A genome-wide association meta-analysis on lipoprotein (a) concentrations adjusted for apolipoprotein (a) isoforms

Elevated lipoprotein(a) levels: A crucial determinant of cardiovascular disease risk and target for emerging therapies

Cardiovascular disease (CVD) remains a significant global health challenge despite advancements in prevention and treatment. Elevated Lipoprotein(a) [Lp(a)] levels have emerged as a crucial risk factor for CVD and aortic stenosis, affecting approximately 20 of the global population. Research over the last decade has established Lp(a) as an independent genetic contributor to CVD and aortic stenosis, beginning with Kare Berg's discovery in 1963. This has led to extensive exploration of its molecular structure and pathogenic roles. Despite the unknown physiological function of Lp(a), studies have shed light on its metabolism, genetics, and involvement in atherosclerosis, inflammation, and thrombosis. Epidemiological evidence highlights the link between high Lp(a) levels and increased cardiovascular morbidity and mortality. Newly emerging therapies, including pelacarsen, zerlasiran, olpasiran, muvalaplin, and lepodisiran, show promise in significantly lowering Lp(a) levels, potentially transforming the management of cardiovascular disease. However, further research is essential to assess these novel therapies' long-term efficacy and safety, heralding a new era in cardiovascular disease prevention and treatment and providing hope for at-risk patients.

A Polynesian-specific SLC22A3 variant associates with low plasma lipoprotein(a) concentrations independent of apo(a) isoform size in males

Lipoprotein(a) (Lp(a)) is a low-density lipoprotein (LDL)-like particle in which the apolipoprotein B component is covalently linked to apolipoprotein(a) (apo(a)). Lp(a) is a well-established independent risk factor for cardiovascular diseases. Plasma Lp(a) concentrations vary enormously between individuals and ethnic groups. Several nucleotide polymorphisms in the SLC22A3 gene associate with Lp(a) concentration in people of different ethnicities. We investigated the association of a Polynesian-specific (Māori and Pacific peoples) SLC22A3 gene coding variant p.Thr44Met) with the plasma concentration of Lp(a) in a cohort of 302 healthy Polynesian males. An apo(a)-size independent assay assessed plasma Lp(a) concentrations; all other lipid and apolipoprotein concentrations were measured using standard laboratory techniques. Quantitative real-time polymerase chain reaction was used to determine apo(a) isoforms. The range of metabolic (HbA1c, blood pressure, and blood lipids) and blood lipid variables were similar between the non-carriers and carriers in age, ethnicity and BMI adjusted models. However, rs8187715 SLC22A3 variant was significantly associated with lower Lp(a) concentrations. Median Lp(a) concentration was 10.60 nmol/L (IQR: 5.40-41.00) in non-carrier group, and was 7.60 nmol/L (IQR: 5.50-12.10) in variant carrier group (P<0.05). Lp(a) concentration inversely correlated with apo(a) isoform size. After correction for apo(a) isoform size, metabolic parameters and ethnicity, the association between the SLC22A3 variant and plasma Lp(a) concentration remained. The present study is the first to identify the association of this gene variant and low plasma Lp(a) concentrations. This provides evidence for better guidance on ethnic specific cut-offs when defining 'elevated' and 'normal' plasma Lp(a) concentrations in clinical applications.

Abdominal aortic aneurysm and cardiometabolic traits share strong genetic susceptibility to lipid metabolism and inflammation

Abdominal aortic aneurysm has a high heritability and often co-occurs with other cardiometabolic disorders, suggesting shared genetic susceptibility. We investigate this commonality leveraging recent GWAS studies of abdominal aortic aneurysm and 32 cardiometabolic traits. We find significant genetic correlations between abdominal aortic aneurysm and 21 of the cardiometabolic traits investigated, including causal relationships with coronary artery disease, hypertension, lipid traits, and blood pressure. For each trait pair, we identify shared causal variants, genes, and pathways, revealing that cholesterol metabolism and inflammation are shared most prominently. Additionally, we show the tissue and cell type specificity in the shared signals, with strong enrichment across traits in the liver, arteries, adipose tissues, macrophages, adipocytes, and fibroblasts. Finally, we leverage drug-gene databases to identify several lipid-lowering drugs and antioxidants with high potential to treat abdominal aortic aneurysm with comorbidities. Our study provides insight into the shared genetic mechanism between abdominal aortic aneurysm and cardiometabolic traits, and identifies potential targets for pharmacological intervention.

Consensus on lipoprotein(a) of the Spanish Society of Arteriosclerosis. Literature review and recommendations for clinical practice

The irruption of lipoprotein(a) (Lp(a)) in the study of cardiovascular risk factors is perhaps, together with the discovery and use of proprotein convertase subtilisin/kexin type 9 (iPCSK9) inhibitor drugs, the greatest novelty in the field for decades. Lp(a) concentration (especially very high levels) has an undeniable association with certain cardiovascular complications, such as atherosclerotic vascular disease (AVD) and aortic stenosis. However, there are several current limitations to both establishing epidemiological associations and specific pharmacological treatment. Firstly, the measurement of Lp(a) is highly dependent on the test used, mainly because of the characteristics of the molecule. Secondly, Lp(a) concentration is more than 80% genetically determined, so that, unlike other cardiovascular risk factors, it cannot be regulated by lifestyle changes. Finally, although there are many promising clinical trials with specific drugs to reduce Lp(a), currently only iPCSK9 (limited for use because of its cost) significantly reduces Lp(a). However, and in line with other scientific societies, the SEA considers that, with the aim of increasing knowledge about the contribution of Lp(a) to cardiovascular risk, it is relevant to produce a document containing the current status of the subject, recommendations for the control of global cardiovascular risk in people with elevated Lp(a) and recommendations on the therapeutic approach to patients with elevated Lp(a).

Resolving intra-repeat variation in medically relevant VNTRs from short-read sequencing data using the cardiovascular risk gene LPA as a model

BACKGROUND

Variable number tandem repeats (VNTRs) are highly polymorphic DNA regions harboring many potentially disease-causing variants. However, VNTRs often appear unresolved ("dark") in variation databases due to their repetitive nature. One particularly complex and medically relevant VNTR is the KIV-2 VNTR located in the cardiovascular disease gene LPA which encompasses up to 70% of the coding sequence.

RESULTS

Using the highly complex LPA gene as a model, we develop a computational approach to resolve intra-repeat variation in VNTRs from largely available short-read sequencing data. We apply the approach to six protein-coding VNTRs in 2504 samples from the 1000 Genomes Project and developed an optimized method for the LPA KIV-2 VNTR that discriminates the confounding KIV-2 subtypes upfront. This results in an F1-score improvement of up to 2.1-fold compared to previously published strategies. Finally, we analyze the LPA VNTR in > 199,000 UK Biobank samples, detecting > 700 KIV-2 mutations. This approach successfully reveals new strong Lp(a)-lowering effects for KIV-2 variants, with protective effect against coronary artery disease, and also validated previous findings based on tagging SNPs.

CONCLUSIONS

Our approach paves the way for reliable variant detection in VNTRs at scale and we show that it is transferable to other dark regions, which will help unlock medical information hidden in VNTRs.

Initial decrease in the lipoprotein(a) level is a novel prognostic biomarker in patients with acute coronary syndrome

BACKGROUND

Lipoprotein(a) [Lp(a)] is a causal risk factor for atherosclerotic cardiovascular diseases; however, its role in acute coronary syndrome (ACS) remains unclear.

AIM

To investigate the hypothesis that the Lp(a) levels are altered by various conditions during the acute phase of ACS, resulting in subsequent cardiovascular events.

METHODS

From September 2009 to May 2016, 377 patients with ACS who underwent emergent coronary angiography, and 249 who completed ≥ 1000 d of follow-up were enrolled. Lp(a) levels were measured using an isoform-independent assay at each time point from before percutaneous coronary intervention (PCI) to 48 h after PCI. The primary endpoint was the occurrence of major adverse cardiac events (MACE; cardiac death, other vascular death, ACS, and non-cardiac vascular events).

RESULTS

The mean circulating Lp(a) level decreased significantly from pre-PCI (0 h) to 12 h after (19.0 mg/dL to 17.8 mg/dL, P < 0.001), and then increased significantly up to 48 h after (19.3 mg/dL, P < 0.001). The changes from 0 to 12 h [Lp(a)Δ0-12] significantly correlated with the basal levels of creatinine [Spearman's rank correlation coefficient (SRCC): -0.181, P < 0.01] and Lp(a) (SRCC: -0.306, P < 0.05). Among the tertiles classified according to Lp(a)Δ0-12, MACE was significantly more frequent in the lowest Lp(a)Δ0-12 group than in the remaining two tertile groups (66.2% vs 53.6%, P = 0.034). A multivariate analysis revealed that Lp(a)Δ0-12 [hazard ratio (HR): 0.96, 95% confidence interval (95%CI): 0.92-0.99] and basal creatinine (HR: 1.13, 95%CI: 1.05-1.22) were independent determinants of subsequent MACE.

CONCLUSION

Circulating Lp(a) levels in patients with ACS decreased significantly after emergent PCI, and a greater decrease was independently associated with a worse prognosis.

