A Pilot Genome-Wide Association Study Identifies Novel Markers of Metabolic Syndrome in Patients with Psoriasis

Abstract

Background

Recent studies have reported that psoriasis is associated with the development of metabolic syndrome. Genome-wide association studies have been used to discover gene variant markers that occur frequently in case group in relation to specific diseases.

Objective

The aim of the present study was to investigate the variants of specific genes involved in metabolic syndrome associated with psoriasis.

Methods

A total of 95 psoriasis patients were recruited and divided into two groups: one with metabolic syndrome (38 patients) and the other without (57 patients). After genotyping, imputation, and quality checking, the association between the several single nucleotide polymorphisms and metabolic syndrome in psoriasis was tested, followed by gene set enrichment analysis.

Results

We found 76 gene polymorphisms that conferred an increased risk for metabolic syndrome in patients with psoriasis. Four single nucleotide polymorphisms (rs17154774 of FRMD4A, rs77498336 of GPR116, rs75949580 and rs187682251 of MAPK4) showed the strongest association between metabolic syndrome and psoriasis. The epidermal growth factor receptor protein was located at the center of the protein interactions for the gene polymorphisms.

Conclusion

This study identified several previously unknown polymorphisms associated with metabolic syndrome in psoriasis. These results highlight the potential for future genetic studies to elucidate the development, and ultimately prevent the onset, of metabolic syndrome in patients with psoriasis.

INTRODUCTION

Psoriasis is a chronic inflammatory skin disease caused by a complex interaction between genetic and environmental risk factors¹. The involvement of genetic factors is suggested by a higher incidence of the disease among relatives and a higher concordance rate among monozygotic twins over dizygotic twins². Environmental factors associated with the development of psoriasis include ultraviolet radiation, drugs, infection and stress³.

Psoriasis is associated with multiple comorbidities, including Crohn’s disease, cancer, psoriatic arthritis, cardiovascular disease, and metabolic syndrome (MetS)⁴. MetS is a clustering of glucose intolerance, insulin resistance, dyslipidemia, central obesity, and hypertension, which significantly increases the risk of developing cardiovascular disease and type 2 diabetes mellitus⁵. An increasing number of studies has reported an association between psoriasis and MetS. A systematic review and meta-analysis of observational studies revealed that psoriasis patients had a higher prevalence of MetS, and patients with more severe psoriasis had greater odds of experiencing MetS than those with milder psoriasis⁶. One study reported that the prevalence of psoriasis was significantly higher in adolescents with obesity than other adolescents. The adolescents with psoriasis also had higher blood lipid levels than those without psoriasis, which could increase the risk for cardiovascular diseases⁷. Multiple inflammatory and cytokine-mediated pathways are reportedly shared between psoriasis and MetS; however, the exact pathogenic mechanism of the association between psoriasis and MetS is complex and not fully understood⁸.

Over the past two decades, large-scale genomic studies have been actively performed to uncover the genetic background of psoriasis. Linkage analysis identified nine genomic regions that co-segregated with psoriasis (PSORS1-9) in multiplex pedigrees⁹. Genome-wide association studies (GWAS) can genotype several million genetic markers across the genome, and this has fundamentally impacted the genetic dissection of complex diseases¹⁰. In 2010, initial GWAS efforts in psoriasis identified twenty-one susceptibility loci in Europeans¹¹. Identification of single nucleotide polymorphisms (SNPs) in MetS is also an active area of research, and one GWAS of MetS in the Korean population identified 17 novel SNPs associated with MetS¹². The genetic basis of the possible association between psoriasis and MetS is yet to be reviewed in detail. The aim of the present study was to perform GWAS to investigate the variants of specific genes associated with MetS involved in psoriasis.

MATERIALS AND METHODS

Study subjects

The study included patients diagnosed with psoriasis who visited the Department of Dermatology, Kyung Hee University Hospital, Seoul from January 1st 2017 to June 25th 2018. The diagnosis of psoriasis was based on clinical features. Table 1 shows the patient demographics. Blood samples were collected and stored in a biorepository. The patients were further classified into ‘MetS’ and ‘non-MetS’ according to the waist circumference (WC), levels of triglyceride, high-density lipoprotein (HDL)-C, fasting blood glucose (FBG), and blood pressure. For the definition of MetS we used the following criteria proposed by the International Diabetes Federation¹³. MetS was diagnosed if more than 3 of the following indications were present: (1) systolic blood pressure (SBP) ≥130 mmHg or diastolic blood pressure (DBP) ≥85 mmHg or currently on hypertension medication, (2) TG ≥150 mg/dl, (3) HDL-C level <40 mg/dl for male and <50 mg/dl for female, (4) FBG level ≥100 mg/dl or currently on diabetes medication, and (5) WC ≥90 cm for male and ≥80 cm for female. All participants signed an informed consent form in accordance with the Helsinki Declaration. All methods were performed in accordance with the relevant guidelines and regulations. This study was approved by the Institutional Review Board of Kyung Hee University Hospital (IRB number: KHUH 2018-06-069).

