Peripheral artery disease risk factors: A focus on lipoprotein(a).

There is a well-established and strong link between high lipoprotein(a) concentration and coronary heart disease, but the evidence regarding peripheral artery disease and carotid atherosclerosis is not as conclusive. This review aims to summarize the relationships between lipoprotein(a), peripheral artery disease and carotid atherosclerosis, in order to try to understand the weight of lipoprotein(a) in determining the development, progression and any complications of atherosclerotic plaque at the carotid and peripheral artery level. There is currently no effective therapy to reduce lipoprotein(a) concentration, but understanding its significance as a vascular risk factor is the starting point to then explore (when effective therapies become available) if there is the possibility, even in patients with peripheral artery disease and carotid atherosclerosis, to achieve better control of the residual vascular risk that is ultimately induced by lipoprotein(a).

Biomarker-enhanced cardiovascular risk prediction in patients with cancer: a prospective cohort study.

BACKGROUND: Continuously improving cancer-specific survival puts a growing proportion of cancer patients at risk of major adverse cardiovascular events (MACE), but tailored tools for cardiovascular risk prediction remain unavailable. OBJECTIVES: To assess a broad panel of cardiovascular biomarkers and risk factors for the prediction of MACE and cardiovascular death in cancer patients. METHODS: In total, 2192 patients with newly diagnosed or recurrent cancer were followed prospectively for the occurrence of 2-year MACE and 5-year cardiovascular death. Univariable and multivariable risk models were fit to assess independent associations of cardiovascular risk factors and biomarkers with adverse outcomes, and a risk score was developed. RESULTS: Traditional cardiovascular risk factors and selected cancer types were linked to higher MACE risk. While levels of Lp(a), CRP, and GDF-15 did not associate with MACE, levels of ICAM-1, P-/E-/L-selectins, and NT-proBNP were independently linked to 2-year MACE risk. A clinical risk score was derived, assigning +1 point for male sex, smoking, and age of ≥60 years and +2 points for atherosclerotic disease, yielding a bootstrapped C-statistic of 0.76 (95% CI: 0.71-0.81) for the prediction of 2-year MACE. Implementation of biomarker data conferred improved performance (0.83, 95% CI: 0.78-0.88), with a simplified model showing similar performance (0.80, 95% CI: 0.74-0.86). The biomarker-enhanced and simplified prediction models achieved a C-statistic of 0.82 (95% CI: 0.71-0.93) and 0.74 (95% CI: 0.64-0.83) for the prediction of 5-year cardiovascular death. CONCLUSION: Biomarker-enhanced risk prediction strategies allow the identification of cancer patients at high risk of MACE and cardiovascular death. While external validation studies are ongoing, this first-of-its-kind risk score may provide the basis for personalized cardiovascular risk assessment across cancer entities.

Association Between Lipoprotein(a) and Obstructive Coronary Artery Disease and High-Risk Plaque: Insights From the PROMISE Trial.

BACKGROUND: The role of lipoprotein (a), or Lp(a), in the development of obstructive coronary artery disease (CAD) and high-risk plaque (HRP) among primary prevention patients with stable chest pain is unknown. We sought to evaluate the relationship of Lp(a), independent of low-density lipoprotein cholesterol (LDL-C), with the presence of obstructive CAD and HRP in an attempt to improve understanding of the residual risk imparted by Lp(a) on CAD. METHODS: We performed a secondary analysis among PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) Trial participants who had coronary computed tomographic angiography (CTA) performed and Lp(a) data available. Lp(a) concentration was analyzed as a binary variable with elevated Lp(a) defined as ≥50 mg/dL. "Stenosis ≥ 50%" was defined as ≥50% coronary artery stenosis in any epicardial vessel, and "Stenosis ≥ 70%" was defined as ≥70% coronary artery stenosis in any epicardial vessel and/or ≥50% left main coronary artery stenosis. HRP was defined as presence of plaque on CTA imaging with evidence of positive remodeling, low CT attenuation, or napkin ring sign. Multivariate logistic regression models were constructed to evaluate the association between Lp(a) and the outcomes of obstructive CAD and HRP stratified by LDL-C ≥100 mg/dL vs. <100 mg/dL. RESULTS: Of the 1,815 patients who underwent CTA and had Lp(a) data available, those with elevated Lp(a) were more commonly female and Black than those with lower Lp(a). Elevated Lp(a) was associated with both Stenosis ≥ 50% (OR 1.57, 95% CI 1.14-2.15, p=0.005) and Stenosis ≥ 70% (OR 2.05, 95% CI 1.34-3.11, p=0.0008) in multivariate models, and this relationship was not modified by LDL-C ≥100 mg/dL vs. <100 mg/dL (interaction p>0.4). Elevated Lp(a) was not associated with HRP when adjusted for obstructive CAD. CONCLUSIONS: This study of patients without known CAD found that elevated Lp(a) ≥50 mg/dL was independently associated with the presence of obstructive CAD regardless of controlled vs. uncontrolled LDL-C, but was not independently associated with HRP when Stenosis ≥ 50% or ≥ 70% was accounted for. Further research is warranted to delineate the role of Lp(a) in the residual risk for ASCVD that patients may have despite optimal LDL-C lowering.