Genetics and Pathophysiological Mechanisms of Lipoprotein(a)-Associated Cardiovascular Risk

Elevated lipoprotein(a) is a genetically transmitted codominant trait that is an independent risk driver for cardiovascular disease. Lipoprotein(a) concentration is heavily influenced by genetic factors, including LPA kringle IV-2 domain size, single-nucleotide polymorphisms, and interleukin-1 genotypes. Apolipoprotein(a) is encoded by the LPA gene and contains 10 subtypes with a variable number of copies of kringle -2, resulting in >40 different apolipoprotein(a) isoform sizes. Genetic loci beyond LPA, such as APOE and APOH, have been shown to impact lipoprotein(a) levels. Lipoprotein(a) concentrations are generally 5% to 10% higher in women than men, and there is up to a 3-fold difference in median lipoprotein(a) concentrations between racial and ethnic populations. Nongenetic factors, including menopause, diet, and renal function, may also impact lipoprotein(a) concentration. Lipoprotein(a) levels are also influenced by inflammation since the LPA promoter contains an interleukin-6 response element; interleukin-6 released during the inflammatory response results in transient increases in plasma lipoprotein(a) levels. Screening can identify elevated lipoprotein(a) levels and facilitate intensive risk factor management. Several investigational, RNA-targeted agents have shown promising lipoprotein(a)-lowering effects in clinical studies, and large-scale lipoprotein(a) testing will be fundamental to identifying eligible patients should these agents become available. Lipoprotein(a) testing requires routine, nonfasting blood draws, making it convenient for patients. Herein, we discuss the genetic determinants of lipoprotein(a) levels, explore the pathophysiological mechanisms underlying the association between lipoprotein(a) and cardiovascular disease, and provide practical guidance for lipoprotein(a) testing.

Predicted deleterious variants in ABCA1, LPL, LPA and KIF6 are associated with statin response and adverse events in patients with familial hypercholesterolemia and disturb protein structure and stability

OBJECTIVES

This study explored the association of deleterious variants in pharmacodynamics (PD) genes with statin response and adverse effects in patients with familial hypercholesterolemia (FH) and analyzed their potential effects on protein structure and stability.

METHODS

Clinical and laboratory data were obtained from 144 adult FH patients treated with statins. A panel of 32 PD genes was analyzed by exon-targeted gene sequencing. Deleterious variants were identified using prediction algorithms and their structural effects were analyzed by molecular modeling studies.

RESULTS

A total of 102 variants were predicted as deleterious (83 missense, 8 stop-gain, 4 frameshift, 1 indel, 6 splicing). The variants ABCA1 rs769705621 (indel), LPA rs41267807 (p.Tyr2023Cys) and KIF6 rs20455 (p.Trp719Arg) were associated with reduced low-density lipoprotein cholesterol (LDLc) response to statins, and the LPL rs1801177 (p.Asp36Asn) with increased LDLc response (P < 0.05). LPA rs3124784 (p.Arg2016Cys) was predicted to increase statin response (P = 0.022), and ABCA1 rs769705621 to increase the risk of statin-related adverse events (SRAE) (P = 0.027). LPA p.Arg2016Cys and LPL p.Asn36Asp maintained interactions with solvent, LPA p.Tyr2023Cys reduced intramolecular interaction with Gln1987, and KIF6 p.Trp719Arg did not affect intramolecular interactions. DDMut analysis showed that LPA p.Arg2016Cys and p.Tyr2023Cys and LPL p.Asp36Asn caused energetically favorable changes, and KIF6 p.Trp719Arg resulted in unfavorable energetic changes, affecting protein stability.

CONCLUSION

Deleterious variants in ABCA1, LPA, LPL and KIF6 are associated with variability in LDLc response to statins, and ABCA1 rs769705621 is associated with SRAE risk in FH patients. Molecular modeling studies suggest that LPA p.Tyr2023Cys and KIF6 p.Trp719Arg disturb protein conformational structure and stability.

Generalizability of polygenic prediction models: how is the R2 defined on test data?

BACKGROUND

Polygenic risk scores (PRS) quantify an individual's genetic predisposition for different traits and are expected to play an increasingly important role in personalized medicine. A crucial challenge in clinical practice is the generalizability and transferability of PRS models to populations with different ancestries. When assessing the generalizability of PRS models for continuous traits, the R 2 is a commonly used measure to evaluate prediction accuracy. While the R 2 is a well-defined goodness-of-fit measure for statistical linear models, there exist different definitions for its application on test data, which complicates interpretation and comparison of results.

METHODS

Based on large-scale genotype data from the UK Biobank, we compare three definitions of the R 2 on test data for evaluating the generalizability of PRS models to different populations. Polygenic models for several phenotypes, including height, BMI and lipoprotein A, are derived based on training data with European ancestry using state-of-the-art regression methods and are evaluated on various test populations with different ancestries.

RESULTS

Our analysis shows that the choice of the R 2  definition can lead to considerably different results on test data, making the comparison of R 2  values from the literature problematic. While the definition as the squared correlation between predicted and observed phenotypes solely addresses the discriminative performance and always yields values between 0 and 1, definitions of the R 2 based on the mean squared prediction error (MSPE) with reference to intercept-only models assess both discrimination and calibration. These MSPE-based definitions can yield negative values indicating miscalibrated predictions for out-of-target populations. We argue that the choice of the most appropriate definition depends on the aim of PRS analysis - whether it primarily serves for risk stratification or also for individual phenotype prediction. Moreover, both correlation-based and MSPE-based definitions of R 2 can provide valuable complementary information.

CONCLUSIONS

Awareness of the different definitions of the R 2 on test data is necessary to facilitate the reporting and interpretation of results on PRS generalizability. It is recommended to explicitly state which definition was used when reporting R 2 values on test data. Further research is warranted to develop and evaluate well-calibrated polygenic models for diverse populations.

Functional interrogation of cellular Lp(a) uptake by genome-scale CRISPR screening

An elevated level of lipoprotein(a), or Lp(a), in the bloodstream has been causally linked to the development of atherosclerotic cardiovascular disease and calcific aortic valve stenosis. Steady state levels of circulating lipoproteins are modulated by their rate of clearance, but the identity of the Lp(a) uptake receptor(s) has been controversial. In this study, we performed a genome-scale CRISPR screen to functionally interrogate all potential Lp(a) uptake regulators in HuH7 cells. Strikingly, the top positive and negative regulators of Lp(a) uptake in our screen were LDLR and MYLIP, encoding the LDL receptor and its ubiquitin ligase IDOL, respectively. We also found a significant correlation for other genes with established roles in LDLR regulation. No other gene products, including those previously proposed as Lp(a) receptors, exhibited a significant effect on Lp(a) uptake in our screen. We validated the functional influence of LDLR expression on HuH7 Lp(a) uptake, confirmed in vitro binding between the LDLR extracellular domain and purified Lp(a), and detected an association between loss-of-function LDLR variants and increased circulating Lp(a) levels in the UK Biobank cohort. Together, our findings support a central role for the LDL receptor in mediating Lp(a) uptake by hepatocytes.

Novel Polygenic Risk Score and Established Clinical Risk Factors for Risk Estimation of Aortic Stenosis

Importance

Polygenic risk scores (PRSs) have proven to be as strong as or stronger than established clinical risk factors for many cardiovascular phenotypes. Whether this is true for aortic stenosis remains unknown.

Objective

To develop a novel aortic stenosis PRS and compare its aortic stenosis risk estimation to established clinical risk factors.

Design, Setting, and Participants

This was a longitudinal cohort study using data from the Million Veteran Program (MVP; 2011-2020), UK Biobank (2006-2010), and 6 Thrombolysis in Myocardial Infarction (TIMI) trials, including DECLARE-TIMI 58 (2013-2018), FOURIER (TIMI 59; 2013-2017), PEGASUS-TIMI 54 (2010-2014), SAVOR-TIMI 53 (2010-2013), SOLID-TIMI 52 (2009-2014), and ENGAGE AF-TIMI 48 (2008-2013), which were a mix of population-based and randomized clinical trials. Individuals from UK Biobank and the MVP meeting a previously validated case/control definition for aortic stenosis were included. All individuals from TIMI trials were included unless they had a documented preexisting aortic valve replacement. Analysis took place from January 2022 to December 2023.

Exposures

PRS for aortic stenosis (developed using data from MVP and validated in UK Biobank) and other previously validated cardiovascular PRSs, defined either as a continuous variable or as low (bottom 20%), intermediate, and high (top 20%), and clinical risk factors.

Main Outcomes

Aortic stenosis (defined using International Classification of Diseases or Current Procedural Terminology codes in UK Biobank and MVP or safety event data in the TIMI trials).

