A Universal Framework for Blood Ionome Extraction and Intelligent Quality Control in ¹H NMR Metabolomics

Area of Science:

• Clinical bioanalysis
• Metabolomics
• Metallomics
• Nuclear Magnetic Resonance (NMR) Spectroscopy

Background:

• Routine clinical adoption of NMR spectroscopy is hindered by quality control (QC) and spectral interpretation issues.
• Ethylenediaminetetraacetic acid (EDTA) and its metal complexes in blood samples cause spectral interference, complicating metabolite analysis.

Purpose of the Study:

• To develop an automated cheminformatics platform for EDTA-aware QC and quantitative metal ion extraction from NMR spectra.
• To preserve metabolic integrity during spectral analysis.
• To enable accurate quantification of key metal ions directly from routine 1H NMR spectra.

Main Methods:

• Development of a fully automated cheminformatics platform for NMR data processing.
• Multicenter validation using large plasma and serum cohorts at 500 and 600 MHz.
• Automated baseline reconstruction for harmonizing data across instruments and cohorts.

Main Results:

• Accurate quantification of calcium (Ca2+), magnesium (Mg2+), and zinc (Zn2+) directly from 1H NMR spectra (R2 > 0.9) was achieved, validated against clinical and spectrometric assays.
• The platform demonstrated successful harmonization of data across diverse cohorts and instruments.
• A stage-dependent decline in circulating Zn2+ was observed in a breast cancer cohort, indicating disrupted zinc homeostasis.

Conclusions:

• The developed platform effectively addresses QC and spectral interpretation challenges in blood NMR analysis.
• This work integrates metabolomics and metallomics, enhancing the translational utility of NMR spectroscopy in precision medicine.
• The findings suggest potential for NMR-based metallomics in diagnosing and monitoring diseases like breast cancer.