Related Experiment Video
Updated: Sep 17, 2025

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
Published on: November 29, 2024
Normalization strategies in neonatal steroid metabolomics: a comparative analysis of probabilistic quotient and peer
Miłosz Lorek1,2, Teresa Joanna Stradomska3, Anna Siejka3
1Department of Neonatal and Pediatric Intensive Care, John Paul II Center for Child and Family Health, Sosnowiec, Poland. lorek.milosz@gmail.com.
Introduction:
Steroid metabolomics in neonatal populations is challenged by considerable physiological heterogeneity and technical variability, which complicate the interpretation and comparability of metabolite profiles. Effective normalization strategies are essential to ensure accurate data analysis in this context.
Material And Methods:
We analyzed 24-hour urinary steroid profiles in a cohort of 50 neonates (including very preterm, late preterm, and full-term infants) using gas chromatography-mass spectrometry. Two normalization techniques were compared: probabilistic quotient normalization (PQN) and peer group normalization (PGN). Normalization performance was assessed via distribution metrics, correlation with anthropometric variables, and principal component analysis (PCA).
Results:
PGN achieved superior distributional normalization, with 27 of 30 metabolites conforming to normality assumptions, compared to 21 using PQN. PGN also eliminated all significant correlations between steroid levels and anthropometric parameters, indicating effective reduction of physiological confounding. In contrast, PQN partially mitigated such associations but was less robust in handling high-abundance metabolites. PCA confirmed improved sample dispersion and group separation after normalization, with method-dependent differences in Scores Plot.
Conclusions:
Peer group normalization is a sophisticated approach to reducing physiological variability in neonatal steroid profiling. These observations lend further credence to PGN as a promising strategy for standardizing steroid metabolomics in the field of neonatology. Nevertheless, further validation is necessary to substantiate these findings.
More Related Videos
08:27Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
11:25Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
Published on: July 11, 2014
Related Concept Videos
Analysis of Population Pharmacokinetic Data
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
Regression Toward the Mean
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
Mechanistic Models: Compartment Models in Individual and Population Analysis