Publishable final activity Report
Project 018733 PREDICTIONS
Specific Targeted Research Project
FP6-2004-LIFESCIHEALTH-5
The Identification of Risk Factors for the Development of Diabetic Nephropathy:
The PREDICTIONS Project
Publishable final activity report PREDICTIONS
Period covered: from
01.12.05
to
28.02.09
Start date of project:
01.12.05
Date of preparation:
27.04.09
Duration:
39 Months
Project coordinator name:
Prof. Dr. Bart Janssen
Project coordinator organisation name:
Ruprecht Karls University Heidelberg
Revision
1
Publishable executive summary
1. Project execution
The PREDICTIONS (PREvention of Diabetic ComplicaTIONS)
Consortium was established in 2004, the project started December 1st,
2005. The general objective of the PREDICITONS Project was to
develop improved strategies for the prevention and management of
diabetic nephropathy (DN).
The main question was “Which biomarkers are
associated with the risk to develop DN?”. To Contact:
Project Co-ordinator:
this end, the problem of DN as a major
Prof. Dr. Bart Janssen
diabetic vascular complication was approached
Formerly: University of Heidelberg
Now: Service XS
in a translational research effort on the
Plesmanlaan 1d
genomic, proteomic and clinical level.
2333 BZ Leiden
Specific scientific objectives from translational
b.janssen@servicexs.com
research were to identify pathophysiologically Web site: www.predictions-project.eu
relevant genes and biomarkers correlated with
onset, progression and response to therapy in DN.
Several partners contributed to the work of PREDICTIONS. Coordinator of the study was Prof.
Bart Janssen from the Ruprecht-Karls-University of Heidelberg (Partner 1). Other contractors are
mentioned at the end of this report. A central webpage was used for dissemination and
communication of contractors and interested public (http://www.predictions-project.eu).
The Consortium was formed around Prof. Dr. med. Fokko J. van der Woude who had worked
together with most of the contractors before the start of this project. His premature death on
December 4th, 2006 has to be considered as a major drawback to the Consortium, because
although his functions were taken over by other consortium members his motivating force, his
creative mind and his solutions to problems were frequently missed.
To develop the first comprehensive profile of diabetic nephropathy in type 2 diabetes, several
methodologies were used.
The core of the project was the case-control trial, recruiting retrospectively and prospectively 457
patients in total. Furthermore, samples from patients who had previously undergone therapy trials
were used to evaluate biochemical markers. As not all examinations could be performed in all
patients, the data packages are shown in the scheme.
2
Cover and matching criteria
Medical history
Concomitant medication
Clinical exam
457
Laboratory
Hannover
Polypeptide factors 148
Heidelberg
Carnosinase 207
Warwick
Proteindamage 159
Graz
Vitamins 162
Leiden/Heidelberg
SNP Genotypes 469
Heidelberg 469
Microsatellite Genotypes
Figure 1. Scheme of data packages
There were seven specific scientific and technological objectives of the PREDICTIONS-Project
which will be elaborated on in the text:
1. Independent confirmation of the identification of CNDP1 as a risk factor
2. Re-evaluation of previously proposed genetic variants
3. Expression profiling for the identification of genes associated with the pathogenesis
of DN
4. Analysis of the urinary proteome for the identification of a secretion patterns
associated both with a specific genetic trait and a high-risk vascular profile of
diabetic patients
5. Assessment of biomarkers of protein glycation and oxidative stress as prognostic
factors
6. Exploration of the association between biomarkers and response to treatment
7. Development of a risk model
In 2005 we published data from a genetic study showing that a trinucleotide repeat in exon 2 of
the CNDP1 gene, coding for a leucine repeat in the leader peptide of the carnosinase-1 precursor
is associated with diabetic nephropathy. The shortest allelic form (CNDP1 Mannheim) was more
common in the absence of nephropathy [1].
Concerning the independent confirmation of CNDP1 as a risk factor, in collaboration with the
group of Barry Freedman (Wake Forest University School of Medicine Winston-Salem, NC,
USA), 858 European Americans were examined. It could be shown that the frequency of the 5-5
leucine genotype is more frequent in healthy controls and in diabetic patients without
nephropathy compared to definite DN cases and the combination of definite and presumable DN
cases, therefore confirming our findings[2].
