Circulating lipoprotein(a) levels and health outcomes: Phenome-wide Mendelian randomization and disease-trajectory analyses

Lipoprotein(a) and panvascular disease

Panvascular disease (PVD) is an emerging clinical concept that encompasses a spectrum of atherosclerotic conditions involving multiple major vascular beds, including the coronary, cerebral, peripheral, and valvular arteries. Although not formally recognized as a nosological entity, in this review, PVD is adopted as a conceptual framework to reflect the systemic nature of atherosclerosis affecting vascular territories supplying the heart, brain, and peripheral circulation. This perspective enables a more integrated understanding of disease processes across organ systems that are often studied in isolation. Lipoprotein(a) [Lp(a)] is a genetically regulated, low-density lipoprotein (LDL)-like particle that has garnered increasing attention as an independent pathogenic risk factor for PVD. Accumulating evidence from epidemiological, genetic, and mechanistic studies has confirmed the multifaceted role of Lp(a) in promoting atherogenesis, vascular calcification, inflammation, and thrombogenesis across multiple vascular beds. Elevated Lp(a) levels are associated with increased cardiovascular and cerebrovascular event risk, even after controlling for traditional risk factors. This review systematically outlines the structure, genetic determinants, and pathogenic mechanisms of Lp(a), and synthesizes current clinical evidence regarding its role in various PVD subtypes. The interactions between Lp(a) and traditional cardiovascular risk factors such as hypercholesterolemia, diabetes, and hypertension are explored in depth, highlighting their synergistic contributions to vascular injury and disease progression. Furthermore, sex-based differences in Lp(a)-associated risk, response to therapy, and biological behavior are discussed, providing insights into personalized cardiovascular risk stratification. In addition, the review summarizes current and emerging therapeutic strategies targeting Lp(a), including niacin, antisense oligonucleotides (ASOs), small interfering RNAs (siRNAs), and gene-editing technologies. These advances offer promising new avenues for reducing residual cardiovascular risk attributable to elevated Lp(a). In conclusion, viewing Lp(a)-associated pathology through the lens of PVD provides a comprehensive and unifying approach to understanding its systemic impact. This framework supports the development of integrated risk assessment tools and multi-targeted interventions, ultimately aiming to improve outcomes for patients with complex, multisite vascular involvement.

Prevalence of Elevated Lipoprotein(a) and its Association With Subclinical Atherosclerosis in 2.9 Million Chinese Adults

BACKGROUND

Elevated lipoprotein(a) [Lp(a)] is strongly associated with an increased risk of atherosclerotic cardiovascular disease; yet, large-scale studies on the epidemiology of elevated Lp(a) as well as its association with subclinical atherosclerosis in the Chinese population are limited.

OBJECTIVES

This study aimed to estimate the prevalence of elevated Lp(a) in a large check-up population of China, and investigate its associations with both site-specific and multisite subclinical atherosclerosis.

METHODS

Adults who underwent Lp(a) testing between 2017 and 2023 at Meinian health check-up centers in 30 provinces of China were included. Because the test results of Lp(a) were reported in either the mass unit (mg/dL) or the molar unit (nmol/L) and conversion between units was not recommended, separate analyses were conducted for each unit. Subclinical atherosclerosis was assessed using various imaging examinations at the carotid artery, the brain, and the coronary artery. The prevalence of elevated Lp(a) was estimated across the overall study population and various subpopulations. The logistic regression model was used to investigate the associations between elevated Lp(a) and subclinical atherosclerosis.

RESULTS

A total of 2,788,206 and 167,114 participants with the mass unit and the molar unit were included. In the mass unit group, the prevalence of Lp(a) >30 and >50 mg/dL was 18.67% and 8.41%, respectively. Significantly higher prevalence was observed among women, elderly individuals, and individuals with various cardio-renal-metabolic risk factors (all P < 0.05). Compared with Lp(a) ≤30 mg/dL, individuals with Lp(a) >30 to ∼50 mg/dL exhibited 11%, 15%, 9%, and 11% greater odds of increased carotid intima-media thickness, carotid plaque, subclinical brain infarcts, and coronary artery calcification, respectively. The odds were even higher for those with Lp(a) >50 mg/dL. Furthermore, elevated Lp(a) was significantly associated with the extent of coronary artery calcification, as well as subclinical atherosclerosis at 1, 2, and 3 sites, with the association being more pronounced in cases with severe extent and multisite involvement. These results were similar in the molar unit group.

