Identification number of the project: 2018-1.3.1-VKE-2018-00024
Title: Multiparametric immunophenotypic study to characterize diabetes patients
Expected duration of the project: 2018.10.01- 2021.09.30.
Cost of project: 833 558 791 Ft
Funding amount: 647 544 171 Ft
Partners of consortium: TS Lab Trade and Service Limited Liability Company, AVIDIN Ltd., HR-Pharma Ltd. and HAS Biological Research Centre
Project summary: Genetic predisposition and life style management contribute to the development of type 2 diabetes mellitus (T2DM). The most frequent complications are cardiovascular diseases, nephropathy, neuropathy, eye damage, skin damage and higher incidence of Alzheimer disease. In order to dissect the systemic patho-mechanisms and predict the evaluation of complications or estimate the benefit (or failure) of a given therapy we need to identify novel markers.
The current project proposal investigates the gene expression pattern by single cell genomics and the proteomic profiling of blood samples of diabetic patients at single cell resolution by mass cytometry. This combinatorial approach could reveal the sub-types of diabetes and the severity of complications. The consortium has access to the cutting-edge mass cytometry technology which is able to analyze single cells stained by heavy metal labeled antibodies. The project aims to classify diabetic patients regarding symptoms and complications associated with a given immune-phenotype based on the multiparametric characterization by mass cytometry and single cell genomics. The consortium intends to establish complex immune panels which can later be developed for diagnostic products. Avidin Ltd. will analyze both animal and human samples by its own high-throughput genetic assays. The novelty of the project is the high dimensional characterisation of the leukocyte sub-populations which could not be done with former technologies prior to the era of mass cytometry. Smaller changes in the percentages of leukocyte sub-types could be detected by mass cytometry which could predict either the severity of diabetes or the probability of certian complications. Ultimate aim is to create and test a diabetes specific immune panel.