Comparison of capillary and venous plasma lipidomes: validation of self-collected blood for plasma lipidomics
Hameed et al.
The finding, in our words
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.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
Self-collected capillary blood samples posted by standard mail showed high concordance with couriered venous samples for HbA1c, creatinine and lipid parameters, supporting their use for remote monitoring in diabetes management and screening.
TAP II capillary serum, both professionally collected and self-collected, correlated with venous serum at R > 0.9 for eight analytes including ALT, AST, cholesterol, HDL and triglycerides. Creatinine correlated acceptably but carried a consistent negative bias, and carbon dioxide, potassium and albumin did not reach acceptable agreement: the useful reading is that the panel has to be validated, not the device alone.
The Tasso SST capillary blood micro-sampling device generated reproducible serum protein measurements, but its concordance with venous samples was analyte-specific: CRP, ferritin, IL-6 and PCT showed strong agreement, while D-dimer, IL-1β and IL-1Ra did not. Self-collection at home with delayed processing led to significant concentration differences for several proteins, underscoring that user proficiency and timely sample handling are critical for decentralised diagnostic applications.
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.
The homeRNA capillary blood collection and stabilization platform successfully captured lipopolysaccharide-induced inflammatory gene expression profiles. These transcriptomic responses were comparable to those obtained from traditional venous blood samples stabilized with RNAlater or PAXgene, demonstrating the platform's suitability for remote transcriptomic monitoring.