCSK9, ALP activity increased compared to NC. After treatment with PCSK9i, ALP activity was decreased compared to PCSK9 group (Fig. 5 C). WESTERN BLOT testing WB results showed that RUNX2 expression was up-regulated and α-SMA expression was down-regulated in OS compared to NC, and RUNX2 expression was down-regulated and α-SMA expression was up-regulated after the treatment with PCSK9i compared to OS. After stimulation of cells with PCSK9, RUNX2 expression was up-regulated and α-SMA expression was down-regulated compared to NC. After treatment with PCSK9 inhibitor, RUNX2 expression was down-regulated and α-SMA expression was up-regulated compared to PCSK9 group(Fig. 5 D). Discussion PCSK9 is a constituent of the secreted chymotrypsin family's ninth member, initially identified as an enzyme involved in regulating apoptosis within the nervous system. Its primary expression is observed in the kidney, liver, and intestine [ 34 ] . PCSK9 instigates hyperlipidemia and atherosclerosis through the stimulation of lysosomal degradation of the low-density lipoprotein receptor (LDL-R) within the liver, consequently impeding the efficiency of LDL-C clearance [ 33 , 34 ] . The primary mechanism of action for PCSK9i involves their binding to the PCSK9 molecule, thereby impeding its interaction with LDL-R and attenuating receptor degradation. Consequently, this process enhances the uptake of LDL-C in the bloodstream, ultimately leading to a reduction in its concentration [ 35 , 36 ] . Alirocumab and evolocumab have received approval from the U.S. Food and Drug Administration (FDA) for the treatment of familial hypercholesterolemia, statin intolerance or contraindications, and atherosclerotic disease among this category of medications [ 37 ] . In recent times, notable progress has been made in the realm of scientific investigation pertaining to the potential cardioprotective effects of PCSK9i that extend beyond their lipid-lowering properties. These advancements encompass the exploration of immune response modulation, involvement in apoptosis, participation in thrombosis, modulation of inflammatory factors and enhancement of arterial endothelial function [ 9 ] . Due to the multifaceted characteristics of PCSK9i and the significant involvement of AS in the pathogenesis of cardiovascular disease, our objective was to investigate the potential association between PCSK9i and AS in individuals diagnosed with ACS. Initially, a two-sample MR analysis was conducted. Considering the established impact of PCSK9 inhibition on LDL levels [ 35 ] , the selection of variants resembling PCSK9 proxies near the PCSK9 gene was based on LDL levels as a criterion. The utilization of a drug-targeted MR method has been extensively employed in prior published studies [ 17 , 19 , 36 – 38 ] . In order to enhance the credibility of these SNPs, we employed the CHDdataset as a positive control and observed a significant decrease in risk of CHD associated with these SNPs, thus validating their suitability as IVs. Based on our findings, it can be inferred that genetically predicted PCSK9 inhibition exhibits a negative correlation with AS parameter PWRI. Consequently, we propose the hypothesis that PCSK9i has the potential to mitigate AS. Similar results have been described in several clinical studies, but no evidence has been published at the genome-wide level, which is the innovation of this study. The relationship between PCSK9i and AS has been documented in a subset of clinical studies involving patients with FH. Ruscica et al. conducted a comprehensive randomized clinical trial, which demonstrated a noteworthy correlation between circulating PCSK9 and PWV. Furthermore, the use of a PCSK9i to decrease circulating PCSK9 levels may have a beneficial impact on the amelioration of AS [ 13 ] . Papaioannou et al. observed a notable enhancement in PWV subsequent to the incorporation of PCSK9i into statin therapy among individuals with FH [ 39 ] . Scicali R et al. found that PCSK9i significantly reduced PWV in patients with FH after 6 months of treatment [ 40 ] and that lowering LDL-C was associated with improved PWV. However, there exist notable distinctions between patients with ACS or FH in relation to their internal environment, pathophysiologic mechanisms and interventions. At present, there is a dearth of research examining whether patients with ACS experience equivalent AS- reducing advantages from PCSK9i. Therefore, we proceeded to conduct a cohort study in order to examine the alterations in lipids, inflammatory markers, and AS among patients with ACS following the administration of statins and PCSK9i. Consistent with numerous contemporary clinical investigations, both PCSK9i and statins exhibited noteworthy lipid-lowering effects in our cohort. However, these effects varied with respect to lipid compositions. After 6 months of treatment, patients in PCSK9i group showed significant decreases in TC, TG, LDL, sdLDL, and Lp (a), while HDL increased significantly. In control group using statins we similarly observed improvements in TC, TG, LDL and HDL, but not in Lp (a) and sdLDL. We chose PWV which is currently considered the "gold standard" in clinical practice as the primary measure to evaluate AS in patients with ACS. Additionally, we utilized ABI as a supplementary measure representing the ratio of ankle arterial pressure to brachial arterial pressure. ABI serves as an indicator for the presence of atherosclerosis or stenosis in the lower extremities [ 41 ] .Based on data from several studies [ 42 ] . ABI < 0.90 has been widely accepted as a diagnostic criterion for lower extremity arterial disease, and the PWV data of such patients with severe atherosclerosis or stenosis of the lower extremity arteries could not reflect the true AS, so we used ABI < 0.9 as an exclusion criterion for the study design. Concurrently, considering the association between ABI and AS, along with ABI's predictive capability for adverse cardiovascular events [ 43 – 45 ] , we incorporated ABI as an additional component in our analysis to achieve a more comprehensive evaluation of AS. There was an absence of disparity in baseline PWV between the PCSK9i and control groups. Following 1 month of treatment, a decrease in RPWV was observed in the PCSK9i group, although no statistically significant variation in PWV was evident between the two groups. However, after 6 months of treatment, PWV was significantly lower in the PCSK9i group compared to 1month, which was not observed in control group. PWV was significantly lower in the PCSK9i group than in the control group after 6 months of treatment. These data suggest that PCSK9i are effective in improving AS in patients with ACS, but may require a longer period of time to demonstrate a significant effect. This finding is similar to that of Papaioannou, Roberto.S, and others, who also found that a reduction in LDL-C was associated with improved PWV in patients with familial hypercholesterolemia [ 40 ] .However, by correlating ΔPWV with ΔLDL in PCSK9i group, we did not reach the same conclusion. The reason for this situation may be due to the difference in the study population. The previous study focused on patients with FH, while our study focused on patients with ACS. Due to the distinct characteristics of these diseases, improving AS in ACS patients with PCSK9i may not solely be achieved by reducing LDL levels. Lp (a) is an LDL particle bound to apolipoprotein (a), which carries oxidized phospholipids that adversely affect a variety of pathways including inflammation, endothelial function, and thrombosis [ 46 ] . Lp (a) is also known to contribute to the progression of atherosclerosis and increase the risk of ASCVD [ 47 ] . High levels of Lp (a) have been linked to a higher risk of diseases like CVD and stroke as indicated by multiple studies [ 47 – 49 ] . Several clinical trials have been conducted to examine the efficacy of PCSK9 inhibitor therapy in reducing Lp(a) and sdLDL [ 46 , 50 , 51 ] .Our cohort study also showed significant reductions in Lp (a) and sdLDL levels in patients treated with PCSK9i, indicating that PCSK9i may target these two lipid components. However, correlation analyses did not find a link between ΔPWV and reductions in these lipoproteins, suggesting that PCSK9i may improve AS through other mechanisms. The conventional perspective posits that lipids are the primary etiological factor in CHD.Despite the general populace has experienced a consistent decline in total plasma cholesterol levels because of the ongoing advancements in lipid-lowering medications [ 52 – 54 ] , nevertheless, a notable prevalence of atherosclerotic cardiovascular disease (ASCVD) events persists, even among individuals who have effectively managed their LDL levels. [ 55 ] As lipids alone proved insufficient in accounting for all occurrences of atherosclerotic cardiovascular disease (ASCVD), subsequent investigations gradually revealed additional potential mechanisms, with inflammation emerging as a particularly significant factor [ 56 ] .Crea et al. summarized the possible mechanisms that predispose to ACS, suggesting that myocardial infarction(MI) may result from plaque rupture triggered by a systemic inflammatory response [ 57 ] .In addition, about 60% of patients with MI have a high initial CRP (≥ 2.0 mg/L) [ 58 ] . In the context of MI, the process of cardiomyocyte necrosis results in the release of harmful molecules that interact with pattern-recognition receptors, such as toll-like receptors. This interaction combined with complement activation and the presence of reactive oxygen species, leads to the upregulation of cytokines and chemokines. Consequently, these molecular events contribute to the development of both coronary and systemic inflammatory responses [ 59 ] . This inflammatory response has the potential to inflict additional harm upon the myocardium, resulting in heart failure, inducing a pervasive inflammation across the coronary arteries, heightening the likelihood of recurring myocardial infarction, and ultimately contributing to elevated post-infarction mortality rates [ 60 ] . However, due to the lack of efficacy demonstrated in multiple trials focusing on the early inflammatory response following ACS [ 61 ] , the majority of clinical guidelines do not endorse the use of anti-inflammatory therapy for patients diagnosed with ACS. However, in clinical practice we have observed that ACS patients with PCSK9i tend to have more significant improvements in inflammatory factors, even if they do not receive anti-inflammatory therapy. PCSK9i may have anti-inflammatory effects due to its close association with inflammatory processes [ 62 , 63 ] . Therefore, we also examined and analyzed changes in commonly observed inflammatory factors in this study. Compared to the baseline, inflammatory factors WBC, N, CRP, IL-6, and PCT consistently decreased in the PCSK9i group at 1 and 6 months. The control group also showed significant decreases in these factors after 1 month, but no further improvement was observed except for IL-6 at 6 months. After 1 and 6 months of treatment, PCSK9i group showed significantly lower levels of CRP, IL-6, and PCT compared to control group. However, there were no significant differences in WBC and N between two groups. All ACS patients we studied were discharged from the hospital with improved conditions after treatment. Therefore, the improvement of inflammatory markers in both groups after 1 month of treatment does not necessarily indicate the anti-inflammatory effects of PCSK9i or statins. It is possible that these inflammatory factors naturally reduce as the disease state improves. However, with continued use of the drug, patients in PCSK9i group demonstrated a sustained decrease in the 3 inflammatory markers after 6 months which was difficult to be explained by the self-limiting nature of the disease. In contrast, control group did not observe the same changes. After 6 months of treatment, the PCSK9i group showed significantly lower levels of the 3 inflammatory factors compared to control group, highlighting the distinct anti-inflammatory impact of PCSK9i in contrast to statins. In addition, we conducted a correlation analysis between alterations in inflammatory factors and ΔPWV after 6 month in PCSK9i group. Interestingly, our findings revealed that only ΔCRP exhibited a significant correlation with ΔPWV. C-reactive protein, a cyclic pentameric glycoprotein predominantly synthesized in the liver, has been extensively investigated in the context of cardiovascular disease. A substantial body of evidence substantiates the utility of CRP as a guide for therapeutic interventions in primary prevention [ 64 ] .A meta-analysis that included more than 160,000 individuals with new-onset ASCVD showed that increased hsCRP levels were associated with an increased risk of CHD, ischemic stroke, and vascular mortality [ 65 ] . The JUPITER trial demonstrated that daily administration of Rosuvastatin significantly reduced the incidence of first MI, stroke, or cardiovascular death in individuals with hsCRP ≥ 2 mg/L and LDL-C < 130 mg/dL [ 66 ] . Based on these observations, the guidelines for blood cholesterol management encourage consideration of statins in patients with hsCRP ≥ 2 mg/L [ 67 ] . While CRP's connection to ASCVD has been extensively researched, its association with AS remains understudied. In patients with hyperlipidemia, there was a significant positive correlation between AS and CRP, with correlations ranging from mild to moderate associations (Pearson r = 0.33 to r = 0.624) [ 68 ] .In atherosclerotic population, higher CRP levels at baseline were independently associated with reduced aortic distensibility [ 69 ] . Previous studies have primarily examined the link between CRP levels and AS, but rarely explored the connection between lower CRP and improved PWV. Our study discovered that lower CRP levels were associated with improved PWV in ACS patients, and this reduction in CRP was due to the anti-inflammatory effects of PCSK9i. Although our spearman correlation analysis only shows a correlation between ΔCRP and ΔPWV but cannot determine causality, our data suggest that CRP levels decrease before significant changes in PWV occur after 1 month of treatment. This indicates that improving CRP levels is prioritized over improving PWV. Therefore, we believe that PCSK9 may improve AS by regulating CRP levels. Further studies are needed to confirm this, and we eagerly await future research results. We further designed cellular experiments to validate the effect of PCSK9i on AS. Osteogenesis of VSMCs is one of the main response indicators of AS at the cellular level.The expression of RUNX2 plays a key role in the osteogenesis of VSMCs. In the physiological condition, the vasculature exhibits a low level of RUNX2 expression. However, when subjected to bone morphogenetic protein (BMP-2) stimulation, high phosphorus levels, oxidative stress or inflammation, VSMCs undergo osteogenic differentiation. This process is characterized by a reduction in the expression of the specific marker smooth muscle actin (Smooth Muscle Actin Alpha 2, α-SMA) and an elevation in RUNX2 expression [ 70 – 73 ] .In addition, its downstream osteogenic marker ALP activity is also increased, further contributing to calcification [ 74 ] . We successfully induced osteogenesis by treating VSMCs with osteogenic medium, resulting in increased RUNX2 expression, decreased α-SMA expression, decreased ALP activity and increased calcium deposition after 7 days. However, Co-incubation with PCSK9i improved these osteogenic indicators, confirming the protective effect of PCSK9i on VSMC osteogenesis. To confirm if PCSK9i's impact is due to PCSK9, we tested the connection between PCSK9 and osteogenesis in VSMCs. By exposing VSMCs to external PCSK9, we observed that it prompted the cells to adopt an osteogenic phenotype, worsening their calcium salt buildup. This demonstrated that PCSK9 can cause osteogenesis in VSMCs and PCSK9 inhibition is a way to improve this condition. Conclusion Overall, the findings from our MR analysis provide evidence that PCSK9i have the potential to enhance AS, as substantiated by our clinical trials and cellular analyses. Our observations of clinical research indicated that PCSK9i effectively ameliorate CRP levels and mitigate PWV in individuals with ACS, thereby suggesting their capacity to attenuate vascular inflammation and diminish AS. Besides, our cell experiments showed that PCSK9i can ameliorate osteogenesis of VSMCs. Consequently, the significance of incorporating PCSK9i into the therapeutic regimen for ACS patients warrants further emphasis. Declarations This study has been retrospectively registered and is pending approval. Ethics approval and consent to participate The clinical study was conducted in accordance with the principles of the Declaration of Helsinki, and all patients who met the inclusion criteria signed informed consent forms. The ethics committee of the Shanghai East Hospital approved the study design and allowed the use of clinical data. Number:【2022】研审第（205）号. Date: April 24, 2022. Informed consent was obtained from all individual participants included in the study. In MR analysis, before the collection of the original database, informed consent was acquired from each participant and approved by the respective local ethics committees of GWAS. Consent for publication Patients signed informed consent regarding publishing their data. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the National Natural Science Foundation of China (Grant Nos. 82070416, 81870296 and 82104632), the Shanghai Key Clinical Specialty Project (shslczdzk06202), and the Top-level Clinical Discipline Project of Shanghai Pudong District (Grant/Award Number: PWYgf2021-01). Authors' contributions LX conducted MR analysis and statistical analysis of clinical data, completed most of the cell experiments, and was a major contributor in writing the manuscript. LW collected major clinical data, completed statistical analysis, and wrote part of manuscript. Yuanqi W & Yiqiong W assisted in statistical analysis and complete cell experiments. YJ, PD& JC contributed to data collection and statistical analysis. CZ, RW , TJ & XL reviewed and edited the manuscript. LX &MT translated and polished the manuscript. JL designed an experimental plan, provided financial support and supervised the entire research. All authors have reviewed and approved the final manuscript. Acknowledgements Not applicable. References Bhatt DL, Lopes RD, Harrington RA. Diagnosis and Treatment of Acute Coronary Syndromes: A Review. JAMA. 2022. 327(7): 662–675. Eisen A, Giugliano RP, Braunwald E. Updates on Acute Coronary Syndrome: A Review. JAMA Cardiol. 2016. 1(6): 718–30. Byrne RA, Rossello X, Coughlan JJ, et al. 2023 ESC Guidelines for the management of acute coronary syndromes. Eur Heart J. 2023. 44(38): 3720–3826. Du L, Cheng Z, Zhang Y, Li Y, Mei D. The impact of medication adherence on clinical outcomes of coronary artery disease: A meta-analysis. Eur J Prev Cardiol. 2017. 24(9): 962–970. Kaasenbrood L, Boekholdt SM, van der Graaf Y, et al. Distribution of Estimated 10-Year Risk of Recurrent Vascular Events and Residual Risk in a Secondary Prevention Population. Circulation. 2016. 134(19): 1419–1429. Mach F, Baigent C, Catapano AL, et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J. 2020. 41(1): 111–188. Rosenson RS, Hegele RA, Fazio S, Cannon CP. The Evolving Future of PCSK9 Inhibitors. J Am Coll Cardiol. 2018. 72(3): 314–329. Navarese EP, Kolodziejczak M, Kereiakes DJ, Tantry US, O'Connor C, Gurbel PA. Proprotein Convertase Subtilisin/Kexin Type 9 Monoclonal Antibodies for Acute Coronary Syndrome: A Narrative Review. Ann Intern Med. 2016. 164(9): 600–7. Ugovšek S, Šebeštjen M. Non-Lipid Effects of PCSK9 Monoclonal Antibodies on Vessel Wall. J Clin Med. 2022. 11(13). Lacolley P, Regnault V, Laurent S. Mechanisms of Arterial Stiffening: From Mechanotransduction to Epigenetics. Arterioscler Thromb Vasc Biol. 2020. 40(5): 1055–1062. Zieman SJ, Melenovsky V, Kass DA. Mechanisms, pathophysiology, and therapy of arterial stiffness. Arterioscler Thromb Vasc Biol. 2005. 25(5): 932–43. Anderson TJ, Phillips SA. Assessment and prognosis of peripheral artery measures of vascular function. Prog Cardiovasc Dis. 2015. 57(5): 497–509. Ruscica M, Ferri N, Fogacci F, et al. Circulating Levels of Proprotein Convertase Subtilisin/Kexin Type 9 and Arterial Stiffness in a Large Population Sample: Data From the Brisighella Heart Study. J Am Heart Assoc. 2017. 6(5). Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018. 362: k601. Gupta V, Walia GK, Sachdeva MP. 'Mendelian randomization': an approach for exploring causal relations in epidemiology. Public Health. 2017. 145: 113–119. Kim S, Chen J, Cheng T, et al. PubChem 2023 update. NUCLEIC ACIDS RESEARCH. 2023. 51(D1): D1373-D1380. Rosoff DB, Bell AS, Jung J, Wagner J, Mavromatis LA, Lohoff FW. Mendelian Randomization Study of PCSK9 and HMG-CoA Reductase Inhibition and Cognitive Function. J Am Coll Cardiol. 2022. 80(7): 653–662. Willer CJ, Schmidt EM, Sengupta S, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013. 45(11): 1274–1283. Li Z, Zhang B, Liu Q, et al. Genetic association of lipids and lipid-lowering drug target genes with non-alcoholic fatty liver disease. EBioMedicine. 2023. 90: 104543. Nikpay M, Goel A, Won HH, et al. A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nat Genet. 2015. 47(10): 1121–1130. Fung K, Ramírez J, Warren HR, et al. Genome-wide association study identifies loci for arterial stiffness index in 127,121 UK Biobank participants. Sci Rep. 2019. 9(1): 9143. Elsworth B, Lyon M, Alexander T, et al. The MRC IEU OpenGWAS data infrastructure. BioRxiv. 2020: 2020–08. Han Y, Zhang J, Huang S, et al. MicroRNA-223-3p inhibits vascular calcification and the osteogenic switch of vascular smooth muscle cells. J Biol Chem. 2021. 296: 100483. Sun Y, Byon CH, Yang Y, et al. Dietary potassium regulates vascular calcification and arterial stiffness. JCI Insight. 2017. 2(19): e94920. Sun Y, Byon CH, Yuan K, et al. Smooth muscle cell-specific runx2 deficiency inhibits vascular calcification. Circ Res. 2012. 111(5): 543–52. Deng L, Huang L, Sun Y, Heath JM, Wu H, Chen Y. Inhibition of FOXO1/3 promotes vascular calcification. Arterioscler Thromb Vasc Biol. 2015. 35(1): 175–83. Yang Y, Sun Y, Chen J, et al. AKT-independent activation of p38 MAP kinase promotes vascular calcification. Redox Biol. 2018. 16: 97–103. Zhang W, Sun Y, Yang Y, Chen Y. Impaired intracellular calcium homeostasis enhances protein O-GlcNAcylation and promotes vascular calcification and stiffness in diabetes. Redox Biol. 2023. 63: 102720. D'Onofrio N, Prattichizzo F, Marfella R, et al. SIRT3 mediates the effects of PCSK9 inhibitors on inflammation, autophagy, and oxidative stress in endothelial cells. Theranostics. 2023. 13(2): 531–542. Martino E, D'Onofrio N, Balestrieri A, et al. MiR-15b-5p and PCSK9 inhibition reduces lipopolysaccharide-induced endothelial dysfunction by targeting SIRT4. Cell Mol Biol Lett. 2023. 28(1): 66. Zulkapli R, Muid SA, Wang SM, Nawawi H. PCSK9 Inhibitors Reduce PCSK9 and Early Atherogenic Biomarkers in Stimulated Human Coronary Artery Endothelial Cells. Int J Mol Sci. 2023. 24(6): 5098. Bao H, Wang X, Zhou H, et al. PCSK9 regulates myofibroblast transformation through the JAK2/STAT3 pathway to regulate fibrosis after myocardial infarction. Biochem Pharmacol. 2024. 220: 115996. Seidah NG, Benjannet S, Wickham L, et al. The secretory proprotein convertase neural apoptosis-regulated convertase 1 (NARC-1): liver regeneration and neuronal differentiation. Proc Natl Acad Sci U S A. 2003. 100(3): 928–33. Cunningham D, Danley DE, Geoghegan KF, et al. Structural and biophysical studies of PCSK9 and its mutants linked to familial hypercholesterolemia. Nat Struct Mol Biol. 2007. 14(5): 413–9. Sabatine MS. PCSK9 inhibitors: clinical evidence and implementation. Nat Rev Cardiol. 2019. 16(3): 155–165. De Marchis GM, Dittrich TD, Malik R, et al. Genetic proxies for PCSK9 inhibition associate with lipoprotein(a): Effects on coronary artery disease and ischemic stroke. Atherosclerosis. 2022. 361: 41–46. Xie W, Li J, Du H, Xia J. Causal relationship between PCSK9 inhibitor and autoimmune diseases: a drug target Mendelian randomization study. Arthritis Res Ther. 2023. 25(1): 148. Cupido AJ, Reeskamp LF, Hingorani AD, et al. Joint Genetic Inhibition of PCSK9 and CETP and the Association With Coronary Artery Disease: A Factorial Mendelian Randomization Study. JAMA Cardiol. 2022. 7(9): 955–964. Papaioannou TG, Alexandraki KI, Tousoulis D. Arterial stiffness improvement after adding on PCSK9 inhibitors in patients with familial hypercholesterolemia. J Clin Lipidol. 2020. 14(4): 542. Scicali R, Di Pino A, Ferrara V, Rabuazzo AM, Purrello F, Piro S. Effect of PCSK9 inhibitors on pulse wave velocity and monocyte-to-HDL-cholesterol ratio in familial hypercholesterolemia subjects: results from a single-lipid-unit real-life setting. Acta Diabetol. 2021. 58(7): 949–957. Carter SA. Indirect systolic pressures and pulse waves in arterial occlusive diseases of the lower extremities. Circulation. 1968. 37(4): 624–37. Kullo IJ, Rooke TW. CLINICAL PRACTICE. Peripheral Artery Disease. N Engl J Med. 2016. 374(9): 861–71. Criqui MH, McClelland RL, McDermott MM, et al. The ankle-brachial index and incident cardiovascular events in the MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol. 2010. 56(18): 1506–12. Resnick HE, Lindsay RS, McDermott MM, et al. Relationship of high and low ankle brachial index to all-cause and cardiovascular disease mortality: the Strong Heart Study. Circulation. 2004. 109(6): 733–9. Newman AB, Siscovick DS, Manolio TA, et al. Ankle-arm index as a marker of atherosclerosis in the Cardiovascular Health Study. Cardiovascular Heart Study (CHS) Collaborative Research Group. Circulation. 1993. 88(3): 837–45. Lampsas S, Xenou M, Oikonomou E, et al. Lipoprotein(a) in Atherosclerotic Diseases: From Pathophysiology to Diagnosis and Treatment. Molecules. 2023. 28(3): 969. Trpkovic A, Resanovic I, Stanimirovic J, et al. Oxidized low-density lipoprotein as a biomarker of cardiovascular diseases. Crit Rev Clin Lab Sci. 2015. 52(2): 70–85. Kamstrup PR, Tybjærg-Hansen A, Nordestgaard BG. Extreme lipoprotein(a) levels and improved cardiovascular risk prediction. J Am Coll Cardiol. 2013. 61(11): 1146–56. Clarke R, Peden JF, Hopewell JC, et al. Genetic variants associated with Lp(a) lipoprotein level and coronary disease. N Engl J Med. 2009. 361(26): 2518–28. O'Donoghue ML, Fazio S, Giugliano RP, et al. Lipoprotein(a), PCSK9 Inhibition, and Cardiovascular Risk. Circulation. 2019. 139(12): 1483–1492. Han Y, Chen J, Chopra VK, et al. ODYSSEY EAST: Alirocumab efficacy and safety vs ezetimibe in high cardiovascular risk patients with hypercholesterolemia and on maximally tolerated statin in China, India, and Thailand. J Clin Lipidol. 2020. 14(1): 98–108.e8. Kuklina EV, Yoon PW, Keenan NL. Trends in high levels of low-density lipoprotein cholesterol in the United States, 1999–2006. JAMA. 2009. 302(19): 2104–10. Rosinger A, Carroll MD, Lacher D, Ogden C. Trends in Total Cholesterol, Triglycerides, and Low-Density Lipoprotein in US Adults, 1999–2014. JAMA Cardiol. 2017. 2(3): 339–341. Carroll MD, Kit BK, Lacher DA, Shero ST, Mussolino ME. Trends in lipids and lipoproteins in US adults, 1988–2010. JAMA. 2012. 308(15): 1545–54. Baigent C, Keech A, Kearney PM, et al. Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins. Lancet. 2005. 366(9493): 1267–78. Lawler PR, Bhatt DL, Godoy LC, et al. Targeting cardiovascular inflammation: next steps in clinical translation. Eur Heart J. 2021. 42(1): 113–131. Crea F, Libby P. Acute Coronary Syndromes: The Way Forward From Mechanisms to Precision Treatment. Circulation. 2017. 136(12): 1155–1166. Cristell N, Cianflone D, Durante A, et al. High-sensitivity C-reactive protein is within normal levels at the very onset of first ST-segment elevation acute myocardial infarction in 41% of cases: a multiethnic case-control study. J Am Coll Cardiol. 2011. 58(25): 2654–61. Frangogiannis NG. The inflammatory response in myocardial injury, repair, and remodelling. Nat Rev Cardiol. 2014. 11(5): 255–65. Burger PM, Koudstaal S, Mosterd A, et al. C-Reactive Protein and Risk of Incident Heart Failure in Patients With Cardiovascular Disease. J Am Coll Cardiol. 2023. 82(5): 414–426. Rymer JA, Newby LK. Failure to Launch: Targeting Inflammation in Acute Coronary Syndromes. JACC Basic Transl Sci. 2017. 2(4): 484–497. Tang ZH, Peng J, Ren Z, et al. New role of PCSK9 in atherosclerotic inflammation promotion involving the TLR4/NF-κB pathway. Atherosclerosis. 2017. 262: 113–122. Ding Z, Pothineni N, Goel A, Lüscher TF, Mehta JL. PCSK9 and inflammation: role of shear stress, pro-inflammatory cytokines, and LOX-1. Cardiovasc Res. 2020. 116(5): 908–915. Ridker PM. A Test in Context: High-Sensitivity C-Reactive Protein. J Am Coll Cardiol. 2016. 67(6): 712–723. Kaptoge S, Di Angelantonio E, Lowe G, et al. C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis. Lancet. 2010. 375(9709): 132–40. Ridker PM, Danielson E, Fonseca FA, et al. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med. 2008. 359(21): 2195–207. Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA /ABC/ACPM/ADA/AGS/APhA/ASPC/ NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019. 139(25): e1082-e1143. Aminuddin A, Lazim M, Hamid AA, et al. The Association between Inflammation and Pulse Wave Velocity in Dyslipidemia: An Evidence-Based Review. Mediators Inflamm. 2020. 2020: 4732987. Swamynathan R, Varadarajan V, Nguyen H, et al. Association between Biomarkers of Inflammation and 10-Year Changes in Aortic Stiffness: The Multi-Ethnic Study of Atherosclerosis. J Clin Med. 2023. 12(15): 5062. Li X, Yang HY, Giachelli CM. BMP-2 promotes phosphate uptake, phenotypic modulation, and calcification of human vascular smooth muscle cells. Atherosclerosis. 2008. 199(2): 271–7. Carracedo M, Artiach G, Witasp A, et al. The G-protein coupled receptor ChemR23 determines smooth muscle cell phenotypic switching to enhance high phosphate-induced vascular calcification. Cardiovasc Res. 2019. 115(10): 1557–1566. Petsophonsakul P, Burgmaier M, Willems B, et al. Nicotine promotes vascular calcification via intracellular Ca2+-mediated, Nox5-induced oxidative stress, and extracellular vesicle release in vascular smooth muscle cells. Cardiovasc Res. 2022. 118(9): 2196–2210. Zhao XK, Zhu MM, Wang SN, et al. Transcription factor 21 accelerates vascular calcification in mice by activating the IL-6/STAT3 signaling pathway and the interplay between VSMCs and ECs. Acta Pharmacol Sin. 2023. 44(8): 1625–1636. Byon CH, Javed A, Dai Q, et al. Oxidative stress induces vascular calcification through modulation of the osteogenic transcription factor Runx2 by AKT signaling. J Biol Chem. 2008. 283(22): 15319–27. Additional Declarations No competing interests reported. Supplementary Files supplementmaterialPDF.pdf supplementmaterialtable.