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Effect of Benzodiazepine Addiction on Genomes

Rabia Iftikhar

TITLE OF PROPOSED PROJECT
Genome wide study of transcriptional and epigenetic changes induces upon addiction to benzodiazepine and their inheritance.
RESEARCH AREA
Pharmacogenetics
PROJECT DIGEST
Some drugs that are available over the counter as well as those prescribed are known to produce side effects of addiction and dependency upon long-term use. Benzodiazepines are a class of drugs that have long been used for treatment of anxiety and sleep disorders. Since the start of their use, they have been known to produce dependency symptoms in patients that use it for more than a month. Upon withdrawal, they cause symptoms of anxiety, irritability, difficulty with concentration, sweating etc. Various studies have been directed to elucidate the mechanism behind this dependency and a number of reasons have been determined. However, a genome wide study for changes in the genome that result in this addiction has not been done yet. The purpose of this study will be to carry out a genome wide study to find out changes in gene expression induced by long-term use of these drugs and to identify the epigenetic factors leading to such changes. Carrying out such a study, will help us find new antagonists for these side effects. It will help us develop drugs that target and thus reverse this addiction in patients who have to use benzodiazepine for their medical condition. Moreover, the inheritance of addiction to these drugs will be studied which will help vulnerable patients to take safety measures for their future generations.
Project Summary
The hypothesis of this study will be that addiction to benzodiazepine is caused by changes in gene expression due to epigenetics which can be transgenerational. The objectives will be to find changes in gene expression in mice exposed to benzodiazepine using microarray. These transcriptional changes will be correlated to epigenetic factors. Changes in DNA methylation of their promoters will be found using bisulfite sequencing. Various antibodies will be used against modified histones in ChIP analysis to determine chromatin remodeling around the differentially expressed genes. Moreover, heritability of these genomic changes will be analyzed for two generations of the treated mice.
Proposed Objectives
HYPOTHESIS/BASIS OF RESEARCH
Benzodiazepine addiction involves differential gene expression due to epigenetic variations which can be inherited to next generations.
RESEARCH OBJECTIVES
To find the changes in genome wide expression induced upon continuous use of benzodiazepine in mice.
To determine the epigenetic factors leading to the differential expression.
To identify the candidate genes that might be involved in addiction and further study their functions.
To observe the inheritance pattern of this addiction to next generations.
Introduction
Addiction to drugs as a result of over-dosage and repeated use is a common problem world-wide. Drugs that come under the class of benzodiazepine are commonly used to treat insomnia and anxiety [1]. Upon long-term use, they have been reported to produce adverse side effects of dependency and addiction [2,3]. Some drug addictions have also been reported to be heritable. According to a survey conducted in Pakistan, benzodiazepine over-dosage was reported to be the most common reason for self-poisoning [4]. The exact mechanistic basis for its addiction and dependency is not yet known. Studying the mechanism and inheritance of this addiction will help vulnerable patients prevent and treat these side-effects and also to take precautionary measures for their future generations.
This study will help elucidate the mechanistic basis of the addiction towards benzodiazepine. The affects of addiction being persistent indicates that it may be due to genetic or epigenetic factors. A genome-wide study will be done to analyze changes in gene expression induced due to continuous consumption of benzodiazepine in mice. The inheritance pattern of its addiction will also be studied.
The objectives of this study will be to find the differential gene expression due to addiction to benzodiazepine and to identify the epigenetic factors leading to these differences. The genes involved in addiction will be identified and further studied to understand how they actually function in causing addiction. Lastly, the inheritance pattern of this addiction to next generations will be determined.
A. Background
Benzodiazepine is one of the most frequently prescribed medication for anxiety and sleep disorders [5]. 25-76% of its users are estimated to be long-term users. Amongst them, 20-50% experience withdrawal symptoms when trying to cease its use after long-term use [6].