Results

The median (IQR) age in MVP was 67 (57-73) years, and 135 140 of 147 104 participants (92%) were male. The median (IQR) age in the TIMI trials was 66 (54-78) years, and 45 524 of 59 866 participants (71%) were male. The best aortic stenosis PRS incorporated 5 170 041 single-nucleotide variants and was associated with aortic stenosis in both the MVP testing sample (odds ratio, 1.41; 95% CI, 1.37-1.45 per 1 SD PRS; P = 4.6 × 10-116) and TIMI trials (hazard ratio, 1.44; 95% CI, 1.27-1.62 per 1 SD PRS; P = 3.2 × 10-9). Among genetic and clinical risk factors, the aortic stenosis PRS performed comparably to most risk factors besides age, and within a given age range, the combination of clinical and genetic risk factors was additive, providing a 3- to 4-fold increased gradient of risk of aortic stenosis. However, the addition of the aortic stenosis PRS to a model including clinical risk factors only improved risk discrimination of aortic stenosis by 0.01 to 0.02 (C index in MVP: 0.78 with clinical risk factors, 0.79 with risk factors and aortic stenosis PRS; C index in TIMI: 0.71 with clinical risk factors, 0.73 with risk factors and aortic stenosis PRS).

Conclusions

This study developed and validated 1 of the first aortic stenosis PRSs. While aortic stenosis genetic risk was independent from clinical risk factors and performed comparably to all other risk factors besides age, genetic risk resulted in only a small improvement in overall aortic stenosis risk discrimination beyond age and clinical risk factors. This work sets the stage for further development of an aortic stenosis PRS.

Lp(a) - an overlooked risk factor

Lipoprotein(a) (Lp(a)) is an increasingly discussed and studied risk factor for atherosclerotic cardiovascular disease and aortic valve stenosis. Many genetic and epidemiological studies support the important causal role that Lp(a) plays in the incidence of cardiovascular disease. Although dependent upon the threshold and unit of measurement of Lp(a), most estimates suggest between 20 and 30% of the world's population have elevated serum levels of Lp(a). Lp(a) levels are predominantly mediated by genetics and are not significantly modified by lifestyle interventions. Efforts are ongoing to develop effective pharmacotherapies to lower Lp(a) and to determine if lowering Lp(a) with these medications ultimately decreases the incidence of adverse cardiovascular events. In this review, the genetics and pathophysiological properties of Lp(a) will be discussed as well as the epidemiological data demonstrating its impact on the incidence of cardiovascular disease. Recommendations for screening and how to currently approach patients with elevated Lp(a) are also noted. Finally, the spectrum of pharmacotherapies under development for Lp(a) lowering is detailed.

Lipoprotein(a): from Causality to Treatment

PURPOSE OF REVIEW

This paper reviews the evidence why lipoprotein(a) (Lp(a)) is a causal risk factor for cardiovascular disease and how high Lp(a) concentrations should be managed now and with an outlook to the future.

REVIEW FINDINGS

No optimal and widely available animal models exist to study the causality of the association between Lp(a) and cardiovascular disease. This has been a major handicap for the entire field. However, genetic studies turned the page. Already in the early 1990s, the principle of Mendelian randomization studies was applied for the first time ever (even if they were not named so at that time). Genetic variants of the LPA gene such as the apolipoprotein(a) isoform size, the number and sum of kringle IV repeats and later single nucleotide polymorphisms are strongly associated with life-long exposure to high Lp(a) concentrations as well as cardiovascular outcomes. This evidence provided a basis for the development of specific Lp(a)-lowering drugs that are currently in clinical testing phase. Lp(a) is one of the most important genetically determined risk factors for cardiovascular disease. With the specific Lp(a)-lowering therapies, we might get tools to fight this common risk factor in case the outcome trials will be positive.

Consideration and Application of Lipoprotein(a) in the Risk Assessment of Atherosclerotic Cardiovascular Disease Risk in Adults

Lipoprotein(a) (Lp[a]) is an low-density lipoprotein (LDL)-like particle in which apolipoprotein (apo) B is covalently bound to a plasminogen-like molecule called apo(a). A High level of Lp(a) has been demonstrated to be an independent, causal, and prevalent risk factor for atherosclerotic cardiovascular disease (ASCVD), as well as aortic valve disease, through mechanisms that promote atherogenesis, inflammation, and thrombosis. With reliable and accessible assays, Lp(a) level has been established to be associated linearly with the risk for ASCVD. The 2021 Canadian Cardiovascular Society Dyslipidemia Guidelines recommend measuring an Lp(a) level once in a person's lifetime as part of the initial lipid screening. The aim of this review is to provide an update and overview of the utility and application of Lp(a) level in the assessment and treatment of adults at risk for ASCVD, consistent with this guideline recommendation.

Is inverse association between lipoprotein(a) and diabetes mellitus another paradox in cardiometabolic medicine?

INTRODUCTION

The impact of Type II Diabetes mellitus (T2DM) on cardiovascular disease (CVD) is well-established, while lipoprotein(a) [Lp(a)] has recently emerged as a recognized CVD risk factor. The rising prevalence of T2DM resulting from modern lifestyles and the development of specific Lp(a)-lowering agents brought the association between T2DM and Lp(a) in the forefront.

AREAS COVERED

Despite advancements in T2DM treatment, diabetic patients remain at very-high risk of CVD. Lp(a) may, to some extent, contribute to the persistent CVD risk seen in diabetic patients, and the coexistence of T2DM and elevated Lp(a) levels appears to synergistically amplify overall CVD risk. The relationship between T2DM and Lp(a) is paradoxical. On one hand, high Lp(a) plasma concentrations elevate the risk of diabetic microvascular and macrovascular complications. On the other hand, low Lp(a) plasma concentrations have been linked to an increased risk of developing T2DM.

EXPERT OPINION

Comprehending the association between T2DM and Lp(a) is critical due to the pivotal roles both entities play in overall CVD risk, as well as the unique aspects of their relationship. The mechanisms underlying the inverse association between T2DM and Lp(a) remain incompletely understood, necessitating further meticulous research.

Consensus document on Lipoprotein(a) from the Italian Society for the Study of Atherosclerosis (SISA)

AIMS

In view of the consolidating evidence on the causal role of Lp(a) in cardiovascular disease, the Italian Society for the Study of Atherosclerosis (SISA) has assembled a consensus on Lp(a) genetics and epidemiology, together with recommendations for its measurement and current and emerging therapeutic approaches to reduce its plasma levels. Data on the Italian population are also provided.

DATA SYNTHESIS

Lp(a) is constituted by one apo(a) molecule and a lipoprotein closely resembling to a low-density lipoprotein (LDL). Its similarity with an LDL, together with its ability to carry oxidized phospholipids are considered the two main features making Lp(a) harmful for cardiovascular health. Plasma Lp(a) concentrations vary over about 1000 folds in humans and are genetically determined, thus they are quite stable in any individual. Mendelian Randomization studies have suggested a causal role of Lp(a) in atherosclerotic cardiovascular disease (ASCVD) and aortic valve stenosis and observational studies indicate a linear direct correlation between cardiovascular disease and Lp(a) plasma levels. Lp(a) measurement is strongly recommended once in a patient's lifetime, particularly in FH subjects, but also as part of the initial lipid screening to assess cardiovascular risk. The apo(a) size polymorphism represents a challenge for Lp(a) measurement in plasma, but new strategies are overcoming these difficulties. A reduction of Lp(a) levels can be currently attained only by plasma apheresis and, moderately, with PCSK9 inhibitor treatment.

CONCLUSIONS

Awaiting the approval of selective Lp(a)-lowering drugs, an intensive management of the other risk factors for individuals with elevated Lp(a) levels is strongly recommended.

Lipoprotein(a) as a Risk Factor for Cardiovascular Diseases: Pathophysiology and Treatment Perspectives

Cardiovascular disease (CVD) is still a leading cause of morbidity and mortality, despite all the progress achieved as regards to both prevention and treatment. Having high levels of lipoprotein(a) [Lp(a)] is a risk factor for cardiovascular disease that operates independently. It can increase the risk of developing cardiovascular disease even when LDL cholesterol (LDL-C) levels are within the recommended range, which is referred to as residual cardiovascular risk. Lp(a) is an LDL-like particle present in human plasma, in which a large plasminogen-like glycoprotein, apolipoprotein(a) [Apo(a)], is covalently bound to Apo B100 via one disulfide bridge. Apo(a) contains one plasminogen-like kringle V structure, a variable number of plasminogen-like kringle IV structures (types 1-10), and one inactive protease region. There is a large inter-individual variation of plasma concentrations of Lp(a), mainly ascribable to genetic variants in the Lp(a) gene: in the general po-pulation, Lp(a) levels can range from <1 mg/dL to >1000 mg/dL. Concentrations also vary between different ethnicities. Lp(a) has been established as one of the risk factors that play an important role in the development of atherosclerotic plaque. Indeed, high concentrations of Lp(a) have been related to a greater risk of ischemic CVD, aortic valve stenosis, and heart failure. The threshold value has been set at 50 mg/dL, but the risk may increase already at levels above 30 mg/dL. Although there is a well-established and strong link between high Lp(a) levels and coronary as well as cerebrovascular disease, the evidence regarding incident peripheral arterial disease and carotid atherosclerosis is not as conclusive. Because lifestyle changes and standard lipid-lowering treatments, such as statins, niacin, and cholesteryl ester transfer protein inhibitors, are not highly effective in reducing Lp(a) levels, there is increased interest in developing new drugs that can address this issue. PCSK9 inhibitors seem to be capable of reducing Lp(a) levels by 25-30%. Mipomersen decreases Lp(a) levels by 25-40%, but its use is burdened with important side effects. At the current time, the most effective and tolerated treatment for patients with a high Lp(a) plasma level is apheresis, while antisense oligonucleotides, small interfering RNAs, and microRNAs, which reduce Lp(a) levels by targeting RNA molecules and regulating gene expression as well as protein production levels, are the most widely explored and promising perspectives. The aim of this review is to provide an update on the current state of the art with regard to Lp(a) pathophysiological mechanisms, focusing on the most effective strategies for lowering Lp(a), including new emerging alternative therapies. The purpose of this manuscript is to improve the management of hyperlipoproteinemia(a) in order to achieve better control of the residual cardiovascular risk, which remains unacceptably high.