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4008037","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276730895,"identity":"030bab66-f7d7-4ca7-8be9-b4773952ef48","order_by":0,"name":"Linghao Xu","email":"","orcid":"","institution":"Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Linghao","middleName":"","lastName":"Xu","suffix":""},{"id":276730896,"identity":"eed3e7af-e1f7-470b-af76-3103a0761bc9","order_by":1,"name":"Liang Wang","email":"","orcid":"","institution":"Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Liang","middleName":"","lastName":"Wang","suffix":""},{"id":276730897,"identity":"914f8002-ef74-42ae-9ff5-02542aca19b9","order_by":2,"name":"Yuanqi Wang","email":"","orcid":"","institution":"Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Yuanqi","middleName":"","lastName":"Wang","suffix":""},{"id":276730898,"identity":"7d6a5310-9fa3-465a-b808-d574621d1d0e","order_by":3,"name":"Yiqiong Wang","email":"","orcid":"","institution":"Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Yiqiong","middleName":"","lastName":"Wang","suffix":""},{"id":276730899,"identity":"598286e0-96f2-400c-954f-e94d39ffa14f","order_by":4,"name":"Yuanzhen Jiang","email":"","orcid":"","institution":"Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuanzhen","middleName":"","lastName":"Jiang","suffix":""},{"id":276730900,"identity":"0a259580-94b3-44a7-8ab3-ddd92bf3e633","order_by":5,"name":"Peizhao Du","email":"","orcid":"","institution":"Baoshan District Hospital of Integrated Traditional Chinese and Western Medicine of Shanghai, Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Peizhao","middleName":"","lastName":"Du","suffix":""},{"id":276730901,"identity":"06245a32-f9fe-4628-bcb2-cf8b588d3fca","order_by":6,"name":"Jing Cheng","email":"","orcid":"","institution":"Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Cheng","suffix":""},{"id":276730902,"identity":"8190e2e3-41cc-4829-9bce-847e4ad98781","order_by":7,"name":"Chunsheng Zhang","email":"","orcid":"","institution":"East Hospital of Clinical Medical College, Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chunsheng","middleName":"","lastName":"Zhang","suffix":""},{"id":276730903,"identity":"bed58124-e9e2-4301-a044-58f4971cde05","order_by":8,"name":"Ruijie Wang","email":"","orcid":"","institution":"Harbin Medical University First Affiliated Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ruijie","middleName":"","lastName":"Wang","suffix":""},{"id":276730904,"identity":"5eedcbe3-2bec-4fc4-a670-ef2da5b3ab91","order_by":9,"name":"Tiantian Jiao","email":"","orcid":"","institution":"Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Tiantian","middleName":"","lastName":"Jiao","suffix":""},{"id":276730905,"identity":"e2341304-f4c6-4ad0-bbfc-f560c83fada1","order_by":10,"name":"Xueqi Lin","email":"","orcid":"","institution":"Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Xueqi","middleName":"","lastName":"Lin","suffix":""},{"id":276730906,"identity":"0407e438-07d9-426d-bf57-9b1880127f81","order_by":11,"name":"Lijian Xing","email":"","orcid":"","institution":"Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Lijian","middleName":"","lastName":"Xing","suffix":""},{"id":276730907,"identity":"c5e1020b-3032-4d0d-a107-4c6110f48694","order_by":12,"name":"Md Sakibur Rahman Tapu","email":"","orcid":"","institution":"Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Md","middleName":"Sakibur Rahman","lastName":"Tapu","suffix":""},{"id":276730908,"identity":"c0fe1700-bd88-4616-9e8f-56c2c9c85055","order_by":13,"name":"Jiming Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIie2RPWrDQBBGZ1nYNF+slLugQwgCJoWwcxQHgdK4yBEEKtzoAiGXEBhcz7KQFInj1uAm4AtIXYoQ4r/OsOsyxb5yZh4fM0MUifxDBsRku289SqS02x/kSK4qv6KIhTNNXpiZKjKkZWoaDikkGaoU7QrDG+Quz9b3AUW8T1jDSVOrkvR0BVqT6PqpL2XZ8tOdG+x2ef3KPjYQL5U0z4uAckp5zB6aDWTKSl6HFCgnWoehtr+fUHpykVIeFFOBgUuU45FrVdwSCmjY2rtLopfz/vDKxNktYTQev9W26z0KaT4ricozv48J9CORSCRCf7HIVAn63iznAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University","correspondingAuthor":true,"prefix":"","firstName":"Jiming","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-03-03 09:02:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4008037/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4008037/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52295378,"identity":"4d5d15a7-2f0b-4906-8475-64d56e0e184b","added_by":"auto","created_at":"2024-03-08 17:48:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":265584,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of MR design (Draw by figdraw, ID: TRRYUf1311)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"FIGURE1.png","url":"https://assets-eu.researchsquare.com/files/rs-4008037/v1/7204672ee108490c701532c1.png"},{"id":52295757,"identity":"59ab0b3a-7a02-446a-b725-70ce029cb1c6","added_by":"auto","created_at":"2024-03-08 17:56:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":231661,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of MR analysis(CI: Confidence Interval)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"FIGURE2.png","url":"https://assets-eu.researchsquare.com/files/rs-4008037/v1/cfec7258886ffa8ff71965fd.png"},{"id":52295374,"identity":"887f21d6-20bd-4cee-b88e-31f4dcef89d2","added_by":"auto","created_at":"2024-03-08 17:48:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":437348,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow chart of inclusion and exclusion\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"FIGURE3.png","url":"https://assets-eu.researchsquare.com/files/rs-4008037/v1/c15fdfdc360b3c4534d86a07.png"},{"id":52295375,"identity":"c97a127d-05fc-44a7-b0dd-dba7bdec9723","added_by":"auto","created_at":"2024-03-08 17:48:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":418746,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe differences of indicators in 2 groups at 1 and 6 months of treatment(**\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026lt;0.01)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"FIGURE4.png","url":"https://assets-eu.researchsquare.com/files/rs-4008037/v1/7a60cd223d915b6d2196c5ca.png"},{"id":52295758,"identity":"fc949875-d064-42f9-9100-60c386f5db61","added_by":"auto","created_at":"2024-03-08 17:56:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":396476,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A) Calcium content in VSMCs with different concentration of PCSK9 co-incubated (B) Calcium content in VSMCs of different groups (C) ALP activity in VSMCs of different groups (D)RUNX2 and α-SMA expression\u003c/strong\u003e \u003cstrong\u003ein VSMCs of different groups (**\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026lt;0.01, NC: normal control; OS: osteogenesis; PCSK9i+OS: PCSK9i \u0026amp; osteogenesis; PCSK9: PCSK9 protein; PCSK9i+ PCSK9: PCSK9i \u0026amp; PCSK9 protein)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"FIGURE5.png","url":"https://assets-eu.researchsquare.com/files/rs-4008037/v1/cd2bd33c85e9257b7f964f69.png"},{"id":52295380,"identity":"621ef74f-1886-449f-9d9b-56eedc7a6d97","added_by":"auto","created_at":"2024-03-08 17:48:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2029887,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlizarin Red stain in VSMCs of different groups(NC: normal control; OS: osteogenesis; PCSK9i+OS: PCSK9i \u0026amp; osteogenesis; PCSK9: PCSK9 protein; PCSK9i+ PCSK9: PCSK9i \u0026amp; PCSK9 protein.)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"FIGURE6.png","url":"https://assets-eu.researchsquare.com/files/rs-4008037/v1/c404c342a20d4cc570251941.png"},{"id":52298201,"identity":"193b75e1-4478-44fc-8c44-af55386988c6","added_by":"auto","created_at":"2024-03-08 18:12:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3922529,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4008037/v1/da161be0-4477-434c-a36c-05a0a6a825d2.pdf"},{"id":52295759,"identity":"3c036dd0-9fcc-486b-aa68-ab17ae9b5117","added_by":"auto","created_at":"2024-03-08 17:56:03","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":475254,"visible":true,"origin":"","legend":"","description":"","filename":"supplementmaterialPDF.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4008037/v1/e43122b4313222539d712f87.pdf"},{"id":52295377,"identity":"8d269e50-16ef-4a9e-94b1-8a38be37164e","added_by":"auto","created_at":"2024-03-08 17:48:03","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16439,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"supplementmaterialtable.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4008037/v1/c79b2ad0d3704e1643f36f7c.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"PCSK9 inhibitors ameliorate arterial stiffness in ACS patients: evidences from mendelian randomization, cohort studies and basic experiments","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute coronary syndromes (ACS) encompass a collection of clinical syndromes characterized by the rupture or invasion of coronary atherosclerotic plaques, resulting in the formation of complete or incomplete occlusive thrombi\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e.ACS includes acute ST-segment elevation myocardial infarction(STEMI), acute non-ST-segment elevation myocardial infarction(NSTEMI), and unstable angina(UA)\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e.Several common contributing factors include the process of aging, smoking, dyslipidemia and glycemia disorders, as well as hypertension\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.In clinical practice, various pharmacological treatments including antiplatelet therapy, lipid modulation, blood pressure control, and glucose therapy, alongside revascularization therapies such as percutaneous coronary intervention (PCI) and heart bypass surgery are commonly employed\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, within 10 years, more than 20% of patients with ACS are at more than a 30% risk of recurrence which can lead to myocardial infarction, stroke, and other vascular-related fatal events \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLipid-lowering agents are presently employed as one of the primary therapeutic intervention in clinical pharmacology for the majority of ACS patients\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Proprotein Convertase Subtilisin/kexin Type 9 inhibitors (PCSK9i) have primarily been employed for the purpose of reducing levels of low-density lipoprotein cholesterol (LDL-C) in the bloodstream, thereby exerting an anti-atherosclerotic impact\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. The status of PCSK9i which possess robust lipid-lowering properties is progressively growing within the most recent clinical guidelines for ACS\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Numerous studies have elucidated that PCSK9 inhibitors possess potential broader physiological functions, beyond their established role in lipid level regulation\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eArterial stiffness (AS) serves as a significant predictor of cardiovascular disease (CVD) and cardiovascular adverse events. In patients with ACS, elevated AS emerges as a risk factor contributing to unfavorable prognosis. The primary features of AS encompass intravascular collagen deposition, calcium deposition, fibroblast proliferation, and diminished endothelial diastolic function\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. The augmentation of AS may result in a decrease in myocardial afterload and coronary perfusion pressure, consequently precipitating a cascade of severe implications including hypertension, heart failure, and organic heart disease\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. The methods of assessing AS include Pulse Wave Velocity (PWV), Ankle Brachial Index (ABI), Ambulatory arterial stiffness Index (AASI) and so on, among which the most widely used in clinical practice is PWV\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Recognizing the presence of AS in patients ACS and promptly intervening is considered a potential strategy to enhance the prognosis of ACS patients. While the efficacy of PCSK9i in improving AS has been demonstrated in individuals with familial hypercholesterolemia (HF)\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, it remains uncertain whether these inhibitors can exert a similar effect in ACS patients. Given the extensive utilization of PCSK9i in ACS patients, our objective was to investigate the potential of these inhibitors in ameliorating AS in this specific population.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) is an analytical approach that employs genetic variations as instrumental variables (IVs) to investigate the potential association between exposures and outcomes\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Mendelian laws of inheritance randomly divide alleles among offspring, creating equal experimental and control groups. This minimizes confounding factors and makes MR studies a powerful tool for disease and clinical research\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe conducted a two-sample MR experiment to evaluate the genetic correlation between PCSK9 inhibition and AS. Additionally, we examined the clinical characteristics of ACS patients treated with PCSK9i and observed alterations in lipid levels, specific inflammatory markers and AS. Furthermore, we conducted cellular experiments to examine the impact of PCSK9 inhibitors on the extent of osteogenesis in vascular smooth muscle cells (VSMCs) of mice, thereby offering a comprehensive elucidation of the role played by PCSK9i in ameliorating AS.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e \u003cb\u003eMR design\u003c/b\u003e Since the clinical effect of PCSK9i on LDL-C reduction is clear, we employed single nucleotide polymorphisms (SNPs) associated with LDL-C as IVs. To establish a causal relationship, it was necessary to satisfy the following criteria: 1.The IVs have no association with confounding factors; 2.The IVs are associated with exposures; 3.The IVs have no direct relationship with outcomes.(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eExposure datasets selection and SNPs identification\u003c/b\u003e Genetically predicted inhibition of PCSK9 was used as an exposure. The gene sequence of PCSK9 was searched using the gene search function of the National Center for Biotechnology Information (NCBI) database\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, and the gene region chr1: 55505221\u0026ndash;55530525 was selected to identify SNPs that serve as proxies for PCSK9. Utilizing a similar approach for the selection of genetic variants as employed in prior research\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e, SNPs were identified within \u0026plusmn;\u0026thinsp;100 kb regions of the corresponding gene sequences and were identified in the genome-wide association study(GWAS) LDL-C dataset (ieu-a-300, n\u0026thinsp;=\u0026thinsp;173082) from Global Lipid Genetics Consortium (GLCC) \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e.SNPs that met the genome-wide significance threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;8 and a linkage disequilibrium (LD) threshold of R\u0026sup2;\u0026lt; 0.2 were utilized as genetic tools. Additionally, the human genotype-phenotype association database PhenoScanner (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.phenoscanner.medschl.cam.ac.uk/\u003c/span\u003e\u003cspan address=\"http://www.phenoscanner.medschl.cam.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was employed to identify traits that were directly linked to the SNPs used as IVs. This approach allowed us to exclude potential confounders from our analysis.