De-regulation of diabetic regulatory genes in psoriasis: Deciphering the unsolved riddle

Gene 593 (2016) 110–116

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Research paper

De-regulation of diabetic regulatory genes in psoriasis: Deciphering the unsolved riddle Suad AlFadhli a,⁎, Alaa A.M. Al-Zufairi a, Rasheeba Nizam a, Huda A. AlSaffar b, Nawaf Al-Mutairi c a b c

Department of Medical Laboratory Sciences, Faculty of Allied Health Sciences, Kuwait University, Kuwait Asad AlHamad Dermatology Centre, Sabah Hospital, Kuwait Department of Medicine, Faculty of Medicine, Kuwait University, Kuwait

a r t i c l e

i n f o

Article history: Received 3 June 2016 Received in revised form 8 August 2016 Accepted 12 August 2016 Available online 13 August 2016 Keywords: Type II diabetes Psoriasis Arabs

a b s t r a c t The purpose of our study was to identify the currently lacking molecular mechanism that accounts for the cooccurrence of two seemingly disparate diseases: psoriasis and type II diabetes. We aimed to investigate a panel of 84 genes related to the diabetic regulatory network in psoriasis (Ps), psoriasis type II diabetes (Ps-T2D), type II diabetes (T2D) and healthy control (HC). We hypothesize that such attempts would provide novel diagnostic markers and/or insights into pathogenesis of the disease. A quantitative Real Time-PCR Human Diabetes RT2 Profiler PCR Array was chosen to explore the expression profile 84 diabetic genes in study subjects. Statistical analysis was carried out using appropriate software. The analysis revealed three candidate genes GSK3B, PTPN1, STX4 that are differentially expressed in study subjects. GSK3B was highly significant in Ps-T2D (P = 0.00018, FR = −26.6), followed by Ps (P = 0.0028, FR = −14.5) and T2D groups (P = 0.032, FR = −5.9). PTPN1 showed significant association only with PS-T2D (P = 0.00027, FR = −8.5). STX4 showed significant association with both Ps (P = 0.0002, FR = −20) and Ps-T2D (P = 0.0016, FR = −11.2). ACE represents an additional marker that showed suggestive association with Ps (P = 0.0079, FR = −9.37). Our study highlights the complex genetics of Ps-T2D and present biomarkers for the development of T2D in Ps cases. © 2016 Published by Elsevier B.V.

1. Introduction Psoriasis (Ps) is a chronic heterogeneous inflammatory skin disease characterised by the hyper proliferation and aberrant differentiation of keratinocytes leading to scaly plaques. It affects about 2–3% of the world wide population and occurs equally in men and women. A compelling evidence for the involvement of genes in the development of Ps is provided by increased concordance rate of Ps among monozygotic twins (65–72%) compared to fraternal (15–30%) (Bowcock and Cookson, 2004). functioning of both innate and adaptive immune system also tends to contribute to the pathogenesis of Ps (Conrad and Nestle, 2006; Lande et al., 2007). The involvement of T-cells in the pathogenesis of Ps has been evidenced by bone marrow transplantation, where Ps was transferred from the donor to the healthy recipient Abbreviations: Ps, psoriasis; Ps-T2D, psoriasis type II diabetes; T2D, type II diabetes; HC, healthy controls; B2M, beta-2-microglobuli; HPRT1, hypoxanthine phosphoribosyl transferase; RPL13A, ribosomal protein L13a; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; ACTB, b-actin; STX4, Syntaxin 4; GSK3B, glycogen synthase kinase 3 beta; PTPN1, protein tyrosine phosphatase, non-receptor type 1; ACE, angiotensin I converting enzyme (peptidyl-dipeptidase A) 1; PWBC, peripheral white blood cells. ⁎ Corresponding author at: Department of Medical Laboratory Sciences, Faculty of Allied Health Sciences, Kuwait University, PO Box 31470, Sulaibekhat, Kuwait. E-mail addresses: [email protected], [email protected] (S. AlFadhli).

http://dx.doi.org/10.1016/j.gene.2016.08.024 0378-1119/© 2016 Published by Elsevier B.V.