Daring to dream: Targeting lipoprotein(a) as a causal and risk-enhancing factor

Lipoprotein(a) [Lp(a)], a distinct lipoprotein class, has become a major focus for cardiovascular research. This review is written in light of the recent guideline and consensus statements on Lp(a) and focuses on 1) the causal association between Lp(a) and cardiovascular outcomes, 2) the potential mechanisms by which elevated Lp(a) contributes to cardiovascular diseases, 3) the metabolic insights on the production and clearance of Lp(a) and 4) the current and future therapeutic approaches to lower Lp(a) concentrations. The concentrations of Lp(a) are under strict genetic control. There exists a continuous relationship between the Lp(a) concentrations and risk for various endpoints of atherosclerotic cardiovascular disease (ASCVD). One in five people in the Caucasian population is considered to have increased Lp(a) concentrations; the prevalence of elevated Lp(a) is even higher in black populations. This makes Lp(a) a cardiovascular risk factor of major public health relevance. Besides the association between Lp(a) and myocardial infarction, the relationship with aortic valve stenosis has become a major focus of research during the last decade. Genetic studies provided strong support for a causal association between Lp(a) and cardiovascular outcomes: carriers of genetic variants associated with lifelong increased Lp(a) concentration are significantly more frequent in patients with ASCVD. This has triggered the development of drugs that can specifically lower Lp(a) concentrations: mRNA-targeting therapies such as anti-sense oligonucleotide (ASO) therapies and short interfering RNA (siRNA) therapies have opened new avenues to lower Lp(a) concentrations more than 95%. Ongoing Phase II and III clinical trials of these compounds are discussed in this review.

Lipoprotein(a) in clinical practice: A guide for the clinician

Cardiovascular disease (CVD) remains the leading cause of death worldwide. Serum lipoprotein(a) (Lp(a)) has been shown to be an independent and causative risk factor for atherosclerotic CVD and calcific aortic valvular disease. Lp(a) continues to be studied, with emerging insights into the epidemiology of CVD with respect to Lp(a), pathogenic mechanisms of Lp(a) and strategies to mitigate disease. There have been novel insights into genetic polymorphisms of the LPA gene, interactions between concomitant risk factors and Lp(a) based on real-world data, and metabolic pathway targets for Lp(a) reduction. This review highlights these recent advances in our understanding of Lp(a) and discusses management strategies as recommended by cardiovascular professional societies, emerging therapies for lowering Lp(a), and future directions in targeting Lp(a) to reduce CVD.

Lipid-Associated GWAS Loci Predict Antiatherogenic Effects of Rosuvastatin in Patients with Coronary Artery Disease

We have shown that lipid-associated loci discovered by genome-wide association studies (GWAS) have pleiotropic effects on lipid metabolism, carotid intima-media thickness (CIMT), and CAD risk. Here, we investigated the impact of lipid-associated GWAS loci on the efficacy of rosuvastatin therapy in terms of changes in plasma lipid levels and CIMT. The study comprised 116 CAD patients with hypercholesterolemia. CIMT, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) were measured at baseline and after 6 and 12 months of follow-up, respectively. Genotyping of fifteen lipid-associated GWAS loci was performed by the MassArray-4 System. Linear regression analysis adjusted for sex, age, body mass index, and rosuvastatin dose was used to estimate the phenotypic effects of polymorphisms, and p-values were calculated through adaptive permutation tests by the PLINK software, v1.9. Over one-year rosuvastatin therapy, a decrease in CIMT was linked to rs1689800, rs4846914, rs12328675, rs55730499, rs9987289, rs11220463, rs16942887, and rs881844 polymorphisms (Pperm < 0.05). TC change was associated with rs55730499, rs11220463, and rs6065906; LDL-C change was linked to the rs55730499, rs1689800, and rs16942887 polymorphisms; and TG change was linked to polymorphisms rs838880 and rs1883025 (Pperm < 0.05). In conclusion, polymorphisms rs1689800, rs55730499, rs11220463, and rs16942887 were found to be predictive markers for multiple antiatherogenic effects of rosuvastatin in CAD patients.

Lack of significant associations between single nucleotide polymorphisms in LPAL2-LPA genetic region and all cancer incidence and mortality in Japanese population: The Japan public health center-based prospective study

BACKGROUND

High lipoprotein (a) level is an established cardiovascular risk, but its association with non-cardiovascular diseases, especially cancer, is controversial. Serum lipoprotein (a) levels vary widely by genetic backgrounds and are largely determined by the genetic variations of apolipoprotein (a) gene, LPA. In this study, we investigate the association between SNPs in LPA region and cancer incidence and mortality in Japanese.

METHODS

A genetic cohort study was conducted utilizing the data from 9923 participants in the Japan Public Health Center-based Prospective Study (JPHC Study). Twenty-five SNPs in the LPAL2-LPA region were selected from the genome-wide genotyped data. Cox regression analysis adjusted for the covariates and competing risks of death from other causes, were used to estimate the relative risk (hazard ratios (HR) with 95% confidence intervals (CI)) of overall and site-specific cancer incidence and mortality, for each SNP.

RESULTS

No significant association was found between SNPs in the LPAL2-LPA region and cancer incidence or mortality (overall/site-specific cancer). In men, however, HRs for stomach cancer incidence of 18SNPs were estimated higher than 1.5 (e.g., 2.15 for rs13202636, model free, 95%CI: 1.28-3.62) and those for stomach cancer mortality of 2SNPs (rs9365171, rs1367211) were estimated 2.13 (recessive, 95%CI:1.04-4.37) and 1.61 (additive, 95%CI: 1.00-2.59). Additionally, the minor allele for SNP rs3798220 showed increased death risk from colorectal cancer (CRC) in men (HR: 3.29, 95% CI:1.59 - 6.81) and decreased CRC incidence risk in women (HR: 0.46, 95%CI: 0.22-0.94). Minor allele carrier of any of 4SNPs could have risk of prostate cancer incidence (e.g., rs9365171 dominant, HR: 1.71, 95%CI: 1.06-2.77).

CONCLUSIONS

None of the 25 SNPs in the LPAL2-LPA region was found to be significantly associated with cancer incidence or mortality. Considering the possible association between SNPs in LPAL2-LPA region and colorectal, prostate and stomach cancer incidence or mortality, further analysis using different cohorts is warranted.

Frequent questions and responses on the 2022 lipoprotein(a) consensus statement of the European Atherosclerosis Society

In 2022, the European Atherosclerosis Society (EAS) published a new consensus statement on lipoprotein(a) [Lp(a)], summarizing current knowledge about its causal association with atherosclerotic cardiovascular disease (ASCVD) and aortic stenosis. One of the novelties of this statement is a new risk calculator showing how Lp(a) influences lifetime risk for ASCVD and that global risk may be underestimated substantially in individuals with high or very high Lp(a) concentration. The statement also provides practical advice on how knowledge about Lp(a) concentration can be used to modulate risk factor management, given that specific and highly effective mRNA-targeted Lp(a)-lowering therapies are still in clinical development. This advice counters the attitude: "Why should I measure Lp(a) if I can't lower it?". Subsequent to publication, questions have arisen relating to how the recommendations of this statement impact everyday clinical practice and ASCVD management. This review addresses 30 of the most frequently asked questions about Lp(a) epidemiology, its contribution to cardiovascular risk, Lp(a) measurement, risk factor management and existing therapeutic options.

Supporting evidence for lipoprotein(a) measurements in clinical practice

High levels of lipoprotein(a) [Lp(a)] are causal for development of atherosclerotic cardiovascular disease and highly regulated by genetics. Levels are higher in Blacks compared to Whites, and in women compared to men. Lp(a)'s main protein components are apolipoprotein (apo) (a) and apoB100, the latter being the main component of Low-Density Lipoprotein (LDL) particles. Studies have identified Lp(a) to be associated with inflammatory, coagulation and wound healing pathways. Lack of validated and accepted assays to measure Lp(a), risk cutoff values, guidelines for diagnosis, and targeted therapies have added challenges to the field. Scientific efforts are ongoing to address these, including studies evaluating the cardiovascular benefits of decreasing Lp(a) levels with targeted apo(a) lowering treatments. This review will provide a synopsis of evidence-based effects of high Lp(a) on disease presentation, highlight available guidelines and discuss promising therapies in development. We will conclude with current clinical information and future research needs in the field.