\u003c/p\u003e \u003cp\u003e\u003cb\u003ePositive control and outcome dataset selection\u003c/b\u003e Based on previously researches\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e, we used coronary heart disease (CHD, ieu-a-7) data from the Consortium for the Genetics of Coronary Artery Disease (CARDIoGRAMplusC4D) \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e as a positive control dataset, comprising 60801 cases and 123504 controls. Using the pulse wave reflection index (PWRI, ukb-b-11598, n\u0026thinsp;=\u0026thinsp;151546) from the UK Biobank (UKBB) as the primary outcome, the pulse wave peak to peak time (PWPPT, ukb-b-8778, n\u0026thinsp;=\u0026thinsp;151466) and pulse wave arterial stiffness index (PWASI, ukb-b-11971, n\u0026thinsp;=\u0026thinsp;151053) as secondary outcomes. All three parameters serve as indicators of AS, where elevated values correspond to increased levels of AS\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Datasets were chosen from European populations, although the sources of exposure and outcomes differed. Before the collection of the original database, informed consent was acquired from each participant and approved by the respective local ethics committees of GWAS. All datasets were procured via IEU OpenGWAS(Table.S1)\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMR analysis\u003c/b\u003e Heterogeneity among SNPs was assessed through the application of Cochran's Q test. A \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05 was indicative of the absence of significant heterogeneity. The exposure-related drug-targeting instrument variables were aligned with the outcome dataset and subsequently subjected to analysis employing MR Egger, weighted median, and inverse variance weighted (IVW) methods. MR-PRESSO method was employed to detect potential outliers and address any horizontal polytomous outliers in the analyses. To mitigate the influence of individual SNPs on our findings, we employed the leave-one-out approach, systematically excluding each SNP to ascertain its lack of association with the outcome or presence of pleiotropy. All MR results are expressed as OR or beta, and statistical tests were two-sided. Analyses were completed using R language software (4.2.3), and the TwoSampleMR package was used throughout. \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered a statistically significant difference.\u003c/p\u003e \u003cp\u003e\u003cb\u003eClinical trial design\u003c/b\u003e The diagnosis of acute coronary syndrome (ACS) patients adheres to the ACS Emergency Rapid Diagnosis and Treatment Guidelines, which classify cases asSTEM, NSTEMI and UA\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. A total of 76 ACS patients admitted between April 1, 2022, and June 31, 2022, and who underwent coronary angiography at Shanghai East Hospital were included in our evaluation.\u003c/p\u003e \u003cp\u003eInclusion criteria: 1. Age\u0026thinsp;\u0026ge;\u0026thinsp;18 years old. 2. Meets the ACS diagnostic criteria and is clearly diagnosed with ACS\u003c/p\u003e \u003cp\u003eExclusion criteria:\u003c/p\u003e \u003cp\u003e1. Clinical instability, defined as hemodynamic or electrocardiographic instability.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2. Severe renal or hepatic insufficiency, indicated by an estimated glomerular filtration rate (EGFR) less than 30 ml/min or aspartate aminotransferase (AST) or alanine aminotransferase (ALT) levels exceeding 400 IU/L.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3. Patients who have previously been treated with PCSK9 inhibitors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4. Recent use of systemic sex steroids or cytotoxic drugs within the past 3 months.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e5. Active infection or significant hematological, metabolic, or endocrine dysfunction.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e6. Patients with active malignant tumors requiring treatment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e7. Pregnancy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e8. Persistent atrial fibrillation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9. Severe aortic valve insufficiency or aortic valve stenosis.\u003c/p\u003e\n\u003cp\u003e10. Peripheral arterial disease indicated by an ankle-brachial index (ABI) of 0.9 or lower, or a history of lower limb bypass grafting and/or endovascular treatment.\u003c/p\u003e \u003cp\u003eThe study involved the random allocation of patients into distinct treatment cohorts, including those receiving PCSK9 inhibitors (specifically, evolocumab 140 mg or alirocumab 75 mg) administered subcutaneously every 2 weeks in conjunction with statins (atorvastatin 20 mg or rosuvastatin 10 mg), as well as a control group receiving statins alone (atorvastatin 20 mg or rosuvastatin 10 mg). All participants were also administered a standard treatment regimen consisting of aspirin, clopidogrel/Tegrelo, angiotensin-converting enzyme inhibitor (ACEI) / adrenergic receptor binder (ARB), and β-blockers, unless contraindications were present for the use of these medications.\u003c/p\u003e \u003cp\u003e \u003cb\u003eClinical data collection\u003c/b\u003e Patient demographics were gathered upon enrollment. Blood samples were obtained and AS indicators were evaluated before treatment initiation, as well as at 1 and 6 months post-treatment commencement. The blood samples were expeditiously transported to the laboratory at Shanghai East Hospital for analysis. The collected blood samples were promptly transported to the laboratory at Shanghai East Hospital for analysis. Various indicators including troponin T(Tnt), N-terminal brain natriuretic peptide (NT-pro-BNP), total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), high-density lipoprotein (HDL), small dense low-density lipoprotein (sdLDL), lipoprotein (a)[Lp (a)], C-reactive protein (CRP), Interleukin- 6 (IL-6), procalcitonin (PCT) and fibrinogen (FIB) were collected from all patients. To minimize bias, the same professional physician conducted measurements of PWV and ABI using the Omron Arteriosclerosis Tester (BP-203RPEIII) during a state of rest.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCell culture and treatment\u003c/b\u003e Mouse aortic smooth muscle cell lines (VSMCs, No. YC-A023) were purchased from Yuanjing Biotechnology (China,Guangzhou). The cells were cultured in DMEM/F12 (ShanghaiBasalmedia, China) medium containing 10% fetal bovine serum (Gibco, America)\u0026thinsp;+\u0026thinsp;1% penicillin-streptomycin (NCMBiotech, China) in 5% CO\u003csub\u003e2\u003c/sub\u003e at 37℃. The medium was changed every two days. According to published methods, 10 mmol/L β-gp, 20ug/m dexamethasone and 50ug/mL L-ascorbic acid were added to the routine medium to induce osteogenesis of VSMCs for 7 days, the medium were changed every 2/3 days \u003csup\u003e[\u003cspan additionalcitationids=\"CR24 CR25 CR26 CR27\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. To mimic the effects of PCSK9i in vivo, 100 \u0026micro;g/mL of reagent-grade purified evolocumab (Selleck, America) was used to co-incubate with VSMCs for 7 days during osteogenesis induction\u003csup\u003e[\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. To mimic the stimulation of VSMCs by PCSK9 protein in vivo, refer to previous research \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e, 0 \u0026micro;g/ml, 0.55 \u0026micro;g/ml, 1.1 \u0026micro;g/ml, 2.2 \u0026micro;g/ml, and 4.4 \u0026micro;g/ml of recombinant human PCSK9 (MedChemExpress, USA) were co-incubated with VSMCs for 7 days, and the concentration exhibiting the highest intracellular calcium content was chosen for subsequent experimental procedures.\u003c/p\u003e \u003cp\u003e\u003cb\u003eDetection of calcium content within VSMCs\u003c/b\u003e As per the guidelines provided by the Calcium Ion Assay Kit (Biyun Tian, China), the working solution for the assay was prepared by combining equal volumes of Solution A and Solution B. Subsequently, 50uL of VSMCs lysate was added to each well of the 96-well plate. Then 150uL of working solution per well was added to the 96-well plate and incubate for 10 min at room temperature, protected from light. Measure the absorbance at 575 nm to calculate the standard curve for calcium content. Analyze the remaining samples for BCA protein concentration. Express the Ca\u003csup\u003e2+\u003c/sup\u003e concentration as calcium content divided by protein content in ug/mg.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAlizarin red staining\u003c/b\u003e According to the instructions of the Alizarin Red Staining Kit (Biyun Tian, China), VSMCs were fixed with 4% paraformaldehyde for 30 min at room temperature. The cells were then washed with sterile PBS three times and incubated with Alizarin Red Staining Solution for 30 min at 37\u0026deg;C. After that, the cells were washed with ddH\u003csub\u003e2\u003c/sub\u003eO three times and observed under a 10X light microscope.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAlkaline phosphatase activity assay\u003c/b\u003e According to the instructions of the Alkaline Phosphatase Assay Kit (Biyun Tian, China), prepare the substrate working solution by diluting the color-developing substrate. Then add 25uL of VSMCs lysate, 25uL of detection buffer, and 50uL of the chromogenic substrate to the sample wells of a 96-well plate. Incubate at 37℃ for 10min and stop the reaction by adding 100uL of termination solution to each well. Measure the absorbance at 405 nm. Express the results as the ratio of enzyme activity unit to protein concentration.\u003c/p\u003e \u003cp\u003e \u003cb\u003eWestern blot testing\u003c/b\u003e VSMCs were lysed using RIPA buffer (ShanghaiEpizyme, China) containing a protease inhibitor mixture (ShanghaiEpizyme, China). After centrifugation, the supernatant was extracted. BCA kit (ShanghaiEpizyme, China) was used for protein concentration measurements with appropriate loading buffer. Extracted proteins (30 \u0026micro;g per lane) were run on an SDS-PAGE gel and then transferred to a PVDF membrane (Merck, Germany). Primary antibodies with α-SMA (arigobio, America) and runt-related transcription factor 2(RUNX2, absin, China) were incubated overnight at 4\u0026deg;C. After careful washing with tween-containing triple-buffered saline (TBST), the membranes were incubated with horseradish peroxidase (HRP)-coupled secondary antibody (Biyun Tian, China, 1:2000) for 1 h at room temperature. The membranes were washed again three times for 10 min, and the signals were detected and quantified with Tanon 5200 multifunctional image analysis system (Tanon Technology, Shanghai, China). The average gray values of the bands were analyzed utilizing Image J (NIH, Bethesda, USA) with GAPDH serving as the internal reference protein.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical analysis\u003c/b\u003e Data were analyzed using SPSS 25.0. Count data were described as frequencies (%). Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) when normally distributed or median and interquartile range (IQR) when not normally distributed. Comparisons between the two groups were performed using paired t-tests or Mann-Whitney U-tests for continuous variables, and chi-square or Fisher exact tests for dichotomous variables when appropriate. The Kolmogorov-Smirnov test was used to determine whether the distribution was normal or non-normal. The closeness test was analyzed using spearman correlation analysis. A \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eIdentification of drug target-associated SNPs\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe identified 10 independent SNPs from the GWAS database(Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). These SNPs are located within or near the PCSK9 gene, showing strong associations with PCSK9 and LDL-C levels in the GLCC dataset. Consequently, these SNPs can serve as genetic proxies for PCSK9 and imitate the effects of PCSK9i. To ensure the exclusion of confounding factors, we employed PhenoScanner, heterogeneity analyses, multiplicity analyses, MR-PRESSO and leave-one-out tests to establish the relationship between these SNPs and the outcomes (Table S3).\u003c/p\u003e \u003cp\u003e \u003cb\u003ePositive control analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGiven the widespread utilization of PCSK9i in the treatment of CHD, we employed aggregated data from the coronary GWAS as a means of confirming the reliability of the SNPs. The implementation of the IVW method yielded statistically significant evidence (OR [95%]\u0026thinsp;=\u0026thinsp;0.605 [0.516\u0026thinsp;~\u0026thinsp;0.709], p\u0026thinsp;=\u0026thinsp;0.001) showcasing a noteworthy decrease in the risk of CHD through the use of PCSK9i (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e),. This outcome was consistently observed across both the weighted median and MR Egger approaches. The validation of the positive control further substantiates credibility of the SNPs.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe effect of genetic prediction of PCSK9 inhibition on arterial stiffness\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn our study, we utilized the IVW method to conduct correlation analysis. Our findings indicate a negative correlation between genetic prediction of PCSK9 inhibition and PWRI (beta [95% CI] =-0.058 [-0.094~-0.023], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). However, we did not observe significant correlations with PWPPT and PWASI(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Sensitivity analysis revealed no evidence of heterogeneity or horizontal pleiotropy across all outcomes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Additionally, the retention method demonstrated that removing SNPs did not significantly impact the results. Cochran's Q-test did not identify any indications of heterogeneity (Table S3). The leave-one-out method demonstrated no statistically significant variance in the results following the exclusion of SNPs(Supplementary PDF).\u003c/p\u003e \u003cp\u003e \u003cb\u003eBaseline information for clinical studies\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA total of 88 patients with ACS after PCI were screened. Ultimately, 71 eligible patients were included and randomly divided into the PCSK9i group (n\u0026thinsp;=\u0026thinsp;36) and the control group (n\u0026thinsp;=\u0026thinsp;35) at a ratio of 1:1(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). There were no notable disparities observed in the overall data of the two groups, encompassing fundamental information, medical history, and medication history(Table.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, discrepancies were identified solely in smoking history(Table.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013) and the administration of β-blocker(Table.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). Moreover, no statistically significant variances were found in baseline data, CRP, FIB, IL-6, PCT, or lipid levels between the two groups(Table.2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTable.1 Clinical Characteristics for ACS Study Group (n\u0026thinsp;=\u0026thinsp;71)\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical feature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003etotal(n\u0026thinsp;=\u0026thinsp;71)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ethe treatment group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ethe control group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;35)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66(36\u0026ndash;91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71(49\u0026ndash;88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52(73.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28(77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(68.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI(kg\u0026times;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.6(19.3\u0026ndash;31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.1(19-30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary heart disease, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (25.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(34.