In a recent study done by Leonie and his colleagues, it was found that 50.1% of the investigated 401 BZD users were long-term users and dependent on BZD [7].
Amongst a sample of 1079 patients in a survey conducted in New Zealand, 8.1% of them were extensive benzodiazepines users with a mean of about 3 years and 7 months. The users on a higher dose than the first prescribed dose were 39%. Out of 40 interviewed patients, 17% experienced withdrawal symptoms of varying severity [8].
Because physiological dependence can occur within 4-6 weeks of use, even in prescribed therapeutic dosage [9], prescription for longer than a month can pose the risk of developing dependency.
BZD with a short elimination half-life are known to cause more severe withdrawal and dependency symptoms than slowly eliminated BZD [10].
In a study by Carlos [11], 47% of the benzodiazepine users using the drug for more than a month developed dependence on it. Patients using short half-life benzodiazepines, higher doses and long-term users showed increased frequency of addiction.
Several aspects of benzodiazepine dependency have been studied and medicines have been developed to counteract these side effects. Inhibitory neurons in brain’s ventral tegmental area (VTA) down-regulate the firing rates of dopamine-producing neurons. Benzodiazepines inhibit and weaken these interneurons resulting in increased production of dopamine [12].
VTA interneurons contain a large number of receptors called GABA receptors. The effect of benzodiazepine on these interneurons is due to activation of a subtype of GABA receptors -alpha-1 subtype. Upon administration of benzodiazepine in two groups of mice, the firing rate of interneurons decreased, increasing the production of dopamine. Genetically modification inorder to prevent benzodiazepine from activating alpha-1 receptor prevented this neuron firing [13].
Administration on long-term induces changes in GABAA receptor complex, results in reduced sensitivity, thus requiring higher dosages [14]
Several antagonists have been developed to treat withdrawal syndromes associated with abrupt cessation of benzodiazepine. One such study on rat was done using 5-HT2 antagonists. Rats treated with diazepam for 14 days showed acute withdrawal symptoms, tested using social interaction paradigm and elevated puzzle. Pre-treatment with 5HT2 antagonists before testing produced significant reduction in withdrawal anxiety levels which were comparable to control rats [15].
Administration of antidepressant agomelatine has been reported to reduce craving and improve relapse prognosis in benzodiazepine addicts. This effect may be due to anti-craving effects of agomelatine, or its property of receptor activation [16].
Antagonists for N-methyl-D-aspartate (NMDA), non-NMDA and metabotropic glutamate (mGlu) receptors have been shown to reduce addiction symptoms in rats. The expression NMDA receptors and phosphoinositide hydrolysis mediated by mGluR is increased in cerebrocortical area of these mice. Thus neuroadaptive responses are indicative of benzodiazepine dependence [17].
It has been hypothesized that abusive use of drugs leads to transcriptional changes in genes through different mechanisms. Modifications in the chromatin, actions of various transcription factors and function of non-coding RNAs are all thought to contribute to changes in the brain as a result of this exposure [18].
Repeated administration of cocaine induced differential gene regulation in mouse. In this study, the molecular pathways involved in this regulation were also found. Genome-wide study of the chromatin in mouse nucleus accumbens was done using CHiP and promoter microarray. ?FosB and CREB were found to be two prominent cocaine-induced transcription factors, in this brain region. Moreover, the behavioural effects of cocaine were found to be significantly enhanced by Sirtuins (Sirt1 and Sirt2) [19,20]
In another independent study, genome wide analysis (GWA) of SNPs associated with alcohol dependence was done by blah. Out of the 121 SNPS analysed, 19 were shown to be differentially expressed. Two closely related SNPs among them were found to be located on chromosome region 2q35 and have been linked to alcohol phenotypes. 9 SNPs were located in genes that have been reported to be associated with alcohol addiction [21].