Relationship of apolipoprotein(a) isoform size with clearance and production of lipoprotein(a) in a diverse cohort

Lipoprotein(a) [Lp(a)] has two main proteins, apoB100 and apo(a). High levels of Lp(a) confer an increased risk for atherosclerotic cardiovascular disease. Most people have two circulating isoforms of apo(a) differing in their molecular mass, determined by the number of Kringle IV Type 2 repeats. Previous studies report a strong inverse relationship between Lp(a) levels and apo(a) isoform sizes. The roles of Lp(a) production and fractional clearance and how ancestry affects this relationship remain incompletely defined. We therefore examined the relationships of apo(a) size with Lp(a) levels and both apo(a) fractional clearance rates (FCR) and production rates (PR) in 32 individuals not on lipid-lowering treatment. We determined plasma Lp(a) levels and apo(a) isoform sizes, and used the relative expression of the two isoforms to calculate a "weighted isoform size" (wIS). Stable isotope studies were performed, using D3-leucine, to determine the apo(a) FCR and PR. As expected, plasma Lp(a) concentrations were inversely correlated with wIS (R2 = 0.27; P = 0.002). The wIS had a modest positive correlation with apo(a) FCR (R2 = 0.10, P = 0.08), and a negative correlation with apo(a) PR (R2 = 0.11; P = 0.06). The relationship between wIS and PR became significant when we controlled for self-reported race and ethnicity (SRRE) (R2 = 0.24, P = 0.03); controlling for SRRE did not affect the relationship between wIS and FCR. Apo(a) wIS plays a role in both FCR and PR; however, adjusting for SRRE strengthens the correlation between wIS and PR, suggesting an effect of ancestry.

Lipoprotein(a): Cardiovascular Disease, Aortic Stenosis and New Therapeutic Option

Atherosclerosis is a chronic and progressive inflammatory process beginning early in life with late clinical manifestation. This slow pathological trend underlines the importance to early identify high-risk patients and to treat intensively risk factors to prevent the onset and/or the progression of atherosclerotic lesions. In addition to the common Cardiovascular (CV) risk factors, new markers able to increase the risk of CV disease have been identified. Among them, high levels of Lipoprotein(a)-Lp(a)-lead to very high risk of future CV diseases; this relationship has been well demonstrated in epidemiological, mendelian randomization and genome-wide association studies as well as in meta-analyses. Recently, new aspects have been identified, such as its association with aortic stenosis. Although till recent years it has been considered an unmodifiable risk factor, specific drugs have been developed with a strong efficacy in reducing the circulating levels of Lp(a) and their capacity to reduce subsequent CV events is under testing in ongoing trials. In this paper we will review all these aspects: from the synthesis, clearance and measurement of Lp(a), through the findings that examine its association with CV diseases and aortic stenosis to the new therapeutic options that will be available in the next years.

Consensus and guidelines on lipoprotein(a) - seeing the forest through the trees

PURPOSE OF THE REVIEW

Over the past decade, lipoprotein(a) [Lp(a)] made it to several consensus and guideline documents. This review aims to summarize the literature which underlies the various recommendations and compares recent European and North American consensus and guideline documents of the recent 3-4 years.

RECENT FINDINGS

Multiple large epidemiological and genetic studies have provided strong evidence for a causal association between Lp(a) concentrations and atherosclerotic cardiovascular disease (ASCVD) and aortic valve stenosis. There is a dose-dependent linear relationship between Lp(a) and ASCVD risk advocating to consider Lp(a) on a continuous scale rather than using thresholds. The best way to implement this in the clinic is by individualizing the Lp(a)-related risk using tools such as the 'Lp(a) risk calculator' ( http://www.lpaclinicalguidance.com ) that takes into account the Lp(a) level in the context of an individual's traditional risk factors and global risk for ASCVD. There is growing agreement across the guidelines regarding the clinical utility of measuring Lp(a) and more recent expert groups advocate for a general screening approach applied to all adults. As long as the cardiovascular outcomes trials for specific Lp(a)-lowering drugs are in progress, the current management of patients with high Lp(a) should focus on the comprehensive management of all other modifiable ASCVD risk factors which can be therapeutically addressed as per guideline recommendations.

SUMMARY

Since the contribution of high Lp(a) concentrations to global ASCVD risk has been underestimated in the past, a clear recommendation to measure Lp(a) at least once in a person's lifetime is imperative. Recent expert consensus recommendations provide clinicians with direction on how to manage the excess risk associated with elevated Lp(a) concentration by comprehensive and individualized management of modifiable ASCVD risk factors while awaiting the results of clinical trials of Lp(a) targeted therapies.

Lipoprotein(a) in atherosclerotic cardiovascular disease and aortic stenosis: a European Atherosclerosis Society consensus statement

This 2022 European Atherosclerosis Society lipoprotein(a) [Lp(a)] consensus statement updates evidence for the role of Lp(a) in atherosclerotic cardiovascular disease (ASCVD) and aortic valve stenosis, provides clinical guidance for testing and treating elevated Lp(a) levels, and considers its inclusion in global risk estimation. Epidemiologic and genetic studies involving hundreds of thousands of individuals strongly support a causal and continuous association between Lp(a) concentration and cardiovascular outcomes in different ethnicities; elevated Lp(a) is a risk factor even at very low levels of low-density lipoprotein cholesterol. High Lp(a) is associated with both microcalcification and macrocalcification of the aortic valve. Current findings do not support Lp(a) as a risk factor for venous thrombotic events and impaired fibrinolysis. Very low Lp(a) levels may associate with increased risk of diabetes mellitus meriting further study. Lp(a) has pro-inflammatory and pro-atherosclerotic properties, which may partly relate to the oxidized phospholipids carried by Lp(a). This panel recommends testing Lp(a) concentration at least once in adults; cascade testing has potential value in familial hypercholesterolaemia, or with family or personal history of (very) high Lp(a) or premature ASCVD. Without specific Lp(a)-lowering therapies, early intensive risk factor management is recommended, targeted according to global cardiovascular risk and Lp(a) level. Lipoprotein apheresis is an option for very high Lp(a) with progressive cardiovascular disease despite optimal management of risk factors. In conclusion, this statement reinforces evidence for Lp(a) as a causal risk factor for cardiovascular outcomes. Trials of specific Lp(a)-lowering treatments are critical to confirm clinical benefit for cardiovascular disease and aortic valve stenosis.

Independent Effects of Kidney Function and Cholesterol Efflux on Cardiovascular Mortality

Background: Impaired renal function is associated with cardiovascular and all-cause mortality. In the general population, HDL-cholesterol is associated with cardiovascular events, which is not true in patients with chronic kidney disease (CKD). This has been attributed to abnormal HDL function in CKD. Methods: In this study, we analyzed the association of genetic markers for kidney function with cholesterol efflux capacity as one of the major HDL functions, as well as with cardiovascular mortality, in 2469 patients of the Ludwigshafen Risk and Cardiovascular Health Study who all underwent coronary angiography. Results: A genetic score of 53 SNPs associated with GRF and the uromodulin SNP rs12917707 were inversely correlated with cholesterol efflux capacity. This was in line with the observed association between cholesterol efflux capacity and kidney function in these patients. Adjustment for eGFR and uromodulin as markers of kidney function did not affect the relationship between cholesterol efflux and cardiovascular mortality. Conclusions: Our data propose the view that cholesterol efflux and kidney function are exerting their effects on cardiovascular mortality via different and independent pathways. Decreased cholesterol efflux may therefore not mediate the effects of impaired kidney function on cardiovascular mortality.

Lipoprotein(a) in Cardiovascular Diseases: Insight From a Bibliometric Study

Lipoprotein(a) [Lp(a)] is a complex polymorphic lipoprotein comprised of a low-density lipoprotein particle with one molecule of apolipoprotein B100 and an additional apolipoprotein(a) connected through a disulfide bond. The serum concentration is mostly genetically determined and only modestly influenced by diet and other lifestyle modifications. In recent years it has garnered increasing attention due to its causal role in pre-mature atherosclerotic cardiovascular disease and calcific aortic valve stenosis, while novel effective therapeutic options are emerging [apolipoprotein(a) antisense oligonucleotides and ribonucleic acid interference therapy]. Bibliometric descriptive analysis and mapping of the research literature were made using Scopus built-in services. We focused on the distribution of documents, literature production dynamics, most prolific source titles, institutions, and countries. Additionally, we identified historical and influential papers using Reference Publication Year Spectrography (RPYS) and the CRExplorer software. An analysis of author keywords showed that Lp(a) was most intensively studied regarding inflammation, atherosclerosis, cardiovascular risk assessment, treatment options, and hormonal changes in post-menopausal women. The results provide a comprehensive view of the current Lp(a)-related literature with a specific interest in its role in calcific aortic valve stenosis and potential emerging pharmacological interventions. It will help the reader understand broader aspects of Lp(a) research and its translation into clinical practice.

Lipoprotein(a) measurement issues: Are we making a mountain out of a molehill?