(Eedy et al., 1990). Proliferation and migration of auto reactive T-cells to epidermis is one of the key events in the pathogenesis of Ps, which in turn is facilitated by the expression of alpha beta integrin on So far, 15 locations (loci) on different chromosomes have been associated with Ps and they are named as Ps susceptibility 1–15 (PSORS1 through PSORS15). Inappropriate effector T-cells (Conrad et al., 2007). Systemic inflammation makes Ps patients vulnerable to other chronic and serious medical co-morbidities (Pearce et al., 2005). It is estimated that up to 30% of Ps patients may develop psoriatic arthritis, 58% are more likely to have a major cardiac event, 46% may develop type 2 diabetes, 43% stroke and one fourth of patient's may have depression (www.Psoriais.org, 2016). Recently, increased numbers of publications has been spotted evaluating the risk of type II diabetes (T2D) among Ps patients. T2D, also known as noninsulin-dependent diabetes, is the most common form that comprises 90% of people with diabetes around the world (World Health Organization, 2016). In contrast to type 1 diabetes mellitus which is caused by an absolute lack of insulin due to breakdown of islet cells in pancreas, T2D is characterised by insulin resistance and relative insulin deficiency. Several retrospective and cross sectional studies have been found in the literature investigation the association of Ps with T2D. In a casecontrol study from Israel, the risk of diabetes was reported to be significantly higher in Ps patients (Shapiro et al., 2014). In yet another study

S. AlFadhli et al. / Gene 593 (2016) 110–116 Table 1 Characteristics of study subjects. Characteristics

Ps (n = 16)

Ps-T2D (n =

T2D (n = 8)

HC (n = 8)

16) Gender Ethnic Age (years) Age of onset Smoking & habits BMI (kg/m2) Waist circumference (cm) PASI score Diabetes type II Blood pressure (mm Hg) Inflammatory profile

8F 8M 14K 2A 33.6 ± 5.6⁎

6F 10M 14K 2A 41.5 ± 13⁎

4F 4M 4K 4A 47.25 ± 0.96⁎

4F 4M 4K 4A 27.5 ± 6.5

13.8 ± 4.9 8S 30 ± 3.8⁎ 85.4 ± 38

6.4 ± 7.8 4S 31 ± 5.5⁎ 93.5 ± 27

11 ± 6.481 2S 28.59 ± 5.47 90.5 ± 10.34

Nil 2S 25 ± 1.2 84.5 ± 8.3

4.6 ± 6.6 Nil 128⁎/86⁎ ±13/±7 4 +ve

5.3 ± 3.3 Positive 130/83⁎ ±18/±9 ANA negative 8.2 ± 1.9⁎

Nil Positive 116/78 ±4.9/±5 Nil

Nil Nil 117/73 ±5/4.8 Nil

10.8 ± 2.6⁎

5.2 ± 0.3

4.6 ± 0.81 1.67 ± 1.55

4.5 ± 0.9 1.63 ± 1.41

5.0 ± 0.62 1.2 ± 0.54

14.1 ± 1.1

14.3 ± 1.76

14.6 ±

5.1 ± 0.67 198 ± 10.5⁎ 8.4 ± 1.2⁎

1.88 5.2 ± 0.6 287 ± 43.9 7.2 ± 0.7

Glucose profile (mmol/L) 5.3 ± 0.59 Lipid profile CHOL (mmol/L) 4.8 ± 0.74 TG (mmol/L) 1.95 ± 2.22 Hematological profile Hb (g/dL) RBC (106/μL) PLT (103/μL) WBC (109/L)

13.7 ± 2.35 5.0 ± 0.32 266 ± 91 7.6 ± 1.32

4.8 ± 0.26⁎ 222 ± 25⁎ 7.6 ± 1.08

F - female, M - male, K - Kuwaiti Arab, A - non-Kuwaiti Arab, Nil - not in list or zero, +ve positive, ANA - antinuclear antibody, cm-centimeter, kg/m2 - kilogram/square meter, mm Hg - millimeters of mercury, mmol/L - millimole per liter, g/dL - gram per deciliter, μL - microliter, L - liter, Ps - psoriasis, Ps-T2D - psoriasis type II diabetes, T2D type II diabetes. ⁎ Denotes significant difference between the test group and the healthy control by t-test (P ≤ 0.05).

from Italy, diabetes was reported to be more frequent in psoriatic patients with b 50 years of age (Binazzi et al., 1975). Similarly, several cross sectional studies have reported an increased risk of diabetes among Ps patients ranging from 1.27–2.48 (Shapiro et al., 2014; Binazzi et al., 1975; Brownstein, 1996; Gibson and Perry, 1956;

