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Prevalence of Lp(a) in a real-world Portuguese cohort: implications for cardiovascular risk assessment

Lipids in Health and Disease volume 24, Article number: 16 (2025) Cite this article

Abstract

Background

Cardiovascular disease (CVD) is a major cause of mortality worldwide, necessitating more refined strategies for risk assessment. Recently, lipoprotein(a) [Lp(a)] has gained attention for its distinctive role in atherosclerosis, yet its prevalence and impact for cardiovascular risk assessment are not well-documented in the Portuguese population. This study aimed to characterize Lp(a) levels in a real-world Portuguese cohort, investigating its prevalence and association with CVD risk.

Methods

Retrospective and cross-sectional study of adults who underwent serum Lp(a) analysis in a Portuguese hospital between August 2018 and June 2022. Demographic and anthropometric data, laboratory values, relevant comorbidities and lipid-lowering medication were collected.

Results

Of 1134 participants, 28.7% had elevated Lp(a) levels (> 125 nmol/L). A higher prevalence was observed in those with atherosclerotic cardiovascular disease (ASCVD) (45.9%) or a family history of premature CVD (41.9%). Additionally, a significant association was found between elevated Lp(a) levels and traditional CVD risk factors, including hypertension, dyslipidemia, and diabetes mellitus. Among those classified as having low-to-moderate CVD risk by (Systematic COronary Risk Evaluation 2) SCORE2, 55.7% exhibited high Lp(a) levels (> 75 nmol/L), suggesting a potential higher risk of CVD disease.

Conclusions

The prevalence of elevated Lp(a) in Portugal, notably among those with ASCVD or premature CVD history, is concerning. This study underscores the potential of Lp(a) assessment for a more comprehensive approach to cardiovascular risk assessment. This could improve the stratification of CVD risk and identify individuals who could benefit from early intensive management of their risk factors, ultimately reducing the burden of CVD and cardiovascular-related mortality.

Background

Cardiovascular disease (CVD) remains a major global health concern. According to the World Health Organization, it is the leading cause of death worldwide, accounting for an alarming 32% of all deaths in 2019 [1]. In Europe, the burden is even more pronounced, with CVD contributing to around 45% of all deaths [2]. Atherosclerotic cardiovascular disease (ASCVD) is the most common underlying cause, influenced by multiple factors, including dyslipidemia, particularly low-density lipoprotein cholesterol (LDL-C) [3]. However, despite optimal LDL-C management, residual cardiovascular risk persists, highlighting the need for exploring additional risk factors like Lipoprotein(a) [Lp(a)] [4,5,6,7,8].

Lp(a) is an LDL-like particle with an additional glycoprotein known as apolipoprotein(a) [9, 10], known for its strong affinity for proteoglycans and extracellular matrix components within the arterial wall. This property facilitates the accumulation of Lp(a) in atherosclerotic lesions, contributing to the formation of foam cells, a hallmark of atherosclerosis. Concomitantly, Lp(a)-attached pro-inflammatory oxidized phospholipids contribute to arterial vessel wall inflammation by inducing the monocyte cell extravasation and adhesion molecules activity. In turn, inflammatory cytokines drive both endothelial cell activation and macrophage differentiation. Furthermore, Lp(a) has pro-thrombotic properties that interfere with the breakdown of blood clots (fibrinolysis) and platelet function, which may further increase the risk of thrombotic events. Recent research has shown that elevated levels of Lp(a) represent an inherited and independent causal risk factor for coronary heart disease, myocardial infarction, and stroke [8, 11,12,13]. Therefore, measuring Lp(a) can be crucial for identifying high-risk individuals and improving risk stratification, particularly those with personal or family history of premature ASCVD, familial hypercholesterolemia, ASCVD without traditional risk factors, or recurrent CVD events despite optimal conventional risk factor management [14, 15]. Importantly, currently approved therapies targeting apolipoprotein B (apoB) and LDL-C may not fully mitigate the cardiovascular risk associated with elevated Lp(a) levels [14].

In Portugal, CVD accounts for 29.4% of total mortality [16], with atherosclerosis accounting for 14.3% of mortality and 12.2% of Years of Life Lost in 2016. The economic impact is substantial, with costs surpassing €1.9 billion, equivalent to 1% of the country's gross domestic product and 11% of health expenditure [17]. Despite these figures, routine Lp(a) measurement of is not widespread, even though the European Atherosclerosis Society (EAS) recommends a one-time assessment to refine risk predictions [18], using thresholds of 75 nmol/L as normal and 125 nmol/L as elevated, and a grey zone between these values for assessing cardiovascular risk. Additionally, very high Lp(a) levels (> 430 nmol/L) are considered to confer a lifetime ASCVD risk equivalent to heterozygous familial hypercholesterolemia [19].

Taking this into account, this study aimed to characterize Lp(a) levels in a real-world Portuguese cohort and determine the prevalence of elevated Lp(a) levels within this population. Furthermore, it assesses cardiovascular risk using the Systematic COronary Risk Evaluation 2 (SCORE2) tool, which estimates the 10-year risk of fatal and non-fatal atherosclerotic events by integrating factors like age, sex, smoking, and systolic blood pressure. By applying SCORE2, this research intends to enhance CVD risk stratification and identify individuals who could benefit from early intervention, ultimately aiming to reduce CVD's health and economic burdens in Portugal.

