# Association Study of the Caspase Gene Family and Psoriasis Vulgaris Susceptibility in Northeastern China

Authors: Xinyu Yao; Siyu Hao; Pei Yu
Journal: BioMed Research International
 (2019)

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## Abstract

Background. Abnormal apoptosis of keratinocytes is one of the pathological changes of psoriasis. Caspases (CASPs) are the central engines of apoptosis. Studies to date have shown that some SNPs alter the expression of related genes and lead to changes in disease risk. However, no studies have investigated the associations between gene polymorphisms and the risk of psoriasis in Han population in northeast China. Therefore, we conducted a case-control study to explore this question in Han population of northeastern China.Methods. 540 patients with PsV and 612 healthy age- and sex-matched controls were enrolled in this study. We determined the genotypes of 17 single nucleotide polymorphisms (SNPs) from 11 genes of caspase family by the improved multiplex ligation detection reaction (iMLDR) method. A model-based single SNP frequentist test and haplotype association studies were performed to evaluate the association between SNPs and PsV.Results. In the single SNP tests, rs6704688 inCASP8 was significantly associated with psoriasis vulgaris (PsV) in Han population of northeastern China (P = 0.0169, P’ = 0.0179 under the additive model;P = 0.0126,P’ = 0.0149 under the heterozygous model). In haplotype analyses, theCASP7 haplotype GC was found to be associated with PsV risk (case group versus control group, 47.2% versus 54.4%, respectively,p = 0.0149).Conclusions. Our study presented that the gene polymorphisms ofCASP7 andCASP8 were significantly associated with PsV in Han population of northeastern China, which implied the functional relationship between PsV and caspase genes.CASP8 andCASP7 SNPs could be new potential biomarkers for risk stratification and prevention of PsV.


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## Body

## 1. Introduction

Psoriasis is a common chronic relapsing inflammatory skin disorder that is induced and sustained by lymphocytes infiltrating the skin, affecting about 2-3% of the population [1, 2]. Although its etiology is not clear, we know that it is not only a skin-restricted disease but also a systemic inflammatory immune disorder which is influenced by various genetic and environmental factors [3]. As with many autoimmune diseases, abnormal apoptosis has important implications in psoriasis biology [4, 5]. The data show that, in addition to the hyperproliferation of keratinocytes, deceleration in keratinocyte apoptosis is also a significant pathological change observed in psoriasis [6–8]. Keratinocytes from the lesion of psoriasis are resistant to induction of apoptosis compared to keratinocytes from normal skin [9]. However, the current data on the apoptosis of psoriatic keratinocytes is limited. Therefore, there is a need to better understand the mechanisms of apoptosis in the progression of psoriasis and to identify potential biomarkers for prognostic prediction.Apoptosis, a unique physiological process genetically controlling programmed cell death, is essential for maintaining normal tissue homeostasis, cell differentiation, and development [4]. In the skin, the death of apoptotic cells regulates keratinocyte proliferation and the formation of the stratum corneum [10]. Caspases (CASPs) are cysteine-dependent aspartate-specific proteases that play a central role in the induction, transduction, and amplification of apoptotic signals in cells and thus determination of cell fate [11, 12]. CASPs can be generally classified into three groups based on their biological functions: inflammatory CASPs (CASP1, CASP4, CASP15, CASP11, and CASP12, apoptosis initiator (CASP2, CASP8, CASP9, and CASP10), and apoptosis executioner (CASP3, CASP6, and CASP7). CASP14 plays an important role in the terminal differentiation of epidermal keratinocytes [13]. The apoptotic pathways involved in keratinocyte apoptosis include several mechanisms. But all have to go through the caspase family. CASPs are sequentially activated in apoptosis, and any CASP may lead to apoptosis aberration. The increase of epidermal thickness in psoriasis may be related to the abnormality of the apoptotic pathway [2]. Some of them have even been reported to have abnormal expression in the lesions of psoriasis [1, 14, 15].Psoriasis is a widespread autoimmune disease and systemic inflammatory disorder with which many of comorbidities (e.g., diabetes, cardiovascular diseases, Crohn’s disease, lymphoma, and cancer) are associated. Patients with psoriasis tend to have an increased risk of cancer [16]. Single nucleotide polymorphisms (SNPs) influence the expression or the activities of caspase enzymes. SeveralCASP genes polymorphisms have been found to be associated with kinds of cancers [17–21] and autoimmune inflammatory diseases, such as rheumatoid arthritis [5], coronary artery disease [22], Kawasaki disease [23], acute pancreatitis [24], and ischemic stroke [25], but the relationship with psoriasis has not been studied. And gene expression profiles showed significant differences in the expression of CASP7 and CASP8 between psoriatic lesions and psoriatic nonlesions. With this in mind, we designed a case-control trial to explore the relationship betweenCASP genes and psoriasis vulgaris (PsV) using polymorphism association studies in order to elucidate the pathogenic mechanisms of PsV.


## 2. Materials and Methods

### 2.1. Study Population

The present case-control study included 540 patients with PsV randomly enrolled from the Second Affiliated Hospital of Harbin Medical University from January 2013 to April 2017 and 612 healthy controls randomly recruited from the same hospital during routine health examinations performed during the same period. All samples we collected were between the ages of 5 and 85. The patients with PsV were diagnosed by at least two clinical dermatologists in the Department of Dermatology. All subjects were of Han Chinese descent in northeastern China; all patients underwent a standardized clinical evaluation and the healthy controls were without any known history of PsV (including three levels of relatives).The basic information of all subjects including sex, age, and demographic characteristics (in the case group), including age of onset, severity grade, and family history (including three levels of relatives), was obtained from self-reported questionnaires and medical records. Subjects with systemic, infectious, autoimmune, atopic, or malignant disease were excluded.All of the participants provided written informed consent before participating in the study. All the procedures followed were in accordance with the ethical standards of the 2nd Affiliated Hospital of Harbin Medical University on human experimentation. The Ethics Committees of the 2nd Affiliated Hospital of Harbin Medical University approved this study. All procedures were in accordance with the 1975 Declaration of Helsinki and its later amendments.


### 2.2. DNA Extraction

Genomic DNA was prepared from 2 mL of intravenous whole blood using the QIAamp DNA Blood Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. DNA samples were stored in a freezer (Mitsubishi, Japan) at −20°C.


### 2.3. Selection of Polymorphisms

Seventeen polymorphisms in 11CASP genes were examined. We did not find any SNPs inCASP2 with the appropriate allele frequency in Han population of northeastern China.CASP11,CASP13, andCASP15do not exist in humans. For the 17 common SNPs, 10 polymorphisms (CASP3 rs2705897 and rs4647610,CASP5 rs507879,CASP7 rs2227310,CASP8 rs6704688 and rs2293554,CASP9 rs4233532 and rs1052576, andCASP10 rs12613347 and rs13006529) were selected based on the literature suggesting that these SNPs were associated with the risk of various cancers and autoimmune diseases. ForCASP1,CASP4,CASP6,CASP7,CASP12, andCASP14, we utilized the International HapMap Project database (http://hapmap.ncbi.nlm.nih.gov/) and the NCBI dbSNP database (https://www.ncbi.nlm.nih.gov/projects/SNP/) to select potentially functional SNPs. We set the cutoff at a minor allele frequency of more than 0.05 for the Han Chinese in Beijing (HCB) population and linkage disequilibrium (LD) patterns with r2 values of more than 0.8. Based on the different distributions of SNPs, seven representative common SNPs (CASP1 rs2282659,CASP4 rs547584 and rs672016,CASP6 rs5030545,CASP7 rs17090911,CASP12 rs506601, andCASP14 rs3181304) were finally selected for genotyping.


### 2.4. Genotyping

Genotyping was performed by the Improved Multiple Ligase Detection Reaction technique developed by Genesky Biotechnologies Inc. (Shanghai, China) [26]. Target DNA sequences were amplified using a multiplex polymerase chain reaction (PCR) method with specific primers and probes. The details are shown in Supplementary Tables S1 and S2.Data analysis was carried out using GeneMapper Software version 4.1. For quality control, genotyping was carried out without knowledge of group status. We randomly selected about 10% of samples for further verification and obtained a concordance rate of 100%.