A genome wide analysis of benzodiazepine dependent individuals has not been done yet. Knowing the differential expression in the entire genome will help us identify all the candidate genes that might be involved in causing dependence in patients after long-term use. This will direct us to the detailed mechanism of dependence and therefore its treatment in addicted patients. Moreover, drugs can be designed to inhibit the pathways that result in this addiction. Benzodiazepine can be administered along with these drugs thus preventing their side effects.
B. Research methodology: Phasing
Animals and reagents
12 C57 mice (6 males and 6 females) 10 weeks old will be obtained and housed for a week in three group. One group of mice will be injected intravenously with BZD with short half-life- alprazolam (Xanaxe). The second group with BZD with longer half-life- and the third control group with saline solution. This treatment will be carried out for 4 weeks.
Assay for withdrawal symptoms
After treatment, mice will be tested for symptoms of anxiety (indicative of addiction) by two methods:
Social interaction test
In this test, mice will be placed in circular area. Their interaction with each other will be observed and given an interaction score based on time spent sniffing, grooming, touching, or crawling over each other.
Elevated plus maze
A maze with two arms – open and close will be used. Anxiety in mice will be scored based on the time spent in each arm, exploring the risky open arm which will indicate their anxiety behavior.
Microarray analysis:
Mice from each group will be sacrificed and mRNA will be isolated from their brain tissue. Differently labeled cDNAs will be synthesized from control and treated mice. Differential expression of genes will be checked using microarray chip available for mouse genome. The differentially expressed genes will be studied computationally and their functions predicted. The candidate genes that might be involved in causing addiction in benzodiazepine treated mice will be identified.
Bisulfite sequencing:
The promoters of misregulated genes will be checked for changes in DNA methylation patterns using bisulfite sequencing. The results from treated and control mice will be compared.
Chromatin immunoprecipitation
Chip analysis will be used to determine whether changes in chromatin structure are involved in the differential regulation of the mice. Chip analysis will be done using antibodies against acetylated histone H3, H4, dimethylated H3K9 and H3K27. Immunoprecipitated DNA will be amplified and quantified by qRT-PCR using primers against the candidate genes.
RT-PCR
The expression of the candidate genes will be checked by isolating RNA from the treated and control mice followed by cDNA synthesis and thus quantification of gene expression.
Inheritance of differential expression
The male and female mice from the individual groups will be self-crossed and their offsprings will be analyzed for symptoms of anxiety as done for the parent mice. These symptoms will be correlated to changes in gene expression using microarray which might be inherited from their parents. This experiment will be done for two generations and thus inheritance pattern of benzodiazepine addiction will be analyzed.
C. References
http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2009/09/WC500003774.pdf
M Lader. Benzodiazepine dependence. Proq Neuropsychopharmacol Biol Psychiatry. 1984; 8(1):85-95
CP O’brien. Benzodiazepine use, abuse and dependence. J Clin Psychiatry. 2005; 66 Suppl 2: 28-33
MM Khan, H Reza. Benzodiazepine self-poisoning in Pakistan: implications for prevention and harm reduction. J Pak Med Assoc. 1998; 48(10):293-5
BP Charles, D Cristian. Pharmacotherapy of panic disorder. Neuropsychiatry Dis Treat. 2008; 4(4): 779-795.
L Michael, TG Marie, B Anna, C Carlo. High-dose benzodiazepine dependence: a qualitative studyof patients’ perception on cessation and withdrawal. BMC Psychiatry. 2015; 15:116.
M Leoney et. Al. Correlates of benzodiazepine dependence in the Netherlands study of depression and anxiety. Addiction. 2012; 107(12):2173-82.
A Khan, AR Hornblow, JW Walshe. Benzodiazepine dependence: a general practice survey. The New Zealand medical journal. 1981; 93(687): 19-21.
A David, MD Spiegel, JB Timothy. Benzodiazepine and exposure-based cognitive behavior therapies for panic disorder: conclusions from combined treatment trials. Am J Psychiatry. 1997; 154:773-781.