Methods

Study design and study participants

This was a cross-sectional, retrospective, and single-center study conducted at Centro Hospitalar Universitário de Santo António in Portugal. Eligible participants for this study were adult individuals (over 18 years of age) who had undergone serum Lp(a) analysis at the above hospital between August 2018 and June 2022 as part of their cardiovascular risk assessment or management. Most participants (98.8%) were from outpatient settings (details provided in Table S1), aimed at reflecting the community-based cardiovascular risk assessment focus of this study. Those with a cardiovascular event within 30 days of Lp(a) measurement were ineligible for study participation, as the body’s inflammatory state following such events can affect Lp(a) levels, causing a transient elevation, potentially misrepresenting a patient's baseline values [20,21,22,23].

Data collection and outcome measures

The study relied on secondary data collection from the hospital medical records between August 2018 and June 2022. The data collection process involved the gathering of demographic and clinical information, including comorbidities (Table 1), prescribed therapies, and an extensive array of laboratory values, comprising Lp(a), total cholesterol, high-density lipoprotein-cholesterol (HDL-C), non-HDL-C, LDL-C, very-low-density lipoprotein cholesterol (VLDL-C), triglycerides, ApoB, HbA1c, and creatinine, all collected at the time of Lp(a) measurement.

Table 1 Distribution of medical specialties in outpatient referrals for lipoprotein(a) analysis
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Serum Lp(a) was quantified by an immunoturbidimetric assay, using the Roche Cobas Integra 400 plus chemistry analyzer (Roche Diagnosis, Basilea, Swiss) as per manufacturer instructions. All measurements were conducted in a single laboratory (Laboratório de Química Analítica do Centro Hospitalar Universitário de Santo António) to ensure accuracy and minimize potential bias. This assay used a monoclonal antibody targeting Lp(a) to determine the amount of Lp(a) particles (nmol/L). Calibration of this assay was performed using the IFCC SRM 2B reference reagent. Lp(a) group classes were defined according to the recommendations of the 2022 Atherosclerosis Society Consensus Statement [18], which provides clinical guidance for testing and management of elevated Lp(a) levels and illustrates a pragmatic approach to CVD risk assessment: patients with Lp(a) < 75 nmol/L (considered as normal levels) have the lowest risk, those with Lp(a) between 75–125 nmol/L (grey area) have an intermediate risk, and those with Lp(a) > 125 nmol/L (high/very high levels) have the highest risk for CVD disease.

Statistical analysis

Descriptive analyses summarized the sociodemographic and clinical characteristics of the patient sample.

Numerical variables were described using measures of central tendency, including mean and median, depending on the normality of the data. Appropriate measures of dispersion, such as standard deviation (SD) and quartiles (P25, P75), were also calculated. Categorical variables were characterized by computing absolute and relative frequencies.

Bivariate inferential analyses were performed to compare sociodemographic and clinical characteristics between subgroups. Statistical differences in numerical variables were assessed using Student’s t-test for independent samples when assumptions were validated (Shapiro–Wilk test). In alternative, a non-parametric version (Mann–Whitney U test) was performed. The association between subgroups and categorical variables was evaluated using either a Chi-squared test or a Fisher’s exact. Correlations between Lp(a) levels and other lipidic measurements were determined using the Spearman’s coefficient. P-values obtained from multiple comparisons were adjusted by Benjamini-Hochberg’s correction. The significance level was set at 0.05. Missing values were excluded from the analysis.

For individuals between 40 and 69 years old, the individual ten-year risk of experiencing a fatal or non-fatal ASCVD event was calculated using the SCORE2 [24]. For individuals over the age of 70, a separate risk score, SCORE2-OP (older persons) was computed [24]. For this purpose, the following variables were used: sex, age, smoking status, diabetes mellitus disease status, systolic blood pressure, total cholesterol, HDL, and the individual's region of residence (in Europe). Patients were included if they had information for all the stated variables and met the following criteria: no prior cardiovascular events, no chronic renal disease, no familial history of hypercholesterolemia, and total cholesterol levels ≤ 310 mg/dL and/or LDL-C ≤ 190 mg/dL (n = 265). Of note, SCORE2 risk scores were obtained using the algorithm from the Cardiovascular Epidemiology Unit of the Department of Public Health and Primary Care, University of Cambridge, kindly provided by one of the authors of the SCORE2 working group [19] and computed in Stata® software. Otherwise, all statistical analyses and graphs were performed using RStudio software version 4.2.2.

Results

Patient’s sociodemographic and clinical characteristics

This study included 1134 participants, whose sociodemographic and clinical characteristics are detailed in Table 2. The overall sample had a mean (± SD) age of 50.01 years (± 13.54), with 50.4% being male. Most participants were overweight or obese (71.4%), and the most common comorbidity was dyslipidemia, present in 68.4% of patients. Among those with dyslipidemia, 70.8% were prescribed lipid-lowering medication, primarily statins (70.1%), either in monotherapy (53.8%) or in combination with other drugs (a total of 4 patients took PCKS9 inhibitors and 7 underwent LDL apheresis).

