ISSN 10227954, Russian Journal of Genetics, 2013, Vol. 49, No. 10, pp. 1057–1064. © Pleiades Publishing, Inc., 2013. Original Russian Text © V.V. Sobolev, T.A. Nikol’skaya, A.D. Zolotarenko, E.S. Piruzyan, S.A. Bruskin, 2013, published in Genetika, 2013, Vol. 49, No. 10, pp. 1212–1220.
HUMAN GENETICS
Expression of Bioinformatically Identified Genes in Skin of Psoriasis Patients V. V. Soboleva, T. A. Nikol’skayab, A. D. Zolotarenkoa, E. S. Piruzyana, and S. A. Bruskina a
Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991 Russia email:
[email protected] b Moscow Physics and Technology State University, Dolgoprudnyi, 141700 Russia Received March 20, 2013
Abstract—Gene expression analysis for EPHA2 (EPH receptor A2), EPHB2 (EPH receptor B2), S100A9 (S100 calcium binding protein A9), PBEF (S100 calcium binding protein A8), LILRB2 (nicotinamide phos phoribosyltransferase), PLAUR (leukocyte immunoglobulinlike receptor, subfamily B (with TM and ITIM domains), member 2), LTB (plasminogen activator, urokinase receptor), WNT5A (lymphotoxin beta (TNF superfamily, member 3)), WNT5A (winglesstype MMTV integration site family, member 5A) has been per formed using realtime polymerase chain reaction in affected skin biopsies from patients with psoriasis versus visually unaffected skin of the same 18 patients. It was revealed that the expression of the nine examined genes was upregulated in the affected by psoriasis compared to visually unaffected skin samples. The highest expres sion was observed for S100A9, S100A8, PBEF, WNT5A2, and EPHB2 genes. S100A9 and S100A8 gene expression in the affected skin samples was 100fold higher than in visually intact skin while PBEF, WNT5A, and EPHB2 gene expression was upregulated more than fivefold. We suppose that the high expression of these genes might be associated with the severity of the disease. Moreover, the transcriptional activity of these genes might serve a molecular indicator of the efficacy of treatment of psoriasis. DOI: 10.1134/S1022795413100116
INTRODUCTION Psoriasis is a hereditary, systemic chronic immune mediated inflammatory disease characterized by the presence of squamous skin plaques [1]. The hyperpro liferation and modified differentiation of epidermal cells are the hallmarks of psoriasis. It is suggested that visual tissue changes in psoriasis result from increased levels of proinflammatory cytokines, such as TNFα, IFNγ, IL1β, IL8, IL12, and IL17 [2]. Activated Tcells release chemokines and growth factors, which induce abnormal keratinocyte proliferation and dif ferentiation, and lead to the development of skin inflammation. This is associated with the development of chronic plaques that contain intraepidermal CD8+ Tcells and neutrophils [3]. Studies of genetic predisposition to psoriasis revealed more than ten loci associated with the dis ease, called psoriasis susceptibility (PSORS) [4–6]. Genetic studies of families affected by psoriasis have most often identified the PSORS1 locus, the region of major histocompatibility complex (MHC) located on chromosome 6. This locus is responsible for up to 50% predisposition to psoriasis. Locus PSORS1 contains a gene that encodes human leukocyte antigenC (HLAC). HLACw6 allele is a major risk allele [7].