Elevated High-Sensitivity C-Reactive Protein Level Enhances the Impact of Lipoprotein(a) on Platelet Reactivity in PCI Patients Treated with Clopidogrel.

BACKGROUND: Recently, the effect of Lipoprotein(a) [Lp(a)] on thrombogenesis has aroused great interest, while inflammation has been reported to modify the Lp(a)-associated risks through an unidentified mechanism. PURPOSE: This study aimed to evaluate the association between platelet reactivity with Lp(a) and high-sensitivity C-reactive protein (hs-CRP) levels in percutaneous intervention (PCI) patients treated with clopidogrel. METHODS: Data were collected from 10,724 consecutive PCI patients throughout the year 2013 in Fuwai Hospital. High on-treatment platelet reactivity (HTPR) and low on-treatment platelet reactivity (LTPR) were defined as thrombelastography (TEG) maximum amplitude of adenosine diphosphate-induced platelet (MAADP) > 47 mm and < 31 mm, respectively. RESULTS: 6615 patients with TEG results were finally enrolled. The mean age was 58.24 ± 10.28 years and 5131 (77.6%) were male. Multivariable logistic regression showed that taking Lp(a) < 30 mg/dL and hs-CRP < 2 mg/L as the reference, isolated Lp(a) elevation [Lp(a) ≥ 30 mg/dL and hs-CRP < 2 mg/L] was not significantly associated with HTPR (P = 0.153) or LTPR (P = 0.312). However, the joint elevation of Lp(a) and hs-CRP [Lp(a) ≥ 30 mg/dL and hs-CRP ≥ 2 mg/L] exhibited enhanced association with both HTPR (OR:1.976, 95% CI 1.677-2.329) and LTPR (OR:0.533, 95% CI 0.454-0.627). CONCLUSIONS: The isolated elevation of Lp(a) level was not an independent indicator for platelet reactivity, yet the concomitant elevation of Lp(a) and hs-CRP levels was significantly associated with increased platelet reactivity. Whether intensified antiplatelet therapy or anti-inflammatory strategies could mitigate the risks in patients presenting combined Lp(a) and hs-CRP elevation requires future investigation.

Serum Lipoprotein(a) as Predictive Factor for Early Neurological Deterioration of Acute Ischemic Stroke After Thrombolysis.

Objective: This study aimed to explore the relationship between serum lipoprotein(a) (LP(a)) levels and early neurological deterioration (END) in patients with acute ischemic stroke (AIS) after thrombolysis. Methods: In total, 236 patients with AIS after thrombolysis were enrolled in this study. Serum LP(a) levels were measured on admission after thrombolysis. END was defined as an increase of at least two points in the NIHSS score within 48 hours after thrombolysis. Binary logistic regression analysis was used to assess the association between serum LP(a) levels and END. Results: Overall, patients with END had higher LP(a) than those without END (high LP(a): 38.3% vs 22.2%, intermediate LP(a): 40.3% vs 41.8%, low LP(a): 21.3% vs 36.0%, p<0.005). In the multivariate analysis, high LP(a) (defined as LP(a) level≥ 300 mg/L) was an independent risk factor for END post-thrombolysis (OR=3.154, 95% CI=1.067-9.322, p=0.038). Conclusion: Our findings demonstrated that LP(a) was an independent risk factor for END post-thrombolysis and that LP(a) level≥ 300 mg/L could be associated with END post-thrombolysis in this study population.

Intra-individual variability in lipoprotein(a): the value of a repeat measure for reclassifying individuals at intermediate risk.

Aims: Lipoprotein(a) [Lp(a)] levels are predominantly genetically determined and repeat measurements are generally considered unlikely to be clinically useful. However, the temporal variation of Lp(a) is not well characterized. Our aim was to determine the intra-individual variability of Lp(a) and whether a repeated measure reclassified Lp(a)-specific cardiovascular risk using the European Atherosclerosis Society (EAS) consensus statement risk categories. Methods and results: This retrospective cohort study analysed initial and repeated serum Lp(a) levels measured using the same methodology from 609 individuals in the Nashville Biosciences database, a de-identified electronic medical records database. Baseline and follow-up paired values were significantly different (P < 0.05), with an absolute change of ≥10 mg/dL in 38.1% [95% CI 34.2-42%] and a >25% change in 40.5% [95% CI 36.6-44.3%] of individuals. Although the categories of those whose values were in the EAS low-risk and high-risk categories did not change, 53% of those in the intermediate 'grey-zone' category transitioned to either the low-risk (20%) or high-risk (33%) category. Black individuals exhibited greater variability than White individuals and women exhibited greater variability than men. There was a positive correlation between the baseline Lp(a) levels and the absolute changes in Lp(a), (r = 0.59, P < 0.01). Conclusion: Temporal-related changes in Lp(a) variability were present in many individuals. A repeat Lp(a) measure may allow more precise Lp(a)-specific cardiovascular risk prediction for individuals whose initial value is in the EAS-defined intermediate 'grey-zone' category. Lp(a) variability should be included in calculating the expected effect sizes in future clinical research studies targeting Lp(a).