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.977\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (56.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (49.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTEMI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (64.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSTEMI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (21.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnstable angina, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARB, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58(81.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31(81.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27(73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.572\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-blocker, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61(85.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36(94.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (67.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCB, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18(25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(29.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ediuretic, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34(47.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(43.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.718\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypoglycemic drugs, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.351\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnticoagulation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41(57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(57.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(51.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.561\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTable.2 Clinical feature of the study population at baseline\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical feature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ethe treatment group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ethe control group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;35)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTnt(ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23(0.005-10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.38(0.006-10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBG(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.7(3.74\u0026ndash;18.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.33(3.97\u0026ndash;16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.46(3.13\u0026ndash;9.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.38(2.05\u0026ndash;8.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41(0.65\u0026ndash;3.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.53(0.65\u0026ndash;3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02(0.63-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01(0.67\u0026ndash;1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.96(1.56\u0026ndash;6.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.76(1.76\u0026ndash;5.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.476\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esdLDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84(0.33\u0026ndash;1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.63(0.2\u0026ndash;1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.531\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLp(a) (nmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37(1-257)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(4-235)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC(*10^9/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.09(6-17.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.12(5.77\u0026ndash;17.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN(*10^9/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.91(3.11\u0026ndash;12.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.99(3.09\u0026ndash;12.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP(mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.03(1.6-85.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3(1.6-104.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.13(1.77\u0026ndash;6.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.61(2.06\u0026ndash;7.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6(pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.68(1.73\u0026ndash;91.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.71(3.22\u0026ndash;50.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCT(ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.207(0.02\u0026ndash;0.677)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.32(0.013\u0026ndash;4.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eChanges in lipids and inflammatory factors after treatment in both groups\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn comparison to the baseline data, the PCSK9i group exhibited a statistically significant and persistent reduction in the levels of inflammatory markers WBC, N, CRP, IL-6 and PCT at both 1 and 6 months. Additionally, the levels of TC, LDL, Lp(a), and sdLDL continued to decrease significantly. However, there was no significant decrease in TG levels at 1 month, with the results lacking statistical significance. Nevertheless, a statistically significant decrease was observed at 6 months. Furthermore, the patients' HDL levels displayed a tendency to increase at both 1 month and 6 months, with statistically significant results (Table.3).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable.3 Indicators of the PCSK9i group after 1-mo and 6-mo\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ebaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1month\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6month\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003cp\u003e(1month vs. Baseline)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003cp\u003e(6month vs. 1month)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.46(3.13\u0026ndash;9.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.47(1.79\u0026ndash;4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.778(1.64\u0026ndash;4.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41(0.65\u0026ndash;3.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.31(0.72\u0026ndash;2.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.38(0.70\u0026ndash;2.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02(0.63-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07(0.83\u0026ndash;1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.21(0.73\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.96(1.56\u0026ndash;6.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.89(0.34\u0026ndash;3.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4(0.43\u0026ndash;2.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esdLDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84(0.33\u0026ndash;1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77(0.28\u0026ndash;1.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.72(0.13\u0026ndash;1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.017*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLp(a) (nmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37(1-257)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(2-162)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.5(4\u0026ndash;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC(*10^9/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.09(6-17.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.29(5.12\u0026ndash;11.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.88(5.83\u0026ndash;9.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN(*10^9/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.91(3.11\u0026ndash;12.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.33(2.91\u0026ndash;8.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.35(3.14\u0026ndash;6.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.610\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP(mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.03(1.6-85.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6(1.6\u0026ndash;7.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.6(1.21\u0026ndash;5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.968\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.13(1.77\u0026ndash;6.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.23(1.17\u0026ndash;4.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.99(1.21\u0026ndash;3.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6(pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.68(1.73\u0026ndash;91.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.3(1.71\u0026ndash;21.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.18(1.17\u0026ndash;7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCT(ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.207(0.020\u0026ndash;0.677)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.095(0.010\u0026ndash;0.350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.160(0.010\u0026ndash;0.320)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.030*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn comparison to the baseline data, the control group exhibited a statistically significant reduction in inflammatory factors WBC, N, CRP, IL-6, and PCT following 1 month of treatment. Nonetheless, the extended duration of treatment to 6 months did not yield any additional improvements in the remaining markers, including IL-6. Lp(a) and sdLDL did not exhibit significant changes, and the observed results did not demonstrate statistical significance. Conversely, the patients' TC and LDL continued to decrease in a statistically significant manner. Notably, HDL did not display significant changes at the 1-month checkpoint, and these findings also lacked statistical significance. However, a noteworthy increase was observed at the conclusion of the 6-month follow-up period, with the results demonstrating statistical significance(Table.4).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable.4 Indicators of the control group after 1-mo and 6-mo\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabd\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ebaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1month\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6month\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003cp\u003e(1month vs. Baseline)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003cp\u003e(6month vs. 1month)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.38(2.05\u0026ndash;8.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.92(2.15\u0026ndash;5.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.76(2.56\u0026ndash;5.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.035*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.53(0.65\u0026ndash;3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.40(0.49\u0026ndash;3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38(0.57\u0026ndash;3.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01(0.67\u0026ndash;1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.09(0.73\u0026ndash;1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12(0.72\u0026ndash;1.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.76(1.76\u0026ndash;5.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.10(1.33\u0026ndash;3.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.99(0.76\u0026ndash;3.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esdLDL(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.63(0.2\u0026ndash;1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75(0.32\u0026ndash;1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77(0.29\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLp(a) (nmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25(4-235)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36(7-217)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(7-116)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.959\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC(*10^9/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.12(5.77\u0026ndash;17.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.01(4.27\u0026ndash;9.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.99(5.23\u0026ndash;9.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN(*10^9/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.99(3.09\u0026ndash;12.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.71(2.16\u0026ndash;7.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.87(3.34\u0026ndash;7.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.408\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP(mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.3(1.6-104.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.99(1.6\u0026ndash;68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.47(1.6\u0026ndash;29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.61(2.06\u0026ndash;7.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.07(1.97\u0026ndash;7.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.01(1.66\u0026ndash;5.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6(pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.71(3.22\u0026ndash;50.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.76(2.2\u0026ndash;99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.89(1.65\u0026ndash;20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCT(ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.32(0.013\u0026ndash;4.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.178(0.010\u0026ndash;0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.170(0.010\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.459\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn comparison to the control group, the PCSK9i group exhibited statistically significant enhancements in CRP, FIB, IL-6 and PCT following a 1-month intervention. Nevertheless, there was no notable disparity in lipid levels between the two groups. Subsequent to 6 months of treatment, there was a statistically significant reduction in TC, LDL-C, CRP, FIB, IL-6 and PCT levels(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAlterations in PWV in both groups of patients\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAt the baseline level, there was no statistically significant difference between bilateral PWV and bilateral ABI between the two groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). After 1 month of treatment, RPWV (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and bilateral ABI (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were reduced in the PCSK9i group, and the difference in LPWV was not statistically significant compared with baseline (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), and no significant changes in bilateral PWV and bilateral ABI were observed in the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). After 6 months of treatment, there was a significant decrease in both bilateral PWV and ABI in the PCSK9i group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared to 1 month. In comparison, there was no significant change in bilateral PWV and bilateral ABI in the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table.5).\u003c/p\u003e \u003cp\u003eComparing the AS parameters between the two groups of patients after 6 months of treatment, there was no significant difference in bilateral ABI (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), but bilateral PWV in the PCSK9i group was significantly lower than that in the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table.5).