CONCLUSIONS

A significant burden of elevated Lp(a) was found in China, highlighting the necessity of prioritized Lp(a) screening in high-risk groups. Elevated Lp(a) was identified as a significant risk factor for site-specific subclinical atherosclerosis, with stronger associations observed in severe extent and multisite involvement. Our findings suggest that individuals with elevated Lp(a) should undergo a comprehensive assessment of subclinical atherosclerosis at multiple sites to help prevent ASCVD.

Evidence for a causal link between lipoprotein (a) and mental disorders: A retrospective and Mendelian randomization study

STUDY OBJECTIVES

Lipoprotein (a) [Lp(a)] is a biomarker of atherosclerotic cardiovascular disease, but its role in mental disorders is controversial. Our study aimed to explore the causality between Lp(a) levels and mental disorders by combining retrospective and Mendelian randomization (MR) studies.

METHODS

All genome-wide association study datasets used in the MR study were obtained from UK Biobank, FinnGen, and the Psychiatric Genomics Consortium. The matched case-control study were based on electronic health records from the Second Affiliated Hospital of Nanchang University and NHANES III cohort.

RESULTS

In the MR analysis, Lp(a) had a positive causal effect on the longest period of depression [1.05 (1.02-1.08), P = 0.0001], the number of depressive episodes [1.03 (1.01-1.06), P = 0.009] and a weak negative effect on memory loss [0.84 (0.72-0.99), P = 0.039]. Meanwhile, bipolar and major depressive disorder status was causally associated with significantly lower Lp(a) levels [0.96 (0.93-0.98), P = 0.003]. Retrospective study revealed low Lp(a) levels were associated with a significantly higher risk of depression (n = 670) [1.273 (1.007, 1.609), P = 0.044], anxiety (n = 1284) [1.231 (1.041, 1.456), P = 0.015] and major depression (n = 538) [1.364 (1.012,1.841), P = 0.042].

CONCLUSIONS

This study found there is a causal relationship between the number and longest period of depressive episodes or memory loss and Lp(a), while bipolar disorder and major depressive disorder were associated with a significant causal effect on reduced Lp(a) levels. Future studies should focus on whether a sustained decrease in Lp(a) levels could cause the development of mental disorders, and which target value is suitable for clinical practice.

[The association between biological aging markers and valvular heart diseases]

OBJECTIVES

To analyze the association between biological aging markers (phenotypic age and phenotypic age acceleration) and valvular heart diseases.

METHODS

Research subjects who met the inclusion and exclusion criteria were selected from the UK Biobank from 2006 to 2010. The phenotypic age and phenotypic age acceleration were calculated. Cox multivariate analysis was used to examine the relationship between the aging markers and valvular heart diseases. Sensitivity analysis was conducted by removing missing values and subgroup analysis. The predictive accuracy of phenotypic age and phenotypic age acceleration for valvular heart diseases was analyzed using receiver operating characteristic (ROC) curves, and a clinical decision curve was generated based on logistic regression.

RESULTS

A total of 411 687 subjects were included in the study, among whom there were 14 258 patients with valvular heart diseases. The overall median follow-up time was 12.80 years, the median follow-up time for patients with non-rheumatic aortic valve diseases (n=5238), non-rheumatic mitral valve diseases (n=4558), and non-rheumatic tricuspid valve diseases (n=411) were 12.82 years, 12.83 years and 12.84 years, respectively. After adjusting for demographic factors (gender, race, education, Townsend deprivation index), anthropometric factors (body mass index), lifestyle factors (smoking, alcohol consumption, Dietary Approaches to Stop Hypertension score), hypertension and hyperlipidemia, Cox multivariate analysis showed phenotypic age and phenotypic age acceleration were independent risk factors for valvular heart diseases, including non-rheumatic aortic valve diseases, non-rheumatic mitral valve diseases, and non-rheumatic tricuspid valve diseases (phenotypic age: corrected HR=1.04, P<0.01; phenotypic age acceleration: corrected HR=1.03, P<0.01), which was also confirmed by sensitivity analysis. ROC curves and clinical decision curves demonstrated that compared with the phenotypic age acceleration, phenotypic age had higher accuracy (the areas and the curves were 0.721 and 0.599) and higher net benefit in predicting valvular heart diseases. Moreover, compared with a single indicator, the combination of the two indicators had higher accuracy (the area under the curve was 0.725) and higher net benefit.

