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Int. J. Mol. Sci. 2013, 14(5), 8832-8840; doi:10.3390/ijms14058832
Abstract: A recent prostate cancer (PCa) genome-wide association study (GWAS) identified rs103294, a single nucleotide polymorphism (SNP) located on LILRA3, a key component in the regulation of inflammatory inhibition, to be significantly associated with PCa risk in a Chinese population. Because inflammation may be a common etiological risk factor between PCa and benign prostatic hyperplasia (BPH), the current study was conducted to investigate the association of rs103294 with BPH risk. rs103294 was genotyped in a Chinese population of 426 BPH cases and 1,008 controls from Xinhua Hospital in Shanghai, China. Association between rs103294, BPH risk and clinicopathological traits were tested with adjustment for age. rs103294 was significantly associated with BPH risk with a p-value of 0.0067. Individuals with risk allele “C” had increased risk for BPH (OR = 1.34, 95% CI: 1.09–1.66). Stratified analysis revealed a stronger association risk for younger patients who are below 72 years old (OR = 1.51, 95% CI: 1.06–2.16). Our study represents the first effort to demonstrate that LILRA3 gene is significantly associated with BPH risk in a Chinese population. Our results support a common role of inflammation in the development of PCa and BPH. Additional studies are needed to further evaluate our results.
Benign prostatic hyperplasia (BPH) is a common disease that is increasingly prevalent in men over the age of fifty. It is the fourth most common diagnosis in older men . A quarter of the men in their 50s are affected, a third in their 60s and half of the men past their 80s . BPH is a nonmalignant enlargement of the prostate gland, clinically manifesting as lower urinary tract symptoms (LUTS) or acute urinary retention (AUR). Current management options for BPH include medications, minimally invasive therapies, and prostate surgery with continued surveillance [1,3].
The causes of BPH are not fully known, but the overgrowth of smooth muscle tissue and glandular epithelial tissue is attributed to various factors such as aging, late activation of cell growth, hormones, and genetic factors. Diagnostic factors include age, prostate size, weight, prostate-specific antigen level, and severity of symptoms . Previous studies have observed important anatomic, pathologic, and genetic links, in addition to well-established epidemiological associations, between prostate cancer (PCa) and BPH . Although PCa and BPH form in different areas of the prostate and present in two distinct pathogenetic pathways, studies have suggested several common characteristics between PCa and BPH, including incidence and prevalence rise with increased age, both conditions are hormone dependent and both diseases are associated with prostatic inflammation [4–7].
Prostatic inflammation contributes to the development and progression of BPH, rather than occurring in response to altered tissue architecture, suggesting an immune inflammatory nature . Single-nucleotide polymorphisms (SNPs) associated with inflammation have been implicated in the development of PCa [8,9]. However, very few studies had been conducted to test for association between genes involved in inflammation and BPH risk [8,10,11]. A recent genome-wide association study (GWAS) in PCa identified rs103294 to be significantly associated with PCa risk at a genome-wide significant level (p = 5.34 × 10−16) in the Chinese population . rs103294 is located on LILRA3 gene, which is a key regulator of the inflammatory response. Due to the shared role of inflammation in both PCa and BPH, we conducted the current study to evaluate the association of the LILRA3 SNP and BPH risk. Our study represents the first study to evaluate the role of LILRA3 in BPH development and progression in a Chinese population.
2. Results and Discussion
2.1. Demographic and Clinical Information
Demographic and clinical information for 426 cases and 1008 controls with genotypes are presented in Table 1. Aggressive BPH cases comprised (43.0%) and nonaggressive cases (57.0%). Mean age was higher for cases (71.9 ± 7.9 years) compared to controls (61.2 ± 9.0 years) and was adjusted in the association tests. Baseline clinicopathological parameters are also presented in Table 1.
2.2. Genetic Association Results
Genotype distributions for the SNP were in Hardy Weinberg Equilibrium (HWE) in both case and control groups (p > 0.05, data not shown). rs103294 had missing rates smaller than 5% (data not shown). SNP association results are shown in Table 2. rs103294 showed a significant association with BPH (p = 0.0067). Risk allele “C” of rs103294 was associated with a 1.34 fold increased risk of BPH (95% CI: 1.09–1.66). It was not associated with aggressive BPH (p = 0.28).