Association of elevated lipoprotein(a) levels with ischemic stroke in young patients - a systematic review and meta-analysis.

INTRODUCTION: Lipoprotein(a) [Lp(a)] is an established independent causal risk factor for cardiovascular disease and atherosclerosis. However, its association with young-onset ischemic stroke is not well-established. A systematic review and meta-analysis was performed to investigate the association of elevated Lp(a) with young ischemic stroke. METHODS: Four electronic databases: PubMed (MEDLINE), EMBASE, Scopus and Cochrane Library were systematically searched, profiling studies from inception till 6 Mar 2024. We included studies investigating the relationship between stratified Lp(a) levels and young ischemic stroke. We compared the odds of young stroke patients (age <65 years) having elevated Lp(a) compared to age-matched controls without stroke or transient ischemic attack. RESULTS: Five case-control studies comprising a total of 1345 patients were included; 57.7 % (776/1345) were females, with a mean age of 41.5 years. Among them, 22.5 % (264/1171) were smokers. Additionally, 16.8 % (197/1171) had hypertension, 5.9 % (69/1171) had diabetes, and 29.2 % (284/971) had hyperlipidemia. Young stroke patients were more likely to have high Lp(a) level than age-matched controls (OR 1.61, 95 %CI 1.24-2.10). Four studies defined a high Lp(a) level as ≥30mg/dL, whilst one study used a Lp(a) level of >23.2mg/dL as the cut-off. A sensitivity analysis excluding this study showed that young stroke patients were still more likely to have Lp(a) ≥30mg/dL than controls (OR 1.43, 95 %CI 1.08-1.88). CONCLUSION: Young stroke patients are more likely to have elevated Lp(a) compared to age-matched controls, suggesting an association between elevated Lp(a) and young stroke. Further research is warranted to evaluate the causal relationships between Lp(a) and young-onset ischemic stroke, as well as to conduct a cost-benefit analysis of Lp(a) screening in young adults as part of a primary prevention strategy.

Exploring the Effect of Thyroid Hormone on Serum Lipoprotein (a) Levels in Patients With Thyroid Hormone Dysfunction: A Systematic Review.

Genetic variations among people mainly determine the blood levels of lipoprotein (a) (Lp(a)), and it is relatively stable throughout one's lifetime. Nevertheless, there could still be other factors that control the Lp(a) level. Thyroid hormones are known to influence the serum lipid level by regulating the expression of key enzymes that are involved in lipid metabolism. Both hypo and hyperthyroidism are associated with changes in lipid levels. Even though thyroid hormone abnormalities have been shown to alter traditional lipid parameters like low-density lipoprotein (LDL-C), its influence on Lp(a) has not been established. This review aims to identify the relationship between Lp(a) and thyroid hormones by reviewing data from correlative studies and observing treatment-related Lp(a) level changes in thyroid disorders from interventional studies. We searched MEDLINE, Cochrane, and Google Scholar databases with predefined search criteria and search strategies for paper identification. Individual reviewers reviewed identified papers for selection. Finalized papers were reviewed for Lp(a) levels and their responses to treatment in patients with thyroid disorders to establish the relationship between Lp(a) and thyroid hormone. We concluded that the data were limited and sometimes contradicted one another to establish a clear relationship between Lp(a) and thyroid hormones. Even though correlative studies data showed strong indications that overt-hypothyroidism was associated with high Lp(a) levels, thyroid hormone replacement studies did not show any significant changes in Lp(a) levels compared to pre-treatment in patients with both overt-hypothyroidism and subclinical hypothyroidism. More clinical trials focusing on Lp(a) with longer periods of treatment and follow-up in thyroid patients are needed to establish the relationship between the two. The possibility of dose-related Lp(a) responses to thyroid hormone treatment should also be explored.

Is lipoprotein(a) measurement important for cardiovascular risk stratification in children and adolescents?