W Barbara, RG Roland. Physical dependence on benzodiazepines: differences within the class. Drug and Alcohol Dependence. 1991; 29:153- 156
C Carlos de las, S Emilio, F Juan de la. Benzodiazepines: more “behavioural” addiction than dependence. Psychopharmacology. 2003; 167:297-303.
KR Tan, M Brown, C Yvon, C Luscher, et al. Neural basis for addictive properties of benzodiazepines. Nature. 2010; 463(7282):769-74
Well-known mechanism underlies benzodiazepine addictive properties. Written by NIDA notes staff on April 19,2012. Extracted on 25 May 2015 from: http://www.drugabuse.gov/news-events/nida-notes/2012/04/well-known-mechanism-underlies-benzodiazepines-addictive-properties
Feldman, B Lisa, Riva-Vazquez, A Rafael, Assessment and treatment of social anxiety disorder. Professional psychology: Research and practice. 2003; 34(4): 396-405.
DP Begg, KT Hallam, TR Norman. Attenuation of benzodiazepine withdrawal anxiety in the rat by serotonin antagonists. Behav Brain Res.2005 Jun 20;161(2):286-90.
H Muller, F Seifert, JM Maler, J Kornhuber. Agomelatine reduces craving in benzodiazepine addicts: a follow-up examination of three patients. Singapore Med J.2012 Nov;53(11):e228-30
T Makoto, S Norifumi, S Tsutomu. Contribution of glutamate receptors to benzodiazepine withdrawal signs. Jpn. J. Pharmcol. 1999; 81:1-6
JR Alfred, JN Eric. Transcriptional and Epigenetic Mechanisms of Addiction. Nat Rev Neurosci. 2011 Oct 12; 12(11): 623–637.
R William, K Arvind, X guanghua, W Matthew, et al., Genome Wide Analysis of Chromatin Regulation by Cocaine Reveals a Novel Role for Sirtuins. Neuron. 2009 May 14; 62(3): 335–348.
TCB Mathew, B Camilla, M Manuel, L Gwenael, et al., Drug-Driven AMPA Receptor Redistribution Mimicked by Selective Dopamine Neuron Stimulation. PLoS ONE. 2010; 5(12)
C Sven, et al., Genome wide association study of alcohol. Arch Gen Psychiatry.2009;66(7):773-784
Impact
Benzodiazepine is a very commonly used drug for treating anxiety and sleep disorders. However, cases for addiction to these medicines have been reported very often. Elucidating the mechanism of addiction would help develop methods for preventing and treating it in vulnerable patients by synthesizing antagonists for the side effects of addiction.
Studying the inheritance of benzodiazepine addiction would help patients take necessary precautions for their next generations.

Link Between Genetics and Prostate Cancer

Abstract
Purpose: Prostate cancer (PCa) is one of the most commonly diagnosed male malignancies. Numerous studies have investigated the role of genetic variants in PCa risk. However, the results remain unclearly. The purpose of this study was to evaluate the relationship between rs2228001 in XPC, rs4073 in IL8, and rs2279744 in MDM2 with PCa susceptibility.
Materials and Methods: Electronic database of PubMed, Medline and Embase were searched for relevant studies between 2000 and 2014. The odd ratio (OR) with its 95% corresponding interval (CI) were employed to estimate the strength of association.
Results: Total 18 case-control studies, including 5725 PCa cases and 5900 healthy controls, were screened out. For XPC 939A/C polymorphism, 6 articles were included, and there was no evidence for a significant association between XPC gene 939A/C polymorphism and PCa in the overall population. We also did not find any associations in subgroup by ethnicity. For IL8 -251T/A variant, the A allele was not concerned with PCa risk when compared with those individuals without A allele in any genetic models. For MDM2 -309T/G mutation, the G allele was not associated with increased the risk of PCa in total population and subgroup analysis by ethnicity as well.