Table 2 Patients’ demographic and clinical characteristics
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Other prevalent comorbidities included arterial hypertension (44.4%), diabetes mellitus (26.6%), and CVD (24.1%). Over 12.8% had a family history of CVD, and the median (P25;P75) Lp(a) level of the study population was 42.00 [12.83;147.92] nmol/L.

Significant differences emerged when comparing subgroups with and without ASCVD and early-onset family history of CVD. Patients with ASCVD were older (57.07 vs. 47.80 years, p < 0.001) and predominantly male (78.4% vs. 42.5%, p < 0.001). Moreover, they had lower BMI (27.48 vs. 29.76 kg/m2, p < 0.001) and higher rates of hypertension (53.0% vs. 41.2%, p = 0.002), dyslipidemia (95.6% vs. 60.0%, p < 0.001), and diabetes mellitus (34.4% vs. 24.1%, p = 0.002) than those without ASCVD. The presence of a family history of CVD did not influence the prevalence of these comorbidities. Chronic kidney disease was less frequent in patients with ASCVD (11.5% vs. 15.9%, p = 0.046) and in individuals without a family history of CVD compared to those with (13.2% vs. 0.9%; p < 0.001). Patients with previous ASCVD and family history of CVD were more frequently prescribed lipid-lowering medication. In the subgroup of individuals with ASCVD, lower levels of total cholesterol, HDL-C, non-HDL-C and LDL-C were found, potentially due to the effects of lipid lowering therapy. The distribution of Lp(a) also differed significantly between subgroups (Figure S1). Median Lp(a) levels were significantly higher in patients with ASCVD (100.50 vs. 33.60 nmol/L, p < 0.001) or a family history of CVD (102.25 vs. 38.80 nmol/L, p < 0.001).

Distribution of patients across Lp(a) levels

Table 3 shows the distribution of patients with different Lp(a) levels. Most individuals (60.9%) had normal Lp(a) levels (< 75 nmol/L), while 10.4% fell within the grey zone (75–125 nmol/L) and 28.7% had high values (> 125 nmol/L). Of note, 2.5% of individuals exhibited Lp(a) levels exceeding 430 nmol/L, which could put them at a lifetime cardiovascular risk equivalent to patients with heterozygous familial hypercholesterolemia.

Table 3 Number (%) of patients across Lp(a) levels
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Individuals with a history of ASCVD had a significantly different distribution compared to those without, with 43.1% in the normal range, 11.0% in the grey zone and 45.9% having elevated Lp(a) levels (p < 0.001). Similarly, those with a family history of early-onset CVD showed a distinct pattern, with 42.7% in the normal range, 15.4% in the grey zone, and 41.9% with elevated levels (p < 0.001).

When evaluating the correlation between Lp(a) and other lipidic parameters that impact the risk of CVD (Table S2), only triglycerides levels showed a negligible negative correlation with Lp(a) (Spearman’s coefficient R = -0.06; p = 0.044). No significant correlations were found between Lp(a) levels and HDL-C (R = 0.04; p = 0.194), non-HDL-C (R = 0.01; p = 0.841), LDL-C (R = 0.04; p = 0.206), or total cholesterol (R = 0.02; p = 0.449).

SCORE2 risk prediction and association with Lp(a)

The SCORE2 system, which assesses the ten-year risk for atherosclerotic cardiovascular events, reveals varying risk profiles across age groups in our study (Fig. 1). In those under 50, the majority (61.8%) were in the low-moderate-risk category. Notably, 34.7% (n = 41) presented a high risk, and 1.7% (n = 2) were classified as very high-risk patients. For the 50 to 69 years age range, a shift in risk distribution is observed. Nearly half of the individuals (46.9%) faced an elevated risk of ASCVD, with 36.1% (n = 60) at high-risk and 10.8% (n = 18) at very high-risk. Individuals over 70 showed predominantly high or very high-risk profiles (90.0%).

Fig. 1
figure 1

SCORE2 risk prediction for the whole sample and per age group

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Of note, patients under lipid-lowering therapies were more frequently in higher risk categories (45.2% and 43.5%, respectively), and those with chronic renal disease also exhibited an increasing trend in higher-risk categories, with proportions of 0.6%, 3.8%, and 12.5%, respectively (Table S2).

The distribution of patients with different Lp(a) levels (normal levels, grey zone, high levels) in relation to the three distinct SCORE 2 risk categories is presented in Table 4. In the age group < 50 years (n = 109), most individuals with normal Lp(a) levels were classified in the low-moderate risk category (70.0%). Interestingly, patients in the SCORE2 low-moderate and high-risk groups were similarly distributed within the moderate (grey zone; 55.6% and 44.4%, respectively) and high (56.5% and 43.5%, respectively) Lp(a) levels. Only one individual with normal levels of Lp(a) (< 75 nmol/L) presented a high risk for an ASCVD event according to SCORE2. Within the 50–69 years age category (n = 148), 42.6% of the individuals (n = 63), were classified as having a high or very high risk for ASCVD events according to SCORE2, regardless of their Lp(a) levels. Among individuals aged over 70 years (n = 8), only one individual was categorized in the low-risk category of SCORE2, while the remaining seven were classified in the high or very high-risk category, regardless of their Lp(a) levels.

