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

Background: Reference 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.

Methods: Population 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).

Results: Of 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.

Conclusions: Using 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.