Principal component and correlation analysis of biochemical and endocrine markers in a healthy pediatric population (CALIPER)

Abstract

BackgroundReference intervals (i.e. normative ranges) established from a healthy reference population are essential to accurately interpret disease biomarkers. Biomarker concentration may partially depend on associations with other biomarkers due to various physiological and pathophysiological processes. In this study, a robust correlation analysis was performed to identify physiological biomarker associations in the healthy pediatric CALIPER cohort. MethodsPopulation reference values for 35 biochemical and 20 fertility/endocrine markers were analyzed for correlations in all subjects, male adolescents, female adolescents, and young children. Associations between biomarkers were assessed by Spearman's rank correlation and a multivariate analysis technique, principal component analysis (PCA). ResultsOf 197, 90, 59, and 32 significant correlations between biochemical markers in all subjects, male adolescents, female adolescents, and children, respectively, 23, 19, 16, and 9 were moderately strong (r > 0.5 or r < −0.5). Of 98, 24, 33, and 16 significant correlations between fertility/endocrine markers in all subjects, male adolescents, female adolescents, and children, respectively, 17, 8, 11, and 5 were moderately strong. Results were agreeable between Spearman's rank method and PCA. In some cases, biomarker correlations differed between sexes. ConclusionsUsing PCA, this study provides for the first time an extensive analysis of circulating biomarker associations in a healthy pediatric cohort. These data can inform future studies of potential confounding factors or particular variables that should be considered in test result interpretation for specific diseases.