### 2.5. Statistics

The demographic characteristics were calculated by SPSS version 19.0 (IBM, Chicago, IL, USA).χ2 tests and Student’s t-tests were used to compare clinical characteristics between the two groups. The Hardy-Weinberg equilibrium (HWE; evaluated at < 0.001) test was determined using χ2 tests. Associations between candidate SNPs and PsV risk were determined based on the distributions of allele and genotypic frequencies along with the additive, dominant, recessive, and heterozygous models. Multiple logistic regressions analyses were used to analyze the genotype frequency between groups. The gene interaction analysis (gene epistasis analysis) was performed using the Epistasis Module of Plink. Odds ratios and 95% confidence intervals were calculated to determine the relative risk of PsV, and 10,000 permutations were performed for the multiple test correction. The LD and haplotype were computed and constructed from the genotypes of these polymorphic markers by Haploview 4.0, and LD r2 values were limited to 0.8. All comparisons were two sided, and results with P values of less than 0.05 were considered statistically significant.


## 2.1. Study Population

The present case-control study included 540 patients with PsV randomly enrolled from the Second Affiliated Hospital of Harbin Medical University from January 2013 to April 2017 and 612 healthy controls randomly recruited from the same hospital during routine health examinations performed during the same period. All samples we collected were between the ages of 5 and 85. The patients with PsV were diagnosed by at least two clinical dermatologists in the Department of Dermatology. All subjects were of Han Chinese descent in northeastern China; all patients underwent a standardized clinical evaluation and the healthy controls were without any known history of PsV (including three levels of relatives).The basic information of all subjects including sex, age, and demographic characteristics (in the case group), including age of onset, severity grade, and family history (including three levels of relatives), was obtained from self-reported questionnaires and medical records. Subjects with systemic, infectious, autoimmune, atopic, or malignant disease were excluded.All of the participants provided written informed consent before participating in the study. All the procedures followed were in accordance with the ethical standards of the 2nd Affiliated Hospital of Harbin Medical University on human experimentation. The Ethics Committees of the 2nd Affiliated Hospital of Harbin Medical University approved this study. All procedures were in accordance with the 1975 Declaration of Helsinki and its later amendments.


## 2.2. DNA Extraction

Genomic DNA was prepared from 2 mL of intravenous whole blood using the QIAamp DNA Blood Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. DNA samples were stored in a freezer (Mitsubishi, Japan) at −20°C.


## 2.3. Selection of Polymorphisms

Seventeen polymorphisms in 11CASP genes were examined. We did not find any SNPs inCASP2 with the appropriate allele frequency in Han population of northeastern China.CASP11,CASP13, andCASP15do not exist in humans. For the 17 common SNPs, 10 polymorphisms (CASP3 rs2705897 and rs4647610,CASP5 rs507879,CASP7 rs2227310,CASP8 rs6704688 and rs2293554,CASP9 rs4233532 and rs1052576, andCASP10 rs12613347 and rs13006529) were selected based on the literature suggesting that these SNPs were associated with the risk of various cancers and autoimmune diseases. ForCASP1,CASP4,CASP6,CASP7,CASP12, andCASP14, we utilized the International HapMap Project database (http://hapmap.ncbi.nlm.nih.gov/) and the NCBI dbSNP database (https://www.ncbi.nlm.nih.gov/projects/SNP/) to select potentially functional SNPs. We set the cutoff at a minor allele frequency of more than 0.05 for the Han Chinese in Beijing (HCB) population and linkage disequilibrium (LD) patterns with r2 values of more than 0.8. Based on the different distributions of SNPs, seven representative common SNPs (CASP1 rs2282659,CASP4 rs547584 and rs672016,CASP6 rs5030545,CASP7 rs17090911,CASP12 rs506601, andCASP14 rs3181304) were finally selected for genotyping.


## 2.4. Genotyping

Genotyping was performed by the Improved Multiple Ligase Detection Reaction technique developed by Genesky Biotechnologies Inc. (Shanghai, China) [26]. Target DNA sequences were amplified using a multiplex polymerase chain reaction (PCR) method with specific primers and probes. The details are shown in Supplementary Tables S1 and S2.Data analysis was carried out using GeneMapper Software version 4.1. For quality control, genotyping was carried out without knowledge of group status. We randomly selected about 10% of samples for further verification and obtained a concordance rate of 100%.


## 2.5. Statistics

The demographic characteristics were calculated by SPSS version 19.0 (IBM, Chicago, IL, USA).χ2 tests and Student’s t-tests were used to compare clinical characteristics between the two groups. The Hardy-Weinberg equilibrium (HWE; evaluated at < 0.001) test was determined using χ2 tests. Associations between candidate SNPs and PsV risk were determined based on the distributions of allele and genotypic frequencies along with the additive, dominant, recessive, and heterozygous models. Multiple logistic regressions analyses were used to analyze the genotype frequency between groups. The gene interaction analysis (gene epistasis analysis) was performed using the Epistasis Module of Plink. Odds ratios and 95% confidence intervals were calculated to determine the relative risk of PsV, and 10,000 permutations were performed for the multiple test correction. The LD and haplotype were computed and constructed from the genotypes of these polymorphic markers by Haploview 4.0, and LD r2 values were limited to 0.8. All comparisons were two sided, and results with P values of less than 0.05 were considered statistically significant.


## 3. Results

### 3.1. Participants

Basic information and the clinical characteristics of the participants are shown in Table1. No significant differences were observed in these factors between the two groups.Table 1
Characteristics of the study participants.
Characteristic cases controls P value Total Number 540 612 Gender, n (%)   0.062 Male 332 (0.615) 342 (0.559) Female 208 (0.385) 270 (0.441) Age at onset, n (%) ≤40 years 439 (0.813) >40 years 101 (0.187) Mean age ± SD, years 44.23±12.44 45.47±12.73 0.238 PASI, n (%) ≤10 446 (0.826) >10 94 (0.174) Familial cases (N) 203 (0.376) Sporadic cases(N) 337 (0.624) N: number; PASI: psoriasis area and severity index.


