Transcriptomic analysis of human retinal detachment reveals both inflammatory response and photoreceptor death.

Abstract

Retinal detachment often leads to a severe and permanent loss of vision and its therapeutic management remains to this day exclusively surgical. We have used surgical specimens to perform a differential analysis of the transcriptome of human retinal tissues following detachment in order to identify new potential pharmacological targets that could be used in combination with surgery to further improve final outcome.
Statistical analysis reveals major involvement of the immune response in the disease. Interestingly, using a novel approach relying on coordinated expression, the interindividual variation was monitored to unravel a second crucial aspect of the pathological process: the death of photoreceptor cells. Within the genes identified, the expression of the major histocompatibility complex I gene HLA-C enables diagnosis of the disease, while PKD2L1 and SLCO4A1 -which are both down-regulated- act synergistically to provide an estimate of the duration of the retinal detachment process. Our analysis thus reveals the two complementary cellular and molecular aspects linked to retinal detachment: an immune response and the degeneration of photoreceptor cells. We also reveal that the human specimens have a higher clinical value as compared to artificial models that point to IL6 and oxidative stress, not implicated in the surgical specimens studied here.
This systematic analysis confirmed the occurrence of both neurodegeneration and inflammation during retinal detachment, and further identifies precisely the modification of expression of the different genes implicated in these two phenomena. Our data henceforth give a new insight into the disease process and provide a rationale for therapeutic strategies aimed at limiting inflammation and photoreceptor damage associated with retinal detachment and, in turn, improving visual prognosis after retinal surgery.

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Transcriptomic Analysis of Human Retinal Detachment
Reveals Both Inflammatory Response and Photoreceptor
Death
Marie-Noe ¨lle Delyfer1,2,3,4, Wolfgang Raffelsberger5, David Mercier6, Jean-Franc ¸ois Korobelnik4, Alain
Gaudric7, David G. Charteris8, Ramin Tadayoni7, Florence Metge9, Georges Caputo9, Pierre-Olivier
Barale10, Raymond Ripp5, Jean-Denis Muller6, Olivier Poch1,2,3,5, Jose ´-Alain Sahel1,2,3,9,10, Thierry
Le ´veillard1,2,3*
1INSERM, U968, Paris, France, 2UPMC Univ Paris 06, UMR_S 968, Institut de la Vision, Paris, France, 3CNRS, UMR_7210, Paris, France, 4Unite ´ Re ´tine, Uve ´ite et Neuro-
Ophtalmologie, De ´partement d’Ophtalmologie, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France, 5Laboratoire de BioInformatique et Ge ´nomique
Inte ´gratives, CNRS UMR_7104, Institut de Ge ´ne ´tique et de Biologie Mole ´culaire et Cellulaire, Strasbourg, France, 6CEA, LIST, Information, Models and Learning Laboratory,
Gif-sur-Yvette, France, 7De ´partement d’Ophtalmologie, Ho ˆpital Lariboisie `re, Paris, France, 8Vitreo-retinal Unit, Moorfields Eye Hospital, London, United Kingdom,
9Fondation Ophtalmologique Adolphe de Rothschild, Paris, France, 10Centre Ophtalmologique des Quinze-Vingts, Paris, France
Abstract
Background: Retinal detachment often leads to a severe and permanent loss of vision and its therapeutic management
remains to this day exclusively surgical. We have used surgical specimens to perform a differential analysis of the
transcriptome of human retinal tissues following detachment in order to identify new potential pharmacological targets
that could be used in combination with surgery to further improve final outcome.
Methodology/Principal Findings: Statistical analysis reveals major involvement of the immune response in the disease.
Interestingly, using a novel approach relying on coordinated expression, the interindividual variation was monitored to
unravel a second crucial aspect of the pathological process: the death of photoreceptor cells. Within the genes identified,
the expression of the major histocompatibility complex I gene HLA-C enables diagnosis of the disease, while PKD2L1 and
SLCO4A1 -which are both down-regulated- act synergistically to provide an estimate of the duration of the retinal
detachment process. Our analysis thus reveals the two complementary cellular and molecular aspects linked to retinal
detachment: an immune response and the degeneration of photoreceptor cells. We also reveal that the human specimens
have a higher clinical value as compared to artificial models that point to IL6 and oxidative stress, not implicated in the
surgical specimens studied here.
Conclusions/Significance: This systematic analysis confirmed the occurrence of both neurodegeneration and inflammation
during retinal detachment, and further identifies precisely the modification of expression of the different genes implicated
in these two phenomena. Our data henceforth give a new insight into the disease process and provide a rationale for
therapeutic strategies aimed at limiting inflammation and photoreceptor damage associated with retinal detachment and,
in turn, improving visual prognosis after retinal surgery.
Citation: Delyfer M-N, Raffelsberger W, Mercier D, Korobelnik J-F, Gaudric A, et al. (2011) Transcriptomic Analysis of Human Retinal Detachment Reveals Both
Inflammatory Response and Photoreceptor Death. PLoS ONE 6(12): e28791. doi:10.1371/journal.pone.0028791
Editor: Steven Barnes, Dalhousie University, Canada
Received August 31, 2011; Accepted November 15, 2011; Published December 9, 2011
Copyright: ? 2011 Delyfer et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The work was supported by the Institut National de la Sante ´ et de la Recherche Me ´dicale, CNRS, University of Strasbourg and the network Re ´seaux
National de Ge ´nopo ˆles (RNG 209). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: thierry.leveillard@inserm.fr
Introduction
Retinal detachment (RD) is a potentially blinding condition
characterized by the subretinal accumulation of fluid in a space
created between the neurosensory retina at the level of
photoreceptor cells and the underlying retinal pigment epithelium
(RPE). In most cases, RD occurs secondary to a full thickness
retinal break and is hence called ‘‘rhegmatogenous’’ (from the
Greek word rhegma, a ‘‘rent’’). The incidence of RD is strongly
correlated with age, myopia and vitreoretinal degenerations.