Moreover, we found a null-allele in the CNDP1 gene causing a frame-shift and a non-functional
enzyme [3]. This allele has a frequency of almost 1% in the general population but has not been
observed in DN so far.
To examine the relevance of the CNDP1-genotype in different kidney diseases, 875 dialysis
patients from the NECOSAD cohort (LUMC, Netherlands), 292 dialysis patients from the MIA
cohort (Karolinska institute, Sweden), 158 patients with diabetes from the SMART cohort (UMC
Utrecht, Netherlands) were genotyped. Their genotypes were compared to 732 healthy Caucasian
3
subjects from the NECOSAD cohort and 334 healthy Caucasian subjects from the MIA cohort.
There was no association of the CNDP1 genotype with patients who became dialysis dependent
due to end stage diabetic nephropathy (p=0.29) in the NECOSAD cohort. The latter lack of
association of CNDP1 with end stage DN was confirmed in an independent patient cohort from
the Karolinska Institute (p=0.15). The mortality risk of dialysis patients due to chronic
glomerulonephritis was significantly dependent on their CNDP1 genotype (log rank, p < 0.01).
The CNDP1 genotype was associated with microalbuminuria in patients with diabetes, when
compared to diabetic patients without albuminuria.
Not only CNDP1 genotype was examined, but also functional differences between different
genotypes were further evaluated. As published previously [Janssen et al. 2005], the shortest
allelic form (CNDP1 Mannheim) was associated with lower serum carnosinase levels. To
confirm this finding, special constructs of the leucine repeat were tested in Cos cells. These
invitro studies confirmed that alleles with 4 or 5 leucine repeats have a poorly functioning leader
peptide, leading to a reduced secretion of the protein and reduced carnosinase activity [4].
As we did not expect CNDP1 to be the only DN-causing factor we suspected additional factors to
play an important role in ‘CNDP1- independent’ DN and therefore re-evaluated previously
proposed genetic variants.
This was done in a case-control study: cases were defined as patients with diabetes type 2, a
diabetes duration of at least 5 years, age between 35 and 75 years, presence of macroalbuminuria
(albumin>300mg/day in the urine) and presence of diabetic retinopathy, controls were defined as
patients with diabetes type 2, a diabetes duration of at least 5 years and normoalbuminuria. Cases
and controls were matched for center, sex and diabetes duration. A total of 457 patients could be
examined.
In the application for the PREDICTIONS-Project, the SLC12A3 gene [5] was specially
mentioned, which is, together with CNDP1 the only candidate gene resulting from systematic
genome studies so far. The association with diabetic nephropathy was found in Japanese patients
with type 2 diabetes. Recently, another group [6] could not confirm that a genetic variation at the
SLC12A3 locus explains the risk for advanced diabetic nephropathy in Caucasian type 2
diabetics.
We examined a total of 41 SNP and 5 microsatellite markers in 38 different genes (Table 1). The
single nucleotide polymorphism (SNP) analysis was performed using the Biomark® platform
(Figure 2). Using this 96x96 technology analysing 41 markers in 457 samples, a lot of time and
money could be saved, otherwise more than 200 96-wells plates would have had to be used. The
microsatellite markers were determined using fragment-analysis.
After statistical analysis, due to lack of power after adjusting for multiple testing, no significant
association could be found. On the nominal level however, toll-like receptor 4 (TLR4) was found
to be significant (p=0.006). The Asp299Gly SNP of TLR4, is a functional variant that has not
been reported to be genetically associated with DN before. TLR4 is an activator of the NF-κB
inflammatory pathway.
4
Table 1. Genes examined in the course of PREDICTIONS and their corresponding gene symbol.