Conclusions: Our study found that all these three genetic polymorphisms were not associated with an increased risk of developing PCa, which might also provide an insight into the future research. However, further studies with large-scale populations and concerning the interactions of gene-gene and gene-environmental should be considered.
Keywords: prostate cancer; XPC; IL8; MDM2; polymorphism; meta-analysis
Introduction
Prostate cancer (PCa) is one of the most common malignancies among men in the world. It is also the second and third cause of cancer-related death in the USA and Europe, respectively [1, 2]. Every year, a total of 238,590 new cases are emerging and 29,720 death are occurring according to cancer statistics, 2013 [3]. Multi-risk factors such as hormones, family history and lifestyle are associated with PCa. Due to extreme heterogeneity in PCa incidence worldwide, major determining factors have not been described [4], and the pathogenesis is still unciearly. Furthermore, the prevention and treatment of PCa remain complicated for treatment options depending on disease stage and patient choice to a large extent [5]. Thus, there is an urgent need to explore the molecular mechanism under this disease and develop newer target therapies.
During the last two decades, genetic factors are considered to contribute substantially to the development of PCa. For example, high Bcl-2 expression was associated with lower biochemical-free survival in patients with advanced PCa [6]. Polymorphisms of CYPlAl [7] and prostate-specific antigen [8] genes were shown to be related with increase the risk of sporadic PCa, and might be predisposing factors for PCa. Several genes have been the most studied. The xeroderma pigmentosum complementation group C (XPC) gene 1s located on chromosome 3p25 and is a 940-residue DNA binding protein. It serves as the primary initiating factor in the global genome base excision repair (NER) in human. and plays an important role in the early steps. especially in damage recognition. open complex formation and reparation [9]. Recent reports suggest XPC also stimulates repair of oxidative lesions by NER. In cells. XPC binds to hHR23B to form the XPC-hHR23B complex [10].
Which is involved in the DNA damage recognition and DNA repair initiation in the NER pathway. and necessary and sufficient to support NER activity in vitro [11].
Sequence variants of the XPC gene may alter NER capacity and modulate cancer risk.
One polymorphism. Lys939Gln (an A to C transversion) in exon 15 of XPC has been identified and is the most studied.
Interleukin-8 (IL8) gene. located on chromosome 4q12-21 in humans. 1s composed of four exons. three introns. and a proximal promoter region. It is an important member of CXC chemokine family [12]. and is produced by a wide range of normal cells to initiate and amplify acute inflammatory reactions [13]. IL8 is well known for its leukocyte chemotactic proper ties. Many studies have demonstrated that IL8 may play a vital role in tumorigenesis. including angiogenesis. adhesion. invasion. and metastasis [14]. In the promoter region of the IL8 gene -251 base pairs upstream of the transcriptional start sit. aT/A single nucleotide polymorphism was identified. and studies have shown that it influences the production of IL8 and affects the transcriptional activity of the IL8 promoter [15].
Mouse double-minute 2 (MDM2) is an E3-ubiquitin ligase which could bind to p53 with high affinity. inhibiting and promoting the degradation of the tumor suppressor protein, p53 [16, 17]. Overexpression of MDM2 is associated with tumor proliferation, and an early onset of tumorigenesis [18]. Studies have demonstrated that a single nucleotide polymorphism in the promoter region of the MDM2 gene (-309 T/G; SNP309) could result in increasing the expression of MDM2, leading to the attenuation of p53 [19].
Although independent study has identified the association between these polymorphisms and PCa risk, the results remained inconsistent rather than conclusive.
Hirata et al. showed that XPC Lys939Gln polymorphism might be a risk factor for PCa in Japanese population [20]; however, Liu et al. did not found a significant association between this polymorphism and PCa in Chinese population [21].
