Dried blood spots analysis for targeted and non-targeted exposomics

Dried blood spots (DBS) are an established sample type, widely used in newborn screening programs for monitoring metabolic diseases. Their minimally invasive nature offers great promise for assessing chemical exposures, particularly during early life stages and in large-scale epidemiological studies. However, comprehensive evaluations of key analytical parameters such as extraction efficiency and matrix effects across multiple chemical classes remain limited. Moreover, the promising approach of broadly combining targeted and non-targeted mass spectrometric data evaluation remains unexplored in DBS small-molecule omics. Here, we present an optimized LC-HRMS workflow for combined exposomic and metabolomic analysis in DBS samples. Four extraction protocols were systematically compared, with analytical performance evaluated for >200 structurally diverse xenobiotics, including PFAS chemicals, personal care products, pesticides, mycotoxins and other food contaminants, flame retardants, polyphenols and additional pollutants/toxicants or their biomarkers of exposure. The optimized protocol demonstrated acceptable recoveries (60-140 %) and reproducibility (median RSD: 18 %) for a majority of compounds. Matrix effects showed a median value of 76 % (median RSD: 14 %). In a proof-of-principle study, eleven exposure compounds of the target panel with diverse physicochemical properties were identified in real-life samples, with several reported for the first time in DBS human biomonitoring. Complementary non-targeted analysis further expanded the detectable chemical space, enabling reliable annotation of additional exposures. Moreover, high-confidence identification of endogenous metabolites, including amino acids, biogenic amines, fatty acids and acylcarnitines demonstrated the integrated capacity to capture a broad snapshot of the human metabolome. These findings support the use of DBS for integrated exposomics and metabolomics applications, providing toxicological and biological insights from low-volume samples in both, prospective and retrospective studies.