Gene Name
Gene Symbol
angiotensin I converting enzyme (peptidyl-dipeptidase A) 1
adducin 1 (alpha)
advanced glycosylation end product-specific receptor
angiotensinogen (serpin peptidase inhibitor, clade A, member 8)
angiotensin II receptor, type 1
Aldose reductase
apolipoprotein E
caldesmon 1
chymase 1, mast cell
carnosine dipeptidase 1 (metallopeptidase M20 family)
cytochrome P450, family 11, subfamily B, polypeptide 2
UniSTS:61895
engulfment and cell motility 1
ectonucleotide pyrophosphatase/phosphodiesterase 1
glyoxalase I
guanine nucleotide binding protein (G protein), beta polypeptide 3
heparan sulfate proteoglycan 2
interleukin 1, beta
interleukin 6 (interferon, beta 2)
chemokine (C-C motif) ligand 2
Matrix metalloproteinase 9
5,10-methylenetetrahydrofolate reductase (NADPH)
nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha
nephrosis 2, idiopathic, steroid-resistant (podocin)
natriuretic peptide precursor A
Neuropeptide Y
Plasminogen activator inhibitor 1
paraoxonase 1
paraoxonase 2
protein kinase C, beta
Pvt1 oncogene (non-protein coding)
solute carrier family 12 (sodium/chloride transporters), member 3
solute carrier family 2 (facilitated glucose transporter), member 1
transforming growth factor, beta 1
toll-like receptor 4
tumor necrosis factor (TNF superfamily, member 2)
TSC22 domain family, member 1
unc-13 homolog B
ACE
ADD1
AGER
AGT
AGTR1
AKR1B1
APOE
CALD1
CMA1
CNDP1
CYP11B2
D10S1435
ELMO1
ENPP1
GLO1
GNB3
HSPG2
IL1B
IL6
MCP1 / CCL2
MMP9
MTHFR
NFKBIA
NPHS2
NPPA
NPY
PAI1
PON1
PON2
PRKCB
PVT1
SLC12A3
SLC2A1/ GLUT1
TGFB1
TLR4
TNF
TSC22D1
UNC13B
Asp299Gly carriers are known to have lower levels of proinflammatory cytokines, acute-phase
reactants, interleukin-6 and fibrinogen. Although these subjects were found to be more
susceptible to severe bacterial infections, they have a lower risk of atherosclerosis, suggestive
evidence that these individuals also have a lower risk for DN.
5
To perform expression profiling for the identification of genes
associated with the pathogenesis of DN partner 3 has established
a methodology to identify genes and thus new genetic markers
involved in the pathogenesis of DN [9]. As biopsy material suitable
for analysis was hard to find through the original foreseen sources,
Partner 3 had to find other sources and finally 24 biopsies could be
retrieved from Dutch Hospitals. After checking whether they were
of suitable quality, kidney biopsies from 24 independent patients
Figure 2. Image of a
with DN were examined to create expression profiles to
48x48 Fluidigm lab-oncharacterise candidate genes. For expression profiling, RNA was
chip
labelled and hybridised to Illumina chips. The gene expression
profiles were analyzed bioinformatically. For each biopsy the CNDP1 genotype was determined,
as well as the mRNA transcription level of CNDP1 and compared to a panel of 3 household
genes. Non supervised gene clustering of these expression profiles was performed and showed
that they were all closely linked together.
The expression level of CNDP1 has been correlated with 9 candidate genes co-upregulated with
CNDP1, none of these genes has been suggested to play a role in diabetic nephropathy yet, and
two of them are even yet unidentified genes. The results from expression profiling will be
evaluated further, as all genes co-upregulated with CNDP1 are potential candidate genes for
protection from diabetic nephropathy.
One of the early symptoms of diabetic nephropathy is the development of albuminuria. Urinary
Proteome analysis is a method to measure proteins excreted in the urine in very little amounts,
even before albuminuria can be found. Analysis of the urinary proteome for the identification
of a secretion pattern associated both with a specific genetic trait and a high-risk vascular
profile of diabetic patients was performed. To this end urine from diabetes type 2 patients with
and without diabetic nephropathy was collected and analysed using capillary electrophoresis
coupled to mass spectrometry (CE-MS).
When examining urine from the patients in the case-control trial, already existing classification
patterns, e.g. for diabetes [10], chronic kidney disease and diabetic nephropathy [11] were
applied in a blinded fashion, and after unblinding accuracy of classification was assessed using an
in-house software of mosaiques Diagnostics. Classification of subjects in the respective groups
(Diabetes yes/no, chronic kidney disease yes/no and diabetic nephropathy yes/no) was accurate,
showing a sensitivity of 98.6% for diabetes classification, specificity and sensitivity values of
97.1 and 88.2 % for the chronic kidney disease classification and Classification performance for
diabetic nephropathy resulted in an AUC value of 0.966.
