Literature DB >> 30763567

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

Victoria Higgins1, Shabnam Hooshmand2, Khosrow Adeli3.   

Abstract

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.
Copyright © 2019 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Correlation; Pediatric; Principal component analysis

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Year:  2019        PMID: 30763567     DOI: 10.1016/j.clinbiochem.2019.02.004

Source DB:  PubMed          Journal:  Clin Biochem        ISSN: 0009-9120            Impact factor:   3.281


  3 in total

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  3 in total

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