McCarron et al. firstly demonstrated that IL8 variant might have a significant effect on disease development of PCa [22]; whereas Michaud et al. identified that IL8 variant did not play a role in the risk of PCa [23]. Xu et al. suggested that MDM2 309G allele was significantly related with PCa risk [24]; while Jerry et al. found no association between MDM2 SNP309 polymorphism and recurrence risk, clinicopathologic variables, and overall survival outcome in PCa [25]. Therefore, the purpose of this meta-analysis is to summarize the existing evidence on the prevalence of the genetic polymorphisms in patients diagnosed with PCa, and comprehensive and reliable assess of these polymorphisms with PCa risk.
Materials and methods
Identification and eligibility of relevant studies
We conducted a comprehensive literature search using the electronic database of PubMed, Medline and Embase for relevant articles published between January 2000 and April 2014, The following terms: “prostate cancer or prostatic cancer”, “xeroderma pigmentosum complementation group C or XPC”, “interleukin-8 or IL8”, “Murine double minute 2 or MDM2”, and “polymorphisms or variants or mutations” as well as their combinations were used to retrieve the related articles, References of retrieved articles were searched with English language restrictions, The search was focused on studies that had been conducted in human, Only full-text articles and the most recent studies were included in this meta-analysis,
Criteria for inclusion
The inclusion criteria were as follows: 1) the paper should be case-control or cohort association studies: 2) PCa cases were diagnosed and histopathologically confirmed, controls were cancer free, unrelated, age- and sex-matched healthy individuals of similar ethnicity: 3) each study included at least one of the three polymorphisms, rs2228001 in XPC (939A/C), rs4073 in IL8 (-251T/A), and rs2279744 in MDM2 (-309T/G): 4) genotype distribution information and odds ratio (OR) with its 95% confidence interval (CI) were available: and 5) genotype distribution of control for a certain polymorphism must be m Hardy-Weinberg equilibrium (HWE),
Data extraction
Two investigators independently assessed the quality of the included studies according to the data extracted from each study, Any disagreement was subsequently resolved by discussion with a third author, The following information was extracted from each article: first author, year of publication, country, ethnicity, total numbers and genotype distributions in PCa cases and controls.
Statistical analysis
The overall association between genetic polymorphisms and PCa was measured by odds ratio (OR) and its 95% confidence interval (CI), which were calculated according to the method of Woolf. The Z test was employed to determine the significance of the pooled ORs, and a P value less than 0.05 was considered statistically significant. The allelic model (C vs. A for XPC 939A/C; A vs. T for IL8-251A!T; G vs. T for MDM2 -309T/G) and genotype genetic models (co-dominant effects: CC vs. AA XPC 939A/C; AA vs. TT IL8 -251A!T; GG vs. TT MDM2-309T/G; dominant effect: CC AC vs. AAXPC 939A/C; AA AT vs. TT IL8 -251A/T;
GG GT vs. TT MDM2 -309T/G; and recessive effect: CC vs. AC AA XPC 939A/C; AA vs. AT TT IL8 -251A!T; GG vs. GT TT MDM2 -309T/G) were examined. The 12 test and the Q-statistic test were employed to assess the between-study heterogeneity. The fixed-effects model is used when the effects are assumed to be homogenous ce less than 50% for the 12 test and p-value more than 0.01 for the Q-test), while the random effects model is used when they are heterogenous. The evidence of publication bias was assessed by visual funnel plot inspection. Statistical analyses were conducted in Review Manager (version 5.2, The Cochrane Collaboration), and followed the program described by Collaboration et al. [26]. All the tests were two-sided.
Results
Study selection and characteristics
The electronic database search identified 323 references. After applying the inclusion criteria, 32 full-text articles comprehensively assessed against inclusion criteria. Removing duplicate documents, 18 articles were ultimately included in the systematic review and meta-analysis. The study selection process was shown in Figure 1.