Modern high throughput genomewide studies performed on various populations led to the identifi cation of 36 loci associated with psoriasis [8–16]. Pri marily, these include loci involved in the immune response, which contain majorhistocompatibility complex (MHC) genes [13]. For example, the ERAP1 gene affects predisposition to psoriasis in people with HLAC risk allele [10, 12]. In addition, these include genes responsible for the regulation of Tcell functions (RUNX3, TAGAP, and STAT3) [16]; for the modula tion of the Th2 immune response (IL4 and IL13) [9]; interferonmediated antiviral response genes (DDX58 and NOS2) [11, 16]; macrophage activation (ZC3H12C) [16] and NFκB signaling genes (CARD14, CARM1 and NFKBIA) [10, 16]; and genes that regulate that signalling, which are induced by TNFα (TNIP1, TNFAIP2, and TNFAIP3) [8, 9, 12], genes involved in interleukin signalling, which are located in PSORS, are IL12 signaling genes (IL12B) [13], IL23 (IL23A, IL23R, IL12B [9], and IL28RA [10]). Associations with psoriasis and psoriatic arthritis were also revealed for FBXL19 and PSMA6NFKBIA genes, while the association with RNF114 was verified [11]. The loci of combined predisposition to psoriasis and Crohn’s disease, i.e., 9p24 adjacent to JAK2, 10q22 in ZMIZ1, 11q13 adjacent to PRDX5, 16p13
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Table 1. Clinical characteristics of psoriatic (Psoriasis vul garis) patients Num Gender be
Age, years
PASI
Disease duration, years
1
M
30
3.2
11
2
M
24
2.7
3
3
M
40
3.0
22
4
M
27
1.9
13
5
M
50
22
15
6
F
41
35
25
7
F
40
25
20
8
M
33
26
16
9
M
52
20
12
10
F
42
16
22
11
F
51
25
12
12
F
50
32
20
13
F
44
25
23
14
F
50
20
20
15
F
51
25
25
16
F
43
18
20
17
F
41
20
21
18
F
53
22
20
adjacent to SOCS1, 17q21 in STAT3, 19p13 adjacent to FUT2, and 22q11 in YDJC, were also recognized [15]. In addition, the loci associated with structural changes of psoriatic epidermis were discovered. That contained genes of epidermal keratinization (“late cornified envelope”), LCE3B and LCE3C [13, 14], which emphasize the role of skin barrier function dis turbances in the development of the disease. At present, the model of disease development sug gests the involvement of environmental factors along with the genetic predisposition to psoriasis, which results in the initiation of the disease. LL37 proteins produced by keratinocytes in response to trauma or other provoking factors bind with its own DNA or RNA fragments, which are produced by dying or stressed cells. Such complexes of LL37 with nucleic
acids activate plasmacytoid dendritic cells (pDC), which start to produce high amounts of interferon alpha (IFNα). Cytokines IL1β, IL6, TNFγ, com plexes of LL37 with nucleic acids, as well as IFNα produced by keratinocytes activate dermal dendritic cells (DDCs) [17]. Activated DDCs migrate into the skin and drain lymphatic nodes, where they present antigens to naive Tlymphocytes and induce their differentiation into populations of Thelpers 1, 17, and 22 (Th1, Th17, and Th22), as well as to cytotoxic Tlymphocytes 17 (Tc17). At the lesion site, Th can regulate the matura tion of monocytes into dendritic cells (moDC) of var ious populations by producing GMCSF, TNFα, IFNγ, and direct cell–cell contact. Th1 lead to the development of moDC, which secrete IL12. Th17—to the dendritic cells that secrete IL1β, IL6, and IL23. Th22related subpopulations of dendritic cells are currently unknown. Thus, the autoamplification loop could be observed, i.e., Thelpers 1 stimulate the development of Th1inducing dendritic cells, while Thelpers 17—into Th17inducing [18]. Despite the fact that major causes of psoriasis have already been identified, some aspects of the disease pathogenesis are not clear. Today it is still an important challenge to find the missing links and candidate key genes of psoriasis pathogenesis. Current vigorous development of genomic and postgenomic technologies made it possible to use pub lished studies and databases. Therefore, one could create maps and networks containing candidate genes and reveal subprocesses, which might be critical for pathology development, and then experimentally examine the obtained genomic maps using a molecu lar approach. Here a bioinformatic approach was used in order to indentify new psoriasis candidate genes that were fur ther