CONCLUSIONS

Phenotypic age and phenotypic age acceleration,as markers of biological aging, are independent risk factors for valvular heart diseases. Compared with phenotypic age acceleration, phenotypic age has a greater advantage in predicting valvular heart diseases. Overall, the combination of the two indicators offers a more effective approach for predicting valvular heart diseases.

Living with Elevated Lipoprotein(a) Levels: The Experiences of Patients and Caregivers

Background

Elevated lipoprotein(a) (Lp[a]) is an inherited condition that increases cardiovascular disease (CVD) risk, independent of other factors, such as low-density lipoprotein C. Few attempts have been made to explore the life experiences of people with elevated Lp(a).

Objective

To explore the experiences of people living with or caring for a relative with elevated Lp(a).

Methods

Two multinational, virtual, interactive, moderated discussions of specific questions between people with elevated Lp(a) and relatives (caregivers), with experienced clinicians attending.

Results

Fifteen individuals with elevated Lp(a) and nine relatives took part in the virtual discussions. The most frequent reasons to measure Lp(a) levels were prior CVD events, eg, heart attacks, stroke, aortic valve diseases, or a family history of CVD events. Clinicians were often reluctant to measure Lp(a) levels as no effective treatment is available to people with elevated values. The most common interventions after confirmed elevated Lp(a) levels were lifestyle modifications and cholesterol-lowering medications to reduce overall CVD risk. A healthy lifestyle with diet and exercise was perceived as unsuccessful in managing overall CVD risk by 25% of people with elevated Lp(a) and 38% of relatives. Lifestyle advice was considered conflicting, unclear and inconsistent. Participants experienced elevated Lp(a) as an "invisible" disorder with very low awareness in the general population. Physicians' advice was often too superficial to meet patients' needs, putting insufficient emphasis on prevention and focusing on interventions after a CVD event.

Conclusion

Elevated Lp(a) was considered an "invisible" disorder with limited understanding among physicians and the general public. This reduces access to tests and shifts physician focus away from prevention towards reactive intervention.

Factorial Mendelian randomization of lipoprotein (a) lowering, low-density lipoprotein cholesterol lowering, and lifestyle improvements: joint associations with cardiovascular risk

BACKGROUND

High levels of lipoprotein(a) [Lp(a)] have been associated with an increased risk of cardiovascular disease (CVD); however, the effects of Lp(a)-lowering therapy in combination with low-density lipoprotein cholesterol (LDL-C)-lowering treatment or lifestyle improvements on CVD risk remain unexplored.

METHODS

We conducted a factorial Mendelian randomization study among 385 917 participants in the UK Biobank. Separate genetic scores were constructed to proxy the effects of Lp(a) lowering, LDL-C lowering through different targets [HMG-CoA reductase, NPC1-like intracellular cholesterol transporter 1, proprotein convertase subtilisin/kexin Type 9, and low-density lipoprotein receptor (LDLR)], as well as improvements in body mass index (BMI), systolic blood pressure (SBP), and lifestyle factors (cigarette smoking, alcohol consumption, and physical activity).

RESULTS

Genetically predicted lower Lp(a) levels were associated with a decreased risk of CVD and CVD-specific mortality. Per 50-mg/dl, the hazard ratio ranged from 0.73 [95% confidence interval (CI): 0.73, 0.73] for peripheral artery disease (PAD) to 0.95 (95% CI: 0.92, 0.99) for venous thromboembolism. In factorial analyses exploring combined exposure to low-level Lp(a) and low-level LDL-C, there was no consistent evidence for departure from an additive model for any outcome (Pinteraction > .05), with the exception of the analysis using the LDLR score and PAD (Pinteraction = .006). In factorial analyses exploring combination therapies integrating Lp(a) lowering with interventions on BMI, SBP, and lifestyle factors, there was no evidence for departure from an additive model in any analysis (Pinteraction > .05).

CONCLUSIONS

Our study suggests that Lp(a) lowering will have a similar magnitude for reducing cardiovascular events whether it is considered alone, or in conjunction with LDL-C reduction or lifestyle improvements.

