Evaluation of Fatty Acids Profiling in a Blood Drop Spotted on DBS Card by using a Robot-assisted GC Method

Importance of the Topic

Detailed profiling of fatty acid composition in blood is crucial for monitoring metabolic health and guiding disease prevention strategies. Fatty acids play key roles in biological processes and nutritional status evaluation.

Objectives and Study Overview

The study presents a fully automated analytical strategy to quantify fatty acids from a single dried blood spot (DBS). It combines direct derivatization with robot-assisted sample handling and gas chromatography to streamline analysis and support large cohort studies.

Methodology and Instrumentation

• Sample Collection on 903 Whatman DBS cards from a finger-prick blood drop.
• Direct derivatization using a Shimadzu AOC-6000 robotic station: sequential addition of sodium methoxide and boron trifluoride in methanol, reaction at 95°C, and extraction with n-heptane.
• Gas Chromatography: Nexis GC-2030 equipped with SLB-IL60 ionic liquid capillary column, split-splitless injector, and Shimadzu GCMS-TQ8050 NX triple quadrupole MS coupled to FID.
• Identification via MS spectral matching (>85% similarity) and linear retention index (±10) using reference FAME standards.
• Quantification based on FID response of 31 resolved fatty acid methyl esters (FAMEs).

Main Results and Discussion

The method successfully separated and identified 31 FAMEs, covering saturated, monounsaturated, and polyunsaturated families. In the analyzed DBS sample, saturated fatty acids accounted for 37.1%, monounsaturated for 27.5%, and polyunsaturated for 35.4%. The omega-6 to omega-3 ratio was 14.5, consistent with typical blood profiles. The ionic liquid column improved resolution in critical regions and the automated protocol yielded high precision and reproducibility.

Benefits and Practical Applications

• Minimal sample volume with noninvasive finger-prick sampling.
• High throughput and reduced manual error through full automation.
• Robust identification via dual MS and retention index criteria.
• Scalable for large-scale clinical, nutritional, and epidemiological studies.

Future Trends and Opportunities

Building comprehensive fatty acid databases for healthy and disease cohorts will enhance diagnostic capabilities. Integration with lipidomics workflows and point-of-care sampling devices could extend personalized nutrition and therapeutic monitoring applications.

Conclusion

The robot-assisted GC method for fatty acid profiling from DBS offers a rapid, reliable, and scalable workflow suitable for extensive population studies, achieving comprehensive analysis from minimal blood volumes.

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