Lipoprotein(a) [Lp(a)] became besides LDL cholesterol one of the most attractive targets for intervention in cardiovascular disease. Strong genetic evidence supports the causal association between high Lp(a) concentrations and cardiovascular outcomes. Since specific Lp(a)-lowering therapies are under clinical investigation, the interest in measuring Lp(a) has markedly increased. However, the special structure of the lead protein component of Lp(a), named apolipoprotein(a), creates difficulties for an accurate measurement of Lp(a). A highly homologous repetitive structure, called kringle IV repeat with up to more the 40 repeats, causes a highly polymorphic protein. Antibodies raised against apolipoprotein(a) are mostly directed against the repetitive structure of this protein, which complicates the measurement of Lp(a) in molar terms. Both measurements in mass (mg/dL) and molar terms (nmol/L) are described and a conversion from one into the another unit is only approximately possible. Working groups for standardization of Lp(a) measurements are going to prepare widely available and improved reference materials, which will be a major step for the measurement of Lp(a). This review discusses many aspects of the difficulties in measuring Lp(a). It tries to distinguish between academic and practical concerns and warns to make a mountain out of a molehill, which does no longer allow to see the patient behind that mountain by simply staring at the laboratory issues. On the other hand, the calibration of some assays raises major concerns, which are anything else but a molehill. This should be kept in mind and we should start measuring Lp(a) with the aim of a better risk stratification for the patient and to identify those patients who might be in urgent need for a specific Lp(a)-lowering therapy as soon as it becomes available.

Potential protective effect against SARS-CoV-2 infection by APOE rs7412 polymorphism

The pandemic burden caused by the SARS-CoV-2 coronavirus constitutes a global public health emergency. Increasing understanding about predisposing factors to infection and severity is now a priority. Genetic, metabolic, and environmental factors can play a crucial role in the course and clinical outcome of COVID-19. We aimed to investigate the putative relationship between genetic factors associated to obesity, metabolism and lifestyle, and the presence and severity of SARS-CoV-2 infection. A total of 249 volunteers (178 women and 71 men, with mean and ± SD age of 49 ± 11 years) characterized for dietary, lifestyle habits and anthropometry, were studied for presence and severity of COVID-19 infection, and genotyped for 26 genetic variants related to obesity, lipid profile, inflammation, and biorhythm patterns. A statistically significant association was found concerning a protective effect of APOE rs7412 against SARS-CoV-2 infection (p = 0.039; OR 0.216; CI 0.084, 0.557) after correction for multiple comparisons. This protective effect was also ascribed to the APOɛ2 allele (p = 0.001; OR 0.207; CI 0.0796, 0.538). The genetic variant rs7412 resulting in ApoE2, genetic determinant of lipid and lipoprotein levels, could play a significant role protecting against SARS-CoV-2 infection.

Lipoprotein(a) beyond the kringle IV repeat polymorphism: The complexity of genetic variation in the LPA gene

High lipoprotein(a) [Lp(a)] concentrations are one of the most important genetically determined risk factors for cardiovascular disease. Lp(a) concentrations are an enigmatic trait largely controlled by one single gene (LPA) that contains a complex interplay of several genetic elements with many surprising effects discussed in this review. A hypervariable coding copy number variation (the kringle IV type-2 repeat, KIV-2) generates >40 apolipoprotein(a) protein isoforms and determines the median Lp(a) concentrations. Carriers of small isoforms with up to 22 kringle IV domains have median Lp(a) concentrations up to 5 times higher than those with large isoforms (>22 kringle IV domains). The effect of the apo(a) isoforms are, however, modified by many functional single nucleotide polymorphisms (SNPs) distributed over the complete range of allele frequencies (<0.1% to >20%) with very pronounced effects on Lp(a) concentrations. A complex interaction is present between the apo (a) isoforms and LPA SNPs, with isoforms partially masking the effect of functional SNPs and, vice versa, SNPs lowering the Lp(a) concentrations of affected isoforms. This picture is further complicated by SNP-SNP interactions, a poorly understood role of other polymorphisms such as short tandem repeats and linkage structures that are poorly captured by common R² values. A further layer of complexity derives from recent findings that several functional SNPs are located in the KIV-2 repeat and are thus not accessible to conventional sequencing and genotyping technologies. A critical impact of the ancestry on correlation structures and baseline Lp(a) values becomes increasingly evident.

This review provides a comprehensive overview on the complex genetic architecture of the Lp(a) concentrations in plasma, a field that has made tremendous progress with the introduction of new technologies. Understanding the genetics of Lp(a) might be a key to many mysteries of Lp(a) and booster new ideas on the metabolism of Lp(a) and possible interventional targets.

Genome-Wide Characterization of a Highly Penetrant Form of Hyperlipoprotein(a)emia Associated With Genetically Elevated Cardiovascular Risk

Lp(a) (lipoprotein [a]) is a highly atherogenic lipoprotein strongly associated with coronary artery disease (CAD). Lp(a) concentrations are chiefly determined genetically. Investigation of large pedigrees with extreme Lp(a) using modern whole-genome approaches may unravel the genetic determinants underpinning this pathological phenotype.

Genetic and Mechanistic Insights into the Modulation of Circulating Lipoprotein (a) Concentration by Apolipoprotein E Isoforms

PURPOSE OF REVIEW

Lipoprotein (a) [Lp(a)] is a highly atherogenic lipoprotein species. A unique feature of Lp(a) is the strong genetic determination of its concentration. The LPA gene is responsible for up to 90% of the variance in Lp(a), but other genes also have an impact.

RECENT FINDINGS

Genome-wide associations studies indicate that the APOE gene, encoding apolipoprotein E (apoE), is the second most important locus modulating Lp(a) concentrations. Population studies clearly show that carriers of the apoE2 variant (ε2) display reduced Lp(a) levels, the lowest concentrations being observed in ε2/ε2 homozygotes. This genotype can lead predisposed adults to develop dysbetalipoproteinemia, a lipid disorder characterized by sharp elevations in cholesterol and triglycerides. However, dysbetalipoproteinemia does not significantly modulate circulating Lp(a). Mechanistically, apoE appears to impair the production but not the catabolism of Lp(a). These observations underline the complexity of Lp(a) metabolism and provide key insights into the pathways governing Lp(a) synthesis and secretion.

Cis-epistasis at the LPA locus and risk of cardiovascular diseases

AIMS

Coronary artery disease (CAD) has a strong genetic predisposition. However, despite substantial discoveries made by genome-wide association studies (GWAS), a large proportion of heritability awaits identification. Non-additive genetic effects might be responsible for part of the unaccounted genetic variance. Here, we attempted a proof-of-concept study to identify non-additive genetic effects, namely epistatic interactions, associated with CAD.

METHODS AND RESULTS

We tested for epistatic interactions in 10 CAD case-control studies and UK Biobank with focus on 8068 SNPs at 56 loci with known associations with CAD risk. We identified a SNP pair located in cis at the LPA locus, rs1800769 and rs9458001, to be jointly associated with risk for CAD [odds ratio (OR) = 1.37, P = 1.07 × 10-11], peripheral arterial disease (OR = 1.22, P = 2.32 × 10-4), aortic stenosis (OR = 1.47, P = 6.95 × 10-7), hepatic lipoprotein(a) (Lp(a)) transcript levels (beta = 0.39, P = 1.41 × 10-8), and Lp(a) serum levels (beta = 0.58, P = 8.7 × 10-32), while individual SNPs displayed no association. Further exploration of the LPA locus revealed a strong dependency of these associations on a rare variant, rs140570886, that was previously associated with Lp(a) levels. We confirmed increased CAD risk for heterozygous (relative OR = 1.46, P = 9.97 × 10-32) and individuals homozygous for the minor allele (relative OR = 1.77, P = 0.09) of rs140570886. Using forward model selection, we also show that epistatic interactions between rs140570886, rs9458001, and rs1800769 modulate the effects of the rs140570886 risk allele.

CONCLUSIONS

These results demonstrate the feasibility of a large-scale knowledge-based epistasis scan and provide rare evidence of an epistatic interaction in a complex human disease. We were directed to a variant (rs140570886) influencing risk through additive genetic as well as epistatic effects. In summary, this study provides deeper insights into the genetic architecture of a locus important for cardiovascular diseases.

Apolipoproteins in vascular biology and atherosclerotic disease

Apolipoproteins are important structural components of plasma lipoproteins that influence vascular biology and atherosclerotic disease pathophysiology by regulating lipoprotein metabolism. Clinically important apolipoproteins related to lipid metabolism and atherogenesis include apolipoprotein B-100, apolipoprotein B-48, apolipoprotein A-I, apolipoprotein C-II, apolipoprotein C-III, apolipoprotein E and apolipoprotein(a). Apolipoprotein B-100 is the major structural component of VLDL, IDL, LDL and lipoprotein(a). Apolipoprotein B-48 is a truncated isoform of apolipoprotein B-100 that forms the backbone of chylomicrons. Apolipoprotein A-I provides the scaffolding for lipidation of HDL and has an important role in reverse cholesterol transport. Apolipoproteins C-II, apolipoprotein C-III and apolipoprotein E are involved in triglyceride-rich lipoprotein metabolism. Apolipoprotein(a) covalently binds to apolipoprotein B-100 to form lipoprotein(a). In this Review, we discuss the mechanisms by which these apolipoproteins regulate lipoprotein metabolism and thereby influence vascular biology and atherosclerotic disease. Advances in the understanding of apolipoprotein biology and their translation into therapeutic agents to reduce the risk of cardiovascular disease are also highlighted.