BACKGROUND: Elevated lipoprotein (Lp(a)) levels are associated with increased risk of atherosclerotic processes and cardiovascular events in adults. The amount of Lp(a) is mainly genetically determined. Therefore, it is important to identify individuals with elevated Lp(a) as early as possible, particularly if other cardiovascular risk factors are present. The purpose of the study was to investigate whether, in a population of children and adolescents already followed for the presence of one or more cardiovascular risk factors (elevated blood pressure (BP), and/or excess body weight, and/or dyslipidemia), the measurement of Lp(a) can be useful for better stratifying their risk profile. METHODS: In a sample of 195 children and adolescents, height, body weight, waist circumference and systolic (SBP) and diastolic (DBP) BP were measured. Body Mass Index (BMI) and SBP and DBP z-scores were calculated. Plasma Lp(a), total cholesterol, high-density lipoprotein (HDL), triglycerides, glucose, insulin, uric acid and creatinine were assessed. Low-density lipoprotein (LDL) cholesterol was calculated with the Friedewald formula. High Lp(a) was defined as ≥ 75 nmol/L and high LDL cholesterol as ≥ 3.37 mmol/L. RESULTS: Our sample of children and adolescents (54.4% males, mean age 11.5 years) had median LDL cholesterol and Lp(a) values equal to 2.54 (interquartile range, IQR: 2.07-3.06) mmol/L and 22 (IQR: 7.8-68.6) nmol/L respectively. 13.8% of children had LDL cholesterol ≥ 3.37 mmol/L and 22.6 Lp(a) values ≥ 75 nmol/L. Lp(a) values were higher in children of normal weight than in those with excess weight (p = 0.007), but the difference disappeared if normal weight children referred for dyslipidemia only were excluded from the analysis (p = 0.210). 69.4% of children had normal Lp(a) and LDL cholesterol values and only 6.2% showed both elevated Lp(a) and LDL cholesterol levels. However, 16.6% of the sample, despite having normal LDL cholesterol, had elevated Lp(a) values. Multivariable analyses showed a significant association of LDL cholesterol both with Lp(a) values, and with the presence of elevated Lp(a) levels. For each mmol/L increase in LDL cholesterol the risk of having an elevated Lp(a) value increased by 73%. There was an inverse correlation between BMI z-score and Lp(a). Neither BP z-scores, nor other biochemical parameters were associated with Lp(a). CONCLUSIONS: In our population more than one out of five children had elevated Lp(a) values, and in about 17% of children elevated Lp(a) values were present in the absence of increased LDL cholesterol. Our results suggest that Lp(a) measurement can be useful to better define the cardiovascular risk profile in children and adolescents already followed for the presence of other cardiovascular risk factors such as elevated BP, excess body weight and high LDL cholesterol.

Advantages of using Genetically Elevated Lipoprotein(a) Levels in Predicting 5-Year Major Adverse Cardiovascular Events Relating to Coronary Artery Disease in Women.

Background: This study aimed to investigate major adverse cardiovascular events (MACE) in patients with coronary artery disease (CAD) over 5 years, in general, and depending on sex, lipoprotein(a) level, and number of kringle IV type 2 (KIV-2) repeats in the Lipoprotein(A) (LPA) gene. Methods: This study comprised 216 patients (120 women and 96 men) hospitalized with a diagnosis of "CAD, unstable angina IIB class". The three-point risk of MACEs was assessed over 5 years: cardiovascular death, non-fatal myocardial infarction, and stroke. The number of KIV-2 repeats in the LPA gene was determined by quantitative real-time polymerase chain reaction (qPCR). Results: The relative risk of MACE in patients with elevated lipoprotein(a) (Lp(a)) was 2.0 (95% CI 1.04-3.87, p < 0.05) for quartile 4 (Q4) ≥ 48 mg/dL versus quartile 1 (Q1) ≤ 6 mg/dL. This was mainly attributable to an increase in men-relative risk (RR) 2.6 (95% CI 1.10-6.16, p < 0.05)-but not in women: RR 1.4 (95% CI 0.50-3.92). Mean lipoprotein(a) levels were inversely correlated with 42.5 and 7.5 for Q1 and Q4 KIV-2 repeat numbers, respectively. The relative risks of MACE for Q1 vs. Q4 KIV-2 repeats were as follows: 3.0 (95% CI 1.48-6.08, p < 0.001) for all patients; 3.0 (95% CI 1.20-6.55, p < 0.01) for men; 3.3 (95% CI 1.02-10.4, p < 0.05) for women. Conclusions: Quantifying kringle IV type 2 repeat copy number in the LPA gene using qPCR more accurately reflects the risk of major adverse cardiovascular events within 5 years in women with coronary artery disease.

Associations of very low Lipoprotein(a) levels with risks of new-onset diabetes and non-alcoholic liver disease.