Table 1. Patient demographics.

		MetS (n=38)	non-MetS (n=57)
Age (yr)		45.22±15.56	44.93±16.45
Sex
	Female	12 (31.6)	20 (35.1)
	Male	26 (68.4)	37 (64.9)
Duration of psoriasis (yr)		13.38±12.42	14.32±11.21
Comorbidities
	Hypertension	17 (44.7)	5 (8.7)
	Diabetes mellitus	6 (15.8)	3 (5.3)
	Psoriatic arthritis	6 (15.8)	6 (10.5)
PASI score		15.89±11.23	12.61±9.75
BSA (%)		12.92±9.49	10.44±8.68

Values are presented as mean±standard deviation or number (%). MetS: metabolic syndrome, PASI: psoriasis area and severity index, BSA: body surface area.

DNA extraction and genotyping

Genomic DNA was separated from the blood of the subjects using a commercial DNA extraction kit (High Pure Template PCR Preparation Kit; Roche) according to the manufacturer’s protocol. The quality of DNA at both 260/280 and 260/230 absorbance ratios was tested. DNA samples with an absorbance ratio of 1.8 or higher were regarded as pure DNA and authorized for genotyping. Genotype data were generated using the Axiom^® Precision Medicine Research Array (PMRA; Thermo-Fisher Scientific) chip. The following exclusion criteria were applied for SNP quality control: genotype call rate <97% and Hardy–Weinberg equilibrium (HWE) with p-value <0.0001.

Statistical analysis

The association between MetS and SNPs in psoriasis was tested using GWAS. An additive genetic model is usually employed in GWAS. The model encodes “AA”, “Aa”, and “aa” (“a” represents the minor allele) of each SNP. In this model. A linear and uniform increase is assumed based on the number of each copy of the disease-causing allele (a).

For association tests in GWAS, logistic regression analysis was performed using PLINK to search for candidate SNPs of MetS in patients with psoriasis (https://zzz.bwh.harvard.edu/plink/). Odds ratios (OR), 95% confidence intervals (CI), and p-values were used to evaluate statistical significance. Network string analysis is used to visualize the GWAS results to Manhattan plots using R package. A string website was used to view the interaction network of genes containing significant genetic polymorphisms (https://string-db.org/).

RESULTS

The GWAS analysis included 95 patients (38 with MetS and 57 without MetS) (Table 1). A total of 880,589 of 920,744 polymorphisms were produced for GWAS analysis using the Axiom^® PMRA chip.

During the quality check filtering process, 299,269 polymorphisms were excluded due to X, Y, or mitochondrial region; monomorphic SNPs; or HWE error. A total of 617,183 polymorphisms were analyzed in the final GWAS analysis. Among these polymorphisms, 34,833 showed a significant association, with the p-value below 0.05 (data not shown). The Manhattan plot of GWAS (MetS [n=38] versus non-MetS [n=57]) is shown in Fig. 1. Significant genes on the Manhattan plot represent each position on chromosomes 6, 10, 15, and ¹⁸. In the genetic additive model analysis (major homo-genotype versus hetero-genotype versus minor homo-genotype), the most significant genes associated with MetS in psoriasis in GWAS analysis were the FERM domain containing 4A (FRMD4A), G protein-coupled receptor 116 (GPR116), and mitogen-activated protein kinase 4 (MAPK4) (p<0.0001, respectively). The positions of the SNPs (rs17154774 SNP of FRMD4A gene, p=1.78E-07; rs77498336 SNP of GPR116 gene, p=2.15E-07; rs75949580, p=5.44E-07 and rs187682251, p=6.12E-07 SNP of MAPK4 gene) listed in Table 2 and adjacent genes in these significant polymorphisms are shown in Fig. 2. The results of the allele frequency analysis between control and case can be found in the Supplementary Table 1.

Fig. 1. Manhattan plot of GWAS data. The blue line is the cut off line for showing the SNPs shown in Table 1. The SNPs are marked on the Manhattan plot with rs number. GWAS: genome-wide association study, SNP: single nucleotide polymorphism.