Novel Genes Associated With Atrial Fibrillation and the Predictive Models for AF Incorporating Polygenic Risk Score and PheWAS-Derived Risk Factors

BACKGROUND

Atrial fibrillation (AF), the most common atrial arrhythmia, presents with varied clinical manifestations. Despite the identification of genetic loci associated with AF, particularly in specific populations, research within Asian ethnicities remains limited. In this study we aimed to develop predictive models for AF using AF-associated single-nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) on a substantial cohort of Taiwanese individuals, to evaluate the predictive efficacy of the model.

METHODS

There were 75,121 subjects, that included 5694 AF patients and 69,427 normal control subjects with GWAS data, and we merged polygenic risk scores from AF-associated SNPs with phenome-wide association study-derived risk factors. Advanced statistical and machine learning techniques were used to develop and evaluate AF predictive models for discrimination and calibration.

RESULTS

The study identified the top 30 significant SNPs associated with AF, predominantly on chromosomes 10 and 16, implicating genes like NEURL1, SH3PXD2A, INA, NT5C2, STN1, and ZFHX3. Notably, INA, NT5C2, and STN1 were newly linked to AF. The GWAS predictive power using polygenic risk score-continuous shrinkage analysis for AF exhibited an area under the curve of 0.600 (P < 0.001), which improved to 0.855 (P < 0.001) after adjusting for age and sex. Phenome-wide association study analysis showed the top 10 diseases associated with these genes were circulatory system diseases.

CONCLUSIONS

Integrating genetic and phenotypic data enhanced the accuracy and clinical relevance of AF predictive models. The findings suggest promise for refining AF risk assessment, enabling personalized interventions, and reducing AF-related morbidity and mortality burdens.

Low Concentration of Lipoprotein(a) is an Independent Predictor of Incident Type 2 Diabetes

The aim of the study was to assess the association between lipoprotein(a) [Lp(a)] concentration and incident type 2 diabetes. A meta-analysis of qualified studies on the relationship of low levels of Lp(a) concentration with incident type 2 diabetes was conducted. PubMed and Cochrane libraries were searched for randomized controlled trials containing data on events. Seven randomized trials with 227178 subjects were included in this analysis. We found an inverse association of the levels of Lp(a) concentration with risk of type 2 diabetes with approximately 37% lower relative risk in the group with the highest concentration compared with group with the lowest concentration. The current available evidence from prospective studies suggests that there is an inverse association between the levels of Lp(a) concentration and risk of type 2 diabetes, with a higher risk of type 2 diabetes at low levels of Lp(a) concentration. Therefore, we believe that the low levels of Lp(a) concentration is an independent predictor of incident type 2 diabetes.

Assessing the relationship between lipoprotein(a) levels and blood pressure among hypertensive patients beyond conventional measures. An observational study

High lipoprotein(a) (Lp(a)) levels are associated with an increased risk of arterial hypertension (AHT) and atherosclerotic cardiovascular disease. However, little is known about the detailed profile of AHT based on Lp(a) levels. This observational study focused on elucidating the relationship between Lp(a) concentrations and specific indices obtained from 24-h ambulatory blood pressure (BP) monitoring in hypertensive patients over 18 years of age. We gathered and analyzed data on BP indices along with demographic, epidemiological, clinical, and laboratory variables from 227 hypertensive patients, median age 56 years, including 127 women (56%). After comparing hypertensive patients with Lp(a) levels above and below 125 nmol/L, we found that a 10 mmHg increase in nocturnal systolic BP and all pulse pressure indices (24-h, daytime, and night-time) was associated with an increased risk of high Lp(a) levels by more than 20% and 40%, respectively. Similarly, each 10% increase in the area under the function over time of nocturnal diastolic BP dipping was associated with more than a 30% decrease in the odds of belonging to the elevated Lp(a) levels category. Additionally, Lp(a) levels above 125 nmol/L were associated with higher 24-h, daytime, and night-time systolic BP and pulse pressure load. The relationship between Lp(a) and AHT appears to extend beyond conventional BP measurements, which may be relevant given the prognostic implications of nocturnal BP and pulse pressure indices.