Association results with clinicopathological traits are presented in Table 3. rs103294 showed no significant association with the clinicopathological traits(All p > 0.05). Stratified analyses (Table 4) showed a stronger effect for rs103294 for patients under 72 years of age (OR = 1.51). Subjects over the age of 72 showed a weaker effect (OR = 1.27). Similar effects were observed for patients with different total prostate volume (TPV) and International Prostate Symptom Score (IPSS) values (Table 4).
In this study, we investigated the association of rs103294, a recently identified PCa risk-associated SNP through GWAS study in Chinese, with BPH risk in a Chinese population of 426 cases of BPH and 1,008 controls. In our study, rs103294 was significantly associated with BPH risk (p = 0.0067). Our study is among the first efforts which demonstrate a critical role of LILRA3 gene in BPH development.
Currently, the role of gene polymorphisms in the development of BPH remain unclear inconsistent due to BPH’s polygenic and multifactorial nature . Various reasons such as the high prevalence of the disease and demographic trends towards advanced age indicate that genetic markers for clinically determining BPH are relevant and needed . Importantly, SNPs may regulate and predispose disease initiation or progression of chronic prostatic diseases. Though candidate gene and genetic linkage approaches have yielded various candidate genes for BPH, such as CYP3A4 for steroid-metabolism pathways, the androgen receptor (AR) gene and the SRD5A steroid reductase genes, they have been unsuccessful in restricting potential candidates due to inconsistent results . In addition, no GWAS studies have been conducted for BPH related phenotypes. Therefore, identifying genetic factors that are associated with BPH phenotypes are very important in explaining the genetic component of this common disease.
Due to the potential link between PCa and BPH, our study evaluated a SNP proven to have significance with PCa risk at a genome-wide association level with potential functional implication for BPH. In a recent Chinese PCa GWAS study, rs103294 was found to be significantly associated with PCa risk (p = 5.34 × 10−16) in a combined study population of 4484 PCa cases and 8,934 controls . Risk allele “C” of rs103294 was associated with 1.28 fold of increased risk of prostate cancer . In our study, the risk allele “C” of rs103294 was also associated with increased risk of BPH. rs103294 is located in the leukocyte immunoglobulin-like receptor (LIR) gene cluster at 19q13.4, between the region upstream of LILRA3 and downstream of LILRB2. rs103294 is in strong linkage disequilibrium (LD) (r2 = 0.83) with a germ-line deletion of six of seven exons of the functional domains of LILRA3, an inflammatory regulatory gene. LILRA3 is the only secretory leukocyte immunoglobulin-like receptor (LILR) in the LIR cluster, which may regulate the inhibitory immune response induced by LILRB1, LILRB2, and other molecules like LILRA1 . Thus, LILRA3 is likely important for regulating the inflammatory response.
LILRA3’s regulation of the inflammatory response is important because epidemiological data shows an overlap between PCa and BPH through inflammation. Emerging evidence shows that inflammation can promote chronic prostatic diseases by inducing carcinogenesis by causing cell and genome damage. Inflammation has been highly suggestive for prostate growth in both BPH or PCa [5,14,15] and has also been implicated in the progression of BPH [15,16], although the etiology and epidemiology of BPH is complex and not fully understood. A previous study of the role of interleukin 10 (IL10), a multifunctional cytokine with anti-inflammatory and anti-angiogenic properties, in BPH showed that IL10 SNPs play an important role in the process of prostate inflammation and are associated with clinicopathological traits such as TPV and PSA. However, the study did not evaluate BPH susceptibility risk because association studies were conducted within cases only . Therefore, our study is one of the first to show the risk contribution of inflammation in the development of BPH. In addition, because of the important role of rs103294 in PCa and the potential link between PCa and BPH, the association observed in our population more likely represents a true association.