analysed and verified experimentally. MATERIALS AND METHODS For bioinformatic studies, we have used the GEO DataSets database (http://www.ncbi.nlm.nih.gov/ geo/), that contains highthroughput functional genomics data submitted by the research community. MetaCore software (GeneGo Inc., United States; http://www.genego.com) was used to analyze the data. Skin sample collection from patients with plaque type psoriasis (Psoriasis vulgaris) was performed using dermatological punch (4 mm2) under local anaesthe sia. Visually unaffected skin biopsies for comparative analysis were withdrawn at a distance of 3–4 cm next to the lesion [19–22]. Samples were immediately fro zen in liquid nitrogen. The obtained samples were weighted and minced in a mortar without defrosting. The study was approved by a Local Ethic Committee
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Table 2. Primer and probe sequences used in geneexpression studies of corresponding genes by RTPCR Gene
Primers and probes
EPHA2
GAGACTTTCAACCTCTACTA GTGTCAATCTTGGTGAAC FAMACTACGGCACCAACTTCCAGABHQ1
EPHB2
CTCAGTTCGCCTCTGTGAACATC ACGACAGGGTAATGCTGTCCA FAMCCACCAACCAGGCAGCTCCATCBHQ1
S100A9
AACACTCTGTGTGGCTCCTCG TGATGATGGTCTCTATGTTGCGT FAMCTTTGACAGAGTGCAAGACGATGACTTGBHQ1
S100A8
GCTGTCTTTCAGAAGACCTGGTG ACGTCGATGATAGAGTTCAAGGCT FAMCCGTGGGCATCATGTTGACCGABHQ1
PBEF
TGTGCAACCAGGGCAACTCT CCCTCTCACAGCTCATGTCTGAT FAMCACCTATTCCCGAAGCCGTTACCTCBHQ1
LILRB2
GTGCTATGGTTATGACTTG CCTCCTTGTACAGAACAA FAMTCATAGCCGACATCAGAGACACABHQ1
PLAUR
GGTGGAGAAAAGCTGTAC CTGGTTGCACAAGTCTAA FAMACTCAGAGAAGACCAACAGGACCBHQ1
LTB
GTGCCTATCACTGTCCTG GGCTGAGATCTGTTTCTG FAMCTCCTCCTCTGGCAGCTTCTBHQ1
WNT5A
AGGACCACATGCAGTACATCG CGATGTCGGAATTGATACTGG FAMAGAAGGCGCGAAGACAGGCATCABHQ1
at the Institute of General Genetics, Russian Acad emy of Sciences and conformed the principles of the Declaration of Helsinki. The study involved patients treated at Korolenko City Clinical Hospital no. 14 who had a diagnosis “vulgar plaque psoriasis”. The examined group con sisted of 18 patients (7 men and 11 women) aged 24– 53 years, and the duration of the disease varied from 3 to 25 years. To evaluate psoriasis status, the Psoriasis Area and Severity (PASI) index was applied. The max imum value of the PASI index was 35, and the mini mum was 1.9 (Table 1). In the first part of the study, patients did not receive any systemic or PUVA/UV therapy for 1 month before the biopsy was taken. In the second part of the study, RUSSIAN JOURNAL OF GENETICS
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all patients were treated with photochemotherapy (PUVA) using a Waldmann UV1000K UV Therapy System. PUVA therapy is a physiotherapeutic treat ment approach based on the combined application of photosensibilizing drugs and irradiation with long wave ultraviolet light. Amifurin (10 mg orally) was used as a photosensibilizer. The drug was prescribed at a dose 1.0 mg per 1 kg of body mass 2 h before irradia tion. Irradiation was conducted three times per week with an interval of 1 day. A single dose of irradiation was 1–1.5 J/cm2, maximum dose was 6 J/cm2. The total dose of one course was 70–90 J/cm2. Biopsies were taken twice for all the patients (before and after the treatment). 2013
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RNA isolation from biopsies was conducted using an RNeasy Mini Kit ® for skin (Qiagen) according to the manufacturer’s recommendations. To remove DNA contamination from RNA samples, the treat ment of DNase (Qiagen) was applied. The RNA con centration was measured using NanoDrop 1000 spec trophotometer (Thermo Scientific, United States), after which the sample concentrations were equalized in ddH2O. Reverse transcription was performed in PCR tubes in a volume of 200 μL, containing a buffer, dNTP, 100 U MMLV reverse transcriptase (Promega), 20 U RNasin, RNase inhibitor (Promega), 500 ng oligo(dT) primers (DNA Syntes) and RNA to the final concentration not more than 100 ng/μL. The reaction mixture was incubated for 1 h at 37°С. Realtime PCR (RTPCR) was performed using oligonucleotide probes with fluorescent labels and 2.5× reaction mixture with a ROX reference dye (Syn tol). Primers and probes were synthesized by DNA Synthesis (Table 2). Amplification was performed using a PCR machine (BioRad, iQ4) using the following program: (1) denaturation at 95°С, 4 