Relationship Between Lipoprotein(a), Renal Function Indicators, and Chronic Kidney Disease: Evidence From a Large Prospective Cohort Study

BACKGROUND

Chronic kidney disease (CKD) poses a significant global public health challenge. While lipoprotein(a) (Lp[a]) has been established as a significant factor in cardiovascular disease, its connection to CKD risk remains a topic of debate. Existing evidence indicates diverse risks of kidney disease among individuals with various renal function indicators, even when within the normal range.

OBJECTIVE

This study aims to investigate the joint associations between different renal function indicators and Lp(a) regarding the risks of incident CKD in the general population.

METHODS

The analysis involved a cohort of 329,415 participants without prior CKD who were enrolled in the UK Biobank between 2006 and 2010. The participants, with an average age of 56 (SD 8.1) years, included 154,298/329,415 (46.84%) males. At baseline, Lp(a) levels were measured using an immunoturbidimetric assay and classified into 2 groups: low (<75 nmol/L) and high (≥75 nmol/L). To assess participants' baseline renal function, we used the baseline urine albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR). The relationship between Lp(a), renal function indicators, and the risk of CKD was evaluated using multivariable Cox regression models. These models were adjusted for various factors, including sociodemographic variables, lifestyle factors, comorbidities, and laboratory measures.

RESULTS

A total of 6003 incident CKD events were documented over a median follow-up period of 12.5 years. The association between elevated Lp(a) levels and CKD risk did not achieve statistical significance among all participants, with a hazard ratio (HR) of 1.05 and a 95% CI ranging from 0.98 to 1.13 (P=.16). However, a notable interaction was identified between Lp(a) and UACR in relation to CKD risk (P for interaction=.04), whereas no significant interaction was observed between Lp(a) and eGFR (P for interaction=.96). When compared with the reference group with low Lp(a) and low-normal UACR (<10 mg/g), the group with high Lp(a) and low-normal UACR exhibited a nonsignificant association with CKD risk (HR 0.98, 95% CI 0.90-1.08; P=.74). By contrast, both the low Lp(a) and high-normal UACR (≥10 mg/g) group (HR 1.16, 95% CI 1.08-1.24; P<.001) and the high Lp(a) and high-normal UACR group (HR 1.32, 95% CI 1.19-1.46; P<.001) demonstrated significant associations with increased CKD risks. In individuals with high-normal UACR, elevated Lp(a) was linked to a significant increase in CKD risk, with an HR of 1.14 and a 95% CI ranging from 1.03 to 1.26 (P=.01). Subgroup analyses and sensitivity analyses consistently produced results that were largely in line with the main findings.

CONCLUSIONS

The analysis revealed a significant interaction between Lp(a) and UACR in relation to CKD risk. This implies that Lp(a) may act as a risk factor for CKD even when considering UACR. Our findings have the potential to provide valuable insights into the assessment and prevention of CKD, emphasizing the combined impact of Lp(a) and UACR from a public health perspective within the general population. This could contribute to enhancing public awareness regarding the management of Lp(a) for the prevention of CKD.

Measuring lipoprotein(a) for cardiovascular disease prevention - in whom and when?

PURPOSE OF REVIEW

The aim of this study is to summarize major cardiovascular guideline recommendations on lipoprotein(a) and highlighting recent findings that emphasize how measuring lipoprotein(a) once in all adults is meaningful regardless of age, sex, comorbidities, or ethnicity.

RECENT FINDINGS

Many international guidelines now recommend once in a lifetime measurement of lipoprotein(a) in all adult individuals to facilitate accurate risk prediction. Lipoprotein(a)-lowering therapy to reduce cardiovascular disease is on the horizon, with results from the first phase 3 trial expected in 2025.

SUMMARY

Elevated lipoprotein(a) is an independent causal risk factor for atherosclerotic cardiovascular disease and aortic valve stenosis and measuring lipoprotein(a) once in all individuals regardless of age, sex, comorbidities, or ethnicity is meaningful to aid in risk stratification.