Table 4 Distribution of SCORE2 risk categories by age groups per Lp(a) levels
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The analysis of Lp(a) levels stratified by the threshold of < 75 nmol/L and ≥ 75 nmol/L, in relation to SCORE2 risk categories, is detailed in Table 5. Among individuals with normal Lp(a) levels (n = 186), more than half (61.8%) were classified as having a low-moderate SCORE2 risk for ASCVD events, while 32.3% and 5.9% were classified as high and very-high-risk individuals, respectively. On the other hand, among those with elevated Lp(a) levels (n = 79), 55.7% were classified into the low-moderate risk category of SCORE2, 36.7% in the high- and 7.6% in the very high-risk category. As expected, no significant differences were found in the distribution of patients with normal or high Lp(a) levels per SCORE2 risk categories (p-value = 0.631).

Table 5 Association between Lp(a) levels with Cardiovascular Disease (CVD) risk given by SCORE2
Full size table

Discussion

The primary goal of this retrospective cross-sectional study was to elucidate the role of Lp(a) in a real-world Portuguese cohort, providing insights into its prevalence, association with CVD, and potential implications for cardiovascular risk stratification. The study's findings underscore the importance of integrating Lp(a) assessment with traditional risk factors for a more nuanced and comprehensive approach to cardiovascular risk assessment.

Although traditional risk factors significantly contribute to ASCVD, elevated Lp(a) is a well-recognized independent risk factor for this condition, with prevalence estimates varying across different populations. Lp(a) is tightly linked to genetic determinants, with high levels being observed in approximately 20% of the population [23]. Here, a slightly higher prevalence of high Lp(a) levels (28.7%) is reported, possibly because most of the sample derived from a dyslipidemia consultation and therefore may have a genetic predisposition to higher lipid levels. Nevertheless, these results are consistent with the findings from the BiomarCaRE consortium, which showed a higher prevalence of elevated Lp(a) levels in southern European countries [25]. Indeed, in a hospital cohort from southern Spain, a 29.6% prevalence of Lp(a) levels above 50 mg/dL (equivalent to 125 nmol/L) was found [26]. In contrast, a study conducted in Italy documented a lower prevalence of patients with Lp(a) > 50 mg/dL (14.4%) [27]. Interestingly, a study conducted in a global ASCVD population identified 27.9% of patients with levels exceeding the established threshold for increased cardiovascular risk (> 50 mg/dL). This study also identified ethnic, regional, and gender differences in Lp(a) levels, with the highest levels observed in black, younger, and female patients [28]. Altogether, these variations highlight the relevance of considering the population context and study design in interpreting and comparing Lp(a) prevalence [28, 29]. Moreover, the lack of standardized methods for Lp(a) measurement poses challenges when attempting to compare prevalence rates across diverse populations and studies. Differences in laboratory techniques, calibration standards, and assay sensitivity can lead to discrepancies in reported Lp(a) concentrations. These variations may include differences in antibody specificity, assay platforms [30, 31], or the use of different Lp(a) isoform-specific antibodies [32]. Ongoing efforts in the scientific community aim to establish consensus guidelines for Lp(a) measurement, encouraging the adoption of standardized methods across laboratories [33], as this will enhance the reliability and comparability of results, ultimately facilitating a more accurate understanding of Lp(a)’s role in cardiovascular risk assessment. As anticipated, individuals with ASCVD demonstrated a higher prevalence of moderate and high Lp(a) concentrations compared to those without, as previous documented [14, 18, 27, 29, 34,35,36].

The study’s identification of a higher prevalence of traditional cardiovascular risk factors among individuals with ASCVD, such as increased weight, hypertension, dyslipidemia, and diabetes mellitus, underscores the multifactorial nature of cardiovascular risk. Indeed, a previous Portuguese study assessed the Lp(a) profile in a group of patients with high vascular risk but no cardiovascular events and found that Lp(a) levels were correlated with other cardiovascular risk factors, such as metabolic disorders and the presence of at least two risk factors [37]. Similarly, the current study observed a higher prevalence of traditional cardiovascular risk factors, including increased weight, hypertension, dyslipidemia, and diabetes mellitus, among individuals with established ASCVD. The observation of lower BMI levels in individuals with ASCVD or a family history of premature CVD align with prior findings that challenge the conventional association between BMI and cardiovascular risk [38, 39], highlighting the independent nature of family history as a robust predictor of heightened CVD risk, irrespective of BMI levels. These findings support the general understanding that CVD risk is multifactorial, with genetic factors playing a significant role, and emphasize the need to consider risk factors other than obesity for comprehensive risk assessment and management. The significance of elevated Lp(a) as an independent risk factor for identifying individuals at increased risk of CVD, even in the absence of a documented history of cardiovascular events, is underscored by the finding that nearly a quarter of patients without ASCVD had high Lp(a) levels. Similarly, a report from the island of Madeira in Portugal found that among patients with Lp(a) levels ≥ 30 mg/dL, 44.4% experienced a major adverse cardiovascular event (MACE) while 32.0% did not (p < 0.0001). Smoking, hypertension, dyslipidemia, physical inactivity and renal insufficiency all correlated with Lp(a) as independent risk factors for MACE [40]. Furthermore, the association between early-onset family history of CVD and elevated Lp(a) levels was significant (p < 0.001), as reported by others [41,42,43]. A 2023 cross-sectional study found that first-degree relatives were 7.4 times more likely to have high Lp(a) levels (> 125 nmol/L) if their relatives also exhibited elevated levels, while second-degree relatives showed a 3.0-fold increase [42]. The familial clustering of high Lp(a) levels suggest a hereditary pattern, emphasizing the genetic contribution to atherogenic processes and the potential development of ASCVD at an earlier age. From a clinical perspective, this emphasizes the importance of considering family history, especially in cases of premature cardiovascular events, when assessing an individual’s overall cardiovascular risk profile. This integration will allow clinicians to precisely tailor preventive strategies, providing a nuanced understanding of an individual’s cardiovascular risk profile and facilitating the development of targeted interventions for more effective risk mitigation.