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable.5 PWV of the two groups after 1 month and 6 months\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabe\" border=\"1\"\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 month\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 month\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e -Value\u003c/p\u003e \u003cp\u003e(1month vs. Baseline)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e -Value\u003c/p\u003e \u003cp\u003e(6month vs. 1month)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003ePCSK9i group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLPWV (cm/s)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1448.5(1106\u0026ndash;1796)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1467(1098\u0026ndash;1791)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1320(1021\u0026ndash;1543)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRPWV (cm/s)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1497.5(1133\u0026ndash;1912)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1488.5(1103\u0026ndash;1882)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1350(1032\u0026ndash;1679)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.026*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07(1-1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04(1.01\u0026ndash;1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.02(0.99\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03(0.99\u0026ndash;1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03(1-1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.01(0.98\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eControl group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLPWV (cm/s)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1405(1128\u0026ndash;2013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1405(1138\u0026ndash;1987)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1407(1138\u0026ndash;1980)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.850\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRPWV (cm/s)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1451(1176\u0026ndash;1873)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1461(1185\u0026ndash;1882)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1465(1196\u0026ndash;1890)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.702\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03(0.9\u0026ndash;1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04(0.92\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.06(0.94\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02(0.91\u0026ndash;1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04(0.91\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.04(0.95\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e \u003cb\u003e-Value\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(PCSK9i vs. Control)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLPWV (cm/s)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRPWV (cm/s)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA correlation analysis was conducted between the changes in blood lipids and inflammatory factors in the PCSK9i group after 6 months of treatment and the changes in PWV. Only ΔCRP and ΔPWV were correlated(Table.6, r\u0026thinsp;=\u0026thinsp;0.343, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable.6 The relationship between ΔPWV and changes in inflammatory factors and blood lipids\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabf\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003er -\u003c/em\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep -\u003c/em\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔHDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔLDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔsdLDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔLp(a)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.275\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.043*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔFIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.473\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔPCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDetection of calcium content in VSMCs\u003c/b\u003e In the pre-experiment we found that the intracellular calcium content showed a concentration-dependent increase with increasing PCSK9 concentration. The highest intracellular calcium content of 2.2 \u0026micro;g/ml PCSK9 was selected for subsequent experiments(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The intracellular calcium content increased significantly in the osteogenic group(OS) compared to the control group(NC) and decreased after treatment with PCSK9i compared to OS. After stimulating the cells with PCSK9, the intracellular calcium content increased compared to NC. After treatment with PCSK9i, the intracellular calcium content decreased compared to the PCSK9 group(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAlizarin Red stain\u003c/b\u003e In this experiment, an increase in the intensity of red hues correlates with a higher concentration of calcium salt deposition. Calcium salt deposition was significantly increased in OS compared to NC and was significantly decreased after treatment with PCSK9i compared to OS. After stimulation of cells with PCSK9, calcium salt deposition increased compared to NC. After treatment with PCSK9i, calcium salt deposition was decreased compared to PCSK9 group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAlkaline phosphatase activity assay\u003c/b\u003e ALP activity was significantly increased in OS compared to NC and significantly decreased after treatment with PCSK9i compared to OS. After stimulation of cells with PCSK9, ALP activity increased compared to NC. After treatment with PCSK9i, ALP activity was decreased compared to PCSK9 group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003cb\u003eWESTERN BLOT testing\u003c/b\u003e WB results showed that RUNX2 expression was up-regulated and α-SMA expression was down-regulated in OS compared to NC, and RUNX2 expression was down-regulated and α-SMA expression was up-regulated after the treatment with PCSK9i compared to OS. After stimulation of cells with PCSK9, RUNX2 expression was up-regulated and α-SMA expression was down-regulated compared to NC. After treatment with PCSK9 inhibitor, RUNX2 expression was down-regulated and α-SMA expression was up-regulated compared to PCSK9 group(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePCSK9 is a constituent of the secreted chymotrypsin family's ninth member, initially identified as an enzyme involved in regulating apoptosis within the nervous system. Its primary expression is observed in the kidney, liver, and intestine\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. PCSK9 instigates hyperlipidemia and atherosclerosis through the stimulation of lysosomal degradation of the low-density lipoprotein receptor (LDL-R) within the liver, consequently impeding the efficiency of LDL-C clearance\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. The primary mechanism of action for PCSK9i involves their binding to the PCSK9 molecule, thereby impeding its interaction with LDL-R and attenuating receptor degradation. Consequently, this process enhances the uptake of LDL-C in the bloodstream, ultimately leading to a reduction in its concentration\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. Alirocumab and evolocumab have received approval from the U.S. Food and Drug Administration (FDA) for the treatment of familial hypercholesterolemia, statin intolerance or contraindications, and atherosclerotic disease among this category of medications \u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn recent times, notable progress has been made in the realm of scientific investigation pertaining to the potential cardioprotective effects of PCSK9i that extend beyond their lipid-lowering properties. These advancements encompass the exploration of immune response modulation, involvement in apoptosis, participation in thrombosis, modulation of inflammatory factors and enhancement of arterial endothelial function\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Due to the multifaceted characteristics of PCSK9i and the significant involvement of AS in the pathogenesis of cardiovascular disease, our objective was to investigate the potential association between PCSK9i and AS in individuals diagnosed with ACS.\u003c/p\u003e \u003cp\u003eInitially, a two-sample MR analysis was conducted. Considering the established impact of PCSK9 inhibition on LDL levels\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e, the selection of variants resembling PCSK9 proxies near the PCSK9 gene was based on LDL levels as a criterion. The utilization of a drug-targeted MR method has been extensively employed in prior published studies\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. In order to enhance the credibility of these SNPs, we employed the CHDdataset as a positive control and observed a significant decrease in risk of CHD associated with these SNPs, thus validating their suitability as IVs. Based on our findings, it can be inferred that genetically predicted PCSK9 inhibition exhibits a negative correlation with AS parameter PWRI. Consequently, we propose the hypothesis that PCSK9i has the potential to mitigate AS. Similar results have been described in several clinical studies, but no evidence has been published at the genome-wide level, which is the innovation of this study.\u003c/p\u003e \u003cp\u003eThe relationship between PCSK9i and AS has been documented in a subset of clinical studies involving patients with FH. Ruscica et al. conducted a comprehensive randomized clinical trial, which demonstrated a noteworthy correlation between circulating PCSK9 and PWV. Furthermore, the use of a PCSK9i to decrease circulating PCSK9 levels may have a beneficial impact on the amelioration of AS\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Papaioannou et al. observed a notable enhancement in PWV subsequent to the incorporation of PCSK9i into statin therapy among individuals with FH\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. Scicali R et al. found that PCSK9i significantly reduced PWV in patients with FH after 6 months of treatment\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e and that lowering LDL-C was associated with improved PWV. However, there exist notable distinctions between patients with ACS or FH in relation to their internal environment, pathophysiologic mechanisms and interventions. At present, there is a dearth of research examining whether patients with ACS experience equivalent AS- reducing advantages from PCSK9i.\u003c/p\u003e \u003cp\u003eTherefore, we proceeded to conduct a cohort study in order to examine the alterations in lipids, inflammatory markers, and AS among patients with ACS following the administration of statins and PCSK9i. Consistent with numerous contemporary clinical investigations, both PCSK9i and statins exhibited noteworthy lipid-lowering effects in our cohort. However, these effects varied with respect to lipid compositions. After 6 months of treatment, patients in PCSK9i group showed significant decreases in TC, TG, LDL, sdLDL, and Lp (a), while HDL increased significantly. In control group using statins we similarly observed improvements in TC, TG, LDL and HDL, but not in Lp (a) and sdLDL.\u003c/p\u003e \u003cp\u003eWe chose PWV which is currently considered the \"gold standard\" in clinical practice as the primary measure to evaluate AS in patients with ACS. Additionally, we utilized ABI as a supplementary measure representing the ratio of ankle arterial pressure to brachial arterial pressure. ABI serves as an indicator for the presence of atherosclerosis or stenosis in the lower extremities\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e.Based on data from several studies\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. ABI\u0026thinsp;\u0026lt;\u0026thinsp;0.90 has been widely accepted as a diagnostic criterion for lower extremity arterial disease, and the PWV data of such patients with severe atherosclerosis or stenosis of the lower extremity arteries could not reflect the true AS, so we used ABI\u0026thinsp;\u0026lt;\u0026thinsp;0.9 as an exclusion criterion for the study design. Concurrently, considering the association between ABI and AS, along with ABI's predictive capability for adverse cardiovascular events\u003csup\u003e[\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e, we incorporated ABI as an additional component in our analysis to achieve a more comprehensive evaluation of AS.\u003c/p\u003e \u003cp\u003eThere was an absence of disparity in baseline PWV between the PCSK9i and control groups. Following 1 month of treatment, a decrease in RPWV was observed in the PCSK9i group, although no statistically significant variation in PWV was evident between the two groups. However, after 6 months of treatment, PWV was significantly lower in the PCSK9i group compared to 1month, which was not observed in control group. PWV was significantly lower in the PCSK9i group than in the control group after 6 months of treatment. These data suggest that PCSK9i are effective in improving AS in patients with ACS, but may require a longer period of time to demonstrate a significant effect. This finding is similar to that of Papaioannou, Roberto.S, and others, who also found that a reduction in LDL-C was associated with improved PWV in patients with familial hypercholesterolemia\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e.However, by correlating ΔPWV with ΔLDL in PCSK9i group, we did not reach the same conclusion. The reason for this situation may be due to the difference in the study population. The previous study focused on patients with FH, while our study focused on patients with ACS. Due to the distinct characteristics of these diseases, improving AS in ACS patients with PCSK9i may not solely be achieved by reducing LDL levels.\u003c/p\u003e \u003cp\u003eLp (a) is an LDL particle bound to apolipoprotein (a), which carries oxidized phospholipids that adversely affect a variety of pathways including inflammation, endothelial function, and thrombosis\u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e. Lp (a) is also known to contribute to the progression of atherosclerosis and increase the risk of ASCVD\u003csup\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e. High levels of Lp (a) have been linked to a higher risk of diseases like CVD and stroke as indicated by multiple studies\u003csup\u003e[\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]\u003c/sup\u003e. Several clinical trials have been conducted to examine the efficacy of PCSK9 inhibitor therapy in reducing Lp(a) and sdLDL\u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/sup\u003e.Our cohort study also showed significant reductions in Lp (a) and sdLDL levels in patients treated with PCSK9i, indicating that PCSK9i may target these two lipid components. However, correlation analyses did not find a link between ΔPWV and reductions in these lipoproteins, suggesting that PCSK9i may improve AS through other mechanisms.\u003c/p\u003e \u003cp\u003eThe conventional perspective posits that lipids are the primary etiological factor in CHD.Despite the general populace has experienced a consistent decline in total plasma cholesterol levels because of the ongoing advancements in lipid-lowering medications\u003csup\u003e[\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/sup\u003e, nevertheless, a notable prevalence of atherosclerotic cardiovascular disease (ASCVD) events persists, even among individuals who have effectively managed their LDL levels.