min; (2) denaturation at 95°C, 15 s; (3) annealing at 58°С,15 s; (4) elongation at 72°С, 15 s; (5) steps 2–4 were repeated 35 times. The expression of target genes was normalized using the housekeeping GAPDH gene. The amplifica tion of the GAPDH gene and the examined genes were conducted in separate tubes. Results were calculated using the 2–ΔΔCt method, which shows the fold change in gene expression in the affected compared to unaffected skin [23]. ΔΔCt was calculated as follows: ΔΔCt = ΔCt(affected skin) – ΔCt (unaffected skin) and each value was calculated as shown below: ΔCt = Ct(the analyzed gene) – Ct(GAPDH). Each sample was analyzed in triplicate. RESULTS AND DISCUSSION Bioinformatic Analysis of Transcriptomic and Proteomic Data In our previous bioinformatic studies [24], we have used the Database GEO DataSets (http://www.ncbi. nlm.nih.gov/geo/), that contains highthroughput functional genomics data submitted by the research community. In the search for signalling pathways important to psoriasis, we have used the recently avail able GEO Database set with the identification number GSE14905. This dataset contained gene expression patterns from affected and unaffected skin (from each
patient was taken a biopsy from lesion area and pheno typically normal skin). We have analyzed the gene expression data in the samples of each patient and healthy subject separately without calculation of group averages. The identification of significantly deferential expressed genes between the two groups of samples was performed using Welch’s paired Ttest. The false positives were tested using FDR control method. Most of the functional analysis steps were con ducted using MetaCoreTM Software that is based on the database of paired interactions between biologic objects. We have applied the enrichment analysis using maps of canonical signaling pathways. The signifi cance of the map for the differentially expressed genes was assessed as the percent of the observed size of the intersection of the differentially expressed genes com pared to all genes of the map. Hypergeometric distri bution was used as a model of the random intersection. For all genes, the cutoff value of expression change was 2.5 and the pvalue of the Ttest with the correction for multiple tests was less than 0.01. In this case, the cutoff value for significance (p < 0.01) deter mines the expected ratio of falsepositive predictions in finite set of genes subjected to statistical control. The program chose only the genes with more than 2.5fold expression changes. Basing on these map schemes, we have created a network that shows signal transduction pathways from ligands and receptors through transcription factors to their target genes that have altered expression in psori asis (Fig. 1). The revealed differential overexpression of 44 membrane receptors and ligands in the affected psoriatic skin demonstrates excessive complexity and variety of signal transduction pathways activated in psoriasis. This signalling complexity is likely to be the reason of the inefficacy of modern treatment approaches, including the use of monoclonal antibod ies to TNFα and IL23. Our study shows that com bined therapy involving different pathways might be efficient for psoriasis treatment. In our previous study, we have defined more than 20 receptors and ligands that were not associated with psoriasis earlier [24]. In this study, using clinical sam ples, we have verified nine markers presented on the scheme with the most modified expression. Verification of Identified Markers Using Clinical Samples The verification of the identified markers was per formed by evaluating their gene expression in affected skin of psoriatic patient compared to visually unaf fected skin located no more than 3 cm apart. This
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RAGE
ECFR
1061
IL17R B
?
?
?
B
?
?
+P
?
+P
Rac1
ERK1/2 p38 MARK
JAK2
JAK1 +P
+P
B
TR
+P
B
+P
+P +P
STAT1
STAT3
+P
+P
NFkB
TR
TR TR
TR
SP1
B
TR
cMyc
p53
TR TR
TR
TR
TR
TR
AP1
TR
TR TR
TR
TR TR
TR
TR
TR
TR
TR
TR
TR
PBEF
WNT5A LTB
S100A7
S100A8
S100A9
PLAUR
EPHA2
EPHB2
LILRB2
Kinase Proteinase RAS superfamily protein Metalloprotease Binding protein Receptor ligand Receptors with enzyme activity Transcription factor
Fig. 1. Signal transduction pathways from key receptors to their target genes.
