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Towards personalized diagnostics via longitudinal study of the human plasma N-glycome
Ist Teil von
Biochimica et biophysica acta, 2016-08, Vol.1860 (8), p.1728-1738
Ort / Verlag
Netherlands: Elsevier B.V
Erscheinungsjahr
2016
Link zum Volltext
Quelle
Elsevier ScienceDirect Journals Complete
Beschreibungen/Notizen
Facilitated by substantial advances in analytical methods, plasma N-glycans have emerged as potential candidates for biomarkers. In the recent years, several investigations could link aberrant plasma N-glycosylation to numerous diseases. However, due to often limited specificity and sensitivity, only a very limited number of glycan biomarkers were approved by the authorities up to now. The inter-individual heterogeneity of the plasma N-glycomes might mask disease related changes in conventional large cross-sectional cohort studies, with a one-time sampling approach. But, a possible benefit of longitudinal sampling in biomarker discovery could be, that already small changes during disease progression are revealed, by monitoring the plasma N-glycome of individuals over time.
To evaluate this, we collected blood plasma samples of five healthy donors over a time period of up to six years (min. 1.5years). The plasma N-glycome was analyzed by xCGE-LIF, to investigate the intra-individual N-glycome variability over time. It is shown, that the plasma N-glycome of an individual is remarkably stable over a period of several years, and that observed small longitudinal changes are independent from seasons, but significantly correlated with lifestyle and environmental factors. Thus, the potential of future longitudinal biomarker discovery studies could be demonstrated, which is a further step towards personalized diagnostics. This article is part of a Special Issue entitled “Glycans in personalised medicine” Guest Editor: Professor Gordan Lauc.
•Longitudinal sampling of individuals plasma N-glycomes for personalized diagnostics.•Plasma N-glycomics with minimal invasive sampling (single blood droplets) is shown.•Longitudinal monitoring of individuals allows detection of small event related changes.•Time-series from individuals can be beneficial compared to cross-sectional large-scale studies.