Analyses of biomarker traits in diverse UK biobank participants identify associations missed by European-centric analysis strategies

Despite the dramatic underrepresentation of non-European populations in human genetics studies, researchers continue to exclude participants of non-European ancestry, as well as variants rare in European populations, even when these data are available. This practice perpetuates existing research disparities and can lead to important and large effect size associations being missed. Here, we conducted genome-wide association studies (GWAS) of 31 serum and urine biomarker quantitative traits in African (n = 9354), East Asian (n = 2559), and South Asian (n = 9823) ancestry UK Biobank (UKBB) participants. We adjusted for all known GWAS catalog variants for each trait, as well as novel signals identified in a recent European ancestry-focused analysis of UKBB participants. We identify 7 novel signals in African ancestry and 2 novel signals in South Asian ancestry participants (p < 1.61E-10). Many of these signals are highly plausible, including a cis pQTL for the gene encoding gamma-glutamyl transferase and PIEZO1 and G6PD variants with impacts on HbA1c through likely erythrocytic mechanisms. This work illustrates the importance of using the genetic data we already have in diverse populations, with novel discoveries possible in even modest sample sizes.

Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease

The study was designed to evaluate putative mechanisms by which lipid-associated loci identified by genome-wide association studies (GWAS) are involved in the molecular pathogenesis of coronary artery disease (CAD) using a comprehensive statistical and bioinformatics analysis. A total of 1700 unrelated individuals of Slavic origin from the Central Russia, including 991 CAD patients and 709 healthy controls were examined. Sixteen lipid-associated GWAS loci were selected from European studies and genotyped using the MassArray-4 system. The polymorphisms were associated with plasma lipids such as total cholesterol (rs12328675, rs4846914, rs55730499, and rs838880), LDL-cholesterol (rs3764261, rs55730499, rs1689800, and rs838880), HDL-cholesterol (rs3764261) as well as carotid intima-media thickness/CIMT (rs12328675, rs11220463, and rs1689800). Polymorphisms such as rs4420638 of APOC1 (p = 0.009), rs55730499 of LPA (p = 0.0007), rs3136441 of F2 (p < 0.0001), and rs6065906 of PLTP (p = 0.002) showed significant associations with the risk of CAD, regardless of sex, age, and body mass index. A majority of the observed associations were successfully replicated in large independent cohorts. Bioinformatics analysis allowed establishing (1) phenotype-specific and shared epistatic gene–gene and gene–smoking interactions contributing to all studied cardiovascular phenotypes; (2) lipid-associated GWAS loci might be allele-specific binding sites for transcription factors from gene regulatory networks controlling multifaceted molecular mechanisms of atherosclerosis.

Lipoprotein(a) and SARS-CoV-2 infections: Susceptibility to infections, ischemic heart disease and thromboembolic events

BACKGROUND

Comorbidities including ischemic heart disease (IHD) worsen outcomes after SARS-CoV-2 infections. High lipoprotein(a) [Lp(a)] concentrations are a strong risk factor for IHD and possibly for thromboembolic events. We therefore evaluated whether SARS-CoV-2 infections modify the risk of high Lp(a) concentrations for IHD or thromboembolic events during the first 8.5 months follow-up of the pandemic.

METHOD

Cohort study using data from the UK Biobank during the SARS-CoV-2 pandemic. Baseline Lp(a) was compared between SARS-CoV-2 positive patients and the population controls.

RESULTS

SARS-CoV-2 positive patients had Lp(a) concentrations similar to the population controls. The risk for IHD increased with higher Lp(a) concentrations in both, the population controls (n = 435,104) and SARS-CoV-2 positive patients (n = 6937). The causality of the findings was supported by a genetic risk score for Lp(a). A SARS-CoV-2 infection modified the association with a steeper increase in risk for infected patients (interaction p-value = 0.03). Although SARS-CoV-2 positive patients had a five-times higher frequency of thromboembolic events compared to the population controls (1.53% vs. 0.31%), the risk was not influenced by Lp(a).

CONCLUSIONS

SARS-CoV-2 infections enforce the association between high Lp(a) and IHD but the risk for thromboembolic events is not influenced by Lp(a).

Lipoprotein(a): A Genetically Determined, Causal, and Prevalent Risk Factor for Atherosclerotic Cardiovascular Disease: A Scientific Statement From the American Heart Association

High levels of lipoprotein(a) [Lp(a)], an apoB100-containing lipoprotein, are an independent and causal risk factor for atherosclerotic cardiovascular diseases through mechanisms associated with increased atherogenesis, inflammation, and thrombosis. Lp(a) is predominantly a monogenic cardiovascular risk determinant, with ≈70% to ≥90% of interindividual heterogeneity in levels being genetically determined. The 2 major protein components of Lp(a) particles are apoB100 and apolipoprotein(a). Lp(a) remains a risk factor for cardiovascular disease development even in the setting of effective reduction of plasma low-density lipoprotein cholesterol and apoB100. Despite its demonstrated contribution to atherosclerotic cardiovascular disease burden, we presently lack standardization and harmonization of assays, universal guidelines for diagnosing and providing risk assessment, and targeted treatments to lower Lp(a). There is a clinical need to understand the genetic and biological basis for variation in Lp(a) levels and its relationship to disease in different ancestry groups. This scientific statement capitalizes on the expertise of a diverse basic science and clinical workgroup to highlight the history, biology, pathophysiology, and emerging clinical evidence in the Lp(a) field. Herein, we address key knowledge gaps and future directions required to mitigate the atherosclerotic cardiovascular disease risk attributable to elevated Lp(a) levels.

The Variants at APOA1 and APOA4 Contribute to the Susceptibility of Schizophrenia With Inhibiting mRNA Expression in Peripheral Blood Leukocytes

Objective: Abnormal lipid metabolism has a close link to the pathophysiology of schizophrenia (SZ). This study mainly aimed to evaluate the association of variants at apolipoprotein A1 (APOA1) and APOA4 with SZ in a Chinese Han population.

Methods: The rs5072 of APOA1 and rs1268354 of APOA4 were examined in a case–control study involving 2,680 patients with SZ from the hospital and 2,223 healthy controls screened by physical examination from the community population. The association was estimated with the odds ratio (OR) and 95% confidence intervals (95% CIs) by logistic regression. The APOA1 and APOA4 messenger RNA (mRNA) in peripheral blood leukocytes were measured by real-time PCR and compared between SZ cases and controls. Serum apoA1 levels were detected by turbidimetric inhibition immunoassay and high-density lipoprotein cholesterol (HDL-C) levels were detected by the homogeneous method.

Results: Both of the rs5072 of APOA1 and rs1268354 of APOA4 had statistically significant associations with SZ. After adjustment for age and sex, ORs (95% CIs) of the additive model of rs5072 and rs1268354 were 0.82 (0.75–0.90) and 1.120 (1.03–1.23), and p-values were 3.22 × 10⁻⁵ and 0.011, respectively. The association of rs5072 with SZ still presented statistical significance even after Bonferroni correction (p-value×6). SZ patients during the episode presented lower levels of apoA1, HDL-C, mRNA of APOA1 common variants and transcript variant 4, and APOA4 mRNA than controls (p < 0.01) while SZ patients in remission showed a significantly decreased APOA1 transcript variant 3 expression level and increased APOA4 mRNA expression level (p < 0.01). mRNA expression levels of APOA1 transcript variant 4 significantly increased with the variations of rs5072 in SZ during the episode (p_trend = 0.017). After the SZ patients received an average of 27.50 ± 9.90 days of antipsychotic treatment, the median (interquartile) of serum apoA1 in the SZ episode significantly increased from 1.03 (1.00.1.20) g/L to 1.08 (1.00.1.22) g/L with the p-value of 0.044.

Conclusion: Our findings suggest that the genetic variations of APOA1 rs5072 and APOA4 rs1268354 contribute to the susceptibility of SZ, and the expression levels of APOA1 and APOA4 mRNA of peripheral blood leukocytes decreased in SZ patients during the episode while APOA4 increased after antipsychotic treatment.

Bayesian model comparison for rare-variant association studies

Whole-genome sequencing studies applied to large populations or biobanks with extensive phenotyping raise new analytic challenges. The need to consider many variants at a locus or group of genes simultaneously and the potential to study many correlated phenotypes with shared genetic architecture provide opportunities for discovery not addressed by the traditional one variant, one phenotype association study. Here, we introduce a Bayesian model comparison approach called MRP (multiple rare variants and phenotypes) for rare-variant association studies that considers correlation, scale, and direction of genetic effects across a group of genetic variants, phenotypes, and studies, requiring only summary statistic data. We apply our method to exome sequencing data (n = 184,698) across 2,019 traits from the UK Biobank, aggregating signals in genes. MRP demonstrates an ability to recover signals such as associations between PCSK9 and LDL cholesterol levels. We additionally find MRP effective in conducting meta-analyses in exome data. Non-biomarker findings include associations between MC1R and red hair color and skin color, IL17RA and monocyte count, and IQGAP2 and mean platelet volume. Finally, we apply MRP in a multi-phenotype setting; after clustering the 35 biomarker phenotypes based on genetic correlation estimates, we find that joint analysis of these phenotypes results in substantial power gains for gene-trait associations, such as in TNFRSF13B in one of the clusters containing diabetes- and lipid-related traits. Overall, we show that the MRP model comparison approach improves upon useful features from widely used meta-analysis approaches for rare-variant association analyses and prioritizes protective modifiers of disease risk.