### 3.2. Single SNP Analysis

The genotype and allele frequencies of the SNPs in the PsV group and control group are shown in Tables2 and 3. All genotype distributions of cases and controls passed the H-W test. For theCASP8 rs6704688 polymorphism, the major C allele (risk allele) was present in 76.9% of patients and 75.3% of controls. The additive model (C versus T) distribution and the heterozygous model (TT + CC versus TC) distribution were significantly different between cases and controls (P = 0.0169,P’ = 0.0179;P = 0.0126, andP’ = 0.0149, respectively). No associations between the other 16 SNPs and the risk of PsV were observed in this study. However, there were correlations amongCASP8 rs6704688 in the dominant model (CC versus CT + TT;P = 0.0679,P’ = 0.0974),CASP9 rs4233532 in the heterozygous model (CC + TT versus CT;P = 0.0773,P’ = 0.0821),CASP10 rs12613347 in the recessive model (CC + CT versus TT;P = 0.8247,P’ = 0.8681) and heterozygous model (TT + CC versus TC;P = 0.8829,P’ = 0.9316), andCASP10 rs13006529 in the additive model (T versus A;P = 0.0846,P’ = 0.0806). These results were marginally significant with regard to PsV risk and may become significant if an increased sample size is evaluated.Table 2
Candidate SNPs analysis.
Gene SNP Chromosome position Major/minorallele Riskallele Risk allele frequency Case, Control CASP1 rs2282659 11:105026710 A/G A 0.804, 0.791 CASP3 rs2705897 4:184631944 T/G G 0.193, 0.163 rs4647610 4:184646777 T/C C 0.359, 0.328 CASP4 rs547584 11:104943160 T/C C 0.178, 0.157 rs672016 11:104961127 C/G G 0.228, 0.222 CASP5 rs507879 11:105007200 T/C T 0.822, 0.804 CASP6 rs5030545 4:109699714 C/T C 0.917, 0.913 CASP7 rs17090911 10:113719221 G/A A 0.094, 0.072 rs2227310 10:113729393 C/G G 0.433, 0.384 CASP8 rs6704688 2:201241309 C/T C 0.769, 0.753 rs2293554 2:201266864 T/G T 0.780, 0.758 CASP9 rs4233532 1:15495090 T/C C 0.416, 0.413 rs1052576 1:15506048 C/T T 0.369, 0.368 CASP10 rs12613347 2:201190589 C/T T 0.357, 0.351 rs13006529 2:201217736 T/A T 0.785, 0.783 CASP12 rs506601 11:104899754 A/T A 0.698, 0.685 CASP14 rs3181304 19:15050098 A/G G 0.435, 0.413 SNP: single nucleotide polymorphism.Table 3
The single SNP association studies result of CASPs in cases and controls.
Gene Symbol Genotype Cases(n=540) Controls(n= 612) H-W P Value P Value Adjusted P Value Statistical Model P P’ OR(95%CI) CASP1 rs2282659 GG 24(0.044) 30(0.049)    Additive 0.8650 0.8813 GA 164(0.304) 196(0.320) 0.7871 0.5945 0.6279 Dominant 0.7952 0.8528 1.083 AA 352(0.652) 386(0.630)    Recessive 0.5977 0.6057 (0.812,1.444) G/A 212/868 256/968    heterozygous 0.6687 0.7222 0.196/0.804 0.209/0.791 CASP3 rs2705897 TT 350(0.648) 430(0.703)    Additive 0.3765 0.3845 TG 172(0.319) 164(0.268) 0.8629 0.1953 0.2205 Dominant 0.1632 0.1833 1.221 GG 18(0.033) 18(0.029)    Recessive 0.7874 0.8057 (0.902,1.653) T/G 872/208 1024/200    heterozygous 0.1832 0.2056 0.807/0.193 0.837/0.163 rs4647610 TT 222(0.411) 274(0.448)    Additive 0.5322 0.5412 TC 248(0.459) 274(0.448) 0.1773 0.2700 0.2857 Dominant 0.3758 0.4025 1.147 CC 70(0.130) 64(0.105)    Recessive 0.3498 0.3586 (0.899,1.463) T/C 692/388 822/402    heterozygous 0.7812 0.7998 0.641/0.359 0.672/0.328 CASP4 rs547584 TT 368(0.681) 434(0.709)    Additive 0.5413 0.5451 TC 152(0.282) 164(0.268) 0.886 0.3451 0.3884 Dominant 0.4714 0.5293 1.162 CC 20(0.037) 14(0.023)    Recessive 0.3164 0.3403 (0.852,1.585) T/C 888/192 1032/192    heterozygous 0.7170 0.7835 0.822/0.178 0.843/0.157 rs672016 GG 20(0.037) 30(0.049)    Additive 0.5789 0.5968 GC 206(0.382) 212(0.346) 1 0.8180 0.8317 Dominant 0.4794 0.5470 0.969 CC 314(0.581) 370(0.605)    Recessive 0.5734 0.6178 (0.734,1.278) G/C 246/834 272/952    heterozygous 0.3824 0.3873 0.228/0.772 0.222/0.778 CASP5 rs507879 TT 366(0.678) 402(0.657)    Additive 0.6168 0.6265 TC 156(0.289) 180(0.294) 1 0.4362 0.4632 Dominant 0.5950 0.5992 0.886 CC 18(0.033) 30(0.049)    Recessive 0.3439 0.4141 (0.658,1.194) T/C 888/192 984/240    heterozygous 0.8904 0.9258 0.822/0.178 0.804/0.196 CASP6 rs5030545 TT 2(0.004) 0(0)    Additive 0.4295 0.6065 TC 86(0.159) 106(0.173) 0.886 0.8369 0.9111 Dominant - 0.9998 1.043 CC 452(0.837) 506(0.827)    Recessive 0.7430 0.8257 (0.688,1.580) T/C 90/990 106/1118    heterozygous 0.6538 0.6495 0.083/0.917 0.087/0.913 CASP7 rs17090911 GG 442(0.819) 526(0.860)    Additive 0.36448 0.4247 GA 94(0.174) 84(0.137) 0.8727 0.1609 0.1908 Dominant 0.1810 0.2086 1.346 AA 4(0.007) 2(0.003)    Recessive 0.4888 0.6035 (0.884,2.051) G/A 978/102 1136/88    heterozygous 0.2229 0.2461 0.06/0.094 0.928/0.072 rs2227310 GG 104(0.193) 88(0.144)    Additive 0.2164 0.2147 GC 260(0.481) 294(0.480) 0.5244 0.0894 0.0919 Dominant 0.1172 0.1432 0.815 CC 176(0.326) 230(0.376)    Recessive 0.2106 0.2184 (0.644,1.032) G/C 468/612 470/754    heterozygous 0.9792 0.9998 0.433/0.567 0.384/0.616 CASP8 rs6704688 TT 40(0.074) 24(0.039)    Additive 0.0169∗ 0.0179∗ TC 170(0.315) 254(0.415) 0.8725 0.5429 0.5777 Dominant 0.0679 0.0974 1.088 CC 330(0.611) 334(0.546)    Recessive 0.1129 0.1258 (0.829,1.427) T/C 250/830 302/922    heterozygous 0.0126∗ 0.0149∗ 0.231/0.769 0.247/0.753 rs2293554 TT 332(0.615) 358(0.585)    Additive 0.6952 0.6784 TG 178(0.329) 212(0.346) 0.546 0.3999 0.4151 Dominant 0.4656 0.4911 0.886 GG 30(0.056) 42(0.069)    Recessive 0.5166 0.6077 (0.673,1.167) T/G 842/238 928/296    heterozygous 0.6711 0.7163 0.780/0.220 0.758/0.242 CASP9 rs4233532 TT 176(0.326) 224(0.366)    Additive 0.2005 0.2144 TC 278(0.515) 270(0.441) 0.0447 0.9114 0.9544 Dominant 0.3129 0.3380 1.013 CC 86(0.159) 118(0.193)    Recessive 0.2915 0.3272 (0.801,1.281) T/C 630/450 718/506    heterozygous 0.0773 0.0821 0.584/0.416 0.587/0.413 rs1052576 TT 70(0.130) 98(0.160)    Additive 0.2790 0.2851 TC 258(0.478) 254(0.415) 1 0.9761 0.9999 Dominant 0.2994 0.3467 0.996 CC 212(0.392) 260(0.425)    Recessive 0.4321 0.4519 (0.784,1.266) T/C 398/682 450/774    heterozygous 0.1304 0.1623 0.369/0.631 0.368/0.632 CASP10 rs12613347 TT 74(0.137) 82(0.134)    Additive 0.9752 0.9714 TC 238(0.441) 266(0.435) 0.6406 0.8325 0.8550 Dominant 0.9150 0.9998 0.974 CC 228(0.422) 264(0.431)    Recessive 0.8247 0.8681 (0.764,1.240) T/C 386/694 430/794    heterozygous 0.8829 0.9316 0.357/0.643 0.351/0.649 rs13006529 TT 342(0.633) 366(0.598)    Additive 0.0846 0.0806 TA 164(0.304) 226(0.369) 0.4431 0.9179 0.9452 Dominant 0.3849 0.3863 0.985 AA 34(0.063) 20(0.033)    Recessive 0.0856 0.1072 (0.744,1.305) T/A 848/232 958/266    heterozygous 0.0965 0.1112 0.785/0.215 0.783/0.217 CASP12 rs506601 TT 48(0.089) 48(0.078)    Additive 0.5086 0.5049 TA 230(0.426) 290(0.484) 0.6716 0.6101 0.6427 Dominant 0.6507 0.7603 1.065 AA 262(0.485) 274(0.448)    Recessive 0.3682 0.4018 (0.829,1.369) T/A 326/754 386/838    heterozygous 0.2485 0.2688 0.302/0.698 0.315/0.685 CASP14 rs3181304 GG 120(0.222) 104(0.170)    Additive 0.2007 0.2129 GA 230(0.426) 298(0.487) 1 0.4686 0.4826 Dominant 0.1139 0.1425 0.915 AA 190(0.352) 210(0.343)    Recessive 0.8265 0.8582 (0.724,1.156) G/A 470/610 506/718    heterozygous 0.1424 0.1547 0.435/0.565 0.413/0.587 ∗: Significant, compared by paired t test; H-W: Hardy–Weinberg equilibrium test; P: model-based statistical p value; P’: p value adjusted by permutation; OR: odds ratio; and 95%CI: 95% confidence interval.


