Multiplexed measurement of protein biomarkers in high-frequency longitudinal dried blood spot (DBS) samples: characterization of inflammatory responses

Abstract

A detailed understanding of changes in blood protein biomarkers occuring in individuals over time would enable truly personalized approaches to health and disease monitoring. Such measurements could reveal smaller, earlier departures from normal baseline levels of biomarkers thus allowing better disease detection and treatment monitoring. Current practice, however, generally involves infrequent, sporadic biomarker testing, and this undersampling likely fails to capture important biological phenomena. Here we report the use of a robust multiplex immunomass spectrometric method (SISCAPA) to measure a panel of clinically-relevant proteins in a unique collection of 1,522 dried blood spots collected longitudinally by 8 individuals over periods of up to 9 years, with daily sampling during some intervals. Analytical workflow CVs of 2-6% for most assays were achieved by normalizing DBS plasma volume using a set of 3 minimally varying proteins, facilitating temporal analysis of both high-and low-amplitude biomarker changes compared to personalized baselines. The biomarkers included a panel of 9 positive and 5 negative acute phase response (inflammatory) proteins, allowing longitudinal analysis of inflammation markers associated with major and minor infections, influenza vaccination, recovery from hip-replacement surgery and Crohn's disease. The results illustrate complex time-dependent "biomarker trajectories" on multiple timescales and provide a basis for detailed personalized models of inflammation dynamics. The striking stability of most biomarker protein levels over time, combined with the convenience of self-sampling and low cost of multiplexed measurements using mass spectrometry, provide a new window into the temporal dynamics of disease processes. The extensive results obtained using this high throughput approach offer a new source of precision biomarker 'big data' amenable to machine learning approaches and application to more personalized health monitoring.

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

“…Utility of these concepts has recently been demonstrated by selecting suitable standards from a large library of protein fragments, 100 or by spiking-in peptides using stable isotope standards and capture by antipeptide antibodies (SISCA-PA). 101 General Workflow Considerations. With any sample processing workflow, characterizing its technical performance is as important as the potential value that the method may afford.…”

“…The reference can derive from peptides or proteins and can be added prior to or after protein digestion. Utility of these concepts has recently been demonstrated by selecting suitable standards from a large library of protein fragments, or by spiking-in peptides using stable isotope standards and capture by antipeptide antibodies (SISCAPA) …”

The preventive strategy for pandemics in the elderly is to collect in advance samples & data to counteract chronic inflammation (inflammaging)

“…Large numbers of samples can be taken and stored in biobanks (Bjorkesten et al, 2017), and be used to characterize inflammatory responses. For example, multiplex immuno-mass spectrometry can measure acute phase response (inflammatory) proteins from DBS with high precision (Anderson et al, 2019), also allowing longitudinal analyses of inflammation markers, and generating biomarker trajectories of inflammation dynamics. Overall, swabs and dried blood have proven their value, specifically for the identification of infection-and immunity-related biomarkers.…”