comparison provides the maximum exclusion of side effects on the test integrity [19–22]. For all the genes, the cutoff value for gene expres sion changes was established to be equal to 2. Based on our previous analysis, we have identified several genes that seem to be important to analyze experimentally. These genes are EPHA2, EPHB2, S100A9, S100A8, PBEF, LILRB2, PLAUR, LTB, and WNT5A. S100A9, S100A8 genes were previously shown to be involved in psoriasis pathogenesis [25–27] and we have used them as markers. RUSSIAN JOURNAL OF GENETICS
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Using the RTPCR approach, we have analyzed the expression of nine genes in skin affected by psori asis compared to unaffected skin of 18 patients. Our study has shown that the expression of the ana lyzed nine genes (EPHA2, EPHB2, S100A9, S100A8, PBEF, LILRB2, PLAUR, LTB, and WNT5A) was upregulated in affected skin compared to the control (Fig. 2). The highest expression was observed for S100A9, S100A8, PBEF, WNT5A, and EPHB2 genes. Thus, the 2013
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Relative expression, relative units 2–ΔΔCt
1000
100
10
1 EPHA2 EPHB2 S100A9 S100A8 PBEF LILRB2 PLAUR LTB WNT5A
Relative expression, relative units 2–ΔΔCt
1062
0.1
level of expression of S100A9 and S100A8 genes in the affected skin was 100fold higher compared to their expression in unaffected skin of the same patients. This overexpression could be accounted for by the fact that keratinocytes affected by proinflammatory cytok ines overproduce neutrophilattracting chemokines, as well as antibacterial peptides, e.g., LL37 and S100 proteins. The genes that encode S100 proteins are localized as a cluster on chromosome 1 (1q21), which corresponds to the locus of psoriasis sensibility PSORS4 [28, 29]. The expression of PBEF, WNT5A, and EPHB2 genes in affected skin is increased more that fivefold. The high level of expression was observed in all patients and was persistent. The involvement of PBEF in the development of psoriasis has already been noted in other studies. Thus, it has been established that PBEF increases the production of antimicrobial pep tides in skin keratinocytes of psoriatic patients [30], as well as facilitates increased chemokine production in psoriatic keratinocytes [31]. Recent studies have shown that WNT5A signalling can regulate peripheral inflammatory reactions during chronic disorders like psoriasis [32]. It should be noted that the involvement of EPHB2 in the development of the psoriatic process was not reported previously and we were the first to observe it. The expression of EPHA2, LILRB2, PLAUR and LTB genes in affected skin was increased approxi mately 2–5fold compared to visually unaffected skin of the same patients. However, these gene expression patterns in each patient were instable and bidirec tional. The expression of the PLAUR gene was highly bidirectional (Fig. 3).
1 1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18
Patients
0.1 Fig. 3. Comparison of PLAUR gene expression in skin affected by psoriasis in 18 patients. Level of gene expression in visually unaffected skin is taken equal to 1 (p < 0.05).
The strong upregulation of PBEF, WNT5A, and EPHB2 genes that we have observed in psoriasis is a new and interesting result. Therefore, we consider it to be important to study changes in the expression of these genes before and after patient treatment (Fig. 4). At the end of treatment almost all the patients attained sustained remission. Maximum treatment time was one month. By the end of the treatment, no patient complaints were received. Therapy tolerance was assessed to be good by the patients; no patient had side effects over the whole course of treatment. The comparison of gene expression in samples of psoriatic skin before and after treatment was carried out as follows: we have used all values of gene expres Relative expression, relative units 2–ΔΔCt
Fig. 2. mRNA amounts of EPHA2, EPHB2, S100A9, S100A8, PBEF, LILRB2, PLAUR, LTB, and WNT5A genes in skin affected by psoriasis compared to their amounts in visually unaffected skin (taken equal to 1) (p < 0.05).
10
1000 Before treatment After treatment 100
10
1 EPHB2
S100A9
S100A8
PBEF
WNT5A
Fig. 4. Comparison of S100A9, S100A8, PBEF, WNT5A, and EPHB2 gene expression in specimens of skin affected by psoriasis before and after PUVA therapy using nonpara metrical Mann–Whitney test. Level of expression in visu ally unaffected skin is taken equal to 1 (p < 0.05).