Background and aims: We aimed to study the association of very low serum Lipoprotein(a) [Lp(a)] concentrations with new-onset type 2 diabetes (T2D) and non-alcoholic liver disease (NAFLD) in the context of statin usage in the UK Biobank, a large prospective population cohort. Methods: Using an extended biomarker dataset, we identified 47,362 participants with very low Lp(a) concentrations (<3.8 nmol/L) from a total of 451,479 participants. With a median follow-up of 12.3 years, we assessed the risk of new-onset cardiometabolic diseases in participants stratified by statin usage with Cox proportional hazards models. We performed two-sample Mendelian randomization MR analyses to test causal relationship between genetically predicted Lp(a) and T2D and NAFLD. Results: Taking the participants with Lp(a) within reportable range as the reference group, the hazard ratios (HR) for T2D were 1.07 (95 % confidence interval, CI 1.01-1.13) and for NAFLD 1.30 (95 % CI 1.20-1.41) respectively for participants with very low Lp(a) (<3.8 nmol/L). The risk for new-onset T2D was higher in participants using statins (adjusted HR 1.15; 95 % CI 1.05-1.27). The risk estimates for new-onset NAFLD were comparable in the analysis stratified by statin use. There was no evidence for causal links between genetically predicted Lp(a) and T2D nor NAFLD in two-sample MR analyses. Conclusions: Very low Lp(a) was associated with higher risks of T2D and NAFLD in a prospective analysis of the UK Biobank. The association with T2D was influenced by lipid lowering medication usage. MR analyses did not support causality for these inverse associations.

Enhanced predictive performance of the GRACE risk score by incorporating lipoprotein(a) for major adverse cardiac events in acute myocardial infarction patients undergoing PCI.

Background: As scientific research advances, the landscape of detection indicators and methodologies evolves continuously. Our current study aimed to identify some novel perioperative indicators that can enhance the predictive accuracy of the Global Registry of Acute Coronary Events (GRACE) score for the in-hospital major adverse cardiovascular events (MACEs) in patients with acute myocardial infarction. Methods: A total of 647 adult patients with AMI admitted to the emergency department were consecutively enrolled in the retrospective research starting from June 2016 to September 2019. The endpoint was in-hospital MACE. Stepwise regression analysis and multivariate logistic regression were performed to select the indicators for the union model established by nomogram. Bootstrap with 1000 replicates was chosen as the internal validation of the union model. The area under the receiver operating curve (AUC) and calibration plot were used to evaluate the discrimination and calibration. Decision curve analysis (DCA) was performed to evaluate the clinical sufficiency of the nomogram. Akaike's information criterion (AIC) and Bayesian Information Criterion (BIC) were used to evaluate the goodness of fit. Results: Lipoprotein(a) combined with serum uric acid, fasting blood glucose, and hemoglobin could improve the GRACE risk score. The AUC of the union model was 0.86, which indicated a better discriminative ability than the GRACE risk score alone (AUC, 0.81; P < 0.05). The calibration plots of the union model showed favorable consistency between the prediction of the model and actual observations, which was better than the GRACE risk score. DCA plots suggested that the union model had better clinical applicability than the GRACE risk score. Conclusion: Lipoprotein(a) has shown promise in augmenting the predictive capability of the GRACE risk score, however, it may be beneficial to integrate it with other commonly used indicators.

First time ACS in patients with on-target lipid levels: Inflammation at admission and re-event rate at follow-up.

BACKGROUND: Dyslipidaemia, inflammation and elevated Lp(a) levels are associated with the progression of atherosclerosis. This study investigates whether patients with a first-time presentation of chest pain and on-target LDL-C levels and intermediate FRS/ESC-Score risks, display a high inflammatory burden linked to myocardial injury and whether inflammation at admission affects the re-event rate up to 6 years follow-up. METHODS: Blind assessments of novel inflammatory markers such as Glycoprotein A and B via nuclear magnetic resonance (NMR), cytokines, hsCRP, Neutrophil-to-Lymphocyte ratio (NLR) and Lipoprotein(a) levels were examined. Out of 198 chest pain patients screened, 97 met the inclusion criteria at admission. RESULTS: cTnI(+) patients (>61 ng/L) with elevated Lipoprotein(a), showed significantly increased levels of Glycoprotein A and B, hsCRP, IL-6, a high NLR and a reduced left ventricular ejection fraction (%) compared to cTnI(-) individuals. Those patients, with a higher inflammatory burden at hospital admission (hsCRP, IL-6, Glycoprotein A and B, and Lipoprotein(a)) had a higher re-event rate at follow-up. CONCLUSIONS: Inflammation and Lipoprotein(a) levels were particularly prominent in patients presenting with reduced left ventricular ejection fraction. Notably, Glycoproteins A/B emerge as novel markers of inflammation in these patients. Our study highlights the significantly higher impact of inflammatory burden in patients with chest pain and high level of myocardial damage than in those with lower myocardial affectation, even when they all had lipid levels well controlled. Inflammation at the time of admission influenced the re-event rate over a follow-up period of up to 6 years.

Genetically predicted lipoprotein(a) associates with coronary artery plaque severity independent of low-density lipoprotein cholesterol.