Although rs103294 is significantly associated with BPH risk, it was not associated with severity of BPH in our study population. In addition, association results for clinicopathological traits did not reveal potential link with rs103294, further indicating that it may only contributes to BPH susceptibility. Additional studies are needed to identify such markers for severity in order to provide improved risk prognosis for BPH. Clarification risk of progression will lead to more differentiated diagnosis of older men with BPH . In addition, we further examined potential stratified effects by age, TPV and IPSS in order to test for significant effects in subgroups such as younger and older age groups. Subjects under the age of 72 were found to have more of a predisposition (OR = 1.51) towards the risk effect of rs103294 than subjects over the age of 72 (OR = 1.27). The significant association of a genetic effect amongst a younger population supports the role of genetics in determining the etiology of BPH.
A potential limitation to our study is that only one SNP for LILRA3 gene was chosen to be evaluated. However, through a fine-mapping and imputation effort, rs103924 was the leading SNP in this genomic region . No other SNPs remained significant if adjusting for rs103294 in the statistical model, suggesting that no additional independent prostate cancer risk-associated loci existed at this region . Thus, rs103294 is able to capture the majority of the genetic information in the LIL gene cluster at 19q13.4.
3. Experimental Section
3.1. Study Subjects
All subjects were of a Chinese Han ancestry. A total of 426 BPH cases were enrolled from the department of Urology, Xinhua Hospital (Shanghai Jiao Tong University School of Medicine), Shanghai, China, during the period of July 2010 to July 2012. Patients were included in the study with informed consent prior to qualifying study inclusion criteria.
The population underwent the following investigations: International Prostate Symptom Score (IPSS), including the quality of life question (IPSS-Q1); postvoid residual volume (PVR) measurement by transabdominal ultrasonography, determination of prostate size by transrectal ultrasonography; a serum prostate-specific antigen (PSA) determination; liver and renal function; blood glucose level; and routine urine examination. Inclusion criteria for BPH patients at baseline were benign prostatic enlargement (BPE) with LUTS of age > 45 years, prostate size > 30cm, IPSS > 7 and PVR volume ≤ 1500 mL. Patients with PSA < 4 ng/mL were included in the study and some patients with PSA ≥ 4 were included only after DRE (digital rectal examination), true-cut biopsy for confirmation for lack of PCa, and long-time follow-up visit of stabilized PSA. Exclusion criteria were history of urinary tract infection (UTI), previous lower tract surgery or procedures and neurogenic bladder dysfunction.
All eligible subjects were treated with combined therapy of 4 mg α-adrenergic blockers (doxazosin) and 5 mg of 5α-reductase inhibitors (finasteride) once daily. The length of treatment exceeded at least nine months. After adequate treatment time, if subjects suffered from a significant increase in the IPSS score; continuous decrease in maximum urinary flow rate or BPH related complications (AUR; bladder stone or recurrent hematuria, etc.) and had to receive operation by surgery, they were defined as “aggressive BPH” patients. In contrast, patients without complaints of aggravated symptoms, as well as no indications of operation by surgery were defined as a non-aggressive group. Thus, 184 aggressive and 242 non-aggressive BPH cases were defined. The detailed information for controls used was previously reported in Ma et al. . Briefly, 1008 community males were used as controls in the current study. All the controls were collected from April 2010 to November 2010 in Shanghai, China.
3.2. SNP Selection
rs103294 was recently reported to be associated with PCa risk at a genome-wide significant level in a Chinese population  and was evaluated in the current study.
The SNP was genotyped for all study subjects using the MassARRAY iPLEX system (Sequenom, Inc., San Diego, CA, USA) at Fudan University in Shanghai, China. Two duplicates and two water samples were included in each 96-well plate as PCR-negative controls. All assays were performed in a blinded fashion. Genotyping missing rates was 0.7%.