The study’s revelation of a negligible negative correlation between Lp(a) and triglyceride levels, along with the stability of Lp(a) levels despite lipid-lowering therapy, underscores the distinct role of Lp(a) in cardiovascular risk assessment. Previous research has also showed an increased risk of cardiovascular events with higher Lp(a) levels, regardless of LDL-C values [11, 44]. While LDL-C has historically been a focal point in cardiovascular risk assessment, the observed negative correlation between Lp(a) and triglyceride levels and the lack of positive correlation with other lipids found in this study diverges from the more common positive associations reported between Lp(a) and LDL cholesterol or other lipids in existing literature [45] This discrepancy may be influenced by the high proportion of patients on statins in the study population, particularly those with ASCVD, who may represent a higher-risk population. Statins, frequently prescribed for lipid management, can modulate lipid levels, potentially masking associations that might be evident in a non-medicated population. On the other hand, the fact that Lp(a) levels remain high despite lipid-lowering therapy suggests its potential as a more reliable and stable biomarker for long-term cardiovascular risk assessment. This stability gains significance in situations where traditional lipid markers may fluctuate due to factors like medication adherence, alterations in treatment regimens, or other influences on lipid metabolism. This is further supported by the EAS consensus statement, which emphasizes the continuous relationship between Lp(a) concentration and cardiovascular outcomes, even at low levels of LDL-C [46].

The findings from the SCORE2 risk assessment revealed that a substantial proportion of patients with high Lp(a) levels were categorized as low-moderate risk by SCORE2, particularly among individuals under 50 years old. Specifically, 56.5% of patients identified as having a high risk for CVD based on their Lp(a) values were classified as low-moderate risk by SCORE2. Conversely, only a small percentage (1.3%) of subjects classified as low risk based on Lp(a) were considered very high risk by SCORE2. These results echo a similar trend reported in a Dutch study, which demonstrated that incorporating Lp(a) levels into ASCVD risk algorithms resulted in the reclassification of 31% (using SCORE) and 63% (using SMART) of individuals to a higher risk category [34]. Altogether, these results suggest that the presence of elevated Lp(a) levels in individuals categorized as low-moderate risk by SCORE2 may warrant a re-analysis of their risk and careful consideration by clinicians, highlighting the need for Lp(a) integration into risk assessment algorithms to enhance classification and/or reclassification of ASCVD risk [29].

Connecting these findings into a broader context, increasing evidence underscores Lp(a) as a strong predictor of CVD risk, despite remaining underdiagnosed globally – in a sample population of 2,412,020 individuals, only 0.25% had their Lp(a) values measured. Notably, patients with ASCVD and other common CV diseases did not feature highly among tested patients [47]. The limited treatment options available emphasize the importance of measuring Lp(a) to guide clinical practice in managing other risk factors. Currently, the Phase 3 OCEAN(a) and Lp(a) HORIZON trials are exploring novel therapies aimed at lowering Lp(a), with promising preliminary results showing reduced Lp(a) levels in ASCVD patients, sustained overtime. Although final results are not yet available, both trials underscore the growing recognition of Lp(a) as an independent risk factor for ASCVD [48, 49]. With Portugal’s national health system facing a considerable financial impact from atherosclerosis, the cost-efficient strategy of testing Lp(a) once in a lifetime proves invaluable in enhancing ASCVD risk assessment and reducing cardiovascular morbidity and mortality.

This study demonstrates a significant strength in its rigorous quantification of Lp(a) molecules using a reliable immunoturbidimetric assay within a single laboratory, ensuring consistency and accuracy. However, it is important to acknowledge certain limitations inherent to the study. While the sample size is relatively large, selection bias may prevent the generalizability of the findings, as it may not fully represent the general population. The cross-sectional design and regional focus further limit the applicability of the results to other populations, particularly within the Portuguese population. Moreover, lipid comparisons may have been influenced by the use of medications, such as lipid-lowering therapies, which could not be completely accounted for in the analyses. Lastly, the reliance on existing hospital records poses inherent limitations in data quality and completeness. To further advance our understanding of Lp(a)’s impact on cardiovascular risk, future research should consider adopting a longitudinal approach and including a more diverse geographic representation within the Portuguese population.