AIMS: Elevated Lipoprotein(a) [Lp(a)] is a causal risk factor for atherosclerotic cardiovascular disease, but the mechanisms of risk are debated. Studies have found inconsistent associations between Lp(a) and measurements of atherosclerosis. We aimed to assess the relationship between Lp(a), low-density lipoprotein cholesterol (LDL-C) and coronary artery plaque severity. METHODS: The study population consisted of participants of the Million Veteran Program who have undergone an invasive angiogram. The primary exposure was genetically predicted Lp(a), estimated by a polygenic score. Genetically predicted LDL-C was also assessed for comparison. The primary outcome was coronary artery plaque severity, categorized as normal, non-obstructive disease, 1-vessel disease, 2-vessel disease, and 3-vessel or left main disease. RESULTS: Among 18,927 adults of genetically inferred European ancestry and 4,039 adults of genetically inferred African ancestry, we observed consistent associations between genetically predicted Lp(a) and obstructive coronary plaque, with effect sizes trending upward for increasingly severe categories of disease. Associations were independent of risk factors, clinically measured LDL-C and genetically predicted LDL-C. However, we did not find strong or consistent evidence for an association between genetically predicted Lp(a) and risk for non-obstructive plaque. CONCLUSIONS: Genetically predicted Lp(a) is positively associated with coronary plaque severity independent of LDL-C, consistent with Lp(a) promoting atherogenesis. However, the effects of Lp(a) may be greater for progression of plaque to obstructive disease than for the initial development of non-obstructive plaque. A limitation of this study is that Lp(a) was estimated using genetic markers and could not be directly assayed, nor could apo(a) isoform size.

This study assessed the association between genetic propensity towards higher lipoprotein(a) [Lp(a)] in the blood and the severity of coronary artery plaque seen on clinical angiograms, independent of other factors, including low-density lipoprotein cholesterol (LDL-C). The study was conducted in a large U.S. population using data from the Million Veteran Program. Genetically predicted high Lp(a) was associated with obstructive coronary plaque, but it was not associated with non-obstructive coronary plaque. This association was independent of LDL-C, and the association was greater for more severe forms of disease.The mechanisms of association between Lp(a) and cardiovascular events are debated. Prior studies have shown that Lp(a) does not associate with early markers of atherosclerosis. Our analyses support the idea that Lp(a) plays less of a role in early plaque initiation but plays a significant role in the progression of plaque towards more severe disease, independent of LDL-C.

The levels of serum lipoprotein(a) on clinical outcomes in Chinese hospitalized patients with cardiovascular diseases.

OBJECTIVE: Serum lipoprotein(a) [Lp(a)] is a risk factor of cardiovascular diseases. However, the relationship between the serum Lp(a) and clinical outcomes has been seldom studied in Chinese hospitalized patients with cardiovascular diseases. METHODS: We retrospectively collected the clinical data of hospitalized patients with cardiovascular diseases in the Cardiovascular Department of Dongguan People's Hospital from 2016 to 2021 through the electronic case system. Patients were divided into 4 groups based on Lp(a) quartiles: Quartile1 (≤ 80.00 mg/L), Quartile 2 (80.01 ~ 160.90 mg/L), Quartile 3 (160.91 ~ 336.41 mg/L), Quartile 4 (> 336.41 mg/L). Cox proportional hazard regression models were constructed to examine the relationship between Lp(a) and cardiovascular events. RESULTS: A total of 8382 patients were included in this study. After an average follow-up of 619 (320 to 1061) days, 1361 (16.2%) patients developed major adverse cardiovascular events, and 125 (1.5%) all-cause death were collected. The incidence of MACEs was 7.65, 8.24, 9.73 and 10.75 per 100 person-years in each Lp(a) quartile, respectively; the all-cause mortality was 0.48, 0.69, 0.64 and 1.18 per 100 person-years in each Lp(a) quartile, respectively. The multivariate Cox regression analysis suggested that high Lp(a) level was an independent risk factor for MACEs (HR: 1.189, [95% CI: 1.045 to 1.353], P = 0.030) and all-cause death (HR: 1.573, [95% CI: 1.009 to 2.452], P = 0.046). CONCLUSION: In addition to traditional lipid indicators, higher Lp(a) exhibited higher risks of adverse cardiovascular events and death, indicated worse prognosis. Lp(a) may be a new target for the prevention of atherosclerotic diseases.

Lipoprotein(a): Levels and Reference Intervals Among People in Saudi Arabia.

