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Hemoglobin normalization outperforms other methods for standardizing dried blood spot metabolomics: A comparative

Abhishek Jain1, Montana Morris2, Elizabeth Z Lin1

  • 1Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, United States.

The Science of the Total Environment
|September 16, 2022
PubMed
Summary

Hemoglobin (Hb) normalization is the most effective method for accurate dried blood spot (DBS) metabolomics, outperforming other techniques. This method improves data quality for newborn screening and environmental exposure studies.

Keywords:
Dried blood spotHematocritHemoglobinMetabolomicsSpecific gravity

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Area of Science:

  • Biochemistry
  • Analytical Chemistry
  • Environmental Health

Background:

  • Dried blood spot (DBS) metabolomics is crucial for newborn screening, exposomics, and biomonitoring.
  • Accurate metabolite quantification in DBS is challenged by the hematocrit effect and variable blood volumes.
  • Current normalization methods for DBS metabolomics lack consensus, impacting data reliability.

Purpose of the Study:

  • To compare the efficacy of five normalization methods (hemoglobin, specific gravity, protein, spot weight, potassium) against unnormalized data in DBS metabolomics.
  • To evaluate the impact of normalization on reducing intragroup variation, differential metabolic analysis, and classification accuracy.
  • To identify the optimal normalization strategy for DBS metabolomics, particularly for environmental epidemiological studies.

Main Methods:

  • Compared five normalization methods (Hb, SG, protein, spot weight, K+) to unnormalized DBS data in adult and neonatal cohorts.
  • Assessed method performance using criteria including variation reduction (MAD, variance, CV, NMDS, PCA), differential analysis (dendrogram, heatmap, p-value distribution), and classification accuracy (PLS-DA, sPLS-DA, ROC, RF).
  • Investigated the correlation between specific gravity (SG) and hemoglobin (Hb) and derived a predictive equation for SG using Hb.

Main Results:

  • Hemoglobin (Hb) normalization significantly outperformed all other methods across multiple performance metrics and datasets.
  • Hb normalization demonstrated superior reduction in intragroup variation and improved differential metabolic analysis and classification accuracy.
  • A strong correlation between SG and Hb was observed in adults and neonates, enabling SG to serve as a surrogate for Hb normalization via the equation SG = -0.4814Hb² + 2.44Hb + 0.005.

Conclusions:

  • Hemoglobin (Hb) normalization is the most effective method for dried blood spot (DBS) metabolomics, enhancing data accuracy and reliability.
  • The established correlation between specific gravity (SG) and Hb provides a practical alternative for normalization when Hb measurement is not feasible.
  • This study establishes a robust methodological platform for DBS metabolomics, crucial for advancing environmental epidemiology and public health screening.