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Healthy First-Degree Relatives of Patients with Type 1 Diabetes Exhibit Significant Differences in Basal Gene Expression Pattern of Immunocompetent Cells Compared to Controls: Expression Pattern as Predeterminant of Autoimmune Diabetes

Publikace na 1. lékařská fakulta, Fakulta tělesné výchovy a sportu, 2. lékařská fakulta |
2012

Tento text není v aktuálním jazyce dostupný. Zobrazuje se verze "en".Abstrakt

Expression features of genetic landscape which predispose an individual to the type 1 diabetes are poorly understood. We addressed this question by comparing gene expression profile of freshly isolated peripheral blood mononuclear cells isolated from either patients with type 1 diabetes (T1D), or their first-degree relatives or healthy controls.

Our aim was to establish whether a distinct type of prodiabetogenic gene expression pattern in the group of relatives of patients with T1D could be identified. Whole-genome expression profile of nine patients with T1D, their ten first-degree relatives and ten healthy controls was analysed using the human high-density expression microarray chip.

Functional aspects of candidate genes were assessed using the MetaCore software. The highest number of differentially expressed genes (547) was found between the autoantibody-negative healthy relatives and the healthy controls.

Some of them represent genes critically involved in the regulation of innate immune responses such as TLR signalling and CCR3 signalling in eosinophiles, humoral immune reactions such as BCR pathway, costimulation and cytokine responses mediated by CD137, CD40 and CD28 signalling and IL-1 proinflammatory pathway. Our data demonstrate that expression profile of healthy relatives of patients with T1D is clearly distinct from the pattern found in the healthy controls.

That especially concerns differential activation status of genes and signalling pathways involved in proinflammatory processes and those of innate immunity and humoral reactivity. Thus, we posit that the study of the healthy relatives gene expression pattern is instrumental for the identification of novel markers associated with the development of diabetes.