Dried blood spots in clinical lipidomics: optimization and recent findings

Dried blood spots (DBS) are being considered as an alternative sampling method of blood collection that can be used in combination with lipidomic and other omic analysis. DBS are successfully used in the clinical context to collect samples for newborn screening for the measurement of specific fatty acid derivatives, such as acylcarnitines, and lipids from whole blood for diagnostic purposes. However, DBS are scarcely used for lipidomic analysis and investigations. Lipidomic studies using DBS are starting to emerge as a powerful method for sampling and storage in clinical lipidomic analysis, but the major research work is being done in the pre- and analytical steps and procedures, and few in clinical applications. This review presents a description of the impact factors and variables that can affect DBS lipidomic analysis, such as the type of DBS card, haematocrit, homogeneity of the blood drop, matrix/chromatographic effects, and the chemical and physical properties of the analyte. Additionally, a brief overview of lipidomic studies using DBS to unveil their application in clinical scenarios is also presented, considering the studies of method development and validation and, to a less extent, for clinical diagnosis using clinical lipidomics. DBS combined with lipidomic approaches proved to be as effective as whole blood samples, achieving high levels of sensitivity and specificity during MS and MS/MS analysis, which could be a useful tool for biomarker identification. Lipidomic profiling using MS/MS platforms enables significant insights into physiological changes, which could be useful in precision medicine.

Automated summary

Dried blood spots (DBS) are being considered as an alternative method for blood collection in lipidomic and other omic analysis. While DBS are widely used in clinical settings for specific measurements, their application in lipidomic studies is still limited. The combination of DBS with lipidomic approaches has shown high sensitivity and specificity, making it a useful tool for biomarker identification.