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Mallbris et al., 2006; Hollendorff-Curth, 1996; Reeds et al., 1964). A recent meta-analysis on 27 studies has reported that patients with mild Ps are 1.5 times more likely to develop diabetes than the general population while those suffering from severe Ps are twice as likely (Armstrong et al., 2013).Yet, the prospective factor that underlies the increased risk of diabetes among Ps patient remains unclear. In this study, we aim to identify the genes involved in the development of diabetes in Ps by comparative expression profiling of psoriasis (Ps), psoriatic type II diabetes (Ps-T2D), type II diabetes (T2D) patients and carefully selected healthy controls (HC) on a diabetes array containing 84 genes related to the onset, development and progression of diabetes. 2. Results A total of 48 age/gender/ethnically matched Arab subjects were recruited for this study (Table 1). Clinical and immunological profiling of all recruited subjects were carried out at Asa'd Al Hamad dermatological centre. A positive family history of Ps, Ps-T2D and T2D were observed in 75%, 12.5% and 50% of recruited cases respectively. Increased body mass index (BMI) was observed in 50% of Ps and Ps-T2D subjects. None of recruited subjects had any ocular or other immune mediated comorbidity. A comparative analysis of gene expression profile was carried out to find biomarkers for the development of T2D in Ps patients. Three individual patient groups (Ps, Ps-T2D, T2D) and ethnically matched healthy controls were thoroughly investigated for expression of 84 genes related to diabetic network. Sample size calculation for the gene expression array is complicated by the fact that 84 different genes are simultaneously analyzed in four different study groups. A priori calculation indicates that, for a P-value of 0.01 and statistical power of 90%, 20 samples are required to detect a fold change of 2. Hence our study ensures that N60% of power is achieved. The scatter plot indicates the normalized expression of every diabetic gene on the array between Ps, PsT2D, T2D compared to healthy control (Fig. 1). Cluster analysis was carried out to find the list of co-regulated genes (Fig. 2). Majority of diabetic network genes belongs to the category of receptors, transporters and channels. These include ABCC8, ADRB3, AQP2, CCR2, CD28, CEACAM1, CTLA4, GCGR, GLP1R, ICAM1, IL4R, INSR, NSF, RAB4A, SELL, SLC2A4, SNAP23, SNAP25, STX4, STXBP1, STXBP2, TNFRSF1A, VAMP3 and VAPA. Of these genes, only STX4 showed a significant difference in expression between Ps and healthy control (P = 0.0002, fold

Fig. 1. The scatter plot indicates the normalized expression of every diabetic gene on the array between psoriasis (Ps), psoriasis diabetes (Ps-T2D), diabetes (T2D) and healthy control (HC). The central line indicates unchanged gene expression. The fold regulation cut-off is set to 2.

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Fig. 2. Clustergram indicating hierarchical clustering of the entire genes related to diabetic network in psoriasis (Ps), psoriasis diabetes (Ps-T2D) and diabetes (T2D) compared to healthy control (HC). Co-regulated genes across individual groups are indicated by dendrograms.

S. AlFadhli et al. / Gene 593 (2016) 110–116 Table 2 Candidate genes detected in three study groups: Ps, Ps-T2D and T2D. Gene/disease

Ps P-value

GSK3B PTPN1 STX4 ACE

0.0028 0.1647 0.0002 0.0079

Ps-T2D FR −14.5 −5.42 −20 −9.37

P-value 0.000184 0.00027 0.0016 0.5037

Table 3 Comparative expression profile of genes which showed significant difference between PsT2D and T2D.

T2D FR −26.6 −8.5 −11.2 8.2

P-value 0.032 0.936 0.099 0.356

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FR −5.9 −2 −8.8 3.1

Ps - psoriasis, Ps-T2D - psoriasis type II diabetes, T2D type II diabetes. FR = fold regulation.

Gene

Avg dCt (Ps-T2D)

Avg dCt (T2D)

P-value

FR

CCR2 GSK3B ICAM1 IL4R PRKAA1 STXBP1

6.35 9.81 8.03 5.95 5.33 11.1

2.93 7.65 4.63 1.73 2.04 8.38

0.0197 0.034 0.0378 0.0007 0.0299 0.0011

−10.7 −4.5 −10.5 −18.7 −9.8 −6.6

Ps-T2D – psoriasis type II diabetes, T2D type II diabetes. FR = fold regulation.