For XPC 939A/C, 6 studies [27-32] consisted three ethnicity (Asian, Caucasians and African) reporting 2245 cases and 2258 controls. Among them, the research conducted by Agalliu I et al. consisted two study ethnicity. For IL8 -251T/A, 6 studies [33-38] included 1942 cases and 1964 controls, all of which were Caucasians ethnicity. For MDM2 -309T/G, 6 studies [39-44] contained 1538 cases and 1678 controls including Asian and Caucasians ethnicity. The detailed characteristics of the studies included were shown in Table 1. The distributions of genotypes in the individual studies were presented in Table 2.
Association between XPC 939A/C variant and PCa risk
The results of allele and genotypes of XPC polymorphism in this meta-analysis were listed in Table 3. The heterogeneity between studies was calculated, and the fixed effect model or random effect model was employed for assessing the pooled OR.
Overall, the frequency of C allele is a little bit higher in PCa cases than that in the healthy controls (36.1% vs. 34.7%). However, there was no evidence for a significant association between XPC gene 939A/C polymorphism and PCa in the overall population (C vs. A: 0R= l.06, 95% Cl=0.97-1.15, P=0.22; CC vs. AA: 0R= l.19, 95%
Cl= 0.85-1.68, P=0.32; CC AC vs. AA: 0R=l.03, 95% Cl=0.92-1.17, P=0.59; CC vs.
AC AA: 0R=l.20, 95% Cl=0.85-1.70, P=0.30) as shown in Figure 2. We also evaluated the effect of the polymorphism by ethnicity. We also did not detect a significant association between XPC gene 939A/C polymorphism and PCa risk in Asians, Caucasians or African population (P>0.05).
Association of ILS -251 T/A polymorphism and PCa risk
Table 4 displayed the summary of all genetic comparisons between IL8 -251 T/A polymorphism and PCa risk. As shown in Figure 3, the result suggested that the variant A allele did not have a significant increased risk of PCa compared with those individuals without A allele (a vs. C: OR=l.Ol , 95% Cl=0.92-1.10, P=0.88). No significant association was found in other genetic models (AA vs. TT: 0R=l.03, 95% Cl=0.86-1.23, P=0.75; AA AT vs. TT: 0R=0.99, 95% Cl=0.79-1.24, P=0.90; AA vs. AT TT: 0R=l.02, 95% Cl=0.88-1.17, P=0.80).
Association between MDM2 -309T/G polymorphism and PCa risk
The overall analysis of the studies concerning MDM2 polymorphism and PCa risk was listed in Table 5, and revealed no significant association of MDM2-309T/G polymorphism with PCa risk in any genetic models (G vs. T: 0R=0.89, 95% Cl=0.76-1.05, P=0.17; GG vs. TT: 0R=0.81, 95% Cl=0.56-1.17, P=0.25; GG GT vs. TT: 0R=0.84, 95% Cl=0.67-1.06, P=0.14; GG vs. GT TT: 0R=0.96, 95% Cl=0.80-1.16, P=0.69) as shown in Figure 4. In subgroup analysis based on ethnicity, we found that MDM2-309T/G variant did not significantly increase the risk of PCa risk in nether Asian (P>0.05) nor Caucasians (P>0.05) population no matter what kind of genetic model was used.
Sensitivity analyses and publication bias
A single study included in the meta-analysis was deleted each time to reflect the influence of the individual data set to the pooled ORs. The corresponding pooled Ors were not materially changed. which confirmed the stability of our overall result. The shape of funnel plots did not reveal any evidence of funnel plot asymmetry (Figure 5).
Discussion
The present meta-analysis examined the association between three commonly studied gene polymorphisms XPC 939AIC. IL8 -251T/A. MDM2 -309T/G and PCa risk. 18 separate articles including 5725 PCa cases and 5900 health controls were retrieved in the final analysis. Overall. we did not detect a significant association of these three gene polymorphisms with PCa in any genetic models. Similar results were found in stratification analyses by ethnicity.
