The Riskier Lipid: What Is on the HORIZON for Lipoprotein (a) and Should There Be Lp(a) Screening for All?

Acute Coronary Syndrome in Women

Cardiovascular disease (CVD) is one of the leading causes of death in men and women throughout the world even after achieving advancement in the treatment and diagnosis. If considering patients in their old age, women tend to develop CVD later in life as compared to men as they are more likely to develop obesity and also diabetes. Recognizing the differences of sex in terms of acute coronary syndrome (ACS) and its management is very important for improving outcomes in women who present with ACS. This article reviews our current understanding of risk factors related to ACS and also its pathophysiology, management, and its outcomes in women.

Perspectives on the success of plasma lipidomics in cardiovascular drug discovery and future challenges

INTRODUCTION

Plasma lipidomics has emerged as a powerful tool in cardiovascular drug discovery by providing insights into disease mechanisms, identifying potential biomarkers for diagnosis and prognosis, and discovering novel targets for drug development. Widespread application of plasma lipidomics is hampered by technological limitations and standardization and requires a collaborative approach to maximize its use in cardiovascular drug discovery.

AREAS COVERED

This review provides an overview of the utility of plasma lipidomics in cardiovascular drug discovery and discusses the challenges and future perspectives of this rapidly evolving field. The authors discuss the role of lipidomics in understanding the molecular mechanisms of CVD, identifying novel biomarkers for diagnosis and prognosis, and discovering new therapeutic targets for drug development. Furthermore, they highlight the challenges faced in data analysis, standardization, and integration with other omics approaches and propose future directions for the field.

EXPERT OPINION

Plasma lipidomics holds great promise for improving the diagnosis, treatment, and prevention of CVD. While challenges remain in standardization and technology, ongoing research and collaboration among scientists and clinicians will undoubtedly help overcome these obstacles. As lipidomics evolves, its impact on cardiovascular drug discovery and clinical practice is expected to grow, ultimately benefiting patients and healthcare systems worldwide.

Estimating the Prevalence and Characteristics of Patients Potentially Eligible for Lipoprotein(a)-Lowering Therapies in a Real-World Setting

High lipoprotein(a) (Lp(a)) plasma levels are significantly associated with an increased risk of developing atherosclerotic cardiovascular diseases (ASCVD). The aim of this analysis was to estimate the prevalence and characteristics of patients potentially eligible for Lp(a)-lowering therapies in a real-world setting (i.e., patients with ASCVD and Lp(a) levels > 70 mg/dL). For this reason, we pooled data from a large cohort of Italian outpatients (N = 5961; men: 2879, women: 3982) with dyslipidemia. A binary logistic regression analysis was used to determine the significant predictors of ASCVD in the cohort, which were age (Odds Ratio (OR): 1.158, 95% Confidence Interval (CI): 1.114 to 1.203, p < 0.001), low-density lipoprotein cholesterol at entry (OR: 1.989, 95% CI: 1.080 to 1.198, p = 0.020) and Lp(a) (OR: 1.090, 95% CI: 1.074 to 1.107, p < 0.001). In our cohort, almost half of patients with ASCVD (44.7%) may be eligible to be treated with Lp(a)-lowering agents. Interestingly, patients who do not meet the treatment criteria despite high Lp(a) (50-70 mg/dL), respectively, account for 4.7% and 7.3% of those in primary and secondary ASCVD prevention. In conclusion, in our large cohort of outpatients with dyslipidemia, the prevalence of individuals with ASCVD and very high Lp(a) plasma levels is quite high, even with a conservative estimation.

Using genetic association data to guide drug discovery and development: Review of methods and applications

Evidence on the validity of drug targets from randomized trials is reliable but typically expensive and slow to obtain. In contrast, evidence from conventional observational epidemiological studies is less reliable because of the potential for bias from confounding and reverse causation. Mendelian randomization is a quasi-experimental approach analogous to a randomized trial that exploits naturally occurring randomization in the transmission of genetic variants. In Mendelian randomization, genetic variants that can be regarded as proxies for an intervention on the proposed drug target are leveraged as instrumental variables to investigate potential effects on biomarkers and disease outcomes in large-scale observational datasets. This approach can be implemented rapidly for a range of drug targets to provide evidence on their effects and thus inform on their priority for further investigation. In this review, we present statistical methods and their applications to showcase the diverse opportunities for applying Mendelian randomization in guiding clinical development efforts, thus enabling interventions to target the right mechanism in the right population group at the right time. These methods can inform investigators on the mechanisms underlying drug effects, their related biomarkers, implications for the timing of interventions, and the population subgroups that stand to gain the most benefit. Most methods can be implemented with publicly available data on summarized genetic associations with traits and diseases, meaning that the only major limitations to their usage are the availability of appropriately powered studies for the exposure and outcome and the existence of a suitable genetic proxy for the proposed intervention.

