Download PowerPoint-Präsentation

Comparative analysis between
Rheumatoid arthritis and arthritis
model – study of the functional components in
expression profiles of synovitis
Irene Ziska1, Marc Bonin1, Jekaterina Kokatjuhha1, Pascal Schendel1, Karsten Mans1, Biljana Smiljanovic1, Till Sörensen1, Andreas Grützkau2,
Bruno Stuhlmüller1, Thomas Häupl1
1
Department of Rheumatology and Clinical Immunology, Charité University Hospital, Berlin, Germany, 2 German Arthritis Research Center, Berlin, Germany
Background and Objective:
Conclusion:
Microarray experiments can be used to compare samples of healthy and diseased
patients. The objective is to identify up or down regulated genes in the diseased
sample which could be the key to understand the disease and develop a treatment.
The Problem is that the taken samples often not only consist of one but of multiple
different cell types and this composition can greatly differ between the healthy and
the diseased sample because of the migration of immune cells. Therefore it is
important to distinguish if an expression level of a gene is changed due to regulation
or as a result of a change in the cell composition. (Fig. 3)
In summary a model to differentiate between a change in expression level based on
regulation and a change due to a different cell composition was developed and
successfully applied for synovitis. The data indicate differences between human
disease and animal model and can provide important information on the selection of
appropriate animal model for the development of therapeutic targets in human
diseases.
Figure 2
Materials and Methods:
Transcriptomes of immune cell types including T-cells, B-cells, NK-Cells, monocytes
and granulocytes as well as transcriptomes of synovial tissue biopsies from patients
with rheumatoid arthritis and osteoarthritis were generated using the Affymetrix
platform HG-U133Plus 2.0. The MG-4302 GeneChip transcriptomes of the same panel
of cells (GSE6506) and synovial tissues from the collagen induced arthritis model in
DBA-1 mice (GSE13071) were selected from the GEO database.
Results:
We developed a model to compute cell fractions for each sample by using cell-specific
marker genes from reference transcriptomes for each cell type involved. (Fig. 1) Based
on these fractions a virtual profile was computed for each sample that represents the
sample-specific mixed cell profile based on the reference transcriptomes and thus
without the disease-related regulation of genes. These so called virtual signals were
compared to the corresponding real signal to estimated the level of gene regulation.
The given model was used to compare the gene regulation in the human disease of
rheumatoid arthritis with the collagen induced arthritis model in DBA-1 mice. This
new analysis technique revealed activity dependent infiltration of monocytes into the
synovial tissue in the DBA-1 mouse model. In contrast to the mouse model, the
human disease transcriptomes included patterns of T-cells and B-cells as well as
monocytes. With respect to the regulatory changes, there were significant differences
not only by quantity but also by quality. For example differences especially in
chemokine regulation like CXCL13 between human disease and animal model are in
accordance with the observed difference in cell type infiltration. (Fig. 2)
Figure 1
Figure 2: The virtual signals that were calculated by the model were used to find genes that have a change in their signal due to a
regulation and not only because the cell composition has changed. Afterwards the real signals of these genes were clustered and
compared to the signatures of TNF stimulated synovial fibroblasts. In both human (l.) and the mouse model (r.) similarities between
the up regulated genes in RA and accordingly in the arthritis model and the TNF stimulation are a sign of a good filtering because
anti-TNF is already used in the therapy of rheumatoid arthritis. Additionally the similarities with the signatures of the immune cells
are quite low. Therefore in the list of genes that was the result of the filtering no genes were included whose signal values were
only changed due to migrated immune cells. That is a fact which supports the correct function of the developed model.
Figure 3
a
Figure 3a:
Gene regulation vs. change of
the cell composition.
b
Figure 1: In the figures the cell fractions are shown (human l., mouse r.) that were calculated by the given model. The mean values
for each group are highlighted. In both human and in the mouse model the cell fractions of synovial tissue are reduced in the
diseased probes. In contrast the cell fractions of immune cells are increased. Monocytes have the greatest cell fraction compared
to the other immune cells. In human for all immune cells an increase of the cell fraction can be observed. But in the mouse model
only the fractions of monocytes, T-cells and NK cells have changed. Therefore the greatest difference between human disease and
animal model is the unchanged fraction of the B-cells in the mouse model because the B-cells play an important role in rheumatoid
arthritis. All in all there are differences between the cell compositions of healthy and diseased probes and differences between
human and mouse model that could be very important for drug designing and testing therapies in the given mouse model.
Contacts:
Acknowledgement: BTCure IMI grant agreement no. 115142
ArthroMark grant no 01EC1009A
regulation
change in the cell composition
Figure 3b:
Shown is the measured signal
of a gene for OA and RA.
Without calculating the FPCA
it is not possible to know the
cell composition. After the
FPCA, it is clear that the
signal in the RA is strongly
influenced by monocytes and
the synovial tissue which
have migrated into the tissue.
Marc Bonin
Department of Rheumatology
and Clinical Immunology
Charité University Hospital
Charitéplatz 1
D-10117 Berlin Germany
Tel: +49(0) 30 450 513 296
Fax: +49(0) 30 450 513 968
E-Mail: [email protected]
Web: www.charite-bioinformatik.de
www.charite-bioinformatik.de