Purpose: Blood Lp(a) concentration is recognized as an independent risk factor for cardiovascular disease (CVD). Population-based lipoprotein(a) (Lp[a]) research in Saudi Arabia is rare. Thus, the primary goal of this pilot study was to identify age- and sex-specific reference ranges for Lp(a) levels, in addition to the associations between Lp(a) levels and other atherosclerotic markers in Saudi individuals. Patients and methods: A five-year retrospective study of Lp(a) and lipid markers in Saudi patients was conducted using the Al-Borg diagnostics database (2015-2020). The population sample consisted of 361 Saudi individuals aged 18-93 years (162 males, 199 females). An immunoturbidimetric technique was used to determine Lp(a) concentration. Results: The mean and median Lp(a) levels in the study population were 35 nmol/L and 50 nmol/L, respectively. Sex and age did not influence Lp(a) values. Lp(a) values showed a minor correlation with other atherosclerotic markers when the Pearson correlation coefficient was used. In Saudi Arabia, the distribution of Lp(a) concentrations is skewed to the left, favoring lower values. Conclusion: Lp(a) levels in individuals residing in Saudi Arabia were comparable to those observed in other ethnic groups. Additionally, standardizing Lp(a) measurements according to sex and age may enhance broader applicability and facilitate comparisons across different populations. However, larger studies are required to provide more comprehensive data for comparison.

Causal associations between insulin and Lp(a) levels in Caucasian population: a Mendelian randomization study.

BACKGROUND: Numerous observational studies have demonstrated that circulating lipoprotein(a) [Lp(a)] might be inversely related to the risk of type 2 diabetes (T2D). However, recent Mendelian randomization (MR) studies do not consistently support this association. The results of in vitro research suggest that high insulin concentrations can suppress Lp(a) levels by affecting apolipoprotein(a) [apo(a)] synthesis. This study aimed to identify the relationship between genetically predicted insulin concentrations and Lp(a) levels, which may partly explain the associations between low Lp(a) levels and increased risk of T2D. METHODS: Independent genetic variants strongly associated with fasting insulin levels were identified from meta-analyses of genome-wide association studies in European populations (GWASs) (N = 151,013). Summary level data for Lp(a) in the population of European ancestry were acquired from a GWAS in the UK Biobank (N = 361,194). The inverse-variance weighted (IVW) method approach was applied to perform two-sample summary-level MR. Robust methods for sensitivity analysis were utilized, such as MR‒Egger, the weighted median (WME) method, MR pleiotropy residual sum and outlier (MR-PRESSO), leave-one-out analysis, and MR Steiger. RESULTS: Genetically predicted fasting insulin levels were negatively associated with Lp(a) levels (ß = - 0.15, SE = 0.05, P = 0.003). The sensitivity analysis revealed that WME (ß = - 0.26, SE = 0.07, P = 0.0002), but not MR‒Egger (ß = - 0.22, SE = 0.13, P = 0.11), supported a causal relationship between genetically predisposed insulin levels and Lp(a). CONCLUSION: Our MR study provides robust evidence supporting the association between genetically predicted increased insulin concentrations and decreased concentrations of Lp(a). These findings suggest that hyperinsulinaemia, which typically accompanies T2D, can partially explain the inverse relationship between low Lp(a) concentrations and an increased risk of T2D.

Impact of Social Determinants of Health and Lifestyle on Association Between Lipoprotein(a) and Cardiovascular Events.

Background: In European cohorts, healthier lifestyle either attenuated or associated with lower cardiovascular risk despite elevated lipoprotein(a) [Lp(a)]. Objectives: The purpose of this study was to test if social determinants of health (SDOH) and Life's Simple 7 (LS7) scores impact the association of Lp(a) with cardiovascular events in U.S. cohorts. Methods: We performed a sequential multivariable Cox proportional hazard analysis using the ARIC (Atherosclerosis Risk In Communities) and MESA (Multi-Ethnic Study of Atherosclerosis) cohorts. We first adjusted for age, gender, non-high-density lipoprotein-cholesterol, race, and ethnicity, then sequentially added SDOH and LS7 scores. The primary outcomes were time until first myocardial infarction (MI) or stroke. Results: ARIC (n = 15,072; median Lp(a) = 17.3 mg/dL) had 16.2 years and MESA (n = 6,822; median Lp(a) = 18.3 mg/dL) had 12.3 years of average follow-up. In age, gender, race, and ethnicity, and non-high-density lipoprotein-cholesterol adjusted analyses, Lp(a) was associated with MI in ARIC (HR: 1.10, P < 0.001) and MESA (HR: 1.11, P = 0.001), and stroke in ARIC (HR: 1.07, P < 0.001) but not MESA (HR: 0.97, P = 0.53). In models with SDOH and LS7, associations of Lp(a) remained similar with MI (ARIC, HR: 1.08, P < 0.001; MESA, HR: 1.10, P = 0.001) and stroke (ARIC, HR: 1.06, P = 0.002; MESA, HR: 0.96, P = 0.37). Each additional SDOH correlated positively with MI (ARIC, HR: 1.04, P = 0.01; MESA, HR: 1.08, P = 0.003) and stroke in ARIC (HR: 1.08, P = 0.00) but not MESA (HR: 1.03, P = 0.41). Each additional LS7 point correlated negatively with MI (ARIC, HR: 0.88, P < 0.001; MESA, HR: 0.85, P < 0.001) and stroke (ARIC, HR: 0.91, P < 0.001; MESA, HR: 0.86, P < 0.001). Conclusions: SDOH and lifestyle factors associated with risk for MI and stroke but did not largely impact the association between Lp(a) and cardiovascular events.