Conclusions

Our study's findings underscore the significant role of Lp(a) as a biomarker in assessing cardiovascular risk, particularly among individuals with specific risk factors such as a family history of premature ASCVD. The data reveal that elevated Lp(a) levels are prevalent in our Portuguese cohort and correlate with increased cardiovascular risk, supporting the utility of Lp(a) measurement in refining risk stratification models.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

ApoB:

Apolipoprotein B

ASCVD:

Atherosclerotic cardiovascular disease

BMI:

Body mass index

CVD:

Cardiovascular disease

EAS:

European Atherosclerosis Society

HbA1c :

Glycated hemoglobin

HDL-C:

High-density lipoprotein-cholesterol

LDL-C:

Low-density lipoprotein cholesterol

Lp(a):

Lipoprotein a

MACE:

Major adverse cardiovascular event

OP:

Older persons

SCORE2:

Systematic COronary Risk Evaluation 2

SD:

Standard deviation

VLDL-C:

Very-low-density lipoprotein cholesterol

References

  1. Organization WH. Cardiovascular diseases (CVDs) 2021: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds).

  2. The Lancet Regional Health – Europe. Navigating disparities in cardiovascular disease outcomes across Europe: a call to action. The Lancet Regional Health - Europe. 2023;33:100746.

  3. Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, et al. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596–646.

    PubMed  PubMed Central  Google Scholar 

  4. Lawler PR, Akinkuolie AO, Harada P, Glynn RJ, Chasman DI, Ridker PM, et al. Residual Risk of Atherosclerotic Cardiovascular Events in Relation to Reductions in Very-Low-Density Lipoproteins. J Am Heart Assoc. 2017;6(12):e007402.

  5. Dhindsa DS, Sandesara PB, Shapiro MD, Wong ND. The Evolving Understanding and Approach to Residual Cardiovascular Risk Management. Front Cardiovasc Med. 2020;7:88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Nguyen VS, Tran XT, Vo TD, Le QT. Residual Cardiovascular Risk Factors in Dyslipidemia. In: Johnny C, editor. Risk Factors for Cardiovascular Disease. Rijeka: IntechOpen; 2021. Ch. 9.

  7. Wong ND, Zhao Y, Quek RGW, Blumenthal RS, Budoff MJ, Cushman M, et al. Residual atherosclerotic cardiovascular disease risk in statin-treated adults: The Multi-Ethnic Study of Atherosclerosis. J Clin Lipidol. 2017;11(5):1223–33.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Reyes-Soffer G, Ginsberg HN, Berglund L, Duell PB, Heffron SP, Kamstrup PR, et al. Lipoprotein(a): A Genetically Determined, Causal, and Prevalent Risk Factor for Atherosclerotic Cardiovascular Disease: A Scientific Statement From the American Heart Association. Arterioscler Thromb Vasc Biol. 2022;42(1):e48–60.

    Article  CAS  PubMed  Google Scholar 

  9. Alhomoud IS, Talasaz A, Mehta A, Kelly MS, Sisson EM, Bucheit JD, et al. Role of lipoprotein(a) in atherosclerotic cardiovascular disease: A review of current and emerging therapies. Pharmacotherapy. 2023;43(10):1051–63.

    Article  CAS  PubMed  Google Scholar 

  10. Utermann G. Lipoprotein(a). In: Valle DL, Antonarakis S, Ballabio A, Beaudet AL, Mitchell GA, editors. The Online Metabolic and Molecular Bases of Inherited Disease. New York, NY: McGraw-Hill Education; 2019. Part 12

  11. Nordestgaard BG, Chapman MJ, Ray K, Borén J, Andreotti F, Watts GF, et al. Lipoprotein(a) as a cardiovascular risk factor: current status. Eur Heart J. 2010;31(23):2844–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Enas EA, Varkey B, Dharmarajan TS, Pare G, Bahl VK. Lipoprotein(a): An independent, genetic, and causal factor for cardiovascular disease and acute myocardial infarction. Indian Heart J. 2019;71(2):99–112.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Nave AH, Lange KS, Leonards CO, Siegerink B, Doehner W, Landmesser U, et al. Lipoprotein (a) as a risk factor for ischemic stroke: a meta-analysis. Atherosclerosis. 2015;242(2):496–503.

    Article  CAS  PubMed  Google Scholar 

  14. Kamstrup PR. Lipoprotein(a) and Cardiovascular Disease. Clin Chem. 2020;67(1):154–66.

    Article  Google Scholar 

  15. Fogacci F, Cicero AFG, D’Addato S, D’Agostini L, Rosticci M, Giovannini M, et al. Serum lipoprotein(a) level as long-term predictor of cardiovascular mortality in a large sample of subjects in primary cardiovascular prevention: data from the Brisighella Heart Study. Eur J Intern Med. 2017;37:49–55.

    Article  CAS  PubMed  Google Scholar 

  16. Costa J, Alarcão J, Araujo F, Ascenção R, Caldeira D, Fiorentino F, et al. The burden of atherosclerosis in Portugal. European Heart Journal - Quality of Care and Clinical Outcomes. 2020;7(2):154–62.

    Article  PubMed Central  Google Scholar 

  17. Costa J, Alarcão J, Amaral-Silva A, Araújo F, Ascenção R, Caldeira D, et al. Atherosclerosis: The cost of illness in Portugal. Revista Portuguesa de Cardiologia (English Edition). 2021;40(6):409–19.