Table 2. SNPs showing significant association with metabolic syndrome in psoriasis patients by GWAS analysis.

SNP ID	Chromosome	Position	Regression	OR (95% CI)	Gene symbol	Gene full name
			p-value
rs17154774	10	14218967	1.78E-7	40.2 (5.05-320.42)	FRMD4A	FERM domain containing 4A
rs77498336	6	46963418	2.15E-7	13.99 (4.01-48.85)	GPR116	G protein-coupled receptor 116
rs75949580	15	39480510	5.44E-7	5.94 (2.86-12.36)	-	Transcribed locus
rs187682251	18	48323745	6.12E-7	6.43 (2.95-14.02)	MAPK4	Mitogen-activated protein kinase 4
rs151324728	20	51107608	1.40E-6	10.19 (3.64-28.55)	-	-
rs72711706	1	181114807	1.55E-6	6.02 (2.8-12.95)	LOC101928973	Uncharacterized LOC101928973
rs57881454	11	74987469	1.76E-6	12.96 (3.92-42.82)	ARRB1	Arrestin, beta 1
rs142306868	13	47175740	3.14E-6	9 (3.18-25.53)	LRCH1	Leucine-rich repeats and calponin homology (CH) domain containing 1
rs76987874	10	59172879	5.02E-6	11.17 (3.17-39.45)	-	-
rs17820003	17	54346896	9.78E-6	6.12 (2.58-14.55)	ANKFN1	Ankyrin-repeat and fibronectin type-III domain containing 1

OR: odds ratio, CI: confidence interval, GWAS: genome-wide association study, SNP: single nucleotide polymorphism.

Fig. 2. A plot showing the region around the most significant SNPs (p<1.0E^-7) in the present GWAS. The plot was created with LocusZoom. GWAS: genome-wide association study, SNP: single nucleotide polymorphism.

GWAS analysis results confirmed 76 polymorphisms as risk factors, and 190 polymorphisms as protective factors for MetS development in psoriasis patients (p<0.0001). Network string analysis was performed to investigate the interactions between these genes. The network centered on the epidermal growth factor receptor (EGFR) protein, which contributes to the pathogenesis of MetS in patients with psoriasis (Fig. 3).

Fig. 3. Target genes including significant polymorphisms in the STRING network. A total of 190 shared genes are ordered by their connectivity degree in the network. STRING: search tool for the retrieval of interacting genes/proteins.

DISCUSSION

The association between psoriasis and MetS has been reported; however, it is still unclear whether one of the two conditions precedes or causes the other¹⁴. In a population-based study in the UK, psoriasis was associated with MetS in a‘dose-response’ manner in which the odds of developing MetS increased with the severity of psoriasis¹⁵. Although the exact biological mechanism that accounts for the association is yet to be elucidated, a possible hypothesis is that the proinflammatory state associated with psoriasis drives development of MetS¹⁴. Proinflammatory cytokines such as tumor necrosis factor-α and interleukin-6 (IL-6), which are overexpressed in psoriasis lesions, may contribute to hypertension, lipid metabolism and insulin resistance¹⁶. The increased burden of MetS among patients with psoriasis supports the possible benefit of regular screening for MetS in this patient group¹⁷. Recent studies also report genetic associations between psoriasis and MetS. Liu et al.¹⁸ examined 18 SNPs previously reported to be significantly associated with MetS, and found seven which were significantly associated with psoriasis in the Han Chinese population. Abdel Hay and Rashed¹⁹ suggested that the leptin gene (LEP G-2548A) polymorphism could be a predictor for psoriasis and MetS among a sample of the Egyptian population, by showing that patients carrying the LEP G-2548C allele had a significantly higher prevalence of psoriasis and MetS than non-carriers.

Researchers historically have employed markers in candidate genes, or in all the genes belonging to a biological pathway or having a similar biological function, to detect alleles conferring increased or decreased risk to common diseases with a complex genetic component²⁰. The candidate-gene approach assesses the association between genetic variation within a gene relevant to the disease being investigated, and the disease itself²¹. Despite early success, the candidate-gene approach is largely limited by its reliance on existing knowledge about the phenotype under investigation, and low replication in subsequent association studies²². GWAS is a more comprehensive and unbiased approach to employ markers encompassing the entire genome²⁰. GWAS identifies associations between genotypes and phenotypes by testing for differences in allele frequency of genetic variants between individuals who share similar ancestry but differ phenotypically²³. In GWAS analysis, disease markers can be discovered comparative analysis of millions of SNPs through case-control or cohort study design²⁴. GWAS analysis is often employed in large-scale research projects to discover genetic markers for specific diseases. In a pilot study such as ours, GWAS analysis can be a good option to discover candidate markers when utilized in combination with the existing candidate-gene approach.