### 3.3. Interaction Analysis

We performed a gene-gene interaction analysis on all samples. We found that the interaction ofCASP10 -CASP1, CASP10-CASP3, CASP10-CASP4, CASP10-CASP9, CASP10-CASP12, CASP8 - CASP3, CASP8 - CASP4, andCASP1 - CASP12 is important for the risk of psoriasis (Table 4). Additional results that were not found to be significant were shown in Supplementary Materials (Table S3). The age group under 40 is a high-risk age group for psoriasis. The analysis of intergene interactions in this age group found that the interaction between 10 pairs of genes was significant for the risk of psoriasis. They are the interaction ofCASP8 -CASP10,CASP3 -CASP4,CASP3 - CASP6, CASP3-CASP8,CASP1 -CASP8, CASP1-CASP10,CASP6 -CASP7, andCASP7-CASP9 (Table 5). Additional results that were not found to be significant were shown in Supplementary Materials (Table S4).Table 4
Significant results of intergenic interaction analysis of all samples.
SNP (Chr.) SNP (Chr.) OR_INT Chi-square P rs12613347(2) rs672016(11) 1.87 6.8995 0.0086 rs13006529(2) rs506601(11) 0.384 6.6773 0.0098 rs13006529(2) rs4647610(4) 3.039 6.0643 0.0138 rs4233532(1) rs13006529(2) 0.430 4.9705 0.0258 rs6704688(2) rs4647610(4) 0.54 4.6476 0.0311 rs12613347(2) rs2282659(11) 0.41 4.6218 0.0316 rs506601(11) rs2282659(11) 0.43 4.5832 0.0323 rs6704688(2) rs672016(11) 0.58 4.5381 0.0332 SNP: single nucleotide polymorphism; Chr.: chromosome of single nucleotide polymorphism; OR_INT: odds ratio for interaction; P: p-value.Table 5
Significant results of intergene interaction analysis of samples less than 40 years old.
SNP (Chr.) SNP (Chr.) OR_INT Chi-square P rs13006529(2) rs6704688(2) 4.85 8.9000 0.0029 rs5030545(4) rs2705897(4) 0.12 6.1767 0.0129 rs4647610(4) rs547584(11) 2.90 5.9144 0.0150 rs2293554(2) rs4647610(4) 2.45 5.2208 0.0223 rs4233532(1) rs1052576(1) 0.50 4.9522 0.0261 rs5030545(4) rs4647610(4) 0.24 4.6047 0.0319 rs6704688(2) rs2282659(11) 0.34 4.2747 0.0387 rs5030545(4) rs17090911(10) 0.08 4.0495 0.0442 rs4233532(1) rs2227310(10) 1.82 3.9662 0.0464 rs13006529(2) rs2282659(11) 0.34 3.9280 0.0475 SNP: single nucleotide polymorphism; Chr.: chromosome of single nucleotide polymorphism; OR_INT: odds ratio for interaction; P: p-value.


### 3.4. Haplotype Analysis

The haplotype blocks were imputed by Haploview for each of the 11 genes and we obtained four haplotypes inCASP3 andCASP4 and three haplotypes inCASP7,CASP8,CASP9, andCASP10. The results are shown in Table 6. The results showed that, among the 21 haplotypes, theCASP3 haplotype TT andCASP4 haplotype TC were the two most common in the case and control groups (TT frequencies of 0.633 and 0.657, respectively, and TC frequencies of 0.619 and 0.643, respectively). TheCASP7 haplotype GC was significantly different in patients with PsV than in controls (47.2% versus 54.4%,p = 0.0149). We did not identify the other haplotypes to be significantly associated with PsV (P > 0.05).Table 6
The haplotype analyses result of CASPs in cases and controls.
Gene Haplotype Freq. Case, Control Ratio Counts Case, Control Frequencies Chi Square P Value CASP3 TT 0.646 341.8  : 198.2, 401.9  : 210.1 0.633, 0.657 0.712 0.3989 TC 0.177 94.2  : 445.8, 110.1  : 501.9 0.174, 0.180 0.057 0.8118 GC 0.166 99.8  : 440.2, 90.9  : 521.1 0.185, 0.149 2.721 0.099 GT 0.012 4.2  : 535.8, 9.1  : 602.9 0.008, 0.015 1.234 0.2666 CASP4 TC 0.632 334.5  : 205.5, 393.5  : 218.5 0.619, 0.643 0.685 0.408 TG 0.201 109.5  : 430.5, 122.5  : 489.5 0.203, 0.200 0.013 0.911 CC 0.143 82.5  : 457.5, 82.5  : 529.5 0.153, 0.135 0.758 0.384 CG 0.023 13.5  : 526.5, 13.5  : 598.5 0.025, 0.022 0.106 0.7446 CASP7 GC 0.51 255.0  : 285.0, 333.0  : 279.0 0.472, 0.544 5.934 0.0149∗ GG 0.407 234.0  : 306.0, 235.0  : 377.0 0.433, 0.384 2.894 0.0889 AC 0.082 51.0  : 489.0, 44.0  : 568.0 0.094, 0.072 1.928 0.165 CASP8 CT 0.546 304.0  : 236.0, 325.2  : 286.8 0.563, 0.531 1.157 0.282 TT 0.222 117.0  : 423.0, 138.8  : 473.2 0.217, 0.227 0.172 0.6787 CG 0.214 111.0  : 429.0, 135.8  : 476.2 0.205, 0.222 0.457 0.4991 TG 0.018 8.0  : 532.0, 12.2  : 599.8 0.015, 0.020 0.43 0.5121 CASP9 TC 0.582 314.9  : 225.1, 355.9  : 256.1 0.583, 0.582 0.003 0.9559 CT 0.365 198.9  : 341.1, 221.9  : 390.1 0.368, 0.363 0.041 