Annual incidence is estimated at 10.5/100,000 [1] and the
treatment of rhegmatogenous RD remains to this day exclusively
surgical. However, despite retinal reattachment after surgery,
visual outcome remains below expectation in many cases and
patients often report permanent alterations in colour perception
and/or severe loss of visual acuity due to the loss of photoreceptor
cells [2,3,4,5]. The physical separation of photoreceptors from
RPE cells indeed results in the interuption (disruption) of the
transfer of nutrients to photoreceptors, thereby inducing chronic
disturbances in cellular metabolism. Over a period of few days,
retinal remodeling occurs, photoreceptor outer segments shorten
and progressive death through apoptosis takes place [6,7,8]. The
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use of adjuvant neuroprotective molecules that would limit the
damage to photoreceptors in combination with surgery has hence
been proposed [9]. Besides the loss of photoreceptors secondary to
the detachment itself, an inflammatory response develops during
RD that leads to Proliferative Vitreo-Retinopathy (PVR), a clinical
outcome resulting from the formation of contractile cellular
membranes on both surfaces of the retina and in the vitreous. PVR
in turn accelerates photoreceptor degeneration and may even
cause failure of the retinal reattachment after surgery [2,10]. Pilot
studies aimed at preventing PVR with anti-inflammatory agents
have been conducted, but with only limited success [11,12,13].
The main therapeutic challenge in RD is to limit photoreceptor
cell damage and PVR occurrence (or recurrence). We wished to
identify some of the most appropriate molecules that could be used
efficiently in combination with surgery and improve final visual
outcome. We used here a differential transcriptomic analysis to
identify target genes with modified expression following RD.
Human retinal specimens were collected from patients undergoing
retinal surgery for severe retinal detachment with PVR and
requiring retinectomy using a protocol designed for this study,
whereas normal control retina specimens were obtained from post-
mortem donors. We validated these specimens by measuring via
quantitative RT-PCR the expression of genes known to be
modified by RD. We then performed a global analysis with data
obtained from 19 RD RNA preparations and 19 controls that
were hybridized to Affymetrix genechip arrays. A differential
transcriptomic analysis was used to identify target genes with
modified expression following RD. The data were first treated to
highlight genes with statistical difference between the two groups
(RD and controls) using the false discovery rate (FDR) method. As
a complementary approach, we used the inherent variability
between individuals as information for identifying co-regulated
genes using a method based on mutual information (MI) [14].
Interestingly, we found that using the same set of data, the FDR
method points to the involvement of an inflammatory process
linked to PVR, while the MI method identifies more specifically
genes with a decrease in expression linked to photoreceptor loss.
These data point to novel therapeutic strategies. We further show
that these biomarkers can be used to evaluate the duration of the
retinal detachment process.
Results
Validation of the human retinal detachment specimens
by quantitative RT-PCR
Retinal samples resulting from retinectomy are not used for any
clinical analysis and are considered res nullius and currently
discarded (Table 1). We have used this biological material to
perform a transcriptomic analysis of RD. In order to ease the
recovery of RNA from the surgical specimens, we developed
"jouRNAl" a method that allows RNA conservation between the
surgical blocks and the laboratory. To test the method, we
immersed 1 cm2of porcine retinas in 2.4 ml of 6 M Guanidium
chloride (GHCl) [15], homogenized the specimens and stored
them in two different conditions: i) at room temperature for
72 hours, and ii) at room temperature during 72 hours followed by
storage at 280uC for 6 months. We found that no RNA
degradation had occurred in any of these conditions (Figure 1A).
Quantitative RT-PCR demonstrated no modifications in the
amount of rhodopsin or M-opsin mRNAs during storage
(Figure 1B). The clinical value of the human RD specimens was
assessed by quantitative RT-PCR. Transcripts encoding photore-
ceptor markers were drastically down-regulated in RD samples.
Expression of the four visual pigments (i.e. rhodopsin, S-, M- and
L-cone opsins) is decreased in RD patients by 25, 8, 9 and 8-fold,
respectively as is the rod-specific transducin (Table 2). NXNL1, the
gene encoding the trophic factor Rod-derived Cone Viability
factor (RdCVF) [16,17] is down-regulated 3-fold. Neuronal
markers such as cytochrome oxidase or synaptophysin are also
down-regulated as reported [18]. Apoptosis during RD and PVR
was documented [6,7]. Apoptosis signal-regulating kinase 1
(ASK1), a mitogen-activated protein kinase that plays a role in
oxidative stress [19], is up-regulated 1.9-fold in the RD group
(Table 2). Muller Glial Cells (MGCs) have been shown to
proliferate and become hypertrophic during RD expressing high
level of Glial Fibrillary Acidic Protein (GFAP) [18,20,21], as
confirmed in the specimens analyzed here (7.9-fold increase).
Impaired function of MGCs is correlated with a decrease of
glutamine synthetase (GS) as seen here. During RD, RPE cells are
activated, migrate, dedifferentiate and proliferate at the surface of
the detached retina, exerting contractile forces leading to PVR
[22,23,24]. Hence, whereas RPE cells are not present within the
neural retina in controls, RPE markers are found in the detached
retinas. Markers of migrating dedifferentiated RPE cells, CD68
and the a-smooth actin were increased in RD specimens as
reported [25,26]. PVR associated with severe RD involves both
inflammatory and immune responses [27,28]. The expression of
CD4 and ICAM1 is increased 2-fold and 27-fold respectively
[28,29,30,31]. Matrix MetalloProteinases (MMPs) and their
inhibitors (TIMPs) that take part in the remodeling of the extra-
cellular matrix during PVR [32,33,34,35] are up-regulated in RD
specimens here. Altogether, our quantitative RT-PCR analysis of
genes previously reported to be involved in RD validates the
clinical quality of the specimens.
Global gene expression analysis indicates an
inflammatory process
After the qualification of the specimens, we hybridized 19 RD
and 19 controls RNA preparations to genome array (Affymetrix
U133). We then compared the relative expression for probesets
corresponding to 21 out of 24 of the genes tested by quantitative
RT-PCR. All the examined genes have an expression similar to
the quantification made by RT-PCR (Table 2). The photoreceptor
markers RHO, OPN1SW, PDC and NXNL1 were down-regulated,
while GFAP, GLAST (SLC1A3), ASK1 (MAP3K5) and ICAM1 were
up-regulated (Figure 2A). The overall results correlated when the
Log10 of the RD/Ctrs ratio was plotted for both methodologies
(r2=0.94, Figure 2B). This comparison confirms that the arrays
are representative of the RD process.