Patients from previously performed therapy trials with Irbesartan, treated either in a longitudinal
fashion with 300 mg [12] or undergoing high-dose treatment [13] were also evaluated. It could be
demonstrated that the therapy success with 300mg Irbesartan intake over a period of one year can
be proven with the use of proteomic CE-MS analysis. Furthermore, in urine from patients
participating in the longitudinal trial, peptides showing improvement of kidney status of
microalbuminuric type 2 diabetic patients could be identified.
In the patients on high dose Irbesartan, eight potential biomarkers showed a trend to decrease in a
linear and dose dependent manner from microalbuminuric to treated (300,600,900 mg
respectively) to normoalbuminuric type 2 diabetic patients. The fact that four of these eight
identified peptides are uromodulin fragments indicates altered excretion of uromodulin at the
loop of Henle associated with Irbesartan treatment.
6
Due to the late availability of the complete genetic data and the complete clinical data, analysis of
specific secretion patterns associated with a specific genetic trait or a high-risk vascular profile
are ongoing.
The Assessment of biomarkers of protein glycation and oxidative stress as prognostic
factors was addressed in different ways. Partner 10 measured markers of protein glycation in
plasma and urine of diabetic patients with and without diabetic nephropathy as well as patients
undergoing Irbesartan treatment. Manuscripts on those findings are in preparation at the moment.
The presence of diabetic nephropathy did not produce marked changes in protein damage
markers in plasma protein. Rather, urinary outputs of glycation adducts, FL and AGEs, and the
oxidation marker NFK were increased in diabetic nephropathy. This suggest patient with diabetic
nephropathy are suffering increased early and advanced glycation and oxidation in tissues rather
than in plasma.
Exploration of the association between biomarkers and response to treatment: Partner 10
also studied the effect of angiotensin receptor blocker Irbesartan on protein damage markers in
type 2 diabetic patients with early stage nephropathy (microalbuminuria). Irbesartan therapy has
tightened the glomerular filter and decreased the clearance of plasma protein. Protein damage
markers that increased in plasma protein all increased to the same proportionate extent and this is
reflecting decreased clearance of plasma protein. The markers that were unchanged and
decreased indicate that Irbesartan therapy is probably decreasing protein damage of these types in
plasma. This is mostly protein damage by dicarbonyl glycation – markers formed by plasma
protein glycation with glyoxal, methylglyoxal and 3-deoxyglucosone, and protein oxidation
(MetSO) and nitration (3-NT).
It was planned to develop a risk model on the basis of the findings from the re-evaluation of
previously proposed genetic variants, this objective could not be reached as no significant
association could be found. However, urinary proteomics seems to represent a feasible way for
diagnosis of diabetic nephropathy.
There were a couple of other, not yet mentioned, important findings of PREDICTIONS.
Partner 3 performed genetic association analysis on ESRD cohorts, an association with multiple
leucine repeats in the CNDP1 gene was significantly associated with the risk of developing
ESRD in patients with chronic glomerulonephritis (p=0.0006) and with renal vascular disease
(p=0.011) as a primary cause for developing ESRD.
In an animal study, diabetic male Sprague-Dawley rats were unilaterally nephrectomized and
either treated with Carnosine (C), Lisinopril (L), or both (Mix). Controls were untreated, diabetic
(STZ) rats. An Add-on therapy using Carnosine to the standard therapy with ACE-Inhibitors in
this model diminishes albumin excretion, prevents cataract formation and improves glucose
reabsorption.
The data on DN-specific urine-peptides and the results of the in vitro studies have added to
present knowledge on the role of TGF-β and Extra-cellular Matrix accumulation in DN. We
postulated that high glucose in combination with low carnosine levels causes elevated TGF-β
expression and activation of ALK5. This increases ECM assembly. An interim model of this is
depicted in figure 3.
7
Increased collagen transcription might play a role, but reduced breakdown of collagens by
proteases such as MMP9 is a major cause of the ECM accumulation. The genetic analysis of
MMP9 (WP2) has confirmed genetic association of the MMP9 microsatellite with DN, although
only at the nominal level (p=0.02).
This mechanistic approach was used to identify further genes. MMP9, which has been suggested
earlier to be associated with diabetic nephropathy was found to be significant on the nominal
High glucose combined with low carnosine levels
Elevated TGF-ß expression and activation of ALK5 pathway
- Increased collagen transcription and ECM assembly,
- Alternative splicing of ECM transcrips into altered ECM molecules
with a reduced susceptibility to MMP-mediated degradation,
- Inhibition of matrix proteases (e.g. MMP2 and MMP9) by TIMPs
- Increased affinity of ECM receptors (integrins).