3.4. Statistical Analysis
The genotype distributions for the SNP were tested for Hardy-Weinberg equilibrium (HWE). The main effects of the SNP for BPH risk were estimated using a logistic regression model, assuming an additive mode of inheritance, adjusting for age. Quantitative clinicopathological traits including IPSS, TPV, total prostate-specific antigen (tPSA) and free prostate-specific antigen (fPSA) were analyzed using linear models, adjusting for age. Log transformations were conducted for variables that were not normally distributed (fPSA, tPSA, TPV and IPSS). SNP association with aggressive vs. nonaggressive phenotypes was also evaluated using logistic regression with adjustment for age. Stratified analyses were conducted according to age, TPV, and IPSS scores. Subjects were separated at a median value for age and TPV and separated for IPSS at the BPH severity threshold (IPSS ≥ 19). All analyses were conducted using PLINK software . p-values were two-tailed. An alpha of 0.05 was used to claim statistical significance.
In conclusion, we identified the significant association of rs103294 on LILRA3 gene and BPH risk. Our findings demonstrate the significance of inflammation in the progression of BPH and the common genetic influences between PCa and BPH. Additional studies need to be conducted in the Chinese population to further evaluate our findings.
The authors thank all the subjects who participated in this study. The study is supported by a fund from the National Science Foundation of China to J. Qi (81070600), and an intramural fund by Fudan University to J. Xu.
Conflict of Interest
The authors declare no conflict of interest.
- Sausville, J.; Naslund, M. Benign prostatic hyperplasia and prostate cancer: An overview for primary care physicians. Int. J. Clin. Pract 2010, 64, 1740–1745. [Google Scholar]
- Kramer, G.; Mitteregger, D.; Marberger, M. Is benign prostatic hyperplasia (BPH) an immune inflammatory disease? Eur. Urol 2007, 51, 1202–1216. [Google Scholar]
- Dhingra, N.; Bhagwat, D. Benign prostatic hyperplasia: An overview of existing treatment. Indian J. Pharmacol 2011, 43, 6–12. [Google Scholar]
- Alcaraz, A.; Hammerer, P.; Tubaro, A.; Schroder, F.H.; Castro, R. Is there evidence of a relationship between benign prostatic hyperplasia and prostate cancer? Findings of a literature review. Eur. Urol 2009, 55, 864–875. [Google Scholar]
- Sciarra, A.; Di Silverio, F.; Salciccia, S.; Gomez, A.M.A.; Gentilucci, A.; Gentile, V. Inflammation and chronic prostatic diseases: Evidence for a link? Eur. Urol 2007, 52, 964–972. [Google Scholar]
- De Nunzio, C.; Kramer, G.; Marberger, M.; Montironi, R.; Nelson, W.; Schroder, F.; Sciarra, A.; Tubaro, A. The controversial relationship between benign prostatic hyperplasia and prostate cancer: the role of inflammation. Eur. Urol 2011, 60, 106–117. [Google Scholar]
- De Marzo, A.M.; Coffey, D.S.; Nelson, W.G. New concepts in tissue specificity for prostate cancer and benign prostatic hyperplasia. Urology 1999, 53, 29–40. [Google Scholar]
- Xu, J.F.; Lowey, J.; Wiklund, F.; Sun, J.L.; Lindmark, F.; Hsu, F.C.; Dimitrov, L.; Chang, B.L.; Turner, A.R.; Liu, W.N.; et al. The interaction of four genes in the inflammation pathway significantly predicts prostate cancer risk. Cancer Epidemiol. Biomarkers Prev 2005, 14, 2563–2568. [Google Scholar]
- Xu, J.; Mo, Z.; Ye, D.; Wang, M.; Liu, F.; Jin, G.; Xu, C.; Wang, X.; Shao, Q.; Chen, Z.; et al. Genome-wide association study in Chinese men identifies two new prostate cancer risk loci at 9q31.2 and 19q13.4. Nat. Genet 2012, 44, 1231–1235. [Google Scholar]