To find the appropriate genetic marker candidate for the development of MetS in psoriasis patients, we screened the genetic region of psoriasis patients using the PMRA chip. We examined genes with a p-value of less than 0.0001 in the obtained results. In the GWAS analysis results, the four most significant genetic polymorphisms were identified; rs17154774 SNP of the FRMD4A gene; rs77498336 SNP of the GPR116 gene; rs75949580, rs187682251 SNPs of the MAPK4 gene. By virtue of these findings, we presume that these four SNPs are risk factors for the development of MetS in patients with psoriasis. To date, there is no published research identifying these four SNPs as disease markers for the development of MetS in patients with psoriasis.

The FRMD4A gene, also known as FRMD4, CCAFCA, and bA295P9.4 is located on the human chromosome 10p13. This gene encodes a FERM domain-containing protein that regulates epithelial cell polarity by connecting ADP ribosylation factor 6 (ARF6) activation with the par-3 family cell polarity regulator (PAR3) complex²⁵. Hu et al.²⁶ reported that the knockout of ARF6 in podocytes contributed to cholesterol accumulation in podocytes under high glucose condition. In previous studies, it was also confirmed that FRMD4A, a genetic risk factor for late-onset Alzheimer's disease, regulates tau secretion by activating cytohesin–Arf6 signaling²⁷. The GPR116 gene is located on human chromosome 6p12.3. In a recent study by Zhang et al.²⁸, the GPR116 gene encoded ADGRF5 which was found to be a key prognostic marker for clear cell renal cell carcinoma. The MAPK4 gene is located on the human chromosome 18q21.1, and MAPK4 overexpression in patients with lung adenocarcinoma, bladder cancer, low-grade glioma, and thyroid carcinoma is correlated with decreased overall survival, with particularly marked survival effects²⁹. Lu et al.³⁰ found that signaling pathways including the MAPK6/MAPK4 complex could be used as biomarker for osteoporosis using differentially expressed genes (DEG) analysis.

Genetic polymorphisms could affect the mRNA transcription of genes and may further lead to abnormal protein translation³¹. Protein-protein interaction analysis of genes displaying significant polymorphisms could determine the possible detrimental effect of a polymorphism on protein function. It is necessary to evaluate the mutual network of genes containing genetic polymorphisms shared between the two disease groups. In this study, we found 266 polymorphisms (76 risk factors and 190 protective factors) related to the risk of developing MetS in patients with psoriasis. Protein-protein analysis of these polymorphic genes confirmed that several proteins were related to the EGFR protein (Fig. 3). EGFR is a member of the receptor tyrosine kinase family involved in many important activities of cell development such as cell homeostasis, proliferation, division, differentiation and apoptosis³². Previous studies reported that the expression and activity of EGFR and its endogenous ligands were increased in the active epidermal lesions of psoriasis patients³³. Kim et al.³⁴ reported that serum EGFR levels were elevated in patients newly diagnosed with type 2 diabetes mellitus. The protein-protein analysis results suggest that certain genes related to EGFR are associated with the pathogenesis of MetS in psoriasis patients, and genetic polymorphisms within these genes also influence the MetS phenotype in psoriasis patients. The limitation of this study is that the study was performed in a single-center setting, and thus only a small number of subjects were recruited for GWAS. A large sample size is required to ensure high accuracy of significant SNPs found in any GWAS. Although this study is limited by its sample size, the significant SNPs in this study could function as a reference point for future research in genetic studies for the link between MetS and psoriasis.

In conclusion, we found significant polymorphisms with statistically different genotype distributions between the MetS and non-MetS groups in patients with psoriasis (p<0.0001). Although the genes with polymorphisms mentioned above may not be directly related to the development of MetS in patients with psoriasis, the four SNPs with the strongest association could be used as predictive biomarkers for MetS in psoriasis. The significance of the polymorphisms found in this study would be strengthened by comparative analysis of the frequency of the genes in a larger scale study, which in turn would elucidate the genetic background of the pathogenesis of MetS in patients with psoriasis. Further biological studies are required to determine whether the EGFR pathway is involved in the pathogenesis of MetS in psoriasis.

DATA SHARING STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

SUPPLEMENTARY MATERIALS

Supplementary data can be found via http://anndermatol.org/src/sm/ad-22-196-s001.xls.

Supplementary Table 1

The results of allele frequency analysis between control and case