We identified 259 probesets differentially expressed using local
FDR [36] (Table S1, fdr259 ps). We observed mostly up-regulated
genes by RD (239/259, 92.3%). In order to rule out that this
results from the use of post-mortem tissues as controls, we
analyzed the interactions between the 259 identified genes in the
STRING database [37]. Many of the up-regulated genes were
related to an inflammatory process, with the highest fold changes
comprising three members of the complement pathway C1QA,
C1QB, C1QG and C3, five members of the major histocompati-
bility complex of class II (MHCII) HLA-A, -B, -E, -F -J, and the
b2-microglobulin (Figure 3). We also tested for enrichment of
Gene Ontology (GO) terms and clusters of terms [38]. The two
clusters with the highest enrichment scores correspond to immune
response and antigen processing (Table 3 and Table S2). The
other enriched clusters may translate the same inflammatory
process, but the last term (Cell death, 2.02) refers to neuronal
degeneration. Thus, the enrichments demonstrate the existence of
an immune response following RD and rule out the possibility that
the prominence of up-regulated genes results from the difference
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in tissue processing. In order to evaluate the effect of RD duration
on gene expression, we subdivided the RD specimens into early
(RD#1 month), mid-term (1.RD#3 months) and late (RD.3
months) classes, according to Table 1. Here again, the analysis was
dominated by up-regulated genes (Table S2).
Co-regulated genes reveal photoreceptor dysfunction
and death
The graphic representation of the data using Retinobase [39]
shows the all the specimens with RD have an elevated expression
of b2-microglobulin (B2M), likely corresponding to the degree of
inflammatory response (Figure 4A), while rhodopsin (RHO) and
NXNL1 are down-regulated. By closely examining the interindi-
vidual variability (Figure 4B and C), it seems that the patterns of
these two genes somehow matched, in agreement with the fact that
NXNL1 is expressed in a rod-dependent manner [16,40]. We used
the information encoded by the interindividual variability to
identify genes that are co-regulated using a novel approach based
on mutual information (MI). MI relies on the concept that if two
genes are co-regulated, the expression pattern of the first provides
information that predicts the expression pattern of the second [14].
When applied to the three stratified classes of RD specimens,
early, mid-term and late, this method selected 266 probesets
having a normalized MI value above a threshold of 0.5 (Figure
S1). Contrary to the FDR analysis, 58.6% of the 266 probesets
points to genes that are down-regulated in RD.
Table 1. Clinical characteristics of patients with retinal detachment (RD).
Age Sex Prior RD surgical proceduresTotal RD duration PVR at surgery
70M 1 (Vitrectomy + silicone oil tamponade)
1 (Vitrectomy + gas)
1 (Vitrectomy + gas)
1 (Vitrectomy + gas)
1 (Vitrectomy + silicone oil tamponade)
1 week CA2
39F 3 weeks CP2–CA2
55F1 month CP4–CA3
73F1 month CA2
36M 1 monthCP2–CA2
66M No2 months CP12–CA10
54M 2 [(Cryotherapy + gas)/
(Vitrectomy + silicone oil tamponade)]
2 months CP2–CA3
23MNo 2 months CP4–CA4
69M1 (Vitrectomy + silicone oil tamponade)
1 (Vitrectomy + silicone oil tamponade)
1 (Vitrectomy + silicone oil tamponade)
2 [(Cryo + scleral buckling)/
Vitrectomy + gas)]
3 months CP2–CA2
65M 3 months CA3
58M 3 monthsCP2–CA2
55M3 monthsCP12–CA9
31MNo
.3 monthsCP4
74FNo4 monthsCP3–CA2
32M2 [(Cryo + scleral buckling)/
Vitrectomy + gas)]
2 [(Cryo + scleral buckling)/
Vitrectomy + gas)]
1 (Vitrectomy + gas)
2 [(Cryo + scleral buckling)/
Vitrectomy + gas)]
6 monthsCP3–CA3
59F6 months CP3–CA3
53M7 monthsCP4–CA4
49M 1 yearCA4
30M No1 yearCP12–CA8
Proliferative vitreoretinopathy (PVR) is graded using the up-dated classification of the Retina Society Terminology Committee by Machemer [22]. There are three grades
describing increasing severity of the disease: A, B and C. In patients that all required retinectomy, RDs are always associated with grade C of PVR. Posterior (P) and
anterior (A) location of the proliferations are specified. The extent of the abnormalities is detailed by using clock hours. Hence, CP3–CA2 means grade C of PVR with
both posterior (P) and anterior (A) abnormalities extended over three (CP3, meaning J) and two (CA2) clock hours respectively.
doi:10.1371/journal.pone.0028791.t001
Figure 1. The Kit "jouRNAl" for RNA conservation. (A) Denaturing
agarose gel electrophoresis of RNAs purified from porcine retinas.
Retinas were immerged in 2.4 ml of 6 M GHCl and purified: i)
immediately after immersion (H0) or ii) after storage at room
temperature during 72 hours (H72) or iii) after storage at room
temperature during 72 hours and then at -80uC during 6 months
(M6). 28 S and 18 S ribosomal RNA species have a ratio of 2 indicating
the absence of RNA degradation. (B). Agarose gel electrophoresis of RT-
PCR amplification products (b-actin, Rhodopsin, M-cone opsin). Similar
products were obtained for the 3 samples.
doi:10.1371/journal.pone.0028791.g001
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Identification of three biomarkers for retinal detachment
Since the expression profiles of the 266 probesets are all linked
together, we used an iterative calculation to identify the minimal
number of probesets that will fully describe the phenomenon (see
methods). The three probesets 216526_x_at (HLA-C), 221061_at
(PKD2L1) and 219911_s_at (SLCO4A1) are sufficient to describe
the whole dataset. These probesets, among which two are down-
regulated in RD, score both correlated and anticorrelated genes.
We examined the expression of these three probesets with the
delay after RD. We noticed that the expression of both PKD2L1
and SLCO4A1 is particularly low in the late RD group (Figure 5).
