Higgins Victoria, Hooshmand Shabnam, Adeli Khosrow
CALIPER Program, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada.
CALIPER Program, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.
Clin Biochem. 2019 Apr;66:29-36. doi: 10.1016/j.clinbiochem.2019.02.004. Epub 2019 Feb 11.
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.
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).
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.
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.
从健康参考人群中建立的参考区间(即规范范围)对于准确解释疾病生物标志物至关重要。由于各种生理和病理生理过程,生物标志物浓度可能部分取决于与其他生物标志物的关联。在本研究中,进行了稳健的相关性分析,以确定健康儿科CALIPER队列中的生理生物标志物关联。
分析了35种生化标志物和20种生育/内分泌标志物在所有受试者、男性青少年、女性青少年和幼儿中的人群参考值之间的相关性。通过Spearman等级相关性和多变量分析技术主成分分析(PCA)评估生物标志物之间的关联。
在所有受试者、男性青少年、女性青少年和儿童中,生化标志物之间分别有197、90、59和32个显著相关性,其中23、19、16和9个为中度强相关(r > 0.5或r < -0.5)。在所有受试者、男性青少年、女性青少年和儿童中,生育/内分泌标志物之间分别有98、24、33和16个显著相关性,其中17、8、11和5个为中度强相关。Spearman等级法和PCA的结果一致。在某些情况下,生物标志物相关性存在性别差异。
本研究使用PCA首次对健康儿科队列中的循环生物标志物关联进行了广泛分析。这些数据可为未来关于潜在混杂因素或特定疾病检测结果解释中应考虑的特定变量的研究提供参考。