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sion (2–ΔΔCt) and compared them as two sample groups. To confirm the significance of the differences in gene expression before/after treatment, we have used the nonparametric Mann–Whitney test. After PUVA therapy, the expression of the analyzed genes in the affected skin decreased significantly. Thus, the gene expression of EPHB2, S100A8, and S100A9 in the affected skin after treatment decreased more than threefold compared to the baseline. Overall, the increased expression of S100A9, S100A8, PBEF, WNT5A, and EPHB2 genes in all examined patients before the treatment and the decrease in the expression of the same gene after the treatment suggests the presumable key role of these genes in psoriasis pathogenesis. ACKNOWLEDGMENTS The study was supported by the Presidium of the Russian Academy of Sciences, program Basic Science for Medicine.
10.
11.
12.
13.
14.
15.
REFERENCES 1. Gudjonsson, J.E., Ding, J., Johnston, A., et al., Assess ment of the psoriatic transcriptome in a large sample: Additional regulated genes and comparisons with in vitro models, J. Invest. Dermatol., 2010, vol. 130, no. 7, pp. 1829–1840. 2. Hemdan, N.Y., Birkenmeier, G., Wichmann, G., et al., Interleukin17producing T helper cells in autoimmu nity, Autoimm. Rev., 2010, vol. 9, no. 11, pp. 785–792. 3. Gudjonsson, J.E., Karason, A., Runarsdottir, E.H., et al., Distinct clinical differences between HLA Cw*0602 positive and negative psoriasis patients—an analysis of 1019 HLAC and HLABtyped patient, J. Invest. Dermatol., 2006, vol. 126, no. 4, pp. 740–745. 4. Bowcock, A.M., Shannon, W., Du, F., et al., Insights into psoriasis and other inflammatory diseases from largescale gene expression studies, Hum. Mol. Genet., 2001, vol. 10, no. 17, pp. 1793–1805. 5. Piruzyan, E.S., Sobolev, V.V., Abdeev, R.M., et al., Study of molecular mechanisms involved in the patho genesis of immunemediated inflammatory diseases, using psoriasis as a model psoriasis, Acta Nat., 2009, no. 3, pp. 125–135. 6. Galimova, E.S., Akhmetova, V.L., and Khusnutdinova, E.K., Molecular genetic basis of susceptibility to psori asis, Russ. J. Genet., 2008, vol. 44, no. 5, pp. 513–522. 7. Mak, R.K., Hundhausen, C., and Nestle, F.O., Progress in understanding the immunopathogenesis of psoriasis, Actas Dermosifiliogr., 2009, vol. 100, suppl. 2, pp. 2–13. 8. Ellinghaus, E., Ellinghaus, D., Stuart, P.E., et al., Genomewide association study identifies a psoriasis susceptibility locus at TRAF3IP2, Nat. Genet., 2010, vol. 42, no. 11, pp. 991–995. 9. Nair, R.P., Duffin, K.C., Helms, C., et al., Genome wide scan reveals association of psoriasis with IL23 RUSSIAN JOURNAL OF GENETICS
Vol. 49
No. 10
16.
17. 18.
19.
20. 21. 22.
23.
24.
1063
and NFkappaB pathways, Nat. Genet., 2009, vol. 41, no. 2, pp. 199–204. Strange, A., Capon, F., Spencer, C.C., et al., A genomewide association study identifies new psoriasis susceptibility loci and an interaction between HLAC and ERAP1, Nat. Genet., 2010, vol. 42, no. 11, pp. 985–990. Stuart, P.E., Nair, R.P., Ellinghaus, E., et al., Genome wide association analysis identifies three psoriasis sus ceptibility loci, Nat. Genet., 2010, vol. 42, no. 11, pp. 1000–1004. Sun, L.D., Cheng, H., Wang, Z.X., et al., Association analyses identify six new psoriasis susceptibility loci in the Chinese population, Nat. Genet., 2010, vol. 42, no. 11, pp. 1005–1009. Zhang, X.J., Huang, W., Yang, S., et al., Psoriasis genomewide association study identifies susceptibility variants within LCE gene cluster at 1q21, Nat. Genet., 2009, vol. 41, no. 2, pp. 205–210. de Cid, R., RiveiraMunoz, E., Zeeuwen, P.L., et al., Deletion of the late cornified envelope LCE3B and LCE3C genes