Interestingly, while the addition of PKD2L1 to HLA-C reduced the
combined normalized MI from 0.603 to 0.596, the inclusion of the
third probeset (SLCO4A1) resulted in an increase of the normalized
MI to 0.611 above the value of HLA-C alone. It seems that
PKD2L1 and SLCO4A1 act in a synergistic manner. This indicates
that the up-regulation of HLA-C is strictly correlated with RD and
that the down-regulation of SLCO4A1 and PKD2L1 is informative
for the duration of RD with lower expression of SLCO4A1 at early
stage and of PKD2L1 at the late stage.
The mutual information analysis points to photoreceptor
degeneration
The presence of the NXNL1 and five photoreceptor specific genes
(ABCA4, RDH12, CNGB1, SAG and CUCA1C), whose mutations
cause inherited retinal degenerations, in the list of 156 down-
regulated probesets with high MI suggests that MI identifies events
linked to photoreceptor dysfunction or degeneration. These 156
probesets were examined for their expression in a genetic model of
rod photoreceptor degeneration, the rd1 mouse. In this model the
recessive mutation of Pde6b leads to a rapid degeneration of rods
[41]. By 35 post-natal days (PN), all the rods (half of the neurons of
the retina) are lost [42]. We performed a global analysis of the rd1
neural retina using Affymetrix technology (see methods). We
examined the expression of 44 mouse orthologues of genes down-
regulated in RD indentified by MI analysis and for which the
expression value was .20 (Table 4). It should be noticed that their
ratios outer retina/neural retina has an average of 1.19. Since the
outer retina is the portion of the neural retina containing the
photoreceptors, it indicates that this list is enriched for genes rather
specifically expressed by photoreceptors in the retina [43]. Within
this dataset, the expression in the wild-type (wt) and rd1 retina at
PN35 of a subset of 25 orthologous genes down-regulated in RD
and having the highest MI score was compared to 25 up-regulated
genes with the highest FDR value (Figure S2). We found that the
average ratio wt/rd1 is 2.89 for genes down-regulated in RD and
0.85 for those that are up-regulated, suggesting a certain degree of
conservation in the pathways involved in RD and photoreceptor
degeneration in the rd1 model. The kinetic of expression of the
protein phosphatase Ppef2 increases from PN1 to PN8 for both wt
and rd1 during the process of normal post natal maturation of the
retina. From PN11 to PN35 the difference of expression between
the rd1 versus the wt mouse is correlated with rod degeneration
(Figure 6A), as for the protein phosphatase Ppp3cc (Figure 6B). This
Table 2. Comparison of the expression measured by quantitative RT-PCR and by hybridization to array.
Gene Name Gene Symbol
QRT-PCR
Probeset n6
Affymetrix
RD/Ctrs SEpvalueRD/Ctrs SEpvalue
Apoptosis
ASK1 MAP3K51.840.09
,0.005 203836_s_at1.650.032.5e–5
Cellular Stress
AlphaB crystallinCRYAB 0.910.04 NS209283_at1.35 0.034.3e–3
Glial Cell Response
GFAPGFAP 7.96 1.00
,0.0005203540_at 12.49 0.395.4e–10
GLASTSLC1A31.38 0.12 NS202800_at2.00 0.04 2.3e–8
Glutamine synthetase GLUL0.400.02
,0.00005 215001_s_at0.700.019.3e–8
RPE Cell Response
CD68CD6811.661.03
,0.005NU
Alpha-smooth muscle actinACTA28.390.32
,0.05 200974_at8.100.44 2.5e–4
Inflammatory and Immune Mediators
CD4 CD41.820.11
,0.05203547_at1.720.05 1.6e–2
Intercellular adhesion molecule 1ICAM127.244.17
,0.0005 202638_s_at17.100.77 3.0e–9
Tissue Remodeling
Matrix MetalloProteinase 2MMP2 3.860.32
,0.0005201069_at 4.650.12 1.0e–9
Tissue Inhibitor Metalloproteinase 1TIMP19.110.51
,0.0001201666_at9.900.23 1.8e–7
Cellular Proliferation and Differentiation
PCNAPCNA0.260.03
,0.0005201202_at0.480.01 3.6e–8
c-fos FOS 0.22 0.04
,0.05209189_at0.490.041.57
Ornithine decarboxylaseODC11.370.11 NS200790_at1.280.02 3.0e–3
Cyclin A1CCNA10.680.10 NSNU
Cyclin D1CCND1 6.09
,0.01 208712_at 4.000.14 1.7e–8
NS, non statistically significant. NU, Not used since the probesets 203507_at (CD68) and 205899_at (CCNA1) have relative expression value ,10 in any condition.
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is even observed earlier, from PN10 for the receptor accessory gene
Reep6 (Figure 6C), and from PN12 for the dopamine receptor Drd4
(Figure 6D). The expression of the Taurine transporter Slc6a6 in the
mutant retina is lagging behind wt from PN11 to PN35 (Figure 6E)
and from PN14 for the phosphodiesterase Pde6d (Figure 6F). The
expression of these target genes, down-regulated in RD, correlated
with the degeneration of rod photoreceptors in the rd1 mouse. The
comparison with the rd1 transcriptome supports the fact that the
mutual information identifies target genes related to the process of
photoreceptor degeneration or dysfunction in RD.