0.8397 CC 0.05 26.1  : 513.9, 31.1  : 580.9 0.048, 0.051 0.037 0.8465 CASP10 CT 0.431 232.3  : 307.7, 264.4  : 347.6 0.430, 0.432 0.004 0.9506 TT 0.353 191.7  : 348.3, 214.6  : 397.4 0.355, 0.351 0.023 0.8783 CA 0.215 114.7  : 425.3, 132.6  : 479.4 0.212, 0.217 0.031 0.8596 ∗: significant; Freq.: frequencies.We also used Haploview to calculate the haplotypes of individual genes on the same chromosome, estimated the haplotype frequencies, and compared the haplotype distribution between the patients and control groups. We found that the haplotype frequency ofCASP3 (rs2705897) on chromosome 4,CASP7(rs17090911) on chromosome 10, CASP10 (rs12613347) on chromosome 2, andCASP12(rs506601) on chromosome 11 was significantly different between the patients group and the control group. The results are shown in Table 7. We performed the same analysis for the age group under 40 years old and found that the haplotype frequency ofCASP7 (rs17090911) on chromosome 10,CASP9(rs4233532) on chromosome 1,CASP10 (rs12613347) on chromosome 2, andCASP12(rs506601) on chromosome 11 was significantly different between the patients group and the control group. The results are shown in Table 8.Table 7
Haplotype analysis of SNPs on the same chromosome for all samples.
Chr. SNP Haplotype Ca-freq. N-Ca (540) Co-freq. N-Co ( 612) P 1 rs4233532 CC 0.048 25.92 0.053 32.436 0.9226 rs1052576 CT 0.369 199.26 0.364 222.768 TC 0.583 314.82 0.583 356.796 11 rs506601 ACCCG 0.034 18.36 0.027 16.524 0.0093 rs547584 ACCTA 0.116 62.64 0.102 62.424 rs672016 ACGTA 0.028 15.12 0.023 14.076 rs507879 ATCCG 0.057 30.78 0.067 41.004 rs2282659 ATCTA 0.265 143.1 0.277 169.524 ATCTG 0.014 7.56 0.022 13.464 ATGCG 0.049 26.46 0.041 25.092 ATGTA 0.141 76.14 0.139 85.068 TTCCG 0.033 17.82 0.047 28.764 TTCTA 0.245 132.3 0.238 145.656 TTCTG 0.018 9.72 0 0 TTGTA 0 0 0.017 10.404 10 rs17090911 AC 0.094 50.76 0.072 44.064 0.0448 rs2227310 GC 0.473 255.42 0.544 332.928 GG 0.433 233.82 0.384 235.008 2 rs12613347 CACT 0 0 0.012 7.344 0.0038 rs13006529 CATG 0 0 0.01 6.12 rs6704688 CATT 0.2 108 0.196 119.952 rs2293554 CTCG 0.159 85.86 0.164 100.368 CTCT 0.263 142.02 0.248 151.776 CTTT 0.023 12.42 0.023 14.076 TTCG 0.05 27 0.064 39.168 TTCT 0.305 164.7 0.268 164.016 TTTT 0 0 0.015 9.18 4 rs2705897 CGC 0.179 96.66 0.124 75.888 0.00004 rs4647610 CGT 0 0 0.016 9.792 rs5030545 CTC 0.164 88.56 0.161 98.532 CTT 0.576 311.04 0.613 375.156 TGC 0 0 0.023 14.076 TTC 0.017 9.18 0.02 12.24 TTT 0.064 34.56 0.043 26.316 Chr.: chromosome; SNP: single nucleotide polymorphism; N-Ca: number of case group; Ca-freq.: case group frequencies; N-Co: number of control group; Co-freq.: control group frequencies; P: p value.Table 8
Haplotype analysis of SNPs on the same chromosome for samples under 40 years old.
chr SNP Haplotype Ca-freq N-Ca ( 439) Co-freq N-Co (216) P 1 rs4233532 CC 0.545 239.255 0.051 11.016 0.00000 rs1052576 CT 0.401 176.039 0.338 73.008 TC 0.054 23.706 0.611 131.976 11 rs506601 ACCCG 0.042 18.438 0.019 4.104 0.00098 rs547584 ACCTA 0.119 52.241 0.105 22.68 rs672016 ACGTA 0.035 15.365 0.024 5.184 ATCCA 0 0 0.019 4.104 rs507879 ATCCG 0.027 11.853 0.058 12.528 rs2282659 ATCTA 0.309 135.651 0.224 48.384 ATCTG 0.015 6.585 0.038 8.208 ATGCG 0.053 23.267 0.043 9.288 ATGTA 0.117 51.363 0.172 37.152 TTCCG 0.026 11.414 0.054 11.664 TTCTA 0.227 99.653 0.229 49.464 TTCTG 0.018 7.902 0 0 TTGTA 0.012 5.268 0.015 3.24 10 rs17090911 AC 0.094 41.266 0.102 22.032 0.08798 rs2227310 GC 0.436 191.404 0.518 111.888 GG 0.47 206.33 0.38 82.08 2 rs12613347 CACT 0 0 0.015 3.24 0.00000 rs13006529 CATT 0.176 77.264 0.187 40.392 rs6704688 CTCC 0 0 0.161 34.776 rs2293554 CTCG 0.198 86.922 0 0 CTCT 0.289 126.871 0.294 63.504 CTTT 0 0 0.028 6.048 TTCC 0 0 0.073 15.768 TTCG 0.075 32.925 0 0 TTCT 0.262 115.018 0.226 48.816 TTTT 0 0 0.016 3.456 4 rs2705897 CGC 0.176 77.264 0.107 23.112 0.00001 rs4647610 CGT 0 0 0.011 2.376 rs5030545 CTC 0.183 80.337 0.182 39.312 CTT 0.533 233.987 0.644 139.104 TGC 0 0 0.02 4.32 TTC 0.014 6.146 0.016 3.456 TTT 0.094 41.266 0.02 4.32 Chr, Chromosome; SNP, single nucleotide polymorphism; N-Ca, number of case group; Ca-freq, case group frequencies; N-Co, Number of control group; Co-freq, control group frequencies; P, p value.