Inter-organ crosstalk during development and progression of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is characterized by tissue-specific insulin resistance and pancreatic β-cell dysfunction, which result from the interplay of local abnormalities within different tissues and systemic dysregulation of tissue crosstalk. The main local mechanisms comprise metabolic (lipid) signalling, altered mitochondrial metabolism with oxidative stress, endoplasmic reticulum stress and local inflammation. While the role of endocrine dysregulation in T2DM pathogenesis is well established, other forms of inter-organ crosstalk deserve closer investigation to better understand the multifactorial transition from normoglycaemia to hyperglycaemia. This narrative Review addresses the impact of certain tissue-specific messenger systems, such as metabolites, peptides and proteins and microRNAs, their secretion patterns and possible alternative transport mechanisms, such as extracellular vesicles (exosomes). The focus is on the effects of these messengers on distant organs during the development of T2DM and progression to its complications. Starting from the adipose tissue as a major organ relevant to T2DM pathophysiology, the discussion is expanded to other key tissues, such as skeletal muscle, liver, the endocrine pancreas and the intestine. Subsequently, this Review also sheds light on the potential of multimarker panels derived from these biomarkers and related multi-omics for the prediction of risk and progression of T2DM, novel diabetes mellitus subtypes and/or endotypes and T2DM-related complications.

Diet-Wide Association Study for the Incidence of Type 2 Diabetes Mellitus in Community-Dwelling Adults Using the UK Biobank Data

This longitudinal study used diet-wide association studies (DWAS) to investigate the association between diverse dietary food and nutrient intakes and the onset of type 2 diabetes mellitus (T2DM). Out of 502,505 participants from the UK Biobank, 119,040 with dietary data free of T2DM at the baseline were included, and 3241 developed T2DM during a median follow-up of 11.7 years. The DWAS analysis, which is based on Cox regression models, was used to analyse the associations between dietary food or nutrient intake factors and T2DM risk. The study found that 10 out of 225 dietary factors were significantly associated with the T2DM risk. Total alcohol (HR = 0.86, 0.85-0.92, p = 1.26 × 10-32), red wine (HR = 0.89, 0.88-0.94, p = 7.95 × 10-19), and fresh tomatoes (HR = 0.92, 0.89-0.94, p = 2.3 × 10-11) showed a negative association with T2DM risk, whereas sliced buttered bread exhibited a positive association. Additionally, 5 out of 21 nutrient intake variables revealed significant associations with the T2DM risk, with iron having the highest protective effect and starch as a risk factor. In conclusion, DWAS is an effective method for discovering novel associations when exploring numerous dietary variables simultaneously and could provide valuable insight into future dietary guidance for T2DM.

Mendelian randomization for cardiovascular diseases: principles and applications

Large-scale genome-wide association studies conducted over the last decade have uncovered numerous genetic variants associated with cardiometabolic traits and risk factors. These discoveries have enabled the Mendelian randomization (MR) design, which uses genetic variation as a natural experiment to improve causal inferences from observational data. By analogy with the random assignment of treatment in randomized controlled trials, the random segregation of genetic alleles when DNA is transmitted from parents to offspring at gamete formation is expected to reduce confounding in genetic associations. Mendelian randomization analyses make a set of assumptions that must hold for valid results. Provided that the assumptions are well justified for the genetic variants that are employed as instrumental variables, MR studies can inform on whether a putative risk factor likely has a causal effect on the disease or not. Mendelian randomization has been increasingly applied over recent years to predict the efficacy and safety of existing and novel drugs targeting cardiovascular risk factors and to explore the repurposing potential of available drugs. This review article describes the principles of the MR design and some applications in cardiovascular epidemiology.

Lipoprotein(a) in patients with breast cancer after chemotherapy: exploring potential strategies for cardioprotection

Developments in neoadjuvant and adjuvant chemotherapy (CHT) have led to an increase in the number of breast cancer survivors. The determination of an appropriate follow-up for these patients is of increasing importance. Deaths due to cardiovascular disease (CVD) are an important part of mortality in patients with breast cancer.This review suggests that chemotherapeutic agents may influence lipoprotein(a) (Lp(a)) concentrations in breast cancer survivors after CHT based on many convincing evidence from epidemiologic and observational researches. Usually, the higher the Lp(a) concentration, the higher the median risk of developing CVD. However, more clinical trial results are needed in the future to provide clear evidence of a possible causal relationship. This review also discuss the existing and emerging therapies for lowering Lp(a) concentrations in the clinical setting. Hormone replacement therapy, statins, proprotein convertase subtilisin/kexin-type 9 (PCSK9) inhibitors, Antisense oligonucleotides, small interfering RNA, etc. may reduce circulating Lp(a) or decrease the incidence of CVD.