Skip to main content

Advertisement

ADVERTISEMENT

Original Research

Risk of Keloid Associated with Polymorphic PTEN Haplotypes in the Chinese Han Population

January 2014
1044-7946
WOUNDS. 2014;26(1):21-27.

Abstract

Chromosomal DNA sequence polymorphisms may contribute to individuality, confer risk for diseases, and most commonly, be used as genetic markers in association studies. This study determined the distribution of the phosphatase and tensin homolog (PTEN) gene polymorphisms (rs2299939, rs17431184, rs555895, rs701848) in the Chinese Han population and investigated whether these polymorphisms were associated with the increased risk of keloids in this population. The rs2299939 and rs17431184 correlated significantly with keloids. The frequency of A allele of rs2299939 was lower in patients with keloids compared with the control group. The population with A allele had lower keloid risk than the population without A allele (OR = 0.69, 95% CI: 0.51-0.94). The CC genotype of rs2299939 was the risk factor of keloids and these patients had a lower rate of the ACTC haplotype (constructed with A allele in rs2299939, C allele in rs17431184, T allele in rs555895, and C allele in rs701848) compared with controls (P < 0.05, χ2 = 4.537). The population with the ACTC haplotype had a 0.263-fold risk to have keloids, and the 95% CI was 0.182-0.899, suggesting this haplotype as a protected factor of keloids. The expression of the PTEN gene was high in individuals with the ACTC haplotpye compared with others. These findings suggested that rs2299939 could play an important role in keloid physiological processes in the Chinese.

Introduction

  Keloid scarring, also known as keloid disease (KD), is a common, abnormally raised fibroproliferative cutaneous lesion that can occur following even minor skin trauma. Keloid is a dermal fibroproliferative growth that results from dysfunction of the wound healing processes.1 The etiopathogenesis of KD has remained an enigma to date, compounded by ill-defined clinical management. There is strong evidence suggesting a genetic susceptibility in individuals affected by KD, including familial heritability, common occurrence in twins, and high prevalence in certain ethnic populations. The highest incidence of keloids is found in the black African population, where it has been estimated around 4-6% and up to 16% in random samples.2 The search for additional loci includes thoughtful selection of candidate genes in key biological pathways, an approach which has been successful in identifying new risk alleles for a variety of cancers.3   Research has indicated a variety of inheritance patterns in KD (predominantly autosomal dominant), such as linkage loci (chromosomes 2q23 and 7p11), several human leukocyte antigen (HLA) alleles (HLA-DRB1*15, HLA-DQA1*0104, DQ-B1*0501, and DQB1*0503), negative candidate gene case-control association studies, and at least 25 dysregulated genes reported in multiple microarray studies.4 Nakashima et al1 reported that 4 single-nucleotide polymorphisms (SNPs) (rs873549, rs1511412, rs940187, rs8032158) were in significant association with keloids by a genome-wide association study in the Japanese population. The expression of the phosphatase and tensin homolog (PTEN) gene was high in individuals with ACTC haplotype compared with others. These findings suggested that rs2299939 could play important roles in the keloid physiological processes in the Chinese Han. Brown and colleagues2 investigated and found the SMAD family may be of significant importance in diagnosis, prognosis, and development of new therapies in the management of keloid scarring. Yan et al5 investigated the relationship between the p53 gene codon 72 polymorphism and genetic predisposition to KD in the Chinese Han population by polymerase chain reaction (PCR)-based restriction fragment length polymorphism (RFLP) analysis, and found that the Arg/Arg genotype was significantly higher than the Pro/Pro genotype among patients with KD in their shoulder and back. They also suggested that further research should be done to investigate the relationship between the p53 gene codon 72 polymorphism and keloids in different sites. Single-nucleotide polymorphisms in TGF-beta receptors I, II, and III (TGF-betaRI, TGF-betaRII, and TGF-betaRIII) were identified and investigated for association with the risk of developing KD.6-8   Keloid disease and hypertrophic scars are dermal tumors that are often familial and typically occur in certain races. Polymorphisms are distributed differently in populations, including those of regions, ethnic groups, and diseased patients.9 Genetic variations in MDM2, PTEN, and P53 might be involved in cancer susceptibility.10 The PTEN gene, a candidate tumor suppressor, is one of the most commonly inactivated and extensively studied genes in cancer research. However, few data are available about the relationship between polymorphic PTEN and KD. Since PTEN is involved in many biological processes, questions about whether or not genomic variations such as SNPs have an effect on the structure and function of PTEN protein, and about whether or not these variations contribute to the different susceptibility of individuals in response to environmental insults, are interesting health-related issues.9,10 The purpose of this study was to determine the involvement of the PTEN gene in KD in the Chinese Han population. To test the hypothesis that genetic variations of PTEN may play a role in the etiology of KD, a population based case-control study was conducted on 400 patients with KD and 400 healthy control subjects. Genotyping technology (MassARRAY System, Sequenom, San Diego, CA) was used to determine the distribution of PTEN genotypes in the Chinese Han population, and revealed the relationship between these polymorphisms and keloids.

