Valutazione di dispositivi DBS per analisi di metabolomica e lipidomica in spettrometria di massa

Blood microsampling is a promising patient-centric approach for overcoming challenges associated with traditional blood collection. This technology offers logistical advantages, such as easier protocols and storage, and it has recently gained popularity because it enables accessible self-sampling by requiring low sample volume. This approach allows for self-sampling procedures and can be implemented in remote areas, enhancing healthcare accessibility. In addition to its logistical advantages, microsampling versatility extends to automated workflows, thereby mitigating biological risks by inactivating pathogens within the dried matrix. Moreover, microsampling’s compatibility with various analytical techniques, including mass spectrometry (MS) allows metabolomic and lipidomic analysis on multiple analytes simultaneously while guaranteeing high sensitivity and specificity. Innovations in MS-based analysis have revolutionized omics science, including metabolomics and lipidomics. By collecting small samples volumes, blood-microsampling provides a promising alternative to address the limitations of traditional blood sampling in omics studies. This provides valuable insights into biological processes and promotes remote and longitudinal sampling. Numerous blood microsampling devices are currently on the market and have been employed in research studies across a wide range of biomedical applications. In this work, three different blood microsampling devices were tested: Whatman® 903 cards, Capitainer® B and Telimmune DUO cards. This study has provided valuable insights on the effectiveness and reliability of DBS/DPS microsampling devices. By testing five different extraction solvents, we identified the optimal extraction method for DBS/DPS samples for polar and/or lipid analytes in terms of extraction yields. This evaluation process aimed to support informed decision-making and improve the efficacy of blood microsampling in metabolomic and lipidomic analyses, considering also the number of total features found in each device.