regulation (FR) = −20, Table 2, Fig. 3)). A suggestive significance was observed in the expression of STX4 between Ps-T2D and healthy control (P = 0.0016, FR = −11.2, Table 2, Fig. 3)). None of the genes encoding for receptors, transporters and channels showed any significant difference in expression between T2D and healthy control (P N 0.0006). Only two nuclear receptor genes PPARA and PPARG were investigated in this study. None of the study groups showed any significant difference in the expression of PPARA and PPARG when compared to healthy control (P N 0.0006). Expression profiles of 19 selected metabolic enzymes: ACE, ACLY, ENPP1, FBP1, G6PC, G6PD, GCK, GPD1, GSK3B, HMOX1, IDE, ME1, NOS3, PARP1 (ADPRT1), PRKAA1, PRKAG2, PRKCB, PYGL revealed a suggestive significance in the expression of GSK3B gene (P = 0.0028, FR = − 14.5) and ACE gene (P = 0.008, FR = − 9.4) in Ps compared individually to healthy control (Table 2, Fig. 3). Similarly, a highly significant difference in the expression of GS3KB was observed between Ps-T2D and healthy control (P = 0.00018, FR = − 26.57, Table 2, Fig. 3). None of the other genes encoding for metabolic enzymes showed any significant difference between Ps-T2D and healthy control (P N 0.0006). No significant difference in expression of genes encoding metabolic enzymes was observed between T2D and healthy control. None of these genes encoding signal transduction factors: AKT2, DUSP4, IGFBP5, IKBKB (IKKbeta), INPPL1 (SHIP2), IRS1, IRS2, MAPK8 (JNK1), MAPK14 (p38 MAPK), PIK3C2B, PIK3CD, PIK3R1, PTPN1 (PTP1B), TRIB3 (SKIP3) showed any significant difference in expression pattern between the tested subjects (P N 0.0006), except for PTPN1 gene which showed a significant difference in expression between Ps-T2D and healthy control (P = 0.00027, FR = −8.52, Table 2, Fig. 3). Expression profiles of 12 selected secretory factors AGT, CCL5, GCG, IFNG, IL6, IL10, IL12B, INS, RETN, TGFB1, TNF, VEGFA revealed no

significant difference in the expression between any of the tested group and healthy control (P N 0.0006). Similarly none of the 14 selected transcription factors CEBPA, FOXC2, FOXG1, FOXP3, HNF4A, PDX1 (IPF1), NEUROD1, NFKB1, NRF1, PPARGC1A, PPARGC1B, SREBF1, HNF1B, NKX2-1 showed any significant difference in expression between tested study group and healthy control (P N 0.0006). We further compared the expression of diabetic related genes between the patient groups (i) Ps-T2D versus Ps and (ii) Ps-T2D versus diabetes. Comparing the expression of genes between Ps-T2D and Ps failed to show any significant difference (P N 0.05). Comparative analysis of Ps-T2D versus T2D revealed six genes that are differentially expressed (P b 0.05, Table 3). These include CCR2, GSK3B, ICAM1, IL4R, PRKAA1 and STXBP1. Of these genes, only IL4R showed highly significant difference in expression between Ps-T2D and T2D (P = 0.0007), with 18.7 fold down regulation in Ps-T2D. Similarly, STXBP1 showed a significant difference (P = 0.001) with 6.6 fold down-regulation in Ps-T2D patients. However, none of the tested genes showed significant difference after Bonferroni correction (P ≤ 0.0006). The effect of confounding factors such as age of onset of disease, BMI, smoking status and lipid profile were investigated on the expression profile of individual patient group. A comparative subgroup analysis of Ps patients with age of onset N and ≤14 years revealed no significant difference in expression profile (P N 0.0006), while that of BMI, gender and smoking status showed suggestive significance (P ≤ 0.05, Supplementary Table 5). Similarly, Ps–T2D subjects showed suggestive significance in expression when subgroup analysis was carried out based on age of onset, BMI and gender (P N 0.05, Supplementary Table 6). However, no significant association was observed after Bonferroni correction (P ≤ 0.0006). Effect of smoking on psoriatic diabetes was not carried out due to limited number of samples.

Fig. 3. Bar plot indicates relative expression of four candidate genes across healthy controls and individual patient group. X-axis represents the study subjects and y-axis represents average dCt of individual gene. Each gene is depicted by a specific bar colour. Lower dCt indicates higher expression (log scale).