Material and Methods

  Study participants. Four hundred participants were recruited at Xiangya Hospital of Central South University, the Second Xiangya Hospital of Central South University, and the Third Xiangya Hospital of Central South University, all located in Changsha, Hunan, China). Informed consent was obtained from individual patients and experimental protocols were approved by the Institutional Review Board of each hospital. Cases were diagnosed histologically. The control subjects, 400 healthy individuals without KD, were recruited from general medical examinations and frequency-matched to cases based on age and region of residence. All subjects enrolled in the study were Chinese Han. There was no significant difference in distribution between patients with KD and the control subjects (Table 1).   Data and biospecimen collection. Information on known and suspected risk factors was collected through in-person interviews. The study participants had an extra vial of blood drawn during their scheduled visit. Samples were bar-coded to ensure accurate and reliable sample processing and storage. Deoxyribonucleic acid was extracted from 5-10 mL fresh peripheral blood using a genome extraction kit (BloodGen Maxi Kit, Kangwei, Beijing, China). Genomic DNA concentrations were prepared to 50µg/µl before genotyping.11,12 Ten biopsies of keloids were collected, and each biopsy sample was divided into 2 sections; 1 was submitted for routine histological diagnosis, and the other was flash-stored at -80º C in a stabilization reagent (RNAlater Stabilization Reagent, Qiagen, Carlsbad, CA).   Single-nucleotide polymorphism information and genotyping. Four SNPs (rs2299939, rs17431184, rs555895, rs701848) are from the PTEN gene in chromosome 10 (10q23.3). These SNPs are located in 89657150 to 89726745 on chromosome 10. Rs2299939, rs17431184, and rs555895 are located in intron 2, 5, and 6, respectively. Rs701848 is in mRNA 3’UTR (Figure 1). Genotyping of 800 genomic samples was performed by BGI, Shenzhen, China, using genotyping technology for automated genotype clustering, and calling separately for genomic information, according to standard protocol.   RNA extraction and real-time quantitative reverse transcription-PCR analysis. Total RNA was extracted from the biopsy samples with an RNA purification kit (RNeasy Mini Kit, Qiagen, Carlsbad, CA) according to the manufacturer’s recommendations. The total RNA samples (1ug) were used to generate cDNA. Total RNA was reverse-transcribed (AMV reverse transcriptase, Promega, Madison, WI) at 42°C for 1 hour and subsequently heated at 95°C for 5 minutes. Reverse transcription (RT) was carried out as previously described.13 After the RT reaction, real-time quantitative PCRs were performed according to manufacturer’s instruction using a Light-Cycler FastStart DNA Master SYBR Green I (Roche Diagnostics, Basel, Switzerland), which fluoresces on binding to double-stranded DNA. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as the internal control. The sequences of the primers used for real-time quantitative RT-PCR were as follows: PTEN forward, 5’- agttccctcagccgttacct -3’, reverse, 5’- aggtttcctctggtcctggt -3’; GAPDH forward, 5’-accacagtccat gccatcac-3’, reverse, and 5’-tccaccaccctgttgctgta-3’. Expression of mRNA was assessed by evaluated threshold cycle (CT) values. The CT values were normalized with the expression levels of GAPDH and the relative amount of mRNA specific to each of the target genes was calculated using the 2-ΔΔCT method.14

Statistical Analysis

  Distribution of age and gender was compared across case status using chi-square tests. Single-nucleotide polymorphisms associations for KD risk were assessed using SHEsis analysis software.15,16 PHASE and Haplotyper software was used for haplotype inference.17 Testing for association was completed using the freely available program SNPGWA.18-20 Each single SNP was tested for departure from Hardy-Weinberg equilibrium.