as a susceptibility factor for psoriasis, Nat. Genet., 2009, vol. 41, no. 2, pp. 211–215. Ellinghaus, D., Ellinghaus, E., Nair, R.P., et al., Com bined analysis of genomewide association studies for Crohn disease and psoriasis identifies seven shared sus ceptibility loci, Am. J. Hum. Genet., 2012, vol. 90, no. 4, pp. 636–647. Tsoi, L.C., Spain, S.L., Knight, J., et al., Identification of 15 new psoriasis susceptibility loci highlights the role of innate immunity, Nat. Genet., 2012, vol. 44, no. 12, pp. 1341–1348. Di Meglio, P.G., Perera, K., and Nestle, F.O., The multitasking organ: recent insights into skin immune function, Immunity, 2011, vol. 35, no. 6, pp. 857–869. Farkas, A. and Kemeny, L., Monocytederived inter feronalpha primed dendritic cells in the pathogenesis of psoriasis: new pieces in the puzzle, Int. Immunophar macol., 2012, vol. 13, no. 2, pp. 215–218. Kulski, J., Kenworthy, W., Bellgard, M., et al., Gene expression profiling of Japanese psoriatic skin reveals an increased activity in molecular stress and immune response signals, J. Mol. Med., 2005, vol. 85, pp. 964– 975. Yao, Y., Richman, L., Morehouse, C., et al., Type I interferon: potential therapeutic target for psoriasis?, PLoS One, 2008, vol. 3, no. 7, pp. 1–14. Sonkoly, E., Wei, T., Janson, P., et al., MicroRNAs: novel regulators involved in the pathogenesis of psoria sis?, PLoS One, 2007, vol. 2, no. 7, p. 610. Sobolev, V.V., Zolotorenko, A.D., Soboleva, A.G., et al., Effects of expression of transcriptional factor AP1 FOSL1 gene on psoriatic process, Bull. Exp. Biol. Med., 2011, vol. 150, no. 5, pp. 632–634. Livak, K.J. and Schmittgen, T.D., Analysis of relative gene expression data using realtime quantitative PCR and the 2(Delta Delta C(T)) method, Methods, 2001, vol. 25, no. 4, pp. 402–408. Piruzian, E., Bruskin, S., Ishkin, A., et al., Integrated network analysis of transcriptomic and proteomic data in psoriasis, BMC Syst. Biol., 2010, vol. 4, pp. 2–24.
2013
1064
SOBOLEV et al.
25. Kelly, S.E., Jones, D.B., and Fleming, S., Calgranulin expression in inflammatory dermatoses, J. Pathol., 1989, vol. 159, no. 1, pp. 17–21. 26. Benoit, S., Toksoy, A., Ahlmann, M., et al., Elevated serum levels of calciumbinding S100 proteins A8 and A9 reflect disease activity and abnormal differentiation of keratinocytes in psoriasis, Br. J. Dermatol., 2006, vol. 155, no. 1, pp. 62–66. 27. Il’ina, S.A., Zolotarenko, A.D., Piruzyan, A.L., et al., Expression of S100A8 and S100A9 genes in the affected by psoriatic process skin, Tekhnol. Zhivykh Sist., 2010, vol. 7, no. 8, pp. 38–44. 28. Hardas, B.D., Zhao, X., Zhang, J., et al., Assignment of psoriasin to human chromosomal band 1q21: coordi nate overexpression of clustered genes in psoriasis, J. Invest. Dermatol., 1996, vol. 106, pp. 753–758. 29. Semprini, S., Capon, F., Tacconelli, A., et al., Evidence for differential S100 gene overexpression in psoriatic
patients from genetically heterogeneous pedigrees, Hum. Genet., 2002, vol. 111, pp. 310–313. 30. Hau, C.S., Kanda, N., Noda, S., et al., Visfatin enhances the production of cathelicidin antimicrobial peptide, human βdefensin2, human βdefensin3, and S100a7 in human keratinocytes and their orthologs in murine imiquimodinduced psoriatic skin, Am. J. Pathol., 2013, vol. 182, no. 5, pp. 1705–1717. 31. Kanda, N., Hau, C.S., Tada, Y., et al., Visfatin enhances CXCL8, CXCL10, and CCL20 production in human keratinocytes, Endocrinology, 2011, vol. 152, no. 8, pp. 3155–3164. 32. Igota, S., Tosa, M., Murakami, M., et al., Identifica tion and characterization of Wnt signaling pathway in keloid pathogenesis, Int. J. Med. Sci., 2013, vol. 10, no. 4, pp. 344–354.
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