    Article  Google Scholar 

  18. Kronenberg F, Mora S, Stroes ESG, Ference BA, Arsenault BJ, Berglund L, et al. Lipoprotein(a) in atherosclerotic cardiovascular disease and aortic stenosis: a European Atherosclerosis Society consensus statement European Heart Journal. 2022;43(39):3925–46.

  19. Mach F, Baigent C, Catapano AL, Koskinas KC, Casula M, Badimon L, et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J. 2020;41(1):111–88.

    Article  PubMed  Google Scholar 

  20. Ziogos E, Vavuranakis MA, Harb T, Foran PL, Blaha MJ, Jones SR, et al. Lipoprotein(a) concentrations in acute myocardial infarction patients are not indicative of levels at six month follow-up. Europ Heart J Open. 2023;3(2):oead035.

  21. Sourij C, Aziz F, Krappinger S, Praschk A, Metzner T, Kojzar H, et al. Changes in Lipoprotein(a) Levels in People after ST Elevation Myocardial Infarction—The STEMI-Lipids Study. Int J Mol Sci. 2023;24(21):15531.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Kostner KM, Marz W, Kostner GM. When should we measure lipoprotein (a)? Eur Heart J. 2013;34(42):3268–76.

    Article  CAS  PubMed  Google Scholar 

  23. Wilson DP, Jacobson TA, Jones PH, Koschinsky ML, McNeal CJ, Nordestgaard BG, et al. Use of Lipoprotein(a) in clinical practice: A biomarker whose time has come. A scientific statement from the National Lipid Association. J Clin Lipidol. 2019;13(3):374–92.

  24. SCORE2 working group and ESC Cardiovascular risk collaboration. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Europ Heart J. 2021;42(25):2439–54.

  25. Waldeyer C, Makarova N, Zeller T, Schnabel RB, Brunner FJ, Jørgensen T, et al. Lipoprotein(a) and the risk of cardiovascular disease in the European population: results from the BiomarCaRE consortium. Eur Heart J. 2017;38(32):2490–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Arrobas Velilla T, Fabiani de la Iglesia J, Martín Pérez S, Calbo Caballos L, Gómez Barrado JJ, León Justel A. Lipoprotein(a) in a selection of hospitals in Andalusia and Extremadura. Underdiagnosed and underused? Rev Esp Cardiol (Engl Ed). 2022;75(10):844–5.

  27. Cicero AFG, Fogacci F, Giovannini M, Grandi E, D’Addato S, Borghi C. Estimating the Prevalence and Characteristics of Patients Potentially Eligible for Lipoprotein(a)-Lowering Therapies in a Real-World Setting. Biomedicines. 2023;11(12):3289.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Nissen SE, Wolski K, Cho L, Nicholls SJ, Kastelein J, Leitersdorf E, et al. Lipoprotein(a) levels in a global population with established atherosclerotic cardiovascular disease. Open Heart. 2022;9(2):e002060corr1.

  29. Kronenberg F, Mora S, Stroes ESG. Consensus and guidelines on lipoprotein(a) - seeing the forest through the trees. Curr Opin Lipidol. 2022;33(6):342–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Boot C. How to measure lipoprotein (a) and in whom. Br J Cardiol. 2022;29(Suppl 1):S15–9.

  31. Cegla J, France M, Marcovina SM, Neely RDG. Lp (a): When and how to measure it. Ann Clin Biochem. 2021;58(1):16–21.

    Article  CAS  PubMed  Google Scholar 

  32. Marcovina SM, Albers JJ. Lipoprotein (a) measurements for clinical application. J Lipid Res. 2016;57(4):526–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Alebna PL, Mehta A. An Update on Lipoprotein(a): The Latest on Testing, Treatment, and Guideline Recommendations: American College of Cardiology; 2023 [Available from: https://www.acc.org/Latest-in-Cardiology/Articles/2023/09/19/10/54/An-Update-on-Lipoprotein-a.

  34. Nurmohamed NS, Kaiser Y, Schuitema PCE, Ibrahim S, Nierman M, Fischer JC, et al. Finding very high lipoprotein(a): the need for routine assessment. Eur J Prev Cardiol. 2022;29(5):769–76.

    Article  PubMed  Google Scholar 

  35. Patel AP, Wang M, Pirruccello JP, Ellinor PT, Ng K, Kathiresan S, et al. Lp(a) (Lipoprotein[a]) Concentrations and Incident Atherosclerotic Cardiovascular Disease: New Insights From a Large National Biobank. Arterioscler Thromb Vasc Biol. 2021;41(1):465–74.

    Article  CAS  PubMed  Google Scholar 

  36. Kamstrup PR, Benn M, Tybjaerg-Hansen A, Nordestgaard BG. Extreme lipoprotein(a) levels and risk of myocardial infarction in the general population: the Copenhagen City Heart Study. Circulation. 2008;117(2):176–84.

    Article  CAS  PubMed  Google Scholar 

  37. Meireles-Brandao JA, Meireles-Brandao LR, Coelho R, Rocha-Goncalves FR. Lipoprotein(a) in the Evaluation of Cardiovascular Risk in the Portuguese Population. Acta Med Port. 2019;32(3):202–7.