Results

  Association of PTEN SNP alleles with keloid risk. The allele frequencies for PTEN gene polymorphisms are shown in Table 2. The allele frequency distributions were in accordance with Hardy-Weinberg equilibrium expectations for both the control group and the patients with KD (P > 0.05). The rs2299939 and rs17431184 correlated significantly with KD. The frequency of A allele of rs2299939 was lower in patients with KD compared with the control group (P < 0.05, χ2=5.86). The population with A allele had lower KD risk than the population without A allele (OR = 0.69, 95% CI: 0.51-0.94). The frequency of C allele of rs17431184 was lower in patients with KD relative to the control group (P < 0.05, χ2 = 5.96). The population with C allele had lower KD risk than the population without C allele (OR = 0.69, 95% CI: 0.50-0.94). No significant differences in the distribution of alleles were observed between the control group and the patients with KD in the rs555895 and rs701848 polymorphism.   Association of PTEN SNP genotypes with keloid risk. The relationship between genotype distribution and KD was analyzed. The genotype frequency distributions were in accordance with Hardy-Weinberg equilibrium expectations for both the control group and the KD patients (P > 0.05). The rs2299939 polymorphism correlated with KD. The frequency of the CC genotype was significantly higher while the AC genotype was significantly lower in KD patients compared with the control group (P < 0.05, χ2 = 5.61). The CC genotype was a risk factor for KD. There was the same distribution of rs17431184. The frequency of the TT genotype was significantly higher, whereas the CT genotype was significantly lower in patients with KD relative to the control group (P < 0.05, χ2=5.83 ). No significant difference in the distribution of genotypes were observed between the control group and the patients with KD in the rs555895 and rs701848 polymorphism (P > 0.05).   Risk of KD associated with common PTEN haplotypes. To discover which haplotypes indicate risk of, or protection from, KD, the authors found the distribution of haplotype between the 2 groups. Patients with KD had a lower rate of ACTC haplotype (constructed with rs2299939, rs17431184, rs555895, rs701848) compared with the control group (P >0.05, χ2=4.537). The population with ACTC haplotype had a 0.263-fold risk of KD, with a 95% CI of 0.182-0.899, indicating the ACTC haplotype protected patients from KD. No significant differences in the distribution of CTGT, CTTC, and CTTT haplotypes were observed between the control group and the patients with KD (P >0.05)(Table 5).   The relationship of ACTC haplotpye with PTEN mRNA expression levels. To reveal the relationship between haplotypes and PTEN expression levels, 10 samples were chosen with or without ACTC haplotype to perform a real-time quantitative RT-PCR. The fold change in the mRNA expression of the PTEN gene relative to the internal control gene (GAPDH) was studied. The expression of the PTEN gene in individuals with ACTC haplotype was 3.34-fold compared to those without ACTC haplotype (Table 5).

Discussion

  Keloid disease and hypertrophic scars are dermal tumors that often have a familial predisposition, and typically occur in certain races. It is desirable to identify disease loci in the human genome based on DNA sequence polymorphism information by using various approaches including linkage-based association studies.21 Decades ago, microsatellite markers of low densities were used in linkage analyses and now SNPs of high densities are used in association studies.22-25 The PTEN gene is a tumor-suppressor gene that controls a variety of biological processes including cell proliferation, migration, and death. This gene, a regulator of the phosphatidylinositol-3-kinase (PI3K)/Akt oncogenic pathway, is mutated in various cancers and its expression has been associated with tumor progression in a dose-dependent fashion. The association of PTEN polymorphisms with risk for many tumors has been reported.9,10,26-28 However, few data are available about the relationship between polymorphic PTEN and KD.   In this study, the authors uncovered the distribution of PTEN gene polymorphisms (rs2299939, rs17431184, rs555895, rs701848) in the Chinese Han population, and found that rs2299939 and rs17431184 correlated significantly with KD. The frequency of A allele of rs2299939 was lower in patients with KD compared with the control group. The population with A allele had lower KD risk than those without A allele (OR = 0.69, 95% CI: 0.51-0.94). There was a similar distribution of rs17431184, but no significant differences in the distribution of alleles were observed between the control group and the patients with KD in the rs555895 and rs701848 polymorhism. Phosphatase and tensin homolog plays an essential role in cellular processes including survival, proliferation, energy metabolism, and cellular architecture. By molecular dynamics approach, SIFT, PolyPhen, I-Mutant 3.0, SNP&GO, and PHD-SNP were used for initial screening of functional nsSNPs. George and Rajith29 found that H61D showed increase in flexibility, radius of gyration, solvent accessibility, and deviated more from the native structure of PTEN, which was supported by the decrease in the number of hydrogen bonds. Single-nucleotide polymorphisms could potentially influence post-translational modifications in the PTEN gene. These in silico predictions could provide a new insight into structural and functional impact of PTEN polymorphisms.29   The following results of genotype showed the frequency of CC genotype of rs2299939 was significantly higher in patients with KD compared with the control group. The CC genotype was a risk factor for KD. Patients with KD had a lower rate of ACTC haplotype (constructed with rs2299939, rs17431184, rs555895, rs701848) compared with the control group (P >0.05, χ2 = 4.537). The population with ACTC haplotype had a 0.263-fold risk for KD, and the 95% CI was 0.182-0.899. It was concluded that ACTC haplotype was the protected factor; the population with these haplotypes had a lower risk than others. To reveal the relationship between haplotypes and PTEN expression levels, the mRNA expression levels in samples, with ACTC haplotype or without, were tested. The expression of the PTEN gene was 3.34-fold higher in individuals with ACTC haplotype compared to those without it. In terms of the relationship of gene polymorphisms and their expression, there were similar results in other labs. Radovich et al30 found that haplotypes in the VEGF gene affected its expression. Ju et al31 found that SERPINE1 intron polymorphisms affecting gene expression were associated with diffuse-type gastric cancer susceptibility. Toepoel et al32 studied and hinted that haplotype-specific expression of the human PDGFRA gene correlated with the risk of glioblastomas. Hirata et al33 showed that COMT polymorphisms affecting protein expression were risk factors for endometrial cancer.