Discussion
The mechanism involved in retinal detachment at the genome
level has only been addressed to date on animal models of the
pathology [44,45,46]. These models involve the artificial detach-
ment of the retina using a surgical procedure and do not address
the human situation, with an accidentally detached retina. This
artificial setting most likely explains why the IL6 and the Aryl
hydrocarbon receptor oxidative stress pathways highlighted in a
rat study [44] are not reproduced the clinical specimens studied
here (Table S3). This difference seriously questions the physio-
pathological relevance of such animal models. The human tissues
have only been studied in vitro [47]. To our knowledge, it is the first
time that the transcriptome of human clinical specimens have been
analyzed providing results that can be directly interpreted in
medical terms. Transcriptomics analysis of human retinal
detachment reveals the existence of two pathophysiological
processes: 1) an inflammatory response that is most likely
implicated in 2) the damage to the photoreceptor cells. In the
retina, inflammatory mediators might also be acting in a paracrine
manner to affect neighboring cells and triggering the PVR process
Figure 3. Interactomic analysis of the genes identified by FDR. The interaction between genes identified using the FDR methods. The circles
on the left and on the right have been named according to their enrichment in gene ontology terms.
doi:10.1371/journal.pone.0028791.g003
Figure 2. Comparison QRT-PCR/Array results. (A) Expression of Affymetrix probesets for mRNA tested by quantitative RT-PCR. The histograms
display controls (Ctrs) and retinal detachment (RD) for each specimen. The horizontal line is the average. (B) Graph displaying the Log10 of ratio
retinal detachments versus controls (RD/Ctrs). CD4 and Cyclin A1 (CCNA1) were excluded from the analysis since the values were inferior to 10 in any
conditions, while the cone long and middle wave opsin genes (OPN1LW and OPN1MW) were averaged since the Affymetrix probeset does not
distinguish the two genes in tandem on the genome.
doi:10.1371/journal.pone.0028791.g002
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[48]. These two aspects were captured by two successive but finally
complementary analyses of the microarray data. The classic FDR
method identified genes that globally participate in the inflam-
matory response. This method is particularly suited for analyzing
the transcriptome of animal models of disease. One reason is that
these animals are often inbred strains in which the variability
within an experimental group is considered as non-informative
and consequently averaged. In the case of surgical specimens, each
individual displays a retinal transcriptome that not only reflects the
disease but is also modulated by the activity of modifier genes in
the genome and by differences in environmental exposure, or
treatment. We have used this interindividual variability as a guide
to identifying co-regulated genes using MI, a method developed to
detect dependencies between variables [14]. MI highlights the
existence of a coordinated program linked to the degeneration of
photoreceptor cells. The two processes are correlated as seen by
the fact that HLA-C, an up-regulated gene involved in the
inflammatory response, is anti-correlated to down-regulated genes
PKD2L1 and SLCO4A1, markers of photoreceptor death. What
could explain why the analysis of the same set of expression data
by these two methods should reveal two different but comple-
mentary aspects of the pathophysiological process? A critical
difference in the nature of these two events is likely translated into
a alternative dynamics of the gene expression changes. The
inflammatory response is massive and results from the induction of
genes from an unstimulated state. This in turn explains the high
ratio (Fold change) observed when comparing RD versus controls
and favours the statistical significance and the identification using
FDR, even when the three stages of the disease were considered.
For example ICAM1, OSMR and ITGB2, all involved in
inflammation are identified by the FDR, but not the MI method
(Figure 7A). On the opposite side, photoreceptor degeneration
results in the loss of expression (called here down-regulation) of
photoreceptor-enriched mRNAs, an on/off situation with an
amplitude limited by the expression level at start, i.e. in normal
condition (controls). This limitation of the amplitude is likely to
impair the statistical significance and results in the low number of
down-regulated genes of at least two-fold as identified by the FDR
method. For example, GUCA1C, ABCA4 and CNGB1 were all
detected by the MI, but not the FDR method (Figure 7B). This
ordered process is most likely variable from one individual to the
other in relation to the stage of the disease, genetic susceptibility
and environmental conditions (e.g. medication). This explains why
some of the photoreceptor-specific genes do not achieve statistical
significance, but also implies that their expression is coordinated
within each individual specimen. Here the ratio (Average Ctrs)/
RD of GUCA1C and ATPA4 for all RD patients are correlated
(r2=0.95, Figure 7D). Conversely, the immune response involves
the activation of a cascade of genes expressed by cells invading the
Table 3. Enrichment scores of clusters of Gene Ontology
terms for targeted identified by FDR or MI.
Enrichment Score Cluster description
259 targets selected with FDR
8.77Immune response
8.31 Antigen processing
7.23 Response to stress
3.41Signal transduction
2.55 Carbohydrate binding
2.48Cell morphogenesis
2.41Membrane
2.02Cell death
266 targets selected with MI
4.58Antigen processing and presentation
2.90Visual perception
1.83 Organelle outer membrane
1.50Membrane docking
1.35Phototransduction
doi:10.1371/journal.pone.0028791.t003
Figure 4. Expression of B2M, RHO and NXNL1 in a radar graph
display. The graph has been designed using Retinobase. The controls
(N1 to N19) and the retinal detached specimens (RD1 to RD19) are
displayed on the left and the right of the radars respectively.
doi:10.1371/journal.pone.0028791.g004
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retina and emitting signals that result in non linear variations,
translated into less coordination and into induction of the various
members of this signalling pathway within each individual. This
finally results in a loose co-regulation that is detrimental to the
mutual information analysis. Here the ratios RD/(Average Ctrs)
for ICAM1 and OSMR are not correlated (r2=0.39, Figure 7C).
From a mechanistic point of view, one of the biomarkers HLA-C
measures the state of inflammatory response, and another,
SLCO4A1, scores photoreceptor degeneration in all three sub-
groups of RD. The anion transporter SLCO4A1 is largely
distributed in the body but is expressed in a rod-dependent
manner in the mouse retina (result not shown), so it is likely that its
down-regulation is related to a disturbance of efflux of ions into the
detached retina. The TRP channel family member PKD2L1 is
involved in sensing acidic taste [49]. Its down-regulation in the late
class of RD may be related to an extended damage to the retina
(Fig 4B). Its role in the retina is unknown but its expression is
rather eye-specific (UniGene Hs.159241) and may represent a
candidate gene for inherited retinal dystrophies, as TRPM1 was
found to be involved in congenital stationary night blindness [50]
(Figure 5).