## 3.1. Participants

Basic information and the clinical characteristics of the participants are shown in Table1. No significant differences were observed in these factors between the two groups.Table 1
Characteristics of the study participants.
Characteristic cases controls P value Total Number 540 612 Gender, n (%)   0.062 Male 332 (0.615) 342 (0.559) Female 208 (0.385) 270 (0.441) Age at onset, n (%) ≤40 years 439 (0.813) >40 years 101 (0.187) Mean age ± SD, years 44.23±12.44 45.47±12.73 0.238 PASI, n (%) ≤10 446 (0.826) >10 94 (0.174) Familial cases (N) 203 (0.376) Sporadic cases(N) 337 (0.624) N: number; PASI: psoriasis area and severity index.


## 3.2. Single SNP Analysis

The genotype and allele frequencies of the SNPs in the PsV group and control group are shown in Tables2 and 3. All genotype distributions of cases and controls passed the H-W test. For theCASP8 rs6704688 polymorphism, the major C allele (risk allele) was present in 76.9% of patients and 75.3% of controls. The additive model (C versus T) distribution and the heterozygous model (TT + CC versus TC) distribution were significantly different between cases and controls (P = 0.0169,P’ = 0.0179;P = 0.0126, andP’ = 0.0149, respectively). No associations between the other 16 SNPs and the risk of PsV were observed in this study. However, there were correlations amongCASP8 rs6704688 in the dominant model (CC versus CT + TT;P = 0.0679,P’ = 0.0974),CASP9 rs4233532 in the heterozygous model (CC + TT versus CT;P = 0.0773,P’ = 0.0821),CASP10 rs12613347 in the recessive model (CC + CT versus TT;P = 0.8247,P’ = 0.8681) and heterozygous model (TT + CC versus TC;P = 0.8829,P’ = 0.9316), andCASP10 rs13006529 in the additive model (T versus A;P = 0.0846,P’ = 0.0806). These results were marginally significant with regard to PsV risk and may become significant if an increased sample size is evaluated.Table 2
Candidate SNPs analysis.
Gene SNP Chromosome position Major/minorallele Riskallele Risk allele frequency Case, Control CASP1 rs2282659 11:105026710 A/G A 0.804, 0.791 CASP3 rs2705897 4:184631944 T/G G 0.193, 0.163 rs4647610 4:184646777 T/C C 0.359, 0.328 CASP4 rs547584 11:104943160 T/C C 0.178, 0.157 rs672016 11:104961127 C/G G 0.228, 0.222 CASP5 rs507879 11:105007200 T/C T 0.822, 0.804 CASP6 rs5030545 4:109699714 C/T C 0.917, 0.913 CASP7 rs17090911 10:113719221 G/A A 0.094, 0.072 rs2227310 10:113729393 C/G G 0.433, 0.384 CASP8 rs6704688 2:201241309 C/T C 0.769, 0.753 rs2293554 2:201266864 T/G T 0.780, 0.758 CASP9 rs4233532 1:15495090 T/C C 0.416, 0.413 rs1052576 1:15506048 C/T T 0.369, 0.368 CASP10 rs12613347 2:201190589 C/T T 0.357, 0.351 rs13006529 2:201217736 T/A T 0.785, 0.783 CASP12 rs506601 11:104899754 A/T A 0.698, 0.685 CASP14 rs3181304 19:15050098 A/G G 0.435, 0.413 SNP: single nucleotide polymorphism.Table 3
The single SNP association studies result of CASPs in cases and controls.
Gene Symbol Genotype Cases(n=540) Controls(n= 612) H-W P Value P Value Adjusted P Value Statistical Model P P’ OR(95%CI) CASP1 rs2282659 GG 24(0.044) 30(0.049)    Additive 0.8650 0.8813 GA 164(0.304) 196(0.320) 0.7871 0.5945 0.6279 Dominant 0.7952 0.8528 1.083 AA 352(0.652) 386(0.630)    Recessive 0.5977 0.6057 (0.812,1.444) G/A 212/868 256/968    heterozygous 0.6687 0.7222 0.196/0.804 0.209/0.791 CASP3 rs2705897 TT 350(0.648) 430(0.703)    Additive 0.3765 0.3845 TG 172(0.319) 164(0.268) 0.8629 0.1953 0.2205 Dominant 0.1632 0.1833 1.221 GG 18(0.033) 18(0.029)    Recessive 0.7874 0.8057 (0.902,1.653) T/G 872/208 1024/200    heterozygous 0.1832 0.2056 0.807/0.193 0.837/0.163 rs4647610 TT 222(0.411) 274(0.448)    Additive 0.5322 0.5412 TC 248(0.459) 274(0.448) 0.1773 0.2700 0.2857 Dominant 0.3758 0.4025 1.147 CC 70(0.130) 64(0.105)    Recessive 0.3498 0.3586 (0.899,1.463) T/C 692/388 822/402    heterozygous 0.7812 0.7998 0.641/0.359 0.672/0.328 CASP4 rs547584 TT 368(0.681) 434(0.709)    Additive 0.5413 0.5451 TC 152(0.282) 164(0.268) 0.886 0.3451 0.3884 Dominant 0.4714 0.5293 1.162 CC 20(0.037) 14(0.023)    Recessive 0.3164 0.3403 (0.852,1.585) T/C 888/192 1032/192    heterozygous 0.7170 0.7835 0.822/0.178 0.843/0.157 rs672016 GG 20(0.037) 30(0.049)    Additive 0.5789 0.5968 GC 206(0.382) 212(0.346) 1 0.8180 0.8317 Dominant 0.4794 0.5470 0.969 CC 314(0.581) 370(0.605)    Recessive 0.5734 0.6178 (0.734,1.278) G/C 246/834 272/952    heterozygous 0.3824 0.3873 0.228/0.772 0.222/0.778 CASP5 rs507879 TT 366(0.678) 402(0.657)    Additive 0.6168 0.6265 TC 156(0.289) 180(0.294) 1 0.4362 0.4632 Dominant 0.5950 0.5992 0.886 CC 18(0.033) 30(0.049)    Recessive 0.3439 0.4141 (0.658,1.194) T/C 888/192 984/240    heterozygous 0.8904 0.9258 0.822/0.178 0.804/0.196 CASP6 rs5030545 TT 2(0.004) 0(0)    Additive 0.4295 0.6065 TC 86(0.159) 106(0.173) 0.886 0.8369 0.9111 Dominant - 0.9998 1.043 CC 452(0.837) 506(0.827)    Recessive 0.7430 0.8257 (0.688,1.580) T/C 90/990 106/1118    heterozygous 0.6538 0.6495 0.083/0.917 0.087/0.913 CASP7 rs17090911 GG 442(0.819) 526(0.860)    Additive 0.36448 0.4247 GA 94(0.174) 84(0.137) 0.8727 0.1609 0.1908 Dominant 0.1810 0.2086 1.346 AA 4(0.007) 2(0.003)    Recessive 0.4888 0.6035 (0.884,2.051) G/A 978/102 1136/88    heterozygous 0.2229 0.2461 0.06/0.094 0.928/0.072 rs2227310 GG 104(0.193) 88(0.144)    Additive 0.2164 0.2147 GC 260(0.481) 294(0.480) 0.5244 0.0894 0.0919 Dominant 0.1172 0.1432 0.815 CC 176(0.326) 230(0.376)    Recessive 0.2106 0.2184 (0.644,1.032) G/C 468/612 470/754    heterozygous 0.9792 0.9998 0.433/0.567 0.384/0.616 CASP8 rs6704688 TT 40(0.074) 24(0.039)    Additive 0.0169∗ 0.0179∗ TC 170(0.315) 254(0.415) 0.8725 0.5429 0.5777 Dominant 0.0679 0.0974 1.088 CC 330(0.611) 334(0.546)    Recessive 0.1129 0.1258 (0.829,1.427) T/C 250/830 302/922    heterozygous 0.0126∗ 0.0149∗ 0.231/0.769 0.247/0.753 rs2293554 TT 332(0.615) 358(0.585)    Additive 0.6952 0.6784 TG 178(0.329) 212(0.346) 0.546 0.3999 0.4151 Dominant 0.4656 0.4911 0.886 GG 30(0.056) 42(0.069)    Recessive 0.5166 0.6077 (0.673,1.167) T/G 842/238 928/296    heterozygous 0.6711 0.7163 0.780/0.220 0.758/0.242 CASP9 rs4233532 TT 176(0.326) 224(0.366)    Additive 0.2005 0.2144 TC 278(0.515) 270(0.441) 0.0447 0.9114 0.9544 Dominant 0.3129 0.3380 1.013 CC 86(0.159) 118(0.193)    Recessive 0.2915 0.3272 (0.801,1.281) T/C 630/450 718/506    heterozygous 0.0773 0.0821 0.584/0.416 0.587/0.413 rs1052576 TT 70(0.130) 98(0.160)    Additive 0.2790 0.2851 TC 258(0.478) 254(0.415) 1 0.9761 0.9999 Dominant 0.2994 0.3467 0.996 CC 212(0.392) 260(0.425)    Recessive 0.4321 0.4519 (0.784,1.266) T/C 398/682 450/774    heterozygous 0.1304 0.1623 0.369/0.631 0.368/0.632 CASP10 rs12613347 TT 74(0.137) 82(0.134)    Additive 0.9752 0.9714 TC 238(0.441) 266(0.435) 0.6406 0.8325 0.8550 Dominant 0.9150 0.9998 0.974 CC 228(0.422) 264(0.431)    Recessive 0.8247 0.8681 (0.764,1.240) T/C 386/694 430/794    heterozygous 0.8829 0.9316 0.357/0.643 0.351/0.649 rs13006529 TT 342(0.633) 366(0.598)    Additive 0.0846 0.0806 TA 164(0.304) 226(0.369) 0.4431 0.9179 0.9452 Dominant 0.3849 0.3863 0.985 AA 34(0.063) 20(0.033)    Recessive 0.0856 0.1072 (0.744,1.305) T/A 848/232 958/266    heterozygous 0.0965 0.1112 0.785/0.215 0.783/0.217 CASP12 rs506601 TT 48(0.089) 48(0.078)    Additive 0.5086 0.5049 TA 230(0.426) 290(0.484) 0.6716 0.6101 0.6427 Dominant 0.6507 0.7603 1.065 AA 262(0.485) 274(0.448)    Recessive 0.3682 0.4018 (0.829,1.369) T/A 326/754 386/838    heterozygous 0.2485 0.2688 0.302/0.698 0.315/0.685 CASP14 rs3181304 GG 120(0.222) 104(0.170)    Additive 0.2007 0.2129 GA 230(0.426) 298(0.487) 1 0.4686 0.4826 Dominant 0.1139 0.1425 0.915 AA 190(0.352) 210(0.343)    Recessive 0.8265 0.8582 (0.724,1.156) G/A 470/610 506/718    heterozygous 0.1424 0.1547 0.435/0.565 0.413/0.587 ∗: Significant, compared by paired t test; H-W: Hardy–Weinberg equilibrium test; P: model-based statistical p value; P’: p value adjusted by permutation; OR: odds ratio; and 95%CI: 95% confidence interval.