Conclusion

  The current study’s findings suggest rs2299939, rs17431184, and ACTC haplotype could play important roles in KD physiological processes for the Chinese Han population. Although further studies are needed to investigate the biological role of these PTEN polymorhisms in the pathological implications in the development of KD, the current findings provide new insights into the pathophysiology of keloid formation.

Acknowledgments

Jing Li, PhD is from the Department of Neurology, Xiangya Hosptial, Central South University, Changsha, China. Xiang Chen; Hongfu Xie; Jie Li; Ji Li; Juan Su; Mei Yi; and Wu Zhu, PhD are from the Department of Dermatology, Xiangya Hosptial, Central South University, Changsha, China. Yanhong Zhou is from the Cancer Research Institute, Central South University, Changsha, China.

Address correspondence to: Wu Zhu, PhD Department of Dermatology Xiangya Hosptial Central South University Changsha 410008 China hongyi2011xy@gmail.com

Disclosure: This work was supported by the National Natural Sciences Foundation of China (81272975); the Planned Science and Technology Project of Hunan Province (2010FJ3088); Key Project of Hunan Provincial Natural Science Foundation (12JJ2044); and the National Innovative Experimental Program for Undergraduates of Central South University (YC10112).

References

1. Nakashima M, Chung S, Takahashi A, et al. A genome-wide association study identifies four susceptibility loci for keloid in the Japanese population. Nat Genetics. 2010;42(9):768-771. 2. Brown JJ, Ollier W, Arscott G, et al. Genetic susceptibility to keloid scarring: SMAD gene SNP frequencies in Afro-Caribbeans. Exp Dermatol. 2008;17(7):610-613. 3. Dong LM, Potter JD, White E, Ulrich CM, Cardon LR, Peters U. Genetic susceptibility to cancer: the role of polymorphisms in candidate genes. JAMA. 2008;299(20):2423-2436. 4. Shih B, Bayat A. Genetics of keloid scarring. Arch Dermatol Res. 2010;302(5):319-339. 5. Yan L, Lu XY, Wang CM, et al. Association between p53 gene codon 72 polymorphism and keloid in Chinese population [in Chinese]. Zhonghua Zheng Xing Wai Ke Za Zhi. 2007;23(5):428-430. 6. Bayat A, Bock O, Mrowietz U, Ollier WE, Ferguson MW. Genetic susceptibility to keloid disease: transforming growth factor beta receptor gene polymorphisms are not associated with keloid disease. Exp Dermatol. 2004;13(2):120-124. 7. Bayat A, Bock O, Mrowietz U, Ollier WE, Ferguson MW. Genetic susceptibility to keloid disease and hypertrophic scarring: transforming growth factor beta1 common polymorphisms and plasma levels. Plast Reconstr Surg. 2003;111(2):535-546. 8. Bayat A, Bock O, Mrowietz U, Ollier WE, Ferguson MW. Genetic susceptibility to keloid disease and transforming growth factor beta 2 polymorphisms. Br J Plast Surg. 2002;55(4):283-286. 9. Ohsaka Y, Nishino H. Polymorphisms in the 5’-UTR of PTEN and other gene polymorphisms in normal Japanese individuals. Tsitol Genet. 2012;46(2):24-35. 10. Ma J, Zhang J, Ning T, Chen Z, Xu C. Association of genetic polymorphisms in MDM2, PTEN and P53 with risk of esophageal squamous cell carcinoma. J Hum Genet. 2012;57(4):261-264. 11. Zeng Z, Zhou Y, Zhang W, et al. Family-based association analysis validates chromosome 3p21 as a putative nasopharyngeal carcinoma susceptibility locus. Genet Med. 2006;8(3):156-160. 12. Zhou Y, Zeng Z, Zhang W, et al. Identification of candidate molecular markers of nasopharyngeal carcinoma by microarray analysis of subtracted cDNA libraries constructed by suppression subtractive hybridization. Eur J Cancer Prev. 2008;17(6):561-571. 