Lipoprotein(a): Pathophysiology, measurement, indication and treatment in cardiovascular disease. A consensus statement from the Nouvelle Société Francophone d'Athérosclérose (NSFA)

Lipoprotein(a) is an apolipoprotein B100-containing low-density lipoprotein-like particle that is rich in cholesterol, and is associated with a second major protein, apolipoprotein(a). Apolipoprotein(a) possesses structural similarity to plasminogen but lacks fibrinolytic activity. As a consequence of its composite structure, lipoprotein(a) may: (1) elicit a prothrombotic/antifibrinolytic action favouring clot stability; and (2) enhance atherosclerosis progression via its propensity for retention in the arterial intima, with deposition of its cholesterol load at sites of plaque formation. Equally, lipoprotein(a) may induce inflammation and calcification in the aortic leaflet valve interstitium, leading to calcific aortic valve stenosis. Experimental, epidemiological and genetic evidence support the contention that elevated concentrations of lipoprotein(a) are causally related to atherothrombotic risk and equally to calcific aortic valve stenosis. The plasma concentration of lipoprotein(a) is principally determined by genetic factors, is not influenced by dietary habits, remains essentially constant over the lifetime of a given individual and is the most powerful variable for prediction of lipoprotein(a)-associated cardiovascular risk. However, major interindividual variations (up to 1000-fold) are characteristic of lipoprotein(a) concentrations. In this context, lipoprotein(a) assays, although currently insufficiently standardized, are of considerable interest, not only in stratifying cardiovascular risk, but equally in the clinical follow-up of patients treated with novel lipid-lowering therapies targeted at lipoprotein(a) (e.g. antiapolipoprotein(a) antisense oligonucleotides and small interfering ribonucleic acids) that markedly reduce circulating lipoprotein(a) concentrations. We recommend that lipoprotein(a) be measured once in subjects at high cardiovascular risk with premature coronary heart disease, in familial hypercholesterolaemia, in those with a family history of coronary heart disease and in those with recurrent coronary heart disease despite lipid-lowering treatment. Because of its clinical relevance, the cost of lipoprotein(a) testing should be covered by social security and health authorities.

A Chinese host genetic study discovered IFNs and causality of laboratory traits on COVID-19 severity

The COVID-19 pandemic has caused over 220 million infections and 4.5 million deaths worldwide. Current risk factor cannot fully explain the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients' laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory traits and used Mendelian randomization (MR) analysis to further investigate the causality of traits on disease severity. Two causal traits, WBC counts and cholesterol levels, were identified based on MR study, and their functional genes are located at genes MHC complex and ApoE, respectively. Our gene-based analysis and GSEA revealed four interferon pathways, including type I interferon receptor binding and SARS coronavirus and innate immunity. We hope that our work will contribute to studying the genetic mechanisms of disease and serve as a useful reference for COVID-19 diagnosis and treatment.

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Identification of GWAS associations for 81 phenotypes in COVID-19 patients

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GSEA reveals IFNs pathways including SARS coronavirus and innate immunity

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Discover causality of WBC and LDL-C on COVID-19 functioned by MHC system and ApoE gene

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Insights into the host genetic background of COVID-19 in the Chinese population

Lipoprotein (a) and Cardiovascular Disease: A Missing Link for Premature Atherosclerotic Heart Disease and/or Residual Risk

ABSTRACT

Lipoprotein(a) or lipoprotein "little a" is an under-recognized causal risk factor for cardiovascular (CV) disease (CVD), including coronary atherosclerosis, aortic valvular stenosis, ischemic stroke, heart failure and peripheral arterial disease. Elevated plasma Lp(a) (≥50 mg/dL or ≥100 nmol/L) is commonly encountered in almost 1 in 5 individuals and confers a higher CV risk compared to those with normal Lp(a) levels, although such normal levels have not been generally agreed upon. Elevated Lp(a) is considered a cause of premature and accelerated atherosclerotic CVD. Thus, in patients with a positive family or personal history of premature coronary artery disease (CAD), Lp(a) should be measured. However, elevated Lp(a) may confer increased risk for incident CAD even in the absence of a family history of CAD, and even in those who have guideline-lowered LDL-cholesterol (<70 mg/dl) and continue to have a persisting CV residual risk. Thus, measurement of Lp(a) will have a significant clinical impact on the assessment of atherosclerotic CVD risk, and will assume a more important role in managing patients with CVD with the advent and clinical application of specific Lp(a)-lowering therapies. Conventional therapeutic approaches like lifestyle modification and statin therapy remain ineffective at lowering Lp(a). Newer treatment modalities, such as gene silencing via RNA interference with use of antisense oligonucleotide(s) or small interfering RNA molecules targeting Lp(a) seem very promising. These issues are herein reviewed, accumulated data are scrutinized, meta-analyses and current guidelines are tabulated and Lp(a)-related CVDs and newer therapeutic modalities are pictorially illustrated.

An Integrative Co-localization (INCO) Analysis for SNV and CNV Genomic Features With an Application to Taiwan Biobank Data

Genomic studies have been a major approach to elucidating disease etiology and to exploring potential targets for treatments of many complex diseases. Statistical analyses in these studies often face the challenges of multiplicity, weak signals, and the nature of dependence among genetic markers. This situation becomes even more complicated when multi-omics data are available. To integrate the data from different platforms, various integrative analyses have been adopted, ranging from the direct union or intersection operation on sets derived from different single-platform analysis to complex hierarchical multi-level models. The former ignores the biological relationship between molecules while the latter can be hard to interpret. We propose in this study an integrative approach that combines both single nucleotide variants (SNVs) and copy number variations (CNVs) in the same genomic unit to co-localize the concurrent effect and to deal with the sparsity due to rare variants. This approach is illustrated with simulation studies to evaluate its performance and is applied to low-density lipoprotein cholesterol and triglyceride measurements from Taiwan Biobank. The results show that the proposed method can more effectively detect the collective effect from both SNVs and CNVs compared to traditional methods. For the biobank analysis, the identified genetic regions including the gene VNN2 could be novel and deserve further investigation.

Protein-coding repeat polymorphisms strongly shape diverse human phenotypes

Many human proteins contain domains that vary in size or copy number because of variable numbers of tandem repeats (VNTRs) in protein-coding exons. However, the relationships of VNTRs to most phenotypes are unknown because of difficulties in measuring such repetitive elements. We developed methods to estimate VNTR lengths from whole-exome sequencing data and impute VNTR alleles into single-nucleotide polymorphism haplotypes. Analyzing 118 protein-altering VNTRs in 415,280 UK Biobank participants for association with 786 phenotypes identified some of the strongest associations of common variants with human phenotypes, including height, hair morphology, and biomarkers of health. Accounting for large-effect VNTRs further enabled fine-mapping of associations to many more protein-coding mutations in the same genes. These results point to cryptic effects of highly polymorphic common structural variants that have eluded molecular analyses to date.

Lipoprotein(a): Knowns, unknowns and uncertainties

Over the last 10 years, there have been advances on several aspects of lipoprotein(a) which are reviewed in the present article. Since the standard immunoassays for measuring lipoprotein(a) are not fully apo(a) isoform-insensitive, the application of an LC-MS/MS method for assaying molar concentrations of lipoprotein(a) has been advocated. Genome wide association, epidemiological, and clinical studies have established high lipoprotein(a) as a causal risk factor for atherosclerotic cardiovascular diseases (ASCVD). However, the relative importance of molar concentration, apo(a) isoform size or variants within the LPA gene is still controversial. Lipoprotein(a)-raising single nucleotide polymorphisms has not been shown to add on value in predicting ASCVD beyond lipoprotein(a) concentrations. Although hyperlipoproteinemia(a) represents an important confounder in the diagnosis of familial hypercholesterolemia (FH), it enhances the risk of ASCVD in these patients. Thus, identification of new cases of hyperlipoproteinemia(a) during cascade testing can increase the identification of high-risk individuals. However, it remains unclear whether FH itself increases lipoprotein(a). The ASCVD risk associated with lipoprotein(a) seems to follow a linear gradient across the distribution, regardless of racial subgroups and other risk factors. The inverse association with the risk of developing type 2 diabetes needs consideration as effective lipoprotein(a) lowering therapies are progressing towards the market. Considering that Mendelian randomization analyses have identified the degree of lipoprotein(a)-lowering that is required to achieve ASCVD benefit, the findings of the ongoing outcome trial with pelacarsen will clarify whether dramatically lowering lipoprotein(a) levels can reduce the risk of ASCVD.