\u003csup\u003e[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/sup\u003e As lipids alone proved insufficient in accounting for all occurrences of atherosclerotic cardiovascular disease (ASCVD), subsequent investigations gradually revealed additional potential mechanisms, with inflammation emerging as a particularly significant factor\u003csup\u003e[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]\u003c/sup\u003e.Crea et al. summarized the possible mechanisms that predispose to ACS, suggesting that myocardial infarction(MI) may result from plaque rupture triggered by a systemic inflammatory response\u003csup\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/sup\u003e.In addition, about 60% of patients with MI have a high initial CRP (\u0026ge;\u0026thinsp;2.0 mg/L)\u003csup\u003e[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]\u003c/sup\u003e. In the context of MI, the process of cardiomyocyte necrosis results in the release of harmful molecules that interact with pattern-recognition receptors, such as toll-like receptors. This interaction combined with complement activation and the presence of reactive oxygen species, leads to the upregulation of cytokines and chemokines. Consequently, these molecular events contribute to the development of both coronary and systemic inflammatory responses\u003csup\u003e[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]\u003c/sup\u003e. This inflammatory response has the potential to inflict additional harm upon the myocardium, resulting in heart failure, inducing a pervasive inflammation across the coronary arteries, heightening the likelihood of recurring myocardial infarction, and ultimately contributing to elevated post-infarction mortality rates\u003csup\u003e[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]\u003c/sup\u003e. However, due to the lack of efficacy demonstrated in multiple trials focusing on the early inflammatory response following ACS\u003csup\u003e[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]\u003c/sup\u003e, the majority of clinical guidelines do not endorse the use of anti-inflammatory therapy for patients diagnosed with ACS. However, in clinical practice we have observed that ACS patients with PCSK9i tend to have more significant improvements in inflammatory factors, even if they do not receive anti-inflammatory therapy. PCSK9i may have anti-inflammatory effects due to its close association with inflammatory processes\u003csup\u003e[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]\u003c/sup\u003e. Therefore, we also examined and analyzed changes in commonly observed inflammatory factors in this study.\u003c/p\u003e \u003cp\u003eCompared to the baseline, inflammatory factors WBC, N, CRP, IL-6, and PCT consistently decreased in the PCSK9i group at 1 and 6 months. The control group also showed significant decreases in these factors after 1 month, but no further improvement was observed except for IL-6 at 6 months. After 1 and 6 months of treatment, PCSK9i group showed significantly lower levels of CRP, IL-6, and PCT compared to control group. However, there were no significant differences in WBC and N between two groups. All ACS patients we studied were discharged from the hospital with improved conditions after treatment. Therefore, the improvement of inflammatory markers in both groups after 1 month of treatment does not necessarily indicate the anti-inflammatory effects of PCSK9i or statins. It is possible that these inflammatory factors naturally reduce as the disease state improves. However, with continued use of the drug, patients in PCSK9i group demonstrated a sustained decrease in the 3 inflammatory markers after 6 months which was difficult to be explained by the self-limiting nature of the disease. In contrast, control group did not observe the same changes. After 6 months of treatment, the PCSK9i group showed significantly lower levels of the 3 inflammatory factors compared to control group, highlighting the distinct anti-inflammatory impact of PCSK9i in contrast to statins.\u003c/p\u003e \u003cp\u003eIn addition, we conducted a correlation analysis between alterations in inflammatory factors and ΔPWV after 6 month in PCSK9i group. Interestingly, our findings revealed that only ΔCRP exhibited a significant correlation with ΔPWV. C-reactive protein, a cyclic pentameric glycoprotein predominantly synthesized in the liver, has been extensively investigated in the context of cardiovascular disease. A substantial body of evidence substantiates the utility of CRP as a guide for therapeutic interventions in primary prevention\u003csup\u003e[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]\u003c/sup\u003e.A meta-analysis that included more than 160,000 individuals with new-onset ASCVD showed that increased hsCRP levels were associated with an increased risk of CHD, ischemic stroke, and vascular mortality\u003csup\u003e[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]\u003c/sup\u003e. The JUPITER trial demonstrated that daily administration of Rosuvastatin significantly reduced the incidence of first MI, stroke, or cardiovascular death in individuals with hsCRP\u0026thinsp;\u0026ge;\u0026thinsp;2 mg/L and LDL-C\u0026thinsp;\u0026lt;\u0026thinsp;130 mg/dL \u003csup\u003e[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]\u003c/sup\u003e. Based on these observations, the guidelines for blood cholesterol management encourage consideration of statins in patients with hsCRP\u0026thinsp;\u0026ge;\u0026thinsp;2 mg/L\u003csup\u003e[\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]\u003c/sup\u003e. While CRP's connection to ASCVD has been extensively researched, its association with AS remains understudied. In patients with hyperlipidemia, there was a significant positive correlation between AS and CRP, with correlations ranging from mild to moderate associations (Pearson r\u0026thinsp;=\u0026thinsp;0.33 to r\u0026thinsp;=\u0026thinsp;0.624)\u003csup\u003e[\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]\u003c/sup\u003e.In atherosclerotic population, higher CRP levels at baseline were independently associated with reduced aortic distensibility\u003csup\u003e[\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]\u003c/sup\u003e. Previous studies have primarily examined the link between CRP levels and AS, but rarely explored the connection between lower CRP and improved PWV. Our study discovered that lower CRP levels were associated with improved PWV in ACS patients, and this reduction in CRP was due to the anti-inflammatory effects of PCSK9i.\u003c/p\u003e \u003cp\u003eAlthough our spearman correlation analysis only shows a correlation between ΔCRP and ΔPWV but cannot determine causality, our data suggest that CRP levels decrease before significant changes in PWV occur after 1 month of treatment. This indicates that improving CRP levels is prioritized over improving PWV. Therefore, we believe that PCSK9 may improve AS by regulating CRP levels. Further studies are needed to confirm this, and we eagerly await future research results.\u003c/p\u003e \u003cp\u003eWe further designed cellular experiments to validate the effect of PCSK9i on AS. Osteogenesis of VSMCs is one of the main response indicators of AS at the cellular level.The expression of RUNX2 plays a key role in the osteogenesis of VSMCs. In the physiological condition, the vasculature exhibits a low level of RUNX2 expression. However, when subjected to bone morphogenetic protein (BMP-2) stimulation, high phosphorus levels, oxidative stress or inflammation, VSMCs undergo osteogenic differentiation. This process is characterized by a reduction in the expression of the specific marker smooth muscle actin (Smooth Muscle Actin Alpha 2, α-SMA) and an elevation in RUNX2 expression\u003csup\u003e[\u003cspan additionalcitationids=\"CR71 CR72\" citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]\u003c/sup\u003e.In addition, its downstream osteogenic marker ALP activity is also increased, further contributing to calcification\u003csup\u003e[\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe successfully induced osteogenesis by treating VSMCs with osteogenic medium, resulting in increased RUNX2 expression, decreased α-SMA expression, decreased ALP activity and increased calcium deposition after 7 days. However, Co-incubation with PCSK9i improved these osteogenic indicators, confirming the protective effect of PCSK9i on VSMC osteogenesis. To confirm if PCSK9i's impact is due to PCSK9, we tested the connection between PCSK9 and osteogenesis in VSMCs. By exposing VSMCs to external PCSK9, we observed that it prompted the cells to adopt an osteogenic phenotype, worsening their calcium salt buildup. This demonstrated that PCSK9 can cause osteogenesis in VSMCs and PCSK9 inhibition is a way to improve this condition.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOverall, the findings from our MR analysis provide evidence that PCSK9i have the potential to enhance AS, as substantiated by our clinical trials and cellular analyses. Our observations of clinical research indicated that PCSK9i effectively ameliorate CRP levels and mitigate PWV in individuals with ACS, thereby suggesting their capacity to attenuate vascular inflammation and diminish AS. Besides, our cell experiments showed that PCSK9i can ameliorate osteogenesis of VSMCs. Consequently, the significance of incorporating PCSK9i into the therapeutic regimen for ACS patients warrants further emphasis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThis study has been retrospectively registered and is pending approval.\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe clinical study was conducted in accordance with the principles of the Declaration of Helsinki, and all patients who met the inclusion criteria signed informed consent forms. The ethics committee of the Shanghai East Hospital approved the study design and allowed the use of clinical data.\u0026nbsp;Number:【2022】研审第（205）号. Date: April 24, 2022.\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn MR analysis, before the collection of the original database, informed consent was acquired from each participant and approved by the respective local ethics committees of GWAS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients signed informed consent regarding publishing their data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Grant Nos. 82070416, 81870296 and 82104632), the Shanghai Key Clinical Specialty Project (shslczdzk06202), and the Top-level Clinical Discipline Project of Shanghai Pudong District (Grant/Award Number: PWYgf2021-01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLX conducted MR analysis and statistical analysis of clinical data, completed most of the cell experiments, and was a major contributor in writing the manuscript. LW collected major clinical data, completed statistical analysis, and wrote part of manuscript. Yuanqi W \u0026amp; Yiqiong W assisted in statistical analysis and complete cell experiments. YJ, PD\u0026amp; JC contributed to data collection and statistical analysis. CZ, RW , TJ \u0026amp; XL reviewed and edited the manuscript. LX \u0026amp;MT translated and polished the manuscript. JL designed an experimental plan, provided financial support and supervised the entire research. All authors have reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBhatt DL, Lopes RD, Harrington RA. Diagnosis and Treatment of Acute Coronary Syndromes: A Review. JAMA. 2022. 327(7): 662\u0026ndash;675.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEisen A, Giugliano RP, Braunwald E. Updates on Acute Coronary Syndrome: A Review. JAMA Cardiol. 2016. 1(6): 718\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eByrne RA, Rossello X, Coughlan JJ, et al. 2023 ESC Guidelines for the management of acute coronary syndromes. Eur Heart J. 2023. 44(38): 3720\u0026ndash;3826.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDu L, Cheng Z, Zhang Y, Li Y, Mei D. The impact of medication adherence on clinical outcomes of coronary artery disease: A meta-analysis. Eur J Prev Cardiol. 2017. 24(9): 962\u0026ndash;970.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaasenbrood L, Boekholdt SM, van der Graaf Y, et al. Distribution of Estimated 10-Year Risk of Recurrent Vascular Events and Residual Risk in a Secondary Prevention Population. Circulation. 2016. 134(19): 1419\u0026ndash;1429.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMach F, Baigent C, Catapano AL, et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J. 2020. 41(1): 111\u0026ndash;188.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosenson RS, Hegele RA, Fazio S, Cannon CP. The Evolving Future of PCSK9 Inhibitors. J Am Coll Cardiol. 2018. 72(3): 314\u0026ndash;329.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavarese EP, Kolodziejczak M, Kereiakes DJ, Tantry US, O'Connor C, Gurbel PA. Proprotein Convertase Subtilisin/Kexin Type 9 Monoclonal Antibodies for Acute Coronary Syndrome: A Narrative Review. Ann Intern Med. 2016. 164(9): 600\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUgovšek S, Šebeštjen M. Non-Lipid Effects of PCSK9 Monoclonal Antibodies on Vessel Wall. J Clin Med. 2022. 11(13).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLacolley P, Regnault V, Laurent S. Mechanisms of Arterial Stiffening: From Mechanotransduction to Epigenetics. Arterioscler Thromb Vasc Biol. 2020. 40(5): 1055\u0026ndash;1062.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZieman SJ, Melenovsky V, Kass DA. Mechanisms, pathophysiology, and therapy of arterial stiffness. Arterioscler Thromb Vasc Biol. 2005. 25(5): 932\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson TJ, Phillips SA. Assessment and prognosis of peripheral artery measures of vascular function. Prog Cardiovasc Dis. 2015. 57(5): 497\u0026ndash;509.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuscica M, Ferri N, Fogacci F, et al. Circulating Levels of Proprotein Convertase Subtilisin/Kexin Type 9 and Arterial Stiffness in a Large Population Sample: Data From the Brisighella Heart Study. J Am Heart Assoc. 2017. 6(5).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018. 362: k601.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta V, Walia GK, Sachdeva MP. 'Mendelian randomization': an approach for exploring causal relations in epidemiology. Public Health. 2017. 145: 113\u0026ndash;119.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim S, Chen J, Cheng T, et al. PubChem 2023 update. NUCLEIC ACIDS RESEARCH. 2023. 51(D1): D1373-D1380.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosoff DB, Bell AS, Jung J, Wagner J, Mavromatis LA, Lohoff FW. Mendelian Randomization Study of PCSK9 and HMG-CoA Reductase Inhibition and Cognitive Function. J Am Coll Cardiol. 2022. 80(7): 653\u0026ndash;662.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWiller CJ, Schmidt EM, Sengupta S, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013. 45(11): 1274\u0026ndash;1283.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Z, Zhang B, Liu Q, et al. Genetic association of lipids and lipid-lowering drug target genes with non-alcoholic fatty liver disease. EBioMedicine. 2023. 90: 104543.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNikpay M, Goel A, Won HH, et al. A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nat Genet. 2015. 47(10): 1121\u0026ndash;1130.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFung K, Ram\u0026iacute;rez J, Warren HR, et al. Genome-wide association study identifies loci for arterial stiffness index in 127,121 UK Biobank participants. Sci Rep. 2019. 9(1): 9143.