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Updated: Aug 22, 2026
Isolation and Analysis of Plasma Lipoproteins by Ultracentrifugation
Published on: January 28, 2021
Retrospective analysis of serial lipoprotein(a) measurements in pediatric patients: Intraindividual variability and
Christian Menke1, Julya Hempel1, Sabine Illsinger1
1Department of Pediatric Kidney, Liver, Metabolic and Neurological Diseases, Hannover Medical School, Hannover, Germany (Menke, Hempel, and Das).
Insights
Lipoprotein(a) [Lp(a)] levels in children show significant variability, impacting cardiovascular risk assessment. A peak-value approach may improve risk evaluation in pediatric patients.
Area of Science:
- Cardiovascular Medicine
- Pediatric Endocrinology
- Clinical Chemistry
Background:
- Current guidelines suggest a single lifetime measurement for lipoprotein(a) [Lp(a)] due to presumed genetic stability.
- Emerging evidence indicates significant intraindividual Lp(a) variability during childhood and adolescence.
- This variability can complicate cardiovascular risk stratification and clinical decision-making in pediatric populations.
Purpose of the Study:
- To quantify intraindividual Lp(a) variability in children and adolescents.
- To evaluate the impact of this variability on cardiovascular risk categorization.
- To compare different risk stratification approaches based on Lp(a) measurements.
Main Methods:
- Retrospective analysis of 736 serial Lp(a) measurements from 224 pediatric patients (2014-2024).
- Assessment of intraindividual variability using maximum percent change (>20% considered significant).
- Comparison of four measurement strategies: first, peak, mean, and last recorded values.
Main Results:
- Over 51% of pediatric patients exhibited >20% intraindividual Lp(a) variability.
- Risk category transitions occurred in 20% of patients, particularly near decision thresholds.
- Lipid-lowering therapy was associated with increased variability; the peak-value strategy showed highest concordance (87%-92%) with other methods.
Conclusions:
- Clinically relevant Lp(a) variability is present in children, especially near risk thresholds.
- Observed variability likely has a biological basis, supported by persistence in untreated patients.
- Risk-stratified monitoring using a peak-value approach may optimize pediatric cardiovascular risk evaluation.
Background:
Current guidelines recommend 1 measurement of lipoprotein(a) [Lp(a)] in lifetime based on presumed genetically-determined stability. Emerging evidence suggests intraindividual variability during childhood, which can affect risk stratification and clinical decision-making.
Objective:
Quantify intraindividual Lp(a) variability in childhood and adolescence and evaluate its impact on risk categorization and different risk stratification approaches.
Methods:
We performed a retrospective analysis of serial Lp(a) measurements in 224 children and adolescents from a pediatric outpatient lipid clinic between 2014 and 2024. 736 measurements were analyzed, with 2 to 12 measurements per patient (median 4) over a median follow-up of 1.7 years. Intraindividual variability was assessed using maximum percent change; significant variation was defined as >20%. Four approaches were compared: first measured, peak, mean, and last measured values.
Results:
Intraindividual variability exceeding 20% was observed in 51% of patients. Risk category transitions occurred in 20% of patients, with particular instability in borderline (50 to <75 nmol/L) and elevated (75 to <120 nmol/L) categories, where upward reclassification dominated. Patients with low (<50 nmol/L) or highly elevated (≥120 nmol/L) values showed higher stability. Lipid-lowering therapy was associated with higher variability (47.6% vs 20.9% with >40% change). The peak-value strategy demonstrated the highest concordance with alternative approaches (87%-92% agreement).
Conclusion:
Clinically relevant Lp(a) variability in children was observed, concentrated near decision thresholds. While a proportion of the observed variability may reflect analytical noise, the persistence of variability among untreated patients and the differential patterns across risk categories support a biological contribution. Risk-stratified monitoring with a peak-value approach may optimize pediatric risk evaluation.
