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Phenotypic clustering identifies heterogeneous cardiovascular risk among patients with elevated lipoprotein(a)
Hyung Joon Joo1, Soon Jun Hong1, Cheol Woong Yu1
1Department of Cardiology, Korea University Anam Hospital, Seoul, Republic of Korea.
Insights
Elevated Lipoprotein(a) [Lp(a)] risk is better understood by patient phenotypes. Clustering high Lp(a) patients revealed distinct cardiovascular event rates, suggesting phenotype-guided risk assessment improves stratification beyond fixed Lp(a) thresholds.
Area of Science:
- Cardiovascular Medicine
- Genetics
- Biochemistry
Background:
- Lipoprotein(a) [Lp(a)] is a known cardiovascular risk enhancer.
- Fixed Lp(a) concentration thresholds may not fully capture individual risk heterogeneity.
Purpose of the Study:
- To identify distinct patient subgroups with elevated Lp(a) levels.
- To assess cardiovascular risk differences between these subgroups.
- To evaluate the utility of phenotype-guided risk stratification.
Main Methods:
- Retrospective analysis of 2355 patients with Lp(a) ≥ 50 mg/dL.
- K-means clustering based on demographic, comorbidity, and laboratory variables.
- Validation of cluster solution using elbow, silhouette, and NbClust methods.
- Analysis of major adverse cardiovascular events (MACE) over a median follow-up of 2.3 years.
Main Results:
- Two distinct patient clusters were identified: Cluster 1 (older, male, higher cardiometabolic burden, lower renal function) and Cluster 2 (younger, female, fewer comorbidities).
- Despite similar Lp(a) levels, Cluster 1 exhibited significantly higher MACE rates (8.9%) compared to Cluster 2 (2.0%) (log-rank p < 0.01).
- Multivariable analysis indicated Cluster 1 was associated with increased MACE risk (HR 1.39) versus the reference group, while Cluster 2 showed no significant difference (HR 1.08).
Conclusions:
- Phenotypic clustering of patients with high Lp(a) effectively delineates subgroups with differing cardiovascular risk profiles.
- Phenotype-guided risk assessment may offer a more refined approach to cardiovascular risk stratification than relying solely on fixed Lp(a) thresholds.
Abstract:
Lipoprotein(a) [Lp(a)] is an established cardiovascular risk enhancer, yet fixed concentration thresholds may not fully capture the heterogeneity of cardiovascular risk among individuals with elevated levels. We retrospectively analyzed 17,653 patients with Lp(a) measurements from three tertiary hospitals (2017-2024). After exclusions, 2355 patients with Lp(a) ≥ 50 mg/dL underwent k-means clustering based on 23 demographic, comorbidity, and laboratory variables, which identified two phenotypic groups. Cluster validation using elbow, silhouette, and NbClust consensus methods supported a two-cluster solution. Cluster 1 consisted of older, male-predominant patients with a higher cardiometabolic burden and lower renal function, whereas Cluster 2 included younger, female-predominant patients with fewer comorbidities and relatively treatment-naïve dyslipidemia. Despite similar Lp(a) levels, over a median follow-up of 2.3 years (interquartile range [IQR] 1.0-3.0), major adverse cardiovascular events (MACE) occurred more frequently in Cluster 1 than Cluster 2 (8.9% vs. 2.0%, log-rank p < 0.01). In multivariable Cox models, Cluster 1 was associated with higher MACE risk compared with the Lp(a) < 30 mg/dL reference group (HR 1.39, 95% CI 1.13-1.72), whereas Cluster 2 showed no significant risk difference (HR 1.08 95% CI 0.69-1.68). These findings suggest that phenotypic clustering of high-Lp(a) patients delineates subgroups with distinct cardiovascular risk profiles. Incorporating phenotype-guided risk assessment may refine cardiovascular risk stratification beyond fixed Lp(a) thresholds.
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