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3. Discussion Increasing number of retrospective and cross sectional studies has been found in the literature investigating the association of Ps with T2D (Shapiro et al., 2014; Binazzi et al., 1975; Brownstein, 1996; Gibson and Perry, 1956; Mallbris et al., 2006; Hollendorff-Curth, 1996; Reeds et al., 1964; Armstrong et al., 2013; Boehncke et al., 2007; Wolf et al., 2008). Despite this remarkable increase, the root cause or triggers that manifest the co-morbid condition remains unidentified. Ps is a chronic skin disorder characterised by the rapid build-up of cells on surface of skin, while T2D is a metabolic disorder characterised by the combination of insulin resistance and relative lack of insulin. Although systemic inflammation and common genetic factors are presumed to predispose Ps patients to impaired glucose tolerance and T2D, the exact mechanism involved is obscure. Peripheral blood cells are the most transcriptionally active cells in the blood and are the readily obtainable surrogate tissue for studying the blood diseases and the immune disorders. They share N80% of the transcriptome with nine different human tissue types such as brain, colon, heart, kidney, liver, lung, prostate, spleen and stomach (Liew et al., 2006; Mohr and Liew, 2007). Apparently, certain tissue-specific gene transcripts including beta-myosin heavy chain and insulin have also been detected in blood cells (Mohr and Liew, 2007). Hence, studying the peripheral blood transcriptome might reflect the physiological and pathological events occurring in different tissues types and provide a clue to the system wide inflammation that predispose psoriasis patients to impaired glucose tolerance and T2D. The present study was aimed to ascertain the diabetic route that Ps patients have taken by comparing the relative expression of diabetic related genes in Ps, Ps-T2D and T2D, with carefully selected healthy control. Three candidate genes and promissory genes showed significant difference in expression indicating their vast significance in pathophysiology of studied diseases. These include GSK3B, STX4, PTPN1 and ACE. 3.1. Deciphering the role of GSK3B in Ps, Ps-T2D and T2D GSK3B represents one of the known isoforms of Glycogen synthase kinase (GSK3) gene that is a ubiquitously expressed, highly conserved serine/threonine protein kinase. It is known to regulate diverse cellular functions such as structure, gene expression, apoptosis, cell cycle, cell mobility etc. (Cohen, 1985). It is widely known for its ability to phosphorylate and inactivate glycogen synthase. In the present study, GSK3B was found to be down regulated in all three studied groups indicating its vast possibility in systemic inflammation. One of the key features of T2D is the impairment in the stimulation of glycogen synthesis in skeletal muscle by insulin (Jope et al., 2007). Activation of three signalling pathways: the phosphatidylinositide 3-kinases (PI3K), the mammalian target of rapamycin (mTOR), and MAPK/ERK pathway are known to inhibit GSK3B activity through phosphorylation of the Serine-9 residue (Cohen, 1985). Inactivated GSK3B accounts for abnormal glycogen synthesis, resulting in altered intracellular routing and metabolism of glucose leading to insulin resistance. One of the most important characteristics of GSK3 is its role in inflammation underlying diabetes, cancer and multiple neurological diseases such as Bipolar, Alzheimer's and Parkinson's disease (Frame and Cohen, 2001). The deregulated activity of GSK3B tends to disturb the delicate balance of pro-inflammatory and anti-inflammatory cytokine secretion, which immensely contributes to the underlying inflammatory process. No study has so far characterised the role of GSK3B in Ps. The downstream effect of PI3K/Akt/mTOR pathway is believed to have an essential function in mediating diabetic neuropathy, Ps, atopic dermatitis etc. (Huang et al., 2014). The pathway regulates cellular growth specifically cell-cycle progression, protein translation and transcription. PI3K and Akt are reported to be upregulated in peripheral blood mononuclear cells of Ps patients (Funding et al., 2007). Apart from its evident role in epidermal keratinocyte proliferation (Funding et al., 2007) and