Effect of Raloxifene Treatment on Apolipoproteins and Lipoprotein(a) Concentrations in Postmenopausal Women: A Meta-Analysis of Randomized Controlled Trials.

BACKGROUND AND AIM: Although various randomized controlled trials (RCTs) have evaluated the effect of raloxifene on apolipoproteins and lipoprotein(a) concentrations in postmenopausal women, the results have been inconsistent and inconclusive. Therefore, we conducted this meta-analysis of RCTs to investigate the effect of raloxifene administration on apolipoproteins and lipoprotein(a) [Lp(a)] concentrations in postmenopausal women. METHODS: Two independent researchers systematically searched the scientific literature (including PubMed/Medline, Scopus, Web of Science, and EMBASE) for English-language randomized controlled trials (RCTs) published up to June 2024. We included RCTs reporting the impact of raloxifene on apolipoprotein A-I (ApoA-I), apolipoprotein B (ApoB), and Lp(a) levels in postmenopausal women. The primary outcome of interest was change in Lp(a), and the secondary outcomes were changes in ApoA-I and ApoB. FINDINGS: The present meta-analysis incorporated 12 publications with 14 RCT arms. The comprehensive outcomes derived from the random-effects model revealed a statistically significant increase in ApoA-I (WMD: 6.06 mg/dL, 95% CI: 4.38, 7.75, P < 0.001) and decrease in ApoB concentrations (WMD: -8.48 mg/dL, 95% CI: -10.60, -6.36, P < 0.001) and Lp(a) (WMD: -3.02 mg/dL, 95% CI: -4.83, -1.21, P < 0.001) following the administration of raloxifene in postmenopausal women. In the subgroup analyses, the increase in ApoA-I and the decrease in ApoB and Lp(a) levels were greater in RCTs with a mean participant age of ≥60 years and a duration of ≤12 weeks. IMPLICATIONS: The current meta-analysis of RCTs demonstrates that treatment with raloxifene reduces ApoB and Lp(a) levels while increasing ApoA-I levels in postmenopausal women. Since these effects on lipid components are associated with a reduced risk of cardiovascular disease (CVD), raloxifene could be a suitable therapy for postmenopausal women who are at an increased risk of CVD and have other medical indications for raloxifene administration.

Lipoprotein (a) and the Occurrence of Lipid Disorders and Other Cardiovascular Risk Factors in Patients without Diagnosed Cardiovascular Disease.

Background: Elevated lipoprotein (a) [Lp(a)] concentrations are linked mainly to genetic factors. The relationship between Lp(a) and other lipid disorders or cardiovascular (CV) risk factors has been less investigated. The aim of this study was to assess the occurrence of lipid disorders and other CV risk factors according to Lp(a) concentrations. Methods: A cross-sectional analysis of 200 primary-care patients who had not been diagnosed with CV disease was conducted. The following risk factors were assessed: older age, history of hypertension, diabetes mellitus or dyslipidemia, smoking, lack of physical activity, body mass index (BMI), and waist circumference. The following lipid parameters were measured: total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), and small, dense LDL (sdLDL-C). Patients were divided into two groups based on their Lp(a) concentrations: <30 mg/dL and ≥30 mg/dL. Results: In 70% of patients, the Lp(a) concentration was <30 mg/dL. The concentrations of lipid parameters did not differ between the groups. The rate of patients with sdLDL-C >1.0 mmol/L was higher in the low-Lp(a) group (10.0 vs. 1.7%, p = 0.04), with no significant differences regarding the other analyzed lipid disorders (p > 0.05). Both in the low- and high-Lp(a) group, most patients had two other abnormal lipid factors (45.0% and 60.0%, respectively). The distribution of impaired lipid parameters (p = 0.41) and other CV risk factors (p = 0.16) was similar in both groups. There was a lower rate of patients >60 years old (15.0% vs. 32.9%, p = 0.01) and with a BMI ≥ 25 kg/m2 (46.7% vs. 63.6%, p = 0.026) in the high-Lp(a) group, and previously diagnosed hyperlipidemia was more prevalent in this group (65.0% vs. 47.1%, p = 0.02). The occurrence of other cardiovascular risk factors did not differ significantly between the Lp(a) groups (p > 0.05). In the high-Lp(a) group, the highest proportion (25.0%) had two CV risk factors, and in the low-Lp(a) group, 31.4% had four CV risk factors. Conclusions: An elevated Lp(a) concentration is not related to the number of conventional CV risk factors or other impairment major lipid parameters.