    Article  CAS  PubMed  Google Scholar 

  38. Wahrenberg A, Kuja-Halkola R, Magnusson PKE, Habel H, Warnqvist A, Hambraeus K, et al. Cardiovascular Family History Increases the Risk of Disease Recurrence After a First Myocardial Infarction. J Am Heart Assoc. 2021;10(23): e022264.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Wong ND, Budoff MJ, Ferdinand K, Graham IM, Michos ED, Reddy T, et al. Atherosclerotic cardiovascular disease risk assessment: An American Society for Preventive Cardiology clinical practice statement. Am J Prev Cardiol. 2022;10: 100335.

    Article  PubMed  PubMed Central  Google Scholar 

  40. D Sa RPDR, M Santos, M Temtem, A C Sousa, E Henriques, M Rodrigues, S Freitas, S Borges, I Ornelas, A Drumond, M I Mendonca. Lipoprotein(a) and cardiovascular outcomes in patients with coronary artery disease and impaired glucose metabolism. European Heart J. 2022;43(Supplement_2): ehac544.1153.

  41. Mehta A, Virani SS, Ayers CR, Sun W, Hoogeveen RC, Rohatgi A, et al. Lipoprotein(a) and Family History Predict Cardiovascular Disease Risk. J Am Coll Cardiol. 2020;76(7):781–93.

    Article  CAS  PubMed  Google Scholar 

  42. Reeskamp LF, Tromp TR, Patel AP, Ibrahim S, Trinder M, Haidermota S, et al. Concordance of a High Lipoprotein(a) Concentration Among Relatives. JAMA Cardiol. 2023;8(12):1111–8.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Gulayin PE, Lozada A, Schreier L, Gutierrez L, López G, Poggio R, et al. Elevated Lipoprotein(a) prevalence and association with family history of premature cardiovascular disease in general population with moderate cardiovascular risk and increased LDL cholesterol. Int J Cardiol Heart Vasc. 2022;42: 101100.

    PubMed  PubMed Central  Google Scholar 

  44. Rikhi R, Hammoud A, Ashburn N, Snavely AC, Michos ED, Chevli P, et al. Relationship of low-density lipoprotein-cholesterol and lipoprotein(a) to cardiovascular risk: The Multi-Ethnic Study of Atherosclerosis (MESA). Atherosclerosis. 2022;363:102–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Rainwater DL, Ludwig MJ, Haffner SM, VandeBerg JL. Lipid and lipoprotein factors associated with variation in Lp(a) density. Arterioscler Thromb Vasc Biol. 1995;15(3):313–9.

    Article  CAS  PubMed  Google Scholar 

  46. Kronenberg F, Mora S, Stroes ESG, Ference BA, Arsenault BJ, Berglund L, et al. Lipoprotein(a) in atherosclerotic cardiovascular disease and aortic stenosis: a European Atherosclerosis Society consensus statement. Eur Heart J. 2022;43(39):3925–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Panza GA, Blazek O, Tortora J, Saucier S, Fernandez AB. Prevalence of lipoprotein(a) measurement in patients with or at risk of cardiovascular disease. J Clin Lipidol. 2023;17(6):748–55.

    Article  PubMed  Google Scholar 

  48. O’Donoghue ML, Rosenson RS, López JAG, Lepor NE, Baum SJ, Stout E, et al. The Off-Treatment Effects of Olpasiran on Lipoprotein(a) Lowering. J Am Coll Cardiol. 2024;84(9):790–7.

    Article  PubMed  Google Scholar 

  49. Malick WA, Goonewardena SN, Koenig W, Rosenson RS. Clinical Trial Design for Lipoprotein(a)-Lowering Therapies. J Am Coll Cardiol. 2023;81(16):1633–45.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

The authors would like to thank W4Research for the statistical analysis (Miguel Cabral) and writing support (Carla Gomes and Ana Ferreira) in the preparation of this manuscript.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Novartis Pharma Portugal supported the statistical analysis and medical writing through an unrestricted grant but had no direct influence in the study design, analysis, or decision to submit for publication.

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Authors and Affiliations

  1. Department of Endocrinology, Diabetes and Metabolism, Local Health Unit of Santo António, Largo Professor Abel Salazar, Porto, 4099-001, Portugal

    Miguel Saraiva, Beatriz Tavares da Silva, Inês Poças Ferreira & Isabel Palma

  2. Department of Clinical Chemistry, Local Health Unit of Santo António, Porto, Portugal

    Jonatas Garcez & José Carlos Oliveira

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  1. Miguel Saraiva
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Contributions

The authors contributed to the paper as follows: study conception and design, analysis and interpretation of data: MS and IP. All authors contributed to data collection, reviewed the results, and approved to the published version of the manuscript.

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Correspondence to Miguel Saraiva.

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The study was conducted in accordance with the Declaration of Helsinki and was approved by the local Ethics Committee – Comissão de Ética do Centro Hospitalar da Universidade do Porto/Instituto Ciências Biomédicas Abel Salazar. Due to the retrospective nature of this study, the need for obtaining informed consent was waived by the local Ethics Committee. All data was de-identified to protect patient privacy.

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Saraiva, M., Garcez, J., da Silva, B.T. et al. Prevalence of Lp(a) in a real-world Portuguese cohort: implications for cardiovascular risk assessment. Lipids Health Dis 24, 16 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12944-025-02433-9

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Keywords

Lipids in Health and Disease

ISSN: 1476-511X