Reduced turnover of collagens, excessive accumulation of ECM
Figure 3. Interim model for
TGF-β induced
glomerulosclerosis
glomerulosclerosis
level (p=0.02), confirming these findings. MMP9 functional variants can therefore be considered
risk factors in diabetic nephropathy.
In conclusion, PREDICTIONS has approached diabetic nephropathy in type 2 diabetic patients
from various sides, including genetic, biochemical and proteomic markers as well as mechanistic
models. The contractors have succeeded in identifying potential new biomarkers for diabetic
nephropathy and its different stages. Further detailed research is necessary to evaluate the
identified markers.
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Contractors:
Partner 1a:
Prof. Dr. Bart Janssen (Co-ordinator)
Formerly: Institute of Human Genetics,University of Heidelberg
Now: Service XS, Plesmanlaan 1d, 2333BZ Leiden
Tel. +49-6221-5639568; E-mail: b.janssen@servicexs.com
Partner 1b:
Prof. Dr. Benito Yard
Universitätsmedizin Mannheim, 68135 Mannheim, Germany
Tel. +49 621 383 2340; Email: benito.yard@umm.de
Partner 2:
Prof. Brigitte M. Winklhofer-Roob, M.D.
The University of Graz: A-8010 Graz, Austria
Tel. +43-316-380-5490; Email: brigitte.winklhoferroob@uni-graz.at
Partner 3 :
Dr. Emile De Heer
Leiden University Medical Center, POB 9600, 2300 RC Leiden, The Netherlands,
Tel. +31 71 526 6623; E-mail: e.de_heer@lumc.nl
Partner 4:
Prof. Dr. GJ Navis
Groningen University Medical Center, Hanzeplein 1, Groningen, The Netherlands
Tel. + 31-503612621/4441; E-mail: g.j.navis@int.umcg.nl
Partner 5/Partner 10:
Prof Paul J. Thornalley
University of Warwick, University Hospital, Coventry CV2 2DX, U.K.
Tel. +44 24 7696 8594; Email: P.J.Thornalley@warwick.ac.uk
Partner 6:
Prof. Dr. Ivan Rychlík
Charles University at Prague, 3rd Medical Faculty, 10000 Prague 10, Czech Republic,
Tel. +420-267102657; E-mail: rychlik@cesnet.cz
Partner 7:
Dr. Lise Tarnow
Novo Nordisk (Steno Diabetes Center), DK-2820 Gentofte, Denmark
Tel. +45 44 43 99 52; E-mail: ltar@steno.dk
Partner 8:
Prof Harald Mischak
Mosaiques Diagnostics GmbH, Mellendorfer Str. 7-9, D-30625 Hannover, Germany
Tel. +49-511-554744-15; E-Mail: mischak@mosaiques-diagnostics.com
Partner 9:
Dr. Marcus Woerwag
Woerwag Pharma GmbH & Co. KG, 71034 Boeblingen, Germany
Tel. 07031/6204-13; E-mail: Heidrun.Gaertner@woerwagpharma.de
9
References:
1.
Janssen, B., et al., Carnosine as a protective factor in diabetic nephropathy: association with a
leucine repeat of the carnosinase gene CNDP1. Diabetes, 2005. 54(8): p. 2320-7.
2.
Freedman, B.I., et al., A leucine repeat in the carnosinase gene CNDP1 is associated with
diabetic end-stage renal disease in European Americans. Nephrol Dial Transplant, 2007. 22(4): p.
1131-5.
3.
Zschocke, J., et al., Allelic variation in the CNDP1 gene and its lack of association with longevity
and coronary heart disease. Mech Ageing Dev, 2006. 127(11): p. 817-20.
4.
Riedl, E., et al., A CTG polymorphism in the CNDP1 gene determines the secretion of serum
carnosinase in Cos-7 transfected cells. Diabetes, 2007. 56(9): p. 2410-3.
5.
Tanaka, N., et al., Association of solute carrier family 12 (sodium/chloride) member 3 with diabetic
nephropathy, identified by genome-wide analyses of single nucleotide polymorphisms. Diabetes,
2003. 52(11): p. 2848-53.
6.