angiogenesis (Mitra et al., 2012) both PI3K heterodimers and mTOR tend to master adaptive immunity and tends to play an important role in maintaining the delicate balance of Th1/Th17 cells (Huang et al., 2014). What causes the over expression and activation of PI3K/Akt/mTOR pathway directs towards endless clues. Interestingly, high levels of GM-CSF has been reported in Ps skin lesions (Mascia et al., 2010) which tends to activate PI3K/Akt/mTOR pathway, probably promoting the differentiation of inflammatory CD11c + DCs (Haidinger et al., 2010). Epidermal growth factor receptor (EGFR) is yet another activator of PI3K reported to be over expressed in Ps (King et al., 1990). These results most likely shed light on the fact that PI3K/Akt/mTOR pathway represents the common susceptibility pathway of T2D and Ps. However, further studies need to be carried out to confirm the latter. 3.2. Pathogenic perspective of STX4 in Ps and Ps-T2D Syntaxin 4 (STX4) is the second prominent gene found to be down regulated in both Ps (20 fold) and Ps-T2D (11 fold), in our study. It belongs to SNARE (soluble NSF attachment receptors) family of protein and is involved in docking/fusion of intracellular GLUT4-containing vesicles with the cell surface in adipocytes (Min et al., 1999). It tends to play an important role in the pancreatic beta cell insulin secretion through the SNARE complex formation with VAMP2. Upon insulin stimulation, STXBP4 dissociates from STX4 complexes and inhibits glucose transport and GLUT4 translocation. Akt2 dependent phosphorylation of STXBP4 on Ser99 is essential for the insulin-stimulated dissociation of STXBP4 from STX4 (Yamada et al., 2005), further indicating the significance of Akt/ PI3-kinase signalling pathway in disease pathogenesis. Supportively, up-regulation of STX4 in human islets has been reported to enhance beta cell function by two fold and significantly improve insulin secretion (Oh et al., 2014). No study has so far characterised the direct role of STX4 in the pathogenesis of Ps. However its clinical significance in hyper keratotic skin diseases has been very recently revealed with its evident role in skin homeostasis and keratinization (Kadono et al., 2012). Down-regulation of STX4 probably accounts for the accelerated keratinization observed in Ps patients and possibly represents a new marker. SNARE family of proteins is also actively involved in the cytolytic T-cell mediated immunity. Any change in STX4 expression may interfere with its ability to counter act an immune challenge by disrupting cytokine or chemokine secretion in activated macrophages, histamine secretion in mast cells, the stimulus-coupled release of granules (Stow et al., 2006) or other trafficking pathways such as insulin regulated of glucose transport in muscle and fat cells (Bryant et al., 2002). Present study provides novel insights to the involvement of STX4 in Ps and Ps diabetes. 3.3. PTPN1: a novel insight into the pathogenesis of Ps-T2D PTPN1 (tyrosine-protein phosphatase non-receptor type 1) is yet another candidate gene linked to Ps T2D in our study. In the present study it was found to be 8 fold down regulated in Ps-T2D. It is widely known to be a negative regulator of insulin signalling pathway and a promising therapeutic target for treatment of T2D, obesity and cancer (Combs, 2010). It is a molecular switch that maintains cellular homeostasis by a balance of tyrosine kinase receptor signalling (Stuible et al., 2008). It is ubiquitously expressed and plays a crucial role in cell proliferation, adhesion, migration and immune and hormonal responses (Combs, 2010). Studies on mouse models indicate that deficiency of PTPN1 leads to increased accumulation of B cells, increased T cell-dependent immune responses, elevated total serum IgG and augmented chemotaxis and chemokinesis (Berdnikovs et al., 2012). PTPN1 deficiency has specifically been reported to aggravate inflammation and accelerates leukocyte trafficking in vivo (Medgyesi et al., 2014). The regulatory effect of PTPN1 on SNARE-interacting protein Munc18c in adipocytes further directs it role in the pathogenesis of psoriasis (Bakke et al., 2013).

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Additional evidences for its involvement in immune response have been put forward by its negative role in IL-4 and STAT6 signalling pathway (Lu et al., 2008). As an antidote to the question what cause inactivation of PTPN1 gene, it is the oxidative stress induced by TH2 cytokines specifically IL-4 and IL-13. It also tends to act against p38 MAPK activation by directly dephosphorylating Tyr (182) this kinase (Medgyesi et al., 2014). Interestingly, down-regulation of PTPN1 leads to sustained MAPK activation and subsequently the other genes involved in the pathogenesis of studied diseases. 3.4. ACE in the aetiopathogenesis of Ps Angiotensin-converting enzyme (ACE) is widely known for its critical role in blood pressure regulation by catalysing the conversion of the inactive angiotensin I to vasoactive angiotensin II (Ehlers and Riordan, 1989). It is reported to play an important role in the aetiopathogenesis of Ps, in contrast to its ability to inhibit inflammation. There are reports indicating that serum ACE level are significantly higher in Ps patients as compared with the normal controls (Rahmati-Roudsari et al., 2010), while conflicting results indicating normal serum ACE level and activity in Ps has also been found in the literature (Ena et al., 1987). We support the notion that administration of ACE inhibitor could either induce or aggravate Ps in clinical practice (Steckelings et al., 2001), as a nine fold reduction in the expression of ACE was observed in Ps subjects of our study. Down-regulation of ACE may possibly affect the kallikreinkinin system, leading increased Bradykinin levels in skin (Coulter and Pillans, 1993), causing Ps. There are reports that Bradykinin stimulates IL-6 and IL-8 production through ERK- and p38 MAPK-dependent mechanisms, further indicating its significance in etiology of Ps (Hayashi et al., 2000). In conclusion, we identified three biomarkers for Ps-T2D namely GSK3B, PTPN1 and STX4. ACE represents an additional marker that showed suggestive association with Ps. We also provide indirect evidence for the significance of PI3K/Akt/mTOR pathway in the aetiopathogenesis of studied diseases. Our study provides substantial evidence to prove the hypothesis that such cases may share a common causative gene or polygenes, leading to the assumption that a common pathway of etiology is deregulated in these diseases. Psoriasis diabetes possibly does not represent a unique disease as the markers detected are either directly or indirectly involved in the pathophysiology of both diseases. An imbalance in the expression of these genes may disrupt the immunological homeostasis leading to dramatic shift in T-cell subtype pathway, oxidative and angiogenic events, fat cell function and interleukin signalling, predisposing Ps patients to diabetes. A wide range of mechanistic events involving genetic, immunological, environmental and life style factors and alongside certain medications such as thiazide and methotrexate could also modulate the risk of T2D in Ps. Application of potent corticosteroids to large areas of psoriatic lesion may result in systemic absorption leading adrenal suppression and some degree of hypercortisolism. Further intensive research need to be carried out validate the results obtained and to understand the mechanism and control of these genes in signal pathway with reference to specific disease. The strength of our study was its novelty and the significant implications that contribute to genetics of Ps T2D.