13. Zhou Y, Zeng Z, Zhang W, et al. Lactotransferrin: a candidate tumor suppressor-deficient expression in human nasopharyngeal carcinoma and inhibition of NPC cell proliferation by modulating the mitogen-activated protein kinase pathway. Int J Cancer. 2008;123(9):2065-2072. 14. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001;25(4):402-408. 15. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21(2):263-265. 16. Shi YY, He L. SHEsis, a powerful software platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci. Cell Res. 2005;15(2):97-98. 17. Niu T. Algorithms for inferring haplotypes. Genet Epidemiol. 2004;27(4):334-347. 18. Bostrom MA, Freedman BI, Langefeld CD, Liu L, Hicks PJ, Bowden DW. Association of adiponectin gene polymorphisms with type 2 diabetes in an African American population enriched for nephropathy. Diabetes. 2009;58(2):499-504. 19. Jacob CO, Zhu J, Armstrong DL, et al. Identification of IRAK1 as a risk gene with critical role in the pathogenesis of systemic lupus erythematosus. Proc Natl Acad Sci U S A. 2009;106(15):6256-6261. 20. Fung HC, Scholz S, Matarin M, et al. Genome-wide genotyping in Parkinson’s disease and neurologically normal controls: first stage analysis and public release of data. Lancet Neurol. 2006;5(11):911-916. 21. Peiffer DA, Gunderson KL. Design of tag SNP whole genome genotyping arrays. Methods Mol Biol. 2009;529:51-61. 22. Gunderson KL. Whole-genome genotyping on bead arrays. Methods Mol Biol. 2009;529:197-213. 23. Dunn G, Hinrichs AL, Bertelsen S, et al. Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures. BMC Genet. 2005;6(suppl 1):S122. 24. Schaid DJ, Guenther JC, Christensen GB, et al. Comparison of microsatellites versus single-nucleotide polymorphisms in a genome linkage screen for prostate cancer-susceptibility Loci. Am J Hum Genet. 2004;75(6):948-965. 25. Evans DM, Cardon LR. Guidelines for genotyping in genomewide linkage studies: single-nucleotide-polymorphism maps versus microsatellite maps. Am J Hum Genet. 2004;75(4):687-692. 26. Baig RM, Mahjabeen I, Sabir M, et al. Genetic changes in the PTEN gene and their association with breast cancer in Pakistan. Asian Pac J Cancer Prev. 2011;12(10):2773-2778. 27. Heikkinen T, Greco D, Pelttari LM, et al. Variants on the promoter region of PTEN affect breast cancer progression and patient survival. Breast Cancer Res. 2011;13(6):R130. 28. Yin L, Liu CX, Nong WX, et al. Mutational analysis of p53 and PTEN in soft tissue sarcoma. Mol Med Report. 2012;5(2):457-461. 29. George Priya Doss C, Rajith B. A new insight into structural and functional impact of single-nucleotide polymorphisms in PTEN gene. Cell Biochem Biophys. 2013;66(2):249-263. 30. Radovich M, Hancock BA, Kassem N, Mi D, Skaar TC, Schneider BP. Resequencing of the vascular endothelial growth factor promoter reveals haplotype structure and functional diversity. Angiogenesis. 2010;13(3):211-218. 31. Ju H, Lim B, Kim M, et al. SERPINE1 intron polymorphisms affecting gene expression are associated with diffuse-type gastric cancer susceptibility. Cancer. 2010;116(18):4248-4255. 32. Toepoel M, Joosten PH, Knobbe CB, et al. Haplotype-specific expression of the human PDGFRA gene correlates with the risk of glioblastomas. Int J Cancer. 2008;123(2):322-329. 33. Hirata H, Hinoda Y, Okayama N, et al. COMT polymorphisms affecting protein expression are risk factors for endometrial cancer. Mol Carcinog. 2008;47(10):768-774.

Advertisement

Advertisement

Advertisement