The XPC gene contains 16 exons and 15 introns. It can form a XPC-RAD23B complex with RAD23B. which is specifically involved in global genome repair and works as the earliest dam age detector to initiate the NER pathway [45]. Studies have proved that XPC is a key component of the NER pathway that participates in DNA damage repair [46]. Mutations in this gene result in xeroderma pigmentosum. a rare autosomal recessive disorder characterized by increased sensitivity to sunlight and the development of skin cancer at an early age [47]. XPC polymorphisms have been associated with increased risk of many human cancers. such as bladder cancer [48] and digestive system cancers [49]. Our results was consistent with previous meta-analysis conducted by Zou YF et al. which screened out five studies including 1966 cases and 1970 controls, suggesting this variant was not associated with PCa risk [50].
IL8 is one of key members of the human a-chemokine subfamily, and acts as a potent chemoattractant and activator of neutrophils [51]. It is produced by normal cells including monocytes, neutrophils, fibroblasts, and endothelial cells. IL8 is involved in thrombophilia and angiogenesis, and highly expressed in various human cancers. It also plays an important role in chronic infection, inflammation, and cancer development, and its overexpression may implicate the increased susceptibility or the modulated clinic-pathological features for different cancers [52]. The corresponding gene polymorphisms may lead to the aberrant expression of IL8 and accordingly increase the risk of cancers. -251Aff polymorphism is aT-to-A change that occurs at
Nucleotide -251, and the less A allele can lead to the increased expression of IL8. Xue et al. found that IL8 -251 AA genotype is associated with the overall risk of developing gastric cancer and may seem to be more susceptible to overall gastric cancer in Asian populations [14]. Andia et al. demonstrated that IL8 gene promoter polymorphism (rs4073) may contribute to chronic reriodontitis [53]. Wang et al. have indicated that IL8 -251Aff polymorphism is associated with a significantly increased risk of cancers and may provide evidence-based medical certificate to study the cancer susceptibility [54]. However, no connection was found in PCa risk in our meta-analysis.
MDM2 is a major regulator of p53 function. It is well known that the functional role of MDM2 is related to the negative regulation of tumor suppressor p53. It acts with P53 in a feedback loop where p53 activates MDM2 at the transcriptional levels while MDM2 binds, inhibits and degrades the p53 protein through E3 ligase activity [55]. Studies have shown that MDM2 antagonists-activated wide-type p53 in combination with androgen depletion may provide an efficacious approach to PCa therapy [56]. The functional importance of this inter-action is illustrated by the findings that reduction of the MDM2 expression level inhibits tumor formation in mice while depletion of the MDM2 gene leads to embryonic lethality, an effect rescued by concomitant p53 deletion [57]. MDM2 amplification and/or protein over-expression has been observed in many human cancers harbouring wild-type TP53, the gene coding for the p53 protein [58], and MDM2 over-xpression has been suggested to act as an alternative mechanism to p53 inactivation, promoting tumor growth [59]. The MDM2 gene plays a key role in the p53 pathway, and the SNP 309T/G single-nucleotide polymorphism in the promoter region of MDM2 has been shown to be associated with increased risk of cancer. However, we did not find a relationship between this polymorphism and PCa risk. Previous meta-analysis covering 4 independent studies showed no significant association between MDM2 309T/G polymorphism and PCa risk in overall analysis as well [60].
Several limitations of this meta-analysis should be addressed. Firstly, the subgroups may have a relatively lower power based on a small number of studies.
Secondly, a more precise analysis should be conducted if individual information including other covariates such as age, sex and smoking condition becomes available.
Thirdly, other genes which may interact with these genes should be considered.
In conclusion, the results from the present meta-analysis suggested that XPC, IL8 and MDM2 variants were not associated with increased risk of PCa. Further large and well-designed studies in various populations are needed to confirm our results.
Moreover, studies of gene-gene and gene-environment interactions between these polymorphisms and PCa risk should also be performed and considered.

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