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElsworth B, Lyon M, Alexander T, et al. The MRC IEU OpenGWAS data infrastructure. BioRxiv. 2020: 2020\u0026ndash;08.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan Y, Zhang J, Huang S, et al. MicroRNA-223-3p inhibits vascular calcification and the osteogenic switch of vascular smooth muscle cells. J Biol Chem. 2021. 296: 100483.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun Y, Byon CH, Yang Y, et al. Dietary potassium regulates vascular calcification and arterial stiffness. JCI Insight. 2017. 2(19): e94920.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun Y, Byon CH, Yuan K, et al. Smooth muscle cell-specific runx2 deficiency inhibits vascular calcification. Circ Res. 2012. 111(5): 543\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeng L, Huang L, Sun Y, Heath JM, Wu H, Chen Y. Inhibition of FOXO1/3 promotes vascular calcification. Arterioscler Thromb Vasc Biol. 2015. 35(1): 175\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang Y, Sun Y, Chen J, et al. AKT-independent activation of p38 MAP kinase promotes vascular calcification. Redox Biol. 2018. 16: 97\u0026ndash;103.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang W, Sun Y, Yang Y, Chen Y. Impaired intracellular calcium homeostasis enhances protein O-GlcNAcylation and promotes vascular calcification and stiffness in diabetes. Redox Biol. 2023. 63: 102720.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD'Onofrio N, Prattichizzo F, Marfella R, et al. SIRT3 mediates the effects of PCSK9 inhibitors on inflammation, autophagy, and oxidative stress in endothelial cells. Theranostics. 2023. 13(2): 531\u0026ndash;542.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartino E, D'Onofrio N, Balestrieri A, et al. MiR-15b-5p and PCSK9 inhibition reduces lipopolysaccharide-induced endothelial dysfunction by targeting SIRT4. Cell Mol Biol Lett. 2023. 28(1): 66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZulkapli R, Muid SA, Wang SM, Nawawi H. PCSK9 Inhibitors Reduce PCSK9 and Early Atherogenic Biomarkers in Stimulated Human Coronary Artery Endothelial Cells. Int J Mol Sci. 2023. 24(6): 5098.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBao H, Wang X, Zhou H, et al. PCSK9 regulates myofibroblast transformation through the JAK2/STAT3 pathway to regulate fibrosis after myocardial infarction. Biochem Pharmacol. 2024. 220: 115996.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeidah NG, Benjannet S, Wickham L, et al. The secretory proprotein convertase neural apoptosis-regulated convertase 1 (NARC-1): liver regeneration and neuronal differentiation. Proc Natl Acad Sci U S A. 2003. 100(3): 928\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCunningham D, Danley DE, Geoghegan KF, et al. Structural and biophysical studies of PCSK9 and its mutants linked to familial hypercholesterolemia. Nat Struct Mol Biol. 2007. 14(5): 413\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSabatine MS. PCSK9 inhibitors: clinical evidence and implementation. Nat Rev Cardiol. 2019. 16(3): 155\u0026ndash;165.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Marchis GM, Dittrich TD, Malik R, et al. Genetic proxies for PCSK9 inhibition associate with lipoprotein(a): Effects on coronary artery disease and ischemic stroke. Atherosclerosis. 2022. 361: 41\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie W, Li J, Du H, Xia J. Causal relationship between PCSK9 inhibitor and autoimmune diseases: a drug target Mendelian randomization study. Arthritis Res Ther. 2023. 25(1): 148.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCupido AJ, Reeskamp LF, Hingorani AD, et al. Joint Genetic Inhibition of PCSK9 and CETP and the Association With Coronary Artery Disease: A Factorial Mendelian Randomization Study. JAMA Cardiol. 2022. 7(9): 955\u0026ndash;964.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapaioannou TG, Alexandraki KI, Tousoulis D. Arterial stiffness improvement after adding on PCSK9 inhibitors in patients with familial hypercholesterolemia. J Clin Lipidol. 2020. 14(4): 542.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScicali R, Di Pino A, Ferrara V, Rabuazzo AM, Purrello F, Piro S. Effect of PCSK9 inhibitors on pulse wave velocity and monocyte-to-HDL-cholesterol ratio in familial hypercholesterolemia subjects: results from a single-lipid-unit real-life setting. Acta Diabetol. 2021. 58(7): 949\u0026ndash;957.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarter SA. Indirect systolic pressures and pulse waves in arterial occlusive diseases of the lower extremities. Circulation. 1968. 37(4): 624\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKullo IJ, Rooke TW. CLINICAL PRACTICE. Peripheral Artery Disease. N Engl J Med. 2016. 374(9): 861\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCriqui MH, McClelland RL, McDermott MM, et al. The ankle-brachial index and incident cardiovascular events in the MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol. 2010. 56(18): 1506\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eResnick HE, Lindsay RS, McDermott MM, et al. Relationship of high and low ankle brachial index to all-cause and cardiovascular disease mortality: the Strong Heart Study. Circulation. 2004. 109(6): 733\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewman AB, Siscovick DS, Manolio TA, et al. Ankle-arm index as a marker of atherosclerosis in the Cardiovascular Health Study. Cardiovascular Heart Study (CHS) Collaborative Research Group. Circulation. 1993. 88(3): 837\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLampsas S, Xenou M, Oikonomou E, et al. Lipoprotein(a) in Atherosclerotic Diseases: From Pathophysiology to Diagnosis and Treatment. Molecules. 2023. 28(3): 969.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrpkovic A, Resanovic I, Stanimirovic J, et al. Oxidized low-density lipoprotein as a biomarker of cardiovascular diseases. Crit Rev Clin Lab Sci. 2015. 52(2): 70\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamstrup PR, Tybj\u0026aelig;rg-Hansen A, Nordestgaard BG. Extreme lipoprotein(a) levels and improved cardiovascular risk prediction. J Am Coll Cardiol. 2013. 61(11): 1146\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClarke R, Peden JF, Hopewell JC, et al. Genetic variants associated with Lp(a) lipoprotein level and coronary disease. N Engl J Med. 2009. 361(26): 2518\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Donoghue ML, Fazio S, Giugliano RP, et al. Lipoprotein(a), PCSK9 Inhibition, and Cardiovascular Risk. Circulation. 2019. 139(12): 1483\u0026ndash;1492.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan Y, Chen J, Chopra VK, et al. ODYSSEY EAST: Alirocumab efficacy and safety vs ezetimibe in high cardiovascular risk patients with hypercholesterolemia and on maximally tolerated statin in China, India, and Thailand. J Clin Lipidol. 2020. 14(1): 98\u0026ndash;108.e8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuklina EV, Yoon PW, Keenan NL. Trends in high levels of low-density lipoprotein cholesterol in the United States, 1999\u0026ndash;2006. JAMA. 2009. 302(19): 2104\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosinger A, Carroll MD, Lacher D, Ogden C. Trends in Total Cholesterol, Triglycerides, and Low-Density Lipoprotein in US Adults, 1999\u0026ndash;2014. JAMA Cardiol. 2017. 2(3): 339\u0026ndash;341.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarroll MD, Kit BK, Lacher DA, Shero ST, Mussolino ME. Trends in lipids and lipoproteins in US adults, 1988\u0026ndash;2010. JAMA. 2012. 308(15): 1545\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaigent C, Keech A, Kearney PM, et al. Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins. Lancet. 2005. 366(9493): 1267\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLawler PR, Bhatt DL, Godoy LC, et al. Targeting cardiovascular inflammation: next steps in clinical translation. Eur Heart J. 2021. 42(1): 113\u0026ndash;131.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrea F, Libby P. Acute Coronary Syndromes: The Way Forward From Mechanisms to Precision Treatment. Circulation. 2017. 136(12): 1155\u0026ndash;1166.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCristell N, Cianflone D, Durante A, et al. High-sensitivity C-reactive protein is within normal levels at the very onset of first ST-segment elevation acute myocardial infarction in 41% of cases: a multiethnic case-control study. J Am Coll Cardiol. 2011. 58(25): 2654\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrangogiannis NG. The inflammatory response in myocardial injury, repair, and remodelling. Nat Rev Cardiol. 2014. 11(5): 255\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurger PM, Koudstaal S, Mosterd A, et al. C-Reactive Protein and Risk of Incident Heart Failure in Patients With Cardiovascular Disease. J Am Coll Cardiol. 2023. 82(5): 414\u0026ndash;426.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRymer JA, Newby LK. Failure to Launch: Targeting Inflammation in Acute Coronary Syndromes. JACC Basic Transl Sci. 2017. 2(4): 484\u0026ndash;497.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang ZH, Peng J, Ren Z, et al. New role of PCSK9 in atherosclerotic inflammation promotion involving the TLR4/NF-κB pathway. Atherosclerosis. 2017. 262: 113\u0026ndash;122.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDing Z, Pothineni N, Goel A, L\u0026uuml;scher TF, Mehta JL. PCSK9 and inflammation: role of shear stress, pro-inflammatory cytokines, and LOX-1. Cardiovasc Res. 2020. 116(5): 908\u0026ndash;915.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRidker PM. A Test in Context: High-Sensitivity C-Reactive Protein. J Am Coll Cardiol. 2016. 67(6): 712\u0026ndash;723.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaptoge S, Di Angelantonio E, Lowe G, et al. C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis. Lancet. 2010. 375(9709): 132\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRidker PM, Danielson E, Fonseca FA, et al. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med. 2008. 359(21): 2195\u0026ndash;207.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e/ABC/ACPM/ADA/AGS/APhA/ASPC/\u003c/span\u003e\u003cspan address=\"http:///ABC/ACPM/ADA/AGS/APhA/ASPC/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003eNLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019. 139(25): e1082-e1143.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAminuddin A, Lazim M, Hamid AA, et al. The Association between Inflammation and Pulse Wave Velocity in Dyslipidemia: An Evidence-Based Review. Mediators Inflamm. 2020. 2020: 4732987.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSwamynathan R, Varadarajan V, Nguyen H, et al. Association between Biomarkers of Inflammation and 10-Year Changes in Aortic Stiffness: The Multi-Ethnic Study of Atherosclerosis. J Clin Med. 2023. 12(15): 5062.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Yang HY, Giachelli CM. BMP-2 promotes phosphate uptake, phenotypic modulation, and calcification of human vascular smooth muscle cells. Atherosclerosis. 2008. 199(2): 271\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarracedo M, Artiach G, Witasp A, et al. The G-protein coupled receptor ChemR23 determines smooth muscle cell phenotypic switching to enhance high phosphate-induced vascular calcification. Cardiovasc Res. 2019. 115(10): 1557\u0026ndash;1566.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetsophonsakul P, Burgmaier M, Willems B, et al. Nicotine promotes vascular calcification via intracellular Ca2+-mediated, Nox5-induced oxidative stress, and extracellular vesicle release in vascular smooth muscle cells. Cardiovasc Res. 2022. 118(9): 2196\u0026ndash;2210.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao XK, Zhu MM, Wang SN, et al. Transcription factor 21 accelerates vascular calcification in mice by activating the IL-6/STAT3 signaling pathway and the interplay between VSMCs and ECs. Acta Pharmacol Sin. 2023. 44(8): 1625\u0026ndash;1636.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eByon CH, Javed A, Dai Q, et al. Oxidative stress induces vascular calcification through modulation of the osteogenic transcription factor Runx2 by AKT signaling. J Biol Chem. 2008. 283(22): 15319\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acute coronary syndrome, PCSK9 inhibitors, Arterial stiffness, C-reactive protein, Mendelian randomization","lastPublishedDoi":"10.21203/rs.3.rs-4008037/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4008037/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCurrent evidences suggest that Proprotein Convertase Subtilisin/kexin Type 9 inhibitors (PCSK9i) exhibit a protective influence on acute coronary syndrome (ACS). Nevertheless, further investigation is required to comprehend the impact and mechanisms of these pharmaceutical agents on inflammatory factors and arterial stiffness (AS) in patients with ACS. Consequently, the objective of this study is to ascertain the influence of PCSK9i on arterial stiffness in ACS patients and elucidate the underlying mechanisms behind their actions.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study employed Mendelian randomization (MR) analysis to examine the association between genetic prediction of PCSK9 inhibition and arterial stiffness. A total of 71 patients with ACS were randomly allocated into either a PCSK9i group or a control group. Blood lipid levels, inflammatory markers and pulse wave velocity (PWV) data were collected before treatment and at 1 and 6 months after treatment for analysis. Additionally, cell experiments were conducted to investigate the impact of PCSK9i on osteogenesis of vascular smooth muscle cells (VSMCs), utilizing western blot (WB), enzyme-linked immunosorbent assay (ELISA), and calcification index measurements.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe results of the MR analysis suggest that genetic prediction of PCSK9 inhibition has potential to reduce the pulse wave reflection index (PWV). Following treatment of statins combined with PCSK9 inhibitors for 1 and 6 months, the PCSK9i group exhibited significantly lower levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), C-reactive protein (CRP), interleukin-6 (IL-6), fibrinogen (FIB) and procalcitonin (PCT) compared to the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, PWV in the PCSK9i group demonstrated significant reduction after 6 months of treatment and was found to be associated with the circulating CRP level. In cell experiments, PCSK9i pretreatment ameliorated osteogenesis of VSMCs through reducing the deposition of calcium ions, alkaline phosphatase (ALP) activity, and expression of runt-related transcription factor 2(RUNX2).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePCSK9i have potential to enhance arterial stiffness at various aspects, including the genetic, clinical, and cellular domains. Specifically, at the clinical level, this impact may be attributed to alterations in circulating CRP levels. At the cellular level, it is associated with the signaling pathway linked to RUNX2.\u003c/p\u003e","manuscriptTitle":"PCSK9 inhibitors ameliorate arterial stiffness in ACS patients: evidences from mendelian randomization, cohort studies and basic experiments","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-08 17:47:58","doi":"10.21203/rs.3.rs-4008037/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"63cc12d1-bde8-46ff-9b4b-4dfe976ef2d8","owner":[],"postedDate":"March 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-08T17:48:01+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-08 17:47:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4008037","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4008037","identity":"rs-4008037","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}