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waist circumference, smoking habits, blood pressure, age of onset, and duration of the disease was noted. The Ps Area and Severity Index (PASI) were assigned for each patient, PASI score N 10 at any time of the disease will be considered as severe while those with PASI ≤ 10 as moderate patients. Inclusion criteria for Ps patients included: age N 18 and b 55 years, clinical diagnosis of chronic plaque Ps (at least for 6 months, and no co-morbid diseases. Metabolic syndrome was diagnosed in the presence of central obesity in addition to two or more criteria of the International Diabetes Foundation. These included: waist circumference ≥ 94 cm in men or ≥ 80 cm in women; Hypertriglyceridemia ≥ 150 mg/dL; HDL b 40 mg/dL in men or b50 mg/dL in women; blood pressure ≥ 130/85 mm Hg and fasting blood glucose ≥ 100 mg/dL. Patients who satisfied both Ps and diabetes criteria were included under the category of Ps-T2D. Only patients who were diagnosed with plaque Ps initially and later diagnosed with diabetes were included in the study. Exclusion criteria in general for patients included: other chronic inflammatory disease, ongoing alcohol/drug abuse, pregnancy or breastfeeding, prolonged immunosuppression regimen and non-Arab ancestry. Age/gender/ethnically matched healthy controls (HC) were carefully selected. Biochemical profile of HC was done from Mubarak Al-Kabeer Hospital. Physical status of patients such as weight, height, waist circumference was also noted. Exclusion Criteria for HC includes: any chronic inflammatory disease or first degree relative relative's with autoimmune disease and non-Arab ancestry. Inclusion criteria were general good health. Both patients' and controls' medical histories were investigated for the occurrence of other comorbid conditions such as hypertension (HT), dyslipidemia (DL), DM2, and ischemic cardiopathy (IC). Written informed consent was obtained from each participant under the protocols approved by the Joined Committee for the Protection of Human Subjects in Research in Kuwait (KIMS). Blood samples were collected from patients and healthy subjects in EDTA treated and plain tubes. 4.2. Expression profiling cDNA reverse transcriptase Kit was used to reverse transcribe 2 μg of total RNA in a final reaction mix of 20ul using (Applied Biosystem, USA) according to manufacturer's instructions. The prepared cDNA was diluted by adding RNase free water and the PCR was carried out using 7500 Fast Real time PCR (Applied Biosystem, USA). For one 96 well-plate of the PCR array, 2,550 μL PCR master mix containing 29μL of SuperArray RT2 qPCR Master Mix and 102μL of diluted cDNA was prepared, and aliquot of 25μL was added to each well. For quality control analysis, PCR reaction with no template and no reverse transcriptase were performed. Universal cycling conditions (10 min at 95 °C, 15 s at 95 °C, 1 min 60 °C for 40 cycles) were carried out. The Human Diabetes RT2 Profiler PCR Array (Qiagen, Germany) was chosen to explore the expression profiles of 84 genes (Supplementary Table 4) related to the Diabetes Network in the PWBC of Ps, Ps-T2D, T2D patients and health controls. This array contains receptors, transporters & channels, nuclear receptors, metabolic enzymes, secreted factors, signal transduction proteins and transcription factors.

4. Materials and method

4.3. Statistical analysis

4.1. Study subjects

Five endogenous control genes were used for normalization. These include B2M, hypoxanthine HPRT1, RPL13A, GAPDH and ACTB. Cycle threshold (CT) was normalized to the average CT of 5 aforementioned endogenous controls. Relative quantification of gene expression was evaluated using comparative CT method, ΔΔCT = ΔCT (patient group) − ΔCT (control group). ΔCT is the difference in CT between the target gene and endogenous controls obtained by subtracting the average CT of controls from each replicate. The fold change for each sample relative to the control sample = 2−ΔΔCT.

