Temporal intra-individual variation of immunological biomarkers in type 1 diabetes patients: implications for future use in cross-sectional assessment

Multiple immune parameters such as frequencies of autoreactive CD4(+), CD8(+) T-cells and CD4(+)CD25(+)Foxp3(+) T-cells have been explored as biomarkers in human T1D. However, intra-individual temporal variation of these parameters has not been assessed systematically over time. We determined the va...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:PloS one 2013-11, Vol.8 (11), p.e79383-e79383
Hauptverfasser: Sarikonda, Ghanashyam, Pettus, Jeremy, Sachithanantham, Sowbarnika, Phatak, Sonal, Miller, Jacqueline F, Ganesan, Lakshmi, Chae, Ji, Mallios, Ronna, Edelman, Steve, Peters, Bjoern, von Herrath, Matthias
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Multiple immune parameters such as frequencies of autoreactive CD4(+), CD8(+) T-cells and CD4(+)CD25(+)Foxp3(+) T-cells have been explored as biomarkers in human T1D. However, intra-individual temporal variation of these parameters has not been assessed systematically over time. We determined the variation in each of these parameters in a cohort of T1D and healthy donors (HDs), at monthly intervals for one year. Despite low intra- and inter-assay co-efficient of variation (CV), mean CVs for each of the immune parameters were 119.1% for CD4(+) T-cell-derived IFN-γ, 50.44% for autoreactive CD8(+) T-cells, and 31.24% for CD4(+)CD25(+)Foxp3(+) T-cells. Further, both HDs and T1D donors had similar CVs. The variation neither correlated with BMI, age, disease duration or insulin usage, nor were there detectable cyclical patterns of variation. However, averaging results from multiple visits for an individual provided a better estimate of the CV between visits. Based on our data we predict that by averaging values from three visits a treatment effect on these parameters with a 50% effect size could be detected with the same power using 1.8-4-fold fewer patients within a trial compared to using values from a single visit. Thus, our present data contribute to a more robust, accurate endpoint design for future clinical trials in T1D and aid in the identification of truly efficacious therapies.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0079383