Ng, D.P., et al., Genetic variation at the SLC12A3 locus is unlikely to explain risk for advanced
diabetic nephropathy in Caucasians with type 2 diabetes. Nephrol Dial Transplant, 2008. 23(7): p.
2260-4.
7.
Kiechl, S., et al., Toll-like receptor 4 polymorphisms and atherogenesis. N Engl J Med, 2002.
347(3): p. 185-92.
8.
Rudofsky, G., Jr., et al., Asp299Gly and Thr399Ile genotypes of the TLR4 gene are associated
with a reduced prevalence of diabetic neuropathy in patients with type 2 diabetes. Diabetes Care,
2004. 27(1): p. 179-83.
9.
Baelde, H.J., et al., Reduction of VEGF-A and CTGF expression in diabetic nephropathy is
associated with podocyte loss. Kidney Int, 2007. 71(7): p. 637-45.
10.
Snell-Bergeon, J.K., et al., Evaluation of urinary biomarkers for coronary artery disease, diabetes,
and diabetic kidney disease. Diabetes Technol Ther, 2009. 11(1): p. 1-9.
11.
Rossing, K., et al., Urinary proteomics in diabetes and CKD. J Am Soc Nephrol, 2008. 19(7): p.
1283-90.
12.
Parving, H.H., et al., The effect of irbesartan on the development of diabetic nephropathy in
patients with type 2 diabetes. N Engl J Med, 2001. 345(12): p. 870-8.
13.
Rossing, K., et al., Enhanced renoprotective effects of ultrahigh doses of irbesartan in patients
with type 2 diabetes and microalbuminuria. Kidney Int, 2005. 68(3): p. 1190-8.
14.
Rabbani, N., et al., High-dose thiamine therapy for patients with type 2 diabetes and
microalbuminuria: a randomised, double-blind placebo-controlled pilot study. Diabetologia, 2009.
52(2): p. 208-12.
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2. Dissemination and use
- Results from the benfotiamine trial:
Since several years, benfotiamine is known as a pathogenetically based treatment option
in diabetic complications, because it inhibits four noxious glucose metabolite pathways.
Whereas several clinical studies on the efficacy in diabetic neuropathy were performed,
clinical experiences with benfotiamine in diabetic complications like nephropathy,
retinopathy or cardiovascular disturbances were lacking. Therefore, the benfotiamine trial
as part of the PREDICTIONS project was the first clinical study of this compound on
diabetic nephropathy.
The goal of the study, to demonstrate a beneficial effect of benfotiamine in patients under
optimal basic treatment of microalbuminuria (i.e. patients under ACE inhibitors or
angiotensin antagonists) is a real challenge, because this basic treatment usually is very
effective to decrease microalbuminuria. Because this trial is the first study in this
indication, no information was available on patient characteristics especially on renal
parameters. Therefore, patient number calculation was difficult to perform. However, this
pilot study within the PREDICTIONS project will deliver data on relevant renal
parameters as base for a following trial, even if the results do not meet the expectations
(i.e. a beneficial effect of benfotiamine). This is a pre-requisite for further clinical
development of a substance with very good tolerability in an indication with important
impact on the quality of life of the patients and socio-economic burden of European
communities by Wörwag Pharma. The results of this trial are expected in the summer of
2009. Meanwhile, a small pilot study [14] with water soluble thiamine in patients with
diabetic nephropathy confirmed the hypothesis, that vitamin B1 might be helpful in this
disease. These results stress the importance of further studies on this indication and
development of appropriate medicinal drugs containing vitamin B1 or derivatives like
benfotiamine.
- Proteomic analysis with CE-MS:
Proteomic analysis with CE-MS is useful for the early diagnosis and prognosis of diabetic
nephropathy. Mosaiques diagnostics GmbH has already patented the biomarkers for
diabetic nephropathy and has already marketed this in vitro diagnostic (IVD) based on
multidimensional proteome analysis of the biomarkers identified in the project. Marketing
accomplished via DiaPat GmbH, a subsidiary of Mosaiques Diagnostics, which already
markets IVD based on proteome analysis for bladder and prostate cancer, as well as
several renal diseases. Further, Mosaiques diagnostics plans to market the use of this
diagnostic biomarker pattern in clinical trials (Pharmaceutical industry being the
customer), which would result in better stratification of patients/improved inclusion
criteria based on proteome pattern, as well as non-invasive and early detection of
therapeutic benefits, but also potential side effects in these trials.
11