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bioRxiv · 10.1101/2025.05.28.656742

Dried Blood Spot Lipidomics in Diabetes

Roberts, J. L.·Ryan, M.·Whiley, L.·Gray, N.·Gay, M.·Holmes, E.·Nicholson, J. K.·Wist, J.·Lawler, N. G.
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Abstract

Comprehensive lipidomic profiling in diabetes has identified disease-associated lipid signatures that may support more personalised monitoring beyond routine glycaemic control. Dried blood spot (DBS) microsampling offers a minimally invasive method for collecting and storing small blood volumes (<50 {micro}L), enabling decentralised and longitudinal sampling. However, its application in lipidomics for cardiometabolic phenotyping remains underexplored. In this study, 34 participants (17 diabetics, 17 non-diabetic controls) self-collected DBS samples using advanced microsampling devices (10 {micro}L, Capitainer(R)B). Lipid extracts were analysed using a validated liquid chromatography-trapped ion mobility-time-of-flight mass spectrometry method optimised for semi-quantitative DBS lipidomics. Multivariate analysis revealed significant differences in lipidomic profiles (n = 432 lipids) between diabetic and non-diabetic individuals (R{superscript 2}Y = 0.82, Q{superscript 2}Y = 0.50, p = 0.05). Key discriminatory lipids (all VIP > 1.44), including HexCer(18:1;O2/24:0), HexCer(18:1;O2/22:0), LPC(16:0), PC(O-34:3), TG(18:0_18:1_20:3), and TG(18:1_18:1_22:6), were consistent with matched venous and capillary plasma samples. Lipid class and structural differences, including elevated long-chain triacylglycerols and reduced lysophosphatidylcholines reflected known dyslipidaemia in diabetes and demonstrate the capacity of DBS to capture biologically meaningful lipid perturbations. Participant-reported outcomes from Problem Areas In Diabetes (PAID-20), Patient Activation Measure (PAM-13), and microsampling perception questionnaires highlighted psychosocial and behavioural insights, and indicated strong support for DBS sampling over venepuncture, citing ease of use and reduced burden. These findings establish DBS lipidomics as a feasible and informative approach for stratifying cardiometabolic disease, supporting broader implementation in remote, personalised monitoring frameworks (Figure 1). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/656742v1_fig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@c53b4org.highwire.dtl.DTLVardef@14b507forg.highwire.dtl.DTLVardef@191e563org.highwire.dtl.DTLVardef@16af172_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Graphical abstract - Chapter 5. C_FIG

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Roberts, J. L., Ryan, M., Whiley, L., Gray, N., Gay, M., Holmes, E., Nicholson, J. K., Wist, J., Lawler, N. G.. 2025-05-30. Dried Blood Spot Lipidomics in Diabetes. https://doi.org/10.1101/2025.05.28.656742

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