## 3.3. Interaction Analysis

We performed a gene-gene interaction analysis on all samples. We found that the interaction ofCASP10 -CASP1, CASP10-CASP3, CASP10-CASP4, CASP10-CASP9, CASP10-CASP12, CASP8 - CASP3, CASP8 - CASP4, andCASP1 - CASP12 is important for the risk of psoriasis (Table 4). Additional results that were not found to be significant were shown in Supplementary Materials (Table S3). The age group under 40 is a high-risk age group for psoriasis. The analysis of intergene interactions in this age group found that the interaction between 10 pairs of genes was significant for the risk of psoriasis. They are the interaction ofCASP8 -CASP10,CASP3 -CASP4,CASP3 - CASP6, CASP3-CASP8,CASP1 -CASP8, CASP1-CASP10,CASP6 -CASP7, andCASP7-CASP9 (Table 5). Additional results that were not found to be significant were shown in Supplementary Materials (Table S4).Table 4
Significant results of intergenic interaction analysis of all samples.
SNP (Chr.) SNP (Chr.) OR_INT Chi-square P rs12613347(2) rs672016(11) 1.87 6.8995 0.0086 rs13006529(2) rs506601(11) 0.384 6.6773 0.0098 rs13006529(2) rs4647610(4) 3.039 6.0643 0.0138 rs4233532(1) rs13006529(2) 0.430 4.9705 0.0258 rs6704688(2) rs4647610(4) 0.54 4.6476 0.0311 rs12613347(2) rs2282659(11) 0.41 4.6218 0.0316 rs506601(11) rs2282659(11) 0.43 4.5832 0.0323 rs6704688(2) rs672016(11) 0.58 4.5381 0.0332 SNP: single nucleotide polymorphism; Chr.: chromosome of single nucleotide polymorphism; OR_INT: odds ratio for interaction; P: p-value.Table 5
Significant results of intergene interaction analysis of samples less than 40 years old.
SNP (Chr.) SNP (Chr.) OR_INT Chi-square P rs13006529(2) rs6704688(2) 4.85 8.9000 0.0029 rs5030545(4) rs2705897(4) 0.12 6.1767 0.0129 rs4647610(4) rs547584(11) 2.90 5.9144 0.0150 rs2293554(2) rs4647610(4) 2.45 5.2208 0.0223 rs4233532(1) rs1052576(1) 0.50 4.9522 0.0261 rs5030545(4) rs4647610(4) 0.24 4.6047 0.0319 rs6704688(2) rs2282659(11) 0.34 4.2747 0.0387 rs5030545(4) rs17090911(10) 0.08 4.0495 0.0442 rs4233532(1) rs2227310(10) 1.82 3.9662 0.0464 rs13006529(2) rs2282659(11) 0.34 3.9280 0.0475 SNP: single nucleotide polymorphism; Chr.: chromosome of single nucleotide polymorphism; OR_INT: odds ratio for interaction; P: p-value.


## 3.4. Haplotype Analysis

The haplotype blocks were imputed by Haploview for each of the 11 genes and we obtained four haplotypes inCASP3 andCASP4 and three haplotypes inCASP7,CASP8,CASP9, andCASP10. The results are shown in Table 6. The results showed that, among the 21 haplotypes, theCASP3 haplotype TT andCASP4 haplotype TC were the two most common in the case and control groups (TT frequencies of 0.633 and 0.657, respectively, and TC frequencies of 0.619 and 0.643, respectively). TheCASP7 haplotype GC was significantly different in patients with PsV than in controls (47.2% versus 54.4%,p = 0.0149). We did not identify the other haplotypes to be significantly associated with PsV (P > 0.05).Table 6
The haplotype analyses result of CASPs in cases and controls.
Gene Haplotype Freq. Case, Control Ratio Counts Case, Control Frequencies Chi Square P Value CASP3 TT 0.646 341.8  : 198.2, 401.9  : 210.1 0.633, 0.657 0.712 0.3989 TC 0.177 94.2  : 445.8, 110.1  : 501.9 0.174, 0.180 0.057 0.8118 GC 0.166 99.8  : 440.2, 90.9  : 521.1 0.185, 0.149 2.721 0.099 GT 0.012 4.2  : 535.8, 9.1  : 602.9 0.008, 0.015 1.234 0.2666 CASP4 TC 0.632 334.5  : 205.5, 393.5  : 218.5 0.619, 0.643 0.685 0.408 TG 0.201 109.5  : 430.5, 122.5  : 489.5 0.203, 0.200 0.013 0.911 CC 0.143 82.5  : 457.5, 82.5  : 529.5 0.153, 0.135 0.758 0.384 CG 0.023 13.5  : 526.5, 13.5  : 598.5 0.025, 0.022 0.106 0.7446 CASP7 GC 0.51 255.0  : 285.0, 333.0  : 279.0 0.472, 0.544 5.934 0.0149∗ GG 0.407 234.0  : 306.0, 235.0  : 377.0 0.433, 0.384 2.894 0.0889 AC 0.082 51.0  : 489.0, 44.0  : 568.0 0.094, 0.072 1.928 0.165 CASP8 CT 0.546 304.0  : 236.0, 325.2  : 286.8 0.563, 0.531 1.157 0.282 TT 0.222 117.0  : 423.0, 138.8  : 473.2 0.217, 0.227 0.172 0.6787 CG 0.214 111.0  : 429.0, 135.8  : 476.2 0.205, 0.222 0.457 0.4991 TG 0.018 8.0  : 532.0, 12.2  : 599.8 0.015, 0.020 0.43 0.5121 CASP9 TC 0.582 314.9  : 225.1, 355.9  : 256.1 0.583, 0.582 0.003 0.9559 CT 0.365 198.9  : 341.1, 221.9  : 390.1 0.368, 0.363 0.041 0.8397 CC 0.05 26.1  : 513.9, 31.1  : 580.9 0.048, 0.051 0.037 0.8465 CASP10 CT 0.431 232.3  : 307.7, 264.4  : 347.6 0.430, 0.432 0.004 0.9506 TT 0.353 191.7  : 348.3, 214.6  : 397.4 0.355, 0.351 0.023 0.8783 CA 0.215 114.7  : 425.3, 132.6  : 479.4 0.212, 0.217 0.031 0.8596 ∗: significant; Freq.: frequencies.We also used Haploview to calculate the haplotypes of individual genes on the same chromosome, estimated the haplotype frequencies, and compared the haplotype distribution between the patients and control groups. We found that the haplotype frequency ofCASP3 (rs2705897) on chromosome 4,CASP7(rs17090911) on chromosome 10, CASP10 (rs12613347) on chromosome 2, andCASP12(rs506601) on chromosome 11 was significantly different between the patients group and the control group. The results are shown in Table 7. We performed the same analysis for the age group under 40 years old and found that the haplotype frequency ofCASP7 (rs17090911) on chromosome 10,CASP9(rs4233532) on chromosome 1,CASP10 (rs12613347) on chromosome 2, andCASP12(rs506601) on chromosome 11 was significantly different between the patients group and the control group. The results are shown in Table 8.Table 7
Haplotype analysis of SNPs on the same chromosome for all samples.
Chr. SNP Haplotype Ca-freq. N-Ca (540) Co-freq. N-Co ( 612) P 1 rs4233532 CC 0.048 25.92 0.053 32.436 0.9226 rs1052576 CT 0.369 199.26 0.364 222.768 TC 0.583 314.82 0.583 356.796 11 rs506601 ACCCG 0.034 18.36 0.027 16.524 0.0093 rs547584 ACCTA 0.116 62.64 0.102 62.424 rs672016 ACGTA 0.028 15.12 0.023 14.076 rs507879 ATCCG 0.057 30.78 0.067 41.004 rs2282659 ATCTA 0.265 143.1 0.277 169.524 ATCTG 0.014 7.56 0.022 13.464 ATGCG 0.049 26.46 0.041 25.092 ATGTA 0.141 76.14 0.139 85.068 TTCCG 0.033 17.82 0.047 28.764 TTCTA 0.245 132.3 0.238 145.656 TTCTG 0.018 9.72 0 0 TTGTA 0 0 0.017 10.404 10 rs17090911 AC 0.094 50.76 0.072 44.064 0.0448 rs2227310 GC 0.473 255.42 0.544 332.928 GG 0.433 233.82 0.384 235.008 2 rs12613347 CACT 0 0 0.012 7.344 0.0038 rs13006529 CATG 0 0 0.01 6.12 rs6704688 CATT 0.2 108 0.196 119.952 rs2293554 CTCG 0.159 85.86 0.164 100.368 CTCT 0.263 142.02 0.248 151.776 CTTT 0.023 12.42 0.023 14.076 TTCG 0.05 27 0.064 39.168 TTCT 0.305 164.7 0.268 164.016 TTTT 0 0 0.015 9.18 4 rs2705897 CGC 0.179 96.66 0.124 75.888 0.00004 rs4647610 CGT 0 0 0.016 9.792 rs5030545 CTC 0.164 88.56 0.161 98.532 CTT 0.576 311.04 0.613 375.156 TGC 0 0 0.023 14.076 TTC 0.017 9.18 0.02 12.24 TTT 0.064 34.56 0.043 26.316 Chr.: chromosome; SNP: single nucleotide polymorphism; N-Ca: number of case group; Ca-freq.: case group frequencies; N-Co: number of control group; Co-freq.: control group frequencies; P: p value.Table 8
Haplotype analysis of SNPs on the same chromosome for samples under 40 years old.
chr SNP Haplotype Ca-freq N-Ca ( 439) Co-freq N-Co (216) P 1 rs4233532 CC 0.545 239.255 0.051 11.016 0.00000 rs1052576 CT 0.401 176.039 0.338 73.008 TC 0.054 23.706 0.611 131.976 11 rs506601 ACCCG 0.042 18.438 0.019 4.104 0.00098 rs547584 ACCTA 0.119 52.241 0.105 22.68 rs672016 ACGTA 0.035 15.365 0.024 5.184 ATCCA 0 0 0.019 4.104 rs507879 ATCCG 0.027 11.853 0.058 12.528 rs2282659 ATCTA 0.309 135.651 0.224 48.384 ATCTG 0.015 6.585 0.038 8.208 ATGCG 0.053 23.267 0.043 9.288 ATGTA 0.117 51.363 0.172 37.152 TTCCG 0.026 11.414 0.054 11.664 TTCTA 0.227 99.653 0.229 49.464 TTCTG 0.018 7.902 0 0 TTGTA 0.012 5.268 0.015 3.24 10 rs17090911 AC 0.094 41.266 0.102 22.032 0.08798 rs2227310 GC 0.436 191.404 0.518 111.888 GG 0.47 206.33 0.38 82.08 2 rs12613347 CACT 0 0 0.015 3.24 0.00000 rs13006529 CATT 0.176 77.264 0.187 40.392 rs6704688 CTCC 0 0 0.161 34.776 rs2293554 CTCG 0.198 86.922 0 0 CTCT 0.289 126.871 0.294 63.504 CTTT 0 0 0.028 6.048 TTCC 0 0 0.073 15.768 TTCG 0.075 32.925 0 0 TTCT 0.262 115.018 0.226 48.816 TTTT 0 0 0.016 3.456 4 rs2705897 CGC 0.176 77.264 0.107 23.112 0.00001 rs4647610 CGT 0 0 0.011 2.376 rs5030545 CTC 0.183 80.337 0.182 39.312 CTT 0.533 233.987 0.644 139.104 TGC 0 0 0.02 4.32 TTC 0.014 6.146 0.016 3.456 TTT 0.094 41.266 0.02 4.32 Chr, Chromosome; SNP, single nucleotide polymorphism; N-Ca, number of case group; Ca-freq, case group frequencies; N-Co, Number of control group; Co-freq, control group frequencies; P, p value.