From a therapeutic point of view, identifying these new targets
implicated either in photoreceptor cell degeneration and/or in
inflammation response is a key step towards achieving a current
challenge in RD management, the development of adjuvant
therapies. We show here that photoreceptor degeneration during
RD proceeds through mechanisms shared with a model of
inherited photoreceptor degeneration, the rd1 mouse. This
suggests that neuroprotective strategies developed for treating
retinitis pigmentosa to prevent photoreceptor cell death could be
used as adjuvant therapy for RD, this includes for example, the use
of the RdCVF protein [40]. As shown in table 4 and Fig. 6, the loss
of expression of the following genes was observed similarly in both
conditions: dopamine receptor D4 (Drd4), receptor expression
enhancing protein 6 (Reep6), taurine transporter Slc6a6, protein
phosphatase EF-hand calcium binding domain 2 (Ppef2) and
protein phosphatase 3 (Ppp3cc). For target genes expressed by the
photoreceptor themselves, such as DRD4 and PPEF2 [51,52,53], it
is difficult to conclude using the data reported here whether the
loss of their expression is correlated to directly to the loss of
photoreceptors or to the mechanism of cell death. Down-
regulation of PPEF2 gene could both reflect and/or accelerate
the degenerative process, and the use of DRD4 agonists may be
beneficial.
PPP3CC encodes for the gamma subunit of the protein
phosphatases 3 (PPP3), one of the major serine/threonine
phosphatases in the brain. PPP3 dephosphorylates the TAU
protein that is involved in forming neurotoxic deposits in the brain
of patients suffering from Alzheimer’s disease [54,55]. The
phosphorylation of TAU is a hallmark of the process leading to
the formation of neurofibrillary tangle made of hyperphosphory-
lated TAU [56]. Interestingly, we reported recently that TAU is
hyperphosphorylated in the retinal degeneration mouse model
carrying an inactivation of the Nxnl1 gene encoding the cone
viability factor RdCVF [57]. Here, we show that Ppp3cc expression
is down-regulated in the rd1 retina (Fig 7B). As PPP3CC
participates in TAU homeostasis, its decrease during retinal
degeneration, either due to inherited condition (rd1) or to retinal
detachment (RD), may induce TAU hyperphosphorylation and
further accelerate neuronal death through TAU fibrillization.
Inhibition of TAU phosphorylation could henceforth represent
means for slowing down photoreceptor degeneration during RD
using either molecules that stimulate PPP3 phosphatase activity or
other inhibitors of TAU phosphorylation such as RdCVFL [57].
Another lead is provided by SLC6A6 expression. Taurine is an
amino acid that plays essential roles during the development of the
central nervous system, and in the maintenance of mature neural
tissues. Taurine inhibits light-induced lipid peroxidation and
protects rod photoreceptors [58]. Taurine transporter knockout
mice (slc6a6-/- or Taut-/- mice) exhibit decreased taurine levels in
many tissues and an age-dependent degeneration of photoreceptor
cells by apoptosis leading to blindness at an early age. [59]. During
RD, the long-lasting separation of the photoreceptors from the
underlying RPE is associated with a decrease of Slc6a6 expression
that could participate in their loss through apoptosis. The over-
expression of Slc6a6 could represent a way of slowing down
photoreceptor degeneration during RD.
In summary, our work sheds new light on the pathophysiolog-
ical events that occur following human retinal detachment and
raises new targets for a pharmacologic adjuvant therapy to be
combined with the current surgical management of RD. Further
studies on animal models of RD will be needed before strategies
using the target genes identified here can be applied to RD
therapeutic management in clinical trials.
Materials and Methods
Patients and control specimens
A total of 56 consecutive patients with rhegmatogenous retinal
detachment (RD), and for which pars plana vitrectomy associated
with large peripheral retinectomy was considered necessary, were
investigated in five departments of ophthalmology. Indications for
retinectomy in eyes with RD were failure of retinal reattachment
by conventional methods and/or severe proliferative vitreoretino-
pathy (PVR). Patients with a history of diabetes, trauma or any
associated concurrent eye condition such as vitreous haemorrhage,
glaucoma, infection or uveitis were excluded. The severity of PVR
was graded according to the updated classification of the Retina
Society Terminology Committee [22]. Data concerning prior
surgeries, duration of retinal detachment and severity of PVR were
documented. Patients included in the study had given their
informed consent and the study complied with the Declaration of
Helsinki. The patients from UK have given their written consent.
For the French patients, the Comite ´ consultative pour la
Figure 5. The role of the three identified biomarkers HLA-C,
PKD2L1 and SLCO4A1 as classifiers. Expression of the three RD
markers HLA-C, PKD2L1 and SLCO4A1 in the specimens. The black line
represents the classes that are: controls, early, RD#1 month, mid-term,
1.RD#3 months and late, RD .3 months.
doi:10.1371/journal.pone.0028791.g005
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protection des personnes dans la recherche biome ´dicale advised
that since the specimens are res nullius (Code civil art. 539), a
written consent is not required. The ethic committees (Comite ´
consultative pour la protection des personnes dans la recherche ´
biome ´dicale) and the British committee (Moorsfields Eye Hospital)
Moorsfields Eye Hospital) approved the study. Retinal samples
Table 4. A Subset of down-regulated genes identified by mutual information analysis.