- Yoo, K.H.; Kim, S.K.; Chung, J.-H.; Chang, S.-G. Association of IL10, IL10RA, and IL10RB polymorphisms with benign prostate hyperplasia in korean population. J. Korean Med. Sci 2011, 26, 659–664. [Google Scholar]
- Konwar, R.; Chattopadhyay, N.; Bid, H.K. Genetic polymorphism and pathogenesis of benign prostatic hyperplasia. BJU Int 2008, 102, 536–544. [Google Scholar]
- Berges, R.; Gsur, A.; Feik, E.; Hoefner, K.; Senge, T.; Pientka, L.; Baierl, A.; Michel, M.C.; Ponholzer, A.; Madersbacher, S. Association of polymorphisms in CYP19A1 and CYP3A4 genes with lower urinary tract symptoms, prostate volume, uroflow and PSA in a population-based sample. World J. Urol 2011, 29, 143–148. [Google Scholar]
- Ryu, M.; Chen, Y.; Qi, J.; Liu, J.; Fan, Z.; Nam, G.; Shi, Y.; Cheng, H.; Gao, G.F. LILRA3 binds both classical and non-classical HLA class I molecules but with reduced affinities compared to lilrb1/lilrb2: structural evidence. PLoS One 2011, 6, e19245. [Google Scholar]
- Sciarra, A.; Mariotti, G.; Salciccia, S.; Gomez, A.A.; Monti, S.; Toscano, V.; Di Silverio, F. Prostate growth and inflammation. J. Steroid Biochem. Mol. Biol 2008, 108, 254–260. [Google Scholar]
- Kramer, G.; Marberger, M. Could inflammation be a key component in the progression of benign prostatic hyperplasia? Curr. Opin. Urol 2006, 16, 25–29. [Google Scholar]
- Roehrborn, C.G. Pathology of benign prostatic hyperplasia. Int. J. Impot. Res. 2008, 20. [Google Scholar] [CrossRef]
- Ma, Z.; Hu, Q.; Chen, Z.; Tao, S.; Macnamara, L.; Kim, S.T.; Tian, L.; Xu, K.; Ding, Q.; Zheng, S.L.; et al. Systematic evaluation of bladder cancer risk-associated single-nucleotide polymorphisms in a Chinese population. Mol. Carcinog. 2012. [Google Scholar] [CrossRef]
- Purcell, S.; Neale, B.; Todd-Brown, K.; Thomas, L.; Ferreira, M.A.R.; Bender, D.; Maller, J.; Sklar, P.; de Bakker, P.I.W.; Daly, M.J.; et al. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet 2007, 81, 559–575. [Google Scholar]
|N = 426||N = 1008|
|Aggressive (N = 184)||Non-Aggressive (N = 242)|
|Mean (SD)||73.84 (7.97)||70.45 (7.44)||61.24 (8.96)|
|<4 (%)||107 (58.2)||139 (57.4)||N/A|
|≥4 (%)||77 (41.8)||103 (42.6)||N/A|
|fPSA 1 (%)|
|<25% fPSA||125 (67.9)||100 (41.3)||N/A|
|≥25% fPSA||58 (31.5)||141 (58.3)||N/A|
|Mean (SD)||18 (6.3)||14 (6.2)||N/A|
1No fPSA phenotype for 1 aggressive BPH case;2TPV = Total Prostate Volume;3IPSS = International Prostate Symptom Score.
|MAF||OR (95% CI) 3|
|SNP||Chr||BP 1||Alleles 2||Risk allele||Cases||Controls||Homozygous non-risk genotypes||Heterozygous risk genotype||Homozygous risk genotype||Additive model||p-value 4|
|Aggressive BPH||Non-Aggressive BPH|
1BP: Base Pair; based on NCBI Build 36;2Alleles are indicated by minor/major alleles;3OR and P are calculated based on logistic regression adjusting for age;4p-values are based on additive models.
|Traits||Allele 1||β (SE) 2||Quantitative means 3||p-value 4|
1Alleles are indicated by minor/major alleles;2Beta and standard error results based on log-transformed data for IPSS, tPSA, fPSA and TPV;3aa indicates homozygous carriers of minor alleles, aA indicates heterozygous carriers, and AA indicates homozygous carriers of major alleles. Means were back-transformed;4p-values calculated using linear regression, assuming additive model, adjusting for age.
|Phenotype||BPH cases (%)||rs103294|
|OR 1 (95% CI)||p-value 1|
1OR and p are calculated based on logistic regression, adjusting for age.
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