Genetic Variants Associated with Colorectal Adenoma Susceptibility

BackgroundCommon low-penetrance genetic variants have been consistently associated with colorectal cancer risk.AimTo determine if these genetic variants are associated also with adenoma susceptibility and may improve selection of patients with increased risk for advanced adenomas and/or multiplicity (≥ 3 adenomas).MethodsWe selected 1,326 patients with increased risk for advanced adenomas and/or multiplicity and 1,252 controls with normal colonoscopy from population-based colorectal cancer screening programs. We conducted a case-control association study analyzing 30 colorectal cancer susceptibility variants in order to investigate the contribution of these variants to the development of subsequent advanced neoplasia and/or multiplicity.ResultsWe found that 14 of the analyzed genetic variants showed a statistically significant association with advanced adenomas and/or multiplicity: the probability of developing these lesions increased with the number of risk alleles reaching a 2.3-fold risk increment in individuals with ≥ 17 risk alleles.ConclusionsNearly half of the genetic variants associated with colorectal cancer risk are also related to advanced adenoma and/or multiplicity predisposition. Assessing the number of risk alleles in individuals within colorectal cancer screening programs may help to identify better a subgroup with increased risk for advanced neoplasia and/or multiplicity in the general population.     

Performance of common genetic variants in risk prediction for colorectal cancer in Chinese: A two-stage and multicenter study

The efficacy of susceptible variants derived from genome-wide association studies (GWAs) optimizing discriminatory accuracy of colorectal cancer (CRC) in Chinese remains unclear. In the present validation study, we assessed 75 recently identified variants from GWAs. A risk predictive model combining 19 variants using the least absolute shrinkage and selection operator (LASSO) statistics offered certain clinical advantages. This model demonstrated an area under the receiver operating characteristic (AUC) of 0.61 during training analysis and yielded robust AUCs from 0.59 to 0.61 during validation analysis in three independent centers. The individuals carrying the highest quartile of risk score revealed over 2-fold risks of CRC (ranging from 2.12 to 2.90) compared with those who presented the lowest quartile of risk score. This genetic model offered the possibility of partitioning risk within the average risk population, which might serve as a first step toward developing individualized CRC prevention strategies in China.     

Colorectal cancer risk factors in the detection of advanced adenoma and colorectal cancer

Several risk factors for colorectal cancer (CRC) have been identified. If individuals with risk factors are more likely to harbor cancer or it precursors screening programs should be targeted toward this population. We evaluated the predictive value of colorectal cancer risk factors for the detection of advanced colorectal adenoma in a population based CRC colonoscopy screening program. Data were collected in a multicenter trial conducted in the Netherlands, in which 6600 asymptomatic men and women between 50 and 75 years were randomly selected from a population registry. They were invited to undergo a screening colonoscopy. Based on a review of the literature CRC risk factors were selected. Information on risk factors was obtained from screening attendees through a questionnaire. For each CRC risk factor, we estimated its odds ratio (OR) relative to the presence of advanced neoplasia as detected at colonoscopy. Of the 1426 screening participants who underwent a