Translating atherosclerosis research from bench to bedside: navigating the barriers for effective preclinical drug discovery

Cardiovascular disease (CVD) remains the leading cause of death worldwide. An ongoing challenge remains the development of novel pharmacotherapies to treat CVD, particularly atherosclerosis. Effective mechanism-informed development and translation of new drugs requires a deep understanding of the known and currently unknown biological mechanisms underpinning atherosclerosis, accompanied by optimization of traditional drug discovery approaches. Current animal models do not precisely recapitulate the pathobiology underpinning human CVD. Accordingly, a fundamental limitation in early-stage drug discovery has been the lack of consensus regarding an appropriate experimental in vivo model that can mimic human atherosclerosis. However, when coupled with a clear understanding of the specific advantages and limitations of the model employed, preclinical animal models remain a crucial component for evaluating pharmacological interventions. Within this perspective, we will provide an overview of the mechanisms and modalities of atherosclerotic drugs, including those in the preclinical and early clinical development stage. Additionally, we highlight recent preclinical models that have improved our understanding of atherosclerosis and associated clinical consequences and propose model adaptations to facilitate the development of new and effective treatments.

A Modern Approach to Dyslipidemia

Lipid disorders involving derangements in serum cholesterol, triglycerides, or both are commonly encountered in clinical practice and often have implications for cardiovascular risk and overall health. Recent advances in knowledge, recommendations, and treatment options have necessitated an updated approach to these disorders. Older classification schemes have outlived their usefulness, yielding to an approach based on the primary lipid disturbance identified on a routine lipid panel as a practical starting point. Although monogenic dyslipidemias exist and are important to identify, most individuals with lipid disorders have polygenic predisposition, often in the context of secondary factors such as obesity and type 2 diabetes. With regard to cardiovascular disease, elevated low-density lipoprotein cholesterol is essentially causal, and clinical practice guidelines worldwide have recommended treatment thresholds and targets for this variable. Furthermore, recent studies have established elevated triglycerides as a cardiovascular risk factor, whereas depressed high-density lipoprotein cholesterol now appears less contributory than was previously believed. An updated approach to diagnosis and risk assessment may include measurement of secondary lipid variables such as apolipoprotein B and lipoprotein(a), together with selective use of genetic testing to diagnose rare monogenic dyslipidemias such as familial hypercholesterolemia or familial chylomicronemia syndrome. The ongoing development of new agents-especially antisense RNA and monoclonal antibodies-targeting dyslipidemias will provide additional management options, which in turn motivates discussion on how best to incorporate them into current treatment algorithms.

Lipoprotein(a) and Metabolic Syndrome

BACKGROUND

An inverse association between lipoprotein(a) (Lp[a]) and type 2 diabetes mellitus is well documented. However, data on the association of the metabolic syndrome (MetS) with Lp(a) are sparse.

METHODS

Cross-sectional data for MetS and Lp(a) were available for 5743 BASE-II and SHIP-0 participants (48.7% men; age 58 [20-85] years) (BASE, Berlin Aging Study; SHIP, Study of Health in Pomerania). The association of MetS and its components with Lp(a) was analyzed by means of median regression adjusted for age, sex, and study. Associations were evaluated for the total population as well as stratified by sex and menopausal status.

RESULTS

Overall, 27.6% (n = 1573) of the participants in the two studies had MetS and 22.5% (n = 1291) were premenopausal women. There was an inverse association between MetS and Lp(a) in the whole study sample (β = -11.9, 95% confidence interval [-21.3; -2.6]) as well as in men (β = -16.5 [-28.6; -4.3]). Participants with MetS (whole study sample) had 11.9 mmol/L lower Lp(a). Analogous results were found in postmenopausal women (β = -25.4 [-46.0; -4.8]). In premenopausal women with MetS, Lp(a) levels were higher by 39.1 mg/L on average [12.3; 65.9]) than in premenopausal women without MetS.

CONCLUSION

Hormonal aspects and menopausal alterations seem to affect the association between MetS and Lp(a), as the expected inverse association was not present in premenopausal women.

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.