Gene Name Gene Symbol Affymetrix OR/NR
ATP-binding cassette, sub-family A, member 4ABCA4 97730_at1.57
Adducin 1 (alpha) ADD194535_at 1.01
A kinase (PRKA) anchor protein 1 AKAP197368_at1.15
Adaptor-related protein complex 1, gamma 1 subunitAP1G1103242_at 1.20
Rho GTPase activating protein 5 ARHGAP5 92247_at1.22
ATPase family, AAA domain containing 2B ATAD2B93426_at 1.43
Carbonic anhydrase XIV CA1498079_at0.63
Calcium channel, voltage-dependent, beta 2 subunitCACNB2 100757_at1.58
Calsequestrin 1 CASQ1102426_at0.99
Dopamine receptor D4 DRD497755_at1.07
Estrogen-related receptor betaESRRB 100301_at1.27
Enhancer of zeste homolog 1 (Drosophila)EZH1100486_at 1.71
UDP-N-acetyl-alpha-D-galactosamineGALNT297553_at 0.95
Heat shock protein 90kDa alpha (cytosolic), class A member 1 HSP90AA195282_at 1.24
Kinesin family member 1B KIF1B160871_at 1.25
Leucine-rich repeats and calponin homology (CH) domain containing 4 LRCH4104151_at1.18
Membrane-bound transcription factor peptidaseMBTPS1 95754_at0.88
Myosin, light chain 6MYL6 97542_at 1.04
NADH dehydrogenase (ubiquinone) 1 alpha subcomplexNDUFA4 160477_at0.95
Poly(A) binding protein interacting protein 2BPAIP2B96158_at 1.06
Phosphodiesterase 6DPDE6D160602_at 1.32
6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 2 PFKFB298329_at1.44
Phospholipase A2, group V PLA2G5101328_at1.17
Polymerase (DNA-directed), epsilon 4 POLE4 95121_at0.90
Protein phosphatase, EF-hand calcium binding domain 2 PPEF2100317_at 1.77
Protein phosphatase 1, catalytic subunit, gamma isoform PPP1CC101482_at 1.21
Protein phosphatase 3 (formerly 2B), catalytic subunit, gamma isoform PPP3CC 160948_at1.25
PTC7 protein phosphatase homolog (S. cerevisiae)PPTC7 99503_at0.81
PRP4 pre-mRNA processing factor 4 homolog B (yeast) PRPF4B 102017_at1.29
ParvalbuminPVALB96719_i_at 0.86
Renal tumor antigen MOKRAGE 104166_at 1.14
Receptor accessory protein 6 REEP696134_at1.65
Retinal G protein coupled receptor RGR95331_at 0.94
Ribosomal RNA processing 1 homolog B (S. cerevisiae) RRP1B 93130_at 1.20
S-antigen; retina and pineal gland (arrestin) SAG94150_at1.16
Splicing factor, arginine/serine-rich 3SFRS3 101004_f_at1.58
Solute carrier family 25 SLC25A493084_at0.84
Solute carrier family 4, sodium bicarbonate cotransporter, member 7SLC4A7 93471_at1.82
Solute carrier family 6SLC6A697383_at1.09
Serine palmitoyltransferase, long chain base subunit 2SPTLC2100893_at1.09
Synovial sarcoma, X breakpoint 2 interacting protein SSX2IP96723_f_at1.02
Syntaxin binding protein 1STXBP1 97983_s_at1.36
T-complex-associated-testis-expressed 3TCTE399134_at1.16
Ubiquinol-cytochrome c reductase binding proteinUQCRB 95472_f_at0.90
OR, outer retina. NR, neural retina.
doi:10.1371/journal.pone.0028791.t004
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were obtained through standard three-port 20-Gauge pars plana
vitrectomy: a conventional surgical procedure aimed at removing
the vitreous to allow retinal surgery. Vitreous was first entirely
removed and an intra-ocular diathermy was performed in the area
of retinectomy to prevent hemorrhages. Retinectomy was
performed after complete posterior hyaloid dissection and
membrane peeling of PVR. The vitreotome was then rinsed by
aspiration of 10 ml of BSSH (Balanced Salt Solution isotonic to the
tissues of the eye, Alcon Laboratories, Inc., Fort Worth, TX). The
aspiration line of the vitreotome was then connected to a 10 ml
syringe and the retinectomy performed using the manual suction.
Retinal fragments of detached retina were collected into the
syringe filled with BSSH. The fragments were rapidly pelleted at
the bottom of the syringe, the buffer discarded and retinal samples
were immersed in Guanidium chloride solution (see below),
homogenized and sent to the laboratory for RNA purification.
Among the 56 samples, only 19 were retained for further analyses
either due to insufficient quantities of RNA (less than 5 mg for 35
samples) or to partial RNA degradation (2 samples). Out of 19
residual patients, 14 were men and 5 were women (Table 1) with a
mean age of 52 years (range 23–74 years). Human retinal
specimens used as controls were post-mortem specimens collected
within 12 hours following death of patients with no past medical
history of eye disease or diabetes and obtained at the Cornea Bank
of Amsterdam (The Netherlands). After corneal removal for
transplantation purposes, the remaining eye tissue was immedi-
ately dissected in BSSH, and the retina cautiously separated from
both vitreous body and retinal pigment epithelium (RPE). Only
peripheral neural retina was considered for further analyses in
order to match the surgical specimens. Nineteen samples were
collected from 19 eyes representing 17 patients. Sex ratio was 12
men/7 women with a mean age of 61 years (range 25–78 years)
(Table 1).
RNA purification and quantitative RT-PCR analysis
Total RNAs were purified using the cesium chloride centrifu-
gation [60]. Absence of RNA degradation was assessed by RNA
denaturing agarose gel electrophoresis and the quantity of RNA
extracted was determined by optical density measurement.
Samples with RNA degradations or yielding less than 5 mg were
excluded.
cDNAs were synthesized by reverse transcription using random
hexamers (pdN6) according to standard protocols. All primer pairs
were validated by sequencing the PCR products (Table S4).
Figure 6. Kinetics of expression of the orthologous of a subset of the target genes in the wild-type and rd1 retina between PN1 and
PN35. (A) Pepf2, (B) Ppp3cc, (C) Slc6a6, (D) Drd4, (E) Reep6 and (F) Pde6d. PN, post-natal day.
doi:10.1371/journal.pone.0028791.g006
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Quantitative RT-PCR was performed on a LightCycler instru-
ment (Roche-Diagnostics, Indianapolis, IN) with SYBR Green I,
according to the manufacturer’s instructions. Quantitative RT-
PCR analyses were performed in duplicate on 8 samples of each
group. Cycling conditions were as follows: initial denaturation at
95uC for 2 min, followed by 40 cycles of denaturation at 95uC for
0 sec, annealing for 5 sec (see Table S4 for annealing tempera-
tures) and elongation at 72uC for 15 sec. Melting curve analysis
was performed as follows: denaturation at 95uC for 2 min,
annealing at 65uC for 2 min, followed by a gradual increase
(0.1uC/sec) in temperature to 95uC. RT-PCR efficiency for each
pair of primers was measured by calculating the slope of a linear
regression graph using manufacturer’s instructions. For each
experiment, crossing points were calculated by the LightCycler
Data Analysis Program (LightCycler-3.5 Software). Target gene
expressions were normalized with respect to b-actin mRNA.
Amplification products (10 ml) were validated by agarose gel
electrophoresis (data not shown). For statistical analyses, unpaired
Student’s t-test was used to compare mRNAs expression in RD
samples and controls. Values of p,0.05 were considered to be
significant.
