Ceramides biomarkers determination in quantitative dried blood spots by UHPLC-MS/MS
Meikopoulos et al.
The finding, in our words
The authors validated a UHPLC-MS/MS method for quantifying four ceramide species in 10 μL quantitative dried blood spots. Ceramides remained stable at room temperature, supporting remote self-collection, and concentrations were higher in fingertip whole blood than in plasma or serum, which is relevant for at-home monitoring of cardiovascular and metabolic disease risk.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
Microsampling enables less invasive, patient-centric self-collection of capillary blood for remote monitoring of metabolites and lipids, overcoming conventional venipuncture constraints. Recent device innovations address dried blood spot limitations, particularly haematocrit and volume variations, expanding decentralised applications in population health, drug discovery and multi-omics research.
Capillary dried blood spots, after haematocrit-dependent conversion, showed good agreement with plasma for 25-hydroxyvitamin D quantification, with 90 per cent of results within 20 per cent of plasma and substantial to almost perfect agreement in status classification, supporting reliable home self-collection for large-scale vitamin D monitoring.
Capillary finger-stick dried blood spots demonstrated strong analytical agreement with venous serum for prostate-specific antigen (R² = 0.987) and remained stable for 31 days across a wide temperature range. This less invasive microsampling approach enables at-home self-collection, supporting decentralised screening and tele-diagnostics for prostate cancer.
Plasma lipidomes from self-collected upper-arm capillary blood were statistically indistinguishable from paired venous plasma, most classes at r=0.95–0.99, validating at-home capillary self-collection for lipidomics.
In an untargeted metabolomics study, microsampling devices, particularly the Mitra and Capitainer, yielded metabolic profiles comparable or superior to plasma in feature number and intensity, and in the precision and stability of some metabolites. This supports their potential for large-scale, decentralised metabolic profiling, though the captured metabolite profile was application-dependent.