## 4. Discussion

Genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms (SNPs) associated with psoriasis risk [27, 28]; however, our study was the first to evaluate the association ofCASP family genes SNPs with risk of PsV in Han population in northeast China. We found thatCASP8 rs6704688 and theCASP7haplotype GC were significantly different between cases and controls. These findings suggested that polymorphisms inCASP7andCASP8 were associated with PsV risk in Han population of northeastern China and provide new insights into the importance ofCASP7 andCASP8 in psoriasis susceptibility.The apoptotic pathways of keratinocytes mainly include two mechanisms, and the process is regulated by a variety of proteins, genes, and internal and external stimuli. The “extrinsic" pathway is triggered by the binding of Fas ligand (FasL) or tumor necrosis factor (TNF) to membrane death receptors and these membrane death receptors recruit adapter molecules resulting in the activation of CASP8 [10]. The activated CASP8 then initiates a downstream apoptotic cascade by cleaving CASP3 and/or CASP7 leading to apoptosis. The “intrinsic” pathway includes mitochondrial release of cytochrome c and, along with the cofactor Apaf-1, the formation of an activated CASP9 apoptosome [10]. CASP3 and/or CASP7 are then activated, ultimately leading to apoptosis. Finally, both pathways end with DNA cleavage, which then forms apoptotic bodies and is phagocytosed by neighboring cells.HumanCASP7is located on chromosome 10q25.3 and contains 13 exons, and humanCASP8 is located on chromosome 2q33.1 and contains 14 exons. GWAS study suggests that there are significant correlations between SNPs in the vicinity ofCASP7 andCASP8 and psoriasis (the details are shown in Supplementary Tables S5 and S6.)CASP7 andCASP8encode CASP7 and CASP8 proteins, respectively. SNPs can strongly influence plasma levels and the biological activities of their corresponding proteins [29]. A six-nucleotide insertion/deletion variant rs3834129, which is located in theCASP8 promoter region, is associated with decreased risk of various cancers including cutaneous melanoma [30–32]. rs6704688 is located in the intron region ofCASP8. While the function of rs6704688 is not yet known, we know that it is located near rs3834129 and is in high LD with rs3834129. Therefore, we inferred that rs6704688 may not be a true causal variant and that the relationship between rs6704688 and PsV could be attributed to the presence of rs3834129 in the population. Computational molecular and biochemical analyses have confirmed that the rs3834129 DEL allele disrupts the binding site of the transcriptional activator Sp1, thereby reducing the transcription and expression ofCASP8 [31]. Low CASP8 expression or functional aberrations may suppress T-lymphocyte apoptosis [31]. T cells and their cytokines play a central role in the pathogenesis of psoriasis [33]. The pathogenic T cells enter the skin, become activated, and release chemokines and cytokines to attract other immune cells to mediate keratinocyte hyperproliferation and maintain the inflammatory process of psoriasis [33]. Studies have shown the DEL allele and DEL carrier of rs3834129 had negative associations with cancer susceptibility in Asian populations and rs6704688 is associated with reduced cancer risk [13]. Combined with our study, we predicted that the T allele and T-carriers of rs6704688 were negatively correlated with the susceptibility to PsV from the additive model, whereas the heterozygous TC genotype had a protective effect from the heterozygous model. In the follow-up, we will conduct a detailed study of rs3834129.Given the role of CASP7 in apoptosis and inflammation, the associations among CASP7 and autoimmune diseases and cancer susceptibility are important. Their relevance has been reported in insulin-dependent diabetes mellitus, rheumatoid arthritis, childhood leukemia, and different types of human cancers [18, 21]. Soung et al. found that aCASP7 gene inactivating mutation (70 Cys to Tyr mutant) could lead to loss of apoptotic function [18]. Thus, we hypothesized that genetic variations inCASP7 may act as strong apoptosis signals to block or delay the apoptosis of keratinocyte cells in PsV. The frequency of the haplotype GC in cases was lower than controls, which implied a protective role with regard to cases versus controls.This study had some limitations. First, it is a hospital-based case-control study and the sample size was relatively small, which may limit the statistical power to explore the real association. In the future, we need to further study the larger sample size and ethnicity to validate our results. Next, we tested limited polymorphisms that were representative inCASPgenes; these polymorphisms may not be the critical loci for psoriasis but may instead be nearby in LD with a causative locus. Studies on the correlations of more gene loci are needed. Additionally, more comprehensive studies, such as additional clinical studies and functional analyses, are needed to explain and supplement our findings. Despite these limitations, our study demonstrated the association betweenCASP7 andCASP8 polymorphisms and the PsV risk.


## 5. Conclusions

In conclusion, our findings demonstrated thatCASP7 andCASP8 gene polymorphisms were associated with PsV risk in Han population of northeastern China. This is the first study describing the relationships between genetic polymorphisms inCASP family genes and PsV susceptibility in Han population in northeast China.CASP7 andCASP8 gene polymorphisms may be involved in the etiopathogenesis of PsV, and analysis of these polymorphisms could provide new insights into the diagnosis and treatment of PsV.



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