Microarray procedures
For human specimen 2 mg of purified total RNA were used. For
mouse tissues, 5 mg from pools of five neural retinas (5 individuals)
from wild-type (C57BL6@N) or rd1 (C3H/He@N) mice were
dissected at 11 post natal (PN) days 1, 4, 5, 8, 10, 11, 12 14, 15 and
35. The RNA were used to generate biotin-labeled cRNA probes
hybridized to the Affymetrix Human genome U133 plus 2.0 array
or Mouse genome U74abc. Quality Control (QC) performed using
RReportGenerator (Data S1).
Bioinformatics analysis
Differential gene expression in the transcriptome of RD was
determined on GCRMA normalized data [61] using moderated t-
test [62] and local false discovery rate (FDR) [36] or mutual
information (MI). MI is considered here as a statistical general-
ization of the correlation For Mutual information analysis, we
consider the relevance of a variable subset Xito predict a target Y
be revealed by the mutual information I Xj,Y
mutual information is a symmetric and non-negative measurement
and is null if and only if the two subsets are statistically
independent. As in [65], the mutual information estimation is
based on the method of Kraskov et al. [66] that was improved here
through bootstrap to reduce the variance of the mutual
information estimator. Indeed, the final estimation is the mean
of the mutual information computed over 50 sampling collections
of the dataset (random sampling with replacement, equal size).
Nevertheless, considering the number of samples, we are far from
the asymptotic conditions of the mutual information estimator and
furthermore the mutual information is homogeneous with the
entropy, which means it is not normalized. This can be a problem
to define relevant thresholds. So, as the correlation is more useful
than the covariance, we defined a normalized mutual information
Infor each target subset Y so that:
??
[63,64]. The
Figure 7. Dynamic of the change in expression. (A) Relative expression of three upregulated probesets selected by FDR but ignored by MI.
ICAM1: intercellular adhesion molecule 1, OSMR: oncostatin M receptor, ITGB2, integrin, beta 2. The histograms display controls (Ctrs) and retinal
detachment (RD) for each specimen. The horizontal line is the average. (B) Relative expression of thee downregulated probesets selected by MI but
ignored by FDR. GUCA1C: guanylate cyclase activator 1C, ABCA4: ATP-binding cassette, CNGB1: cyclic nucleotide gated channel beta 1. (C) Graph
displaying the ratios retinal detachments versus the average value of controls (RD/Ctrs) for ICAM1 and OSMR. D. Graph displaying the ratios of the
average value of controls versus retinal detachments versus (Ctrs/RD) for GUCA1C and ATPA4.
doi:10.1371/journal.pone.0028791.g007
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N
In Xj,Y
of variables we explore, we can consider that the variable with
the lowest mutual information with Y and Y are independent,
in other words the value is the bias of the estimator.
N InY,Y
ð
Finally, InXi,Y
ð
I Y,Y
ð
Protein-protein interactions were analyzed using the STRING
database containing known and predicted, physical and functional
protein-protein interactions as described previously [57]. STRING
in protein mode was used and only interactions with high
confidence levels (.0.7) were kept. We used the DAVID
functional annotation tool to identify the enriched gene ontology
(GO) terms within the gene lists [38]. In particular, we used the
functional annotation clustering procedure at ‘‘high’’ classification
stringency using all 3 categories of GO simultaneously as input.
Resultant clusters represent groups of similar GO ontologies that
were selected based on a cluster-enrichment score [38] higher than
1.0 and a minimum FDR value for the highest enriched GO term
per group of ,50%.
The normalized mutual information was used in three different
ways. First, the normalized mutual information between every
variable (expression pattern of a gene) and the class was computed to
make first a selection of relevant genes. Second, among these relevant
genes, an iterative procedure to build a group of complementary
variables was implemented by selecting each time the variable that
yields a group with the best normalized mutual information for the
class [65,67]. At last, for every variable in the final group, we
evaluated the variables that have the highest normalized mutual
information value and are likely to be implicated in the same
pathway. All data is MIAME compliant and that the raw data has
been deposited in a MIAME compliant database at Gene Expression
Omnibus with the accession numbers GSE28133. Protein-protein
interactions were analyzed as described in Fridlich et al. [57].
??~0 forj~min
i
I Xi,Y
ðÞ: according to the number
Þ~1: the target is fully informative about itself.
Þ~I Xi,Y
Þ{I Xj,Y
ðÞ{I Xj,Y
?
??
?
with j~min
i
I Xi,Y
ðÞ
Supporting Information
Figure S1
The graph plotted the mutual information versus the absolute
Selection of the mutual information values.
value of the correlation coefficient. The green dots correspond to
the 266 probesets selected based on their mutual information.
(PPT)
Figure S2
the target genes in the wild-type and rd1 retina at PN35.
(A) The expression of the down-regulated genes with the highest
MI. (B) The expression of the up-regulated genes with the highest
FDR.
(PPT)
Expression of the orthologous of a subset of
Table S1
rate and mutual information. (http://lbgi.igbmc.fr/Retinal-
Detachment/).
(DOC)
List of probesets selected with false discovery
Table S2
probesets selected with false discovery rate and mutual
information. (http://lbgi.igbmc.fr/RetinalDetachment/).
(DOC)
Enrichment in gene ontology terms for
Table S3
in rat versus human retinal detachment.
(DOC)
Modified expression of Stress-response genes
Table S4
used for quantitative RT-PCR.
(DOC)
Sequences and annotations of the primers
Data S1
portGenerator and R.
(PDF)
Affymetrix Batch Quality Control using RRe-
Acknowledgments
We thank the Cornea Bank of Amsterdam for its contribution and Pr.
Shomi Bhattacharya (Institute of Ophthalmology and Institut de la Vision)
and The ´re `se Cronin (UPenn) for carefully reading the manuscript.
Author Contributions
Conceived and designed the experiments: MND WR DM TL. Performed
the experiments: MND. Analyzed the data: MND WR DM RR JDM OP
TL. Contributed reagents/materials/analysis tools: JFK AG DC RT FM
GC POB JAS. Wrote the paper: MND TL.
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PLoS ONE | www.plosone.org 13December 2011 | Volume 6 | Issue 12 | e28791