A total of 48 subjects belonging to four study groups such as Ps T2D (n = 16), Ps (n = 16), T2D (n = 8) and healthy control (n = 8) were recruited for this study. Ps-T2D and Ps subjects were recruited from the outpatient department of Asad Al Hamad Dermatology Centre (Kuwait) and T2D from Mubarak Al-Kabeer Hospital in Kuwait. Diagnosis of Ps was made based on clinical findings evaluated by a dermatologist. Age, gender, weight, height, body mass index (BMI),

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Two tailed t-test (Graph Pad Prism) was used to identify a list of differentially expressed genes. Changes in genes expression between patients and normal controls are shown as a fold increase/decrease. A fold change of ≤ 1 indicates a down-regulation, while fold change of ≥1 indicate an up-regulation. A P value of b 0.0006 was considered to be statistically significant after Bonferroni correction and P value of ≤0.05 was considered as suggestive significance. All the statistical calculations were conducted based on the webbased program of RT2 Profiler TM PCR Array Data Analysis. Conflict of interest The authors have no conflict of interest to declare. Funding source This work was supported by Kuwait University research administration Grant YN01/13. The funders had no role in study design data collection and analysis, decision to publish or preparation of the manuscript. Acknowledgements This work was supported by Kuwait University Research administration Grant YN01/13 and General Facility Grant #SRUL02/13. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2016.08.024. References www.Psoriais.org. Armstrong, A.W., Harskamp, C.T., Armstrong, E.J., 2013. Psoriasis and the risk of diabetes mellitus: a systematic review and meta-analysis. JAMA Dermatol. 149, 84–91. Bakke, J., Bettaieb, A., Nagata, N., Matsuo, K., Haj, F.G., 2013. Regulation of the SNAREinteracting protein Munc18c tyrosine phosphorylation in adipocytes by proteintyrosine phosphatase 1B. Cell. Commun. Signal. 12, 11–57. Berdnikovs, S., Pavlov, V.I., Abdala-Valencia, H., McCary, C.A., Klumpp, D.J., et al., 2012. PTP1B deficiency exacerbates inflammation and accelerates leukocyte trafficking in vivo. J. Immunol. 188, 874–884. Binazzi, M., Calandra, P., Lisi, P., 1975. Statistical association between psoriasis and diabetes: further results. Arch. Dermatol. Res. 254, 43–48. Boehncke, S., Thaci, D., Beschmann, H., Ludwig, R.J., Ackermann, H., et al., 2007. Psoriasis patients show signs of insulin resistance. Br. J. Dermatol. 157, 1249–1251. Bowcock, A.M., Cookson, W.O., 2004. The genetics of psoriasis psoriactic arthritis and atopic dermatitis. Hum. Mol. Genet. 1, R43–R55. Brownstein, M.H., 1996. Psoriasis and Diabetes Mellitus. 93 Edn. pp. 170–174 134. Bryant, N.J., Govers, R., James, D.E., 2002. Regulated transport of the glucose transporter GLUT4. Nat. Rev. Mol. Cell Biol. 4, 267–277. Cohen, P., 1985. The coordinated control of metabolic pathways by broad-specificity protein kinases and phosphatases. Curr. Top. Cell. Regul. 27, 23–37. Combs, A.P., 2010. Recent advances in the discovery of competitive protein tyrosine phosphatase 1B inhibitors for the treatment of diabetes, obesity, and cancer. J. Med. Chem. 53, 2333–2344. Conrad, C., Nestle, F.O., 2006. Animal models of psoriasis and psoriatic arthritis: an update. Curr. Rheumatol. Rep. 8, 342–347. Conrad, C., Boyman, O., Tonel, G., Tun-Kyi, A., Laggner, U., et al., 2007. Alpha1beta1 integrin is crucial for accumulation of epidermal T cells and the development of psoriasis. Nat. Med. 13, 836–842. Coulter, D.M., Pillans, P.I., 1993. Angiotensin-converting enzyme inhibitors and psoriasis. N. Z. Med. J. 10, 392–393. Eedy, D.J., Burrows, D., Bridges, J.M., Jones, F.G., 1990. Clearance of severe psoriasis after allogenic bone marrow transplantation. BMJ 300, 908. Ehlers, M.R., Riordan, J.F., 1989. Angiotensin-converting enzyme: new concepts concerning its biological role. Biochemistry 28, 5311–5318. Ena, P., Madeddu, P., Rappelli, A., Cerimele, D., 1987. Cerimele, serum angiotensinconverting enzyme activity in psoriasis. Dermatologica 174, 110–113.

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