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Multiomics Analysis of Dried Plasma Spots Using Stable Isotope Internal Standards for Biomarker Discovery
Wenqian Li1, John R Koethe2,3, Curtis L Gabriel4
1Department of Chemistry, University of Florida, Gainesville, Florida 32610, United States.
Analytical Chemistry
|September 17, 2025
Summary
A new multiomics method for dried blood spots (DBS) uses stable isotope internal standards (SIIS) for accurate quantitation. This approach enables reliable analysis of metabolites and lipids from small samples, advancing clinical research.
Area of Science:
- Biochemistry
- Analytical Chemistry
- Clinical Diagnostics
Background:
- Dried blood spots (DBS) offer advantages for biological sample collection and storage.
- Microsampling techniques face challenges in accurate quantitation and normalization.
- Multiomics analysis requires robust methods for comprehensive molecular profiling.
Purpose of the Study:
- To develop and validate a comprehensive analytical strategy for multiomics analysis of DBS.
- To enhance quantitation accuracy in DBS analysis using prespotted stable isotope internal standards (SIIS).
- To enable simultaneous analysis of metabolites and lipids from minimal sample volumes.
Main Methods:
- Developed an optimized Folch extraction protocol for dried plasma spots.
- Utilized high-resolution mass spectrometry (Thermo Q Exactive Orbitrap) coupled with UHPLC (Dionex Ultimate 3000).
- Integrated SIIS directly into the DBS matrix for reliable normalization and improved extraction efficiency.
Main Results:
- Successfully integrated simultaneous analysis of metabolites and lipids, achieving broad molecular coverage.
- Demonstrated method applicability in a cohort of persons with HIV, identifying distinct molecular profiles between diabetic and nondiabetic individuals.
- Identified hundreds of metabolites and thousands of lipids from microliter-range sample volumes.
Conclusions:
- The developed analytical strategy provides a robust platform for quantitative DBS multiomics analysis.
- This methodology overcomes key analytical challenges in microsampling, offering improved extraction efficiency and normalization.
- The approach is particularly valuable for large-scale clinical studies and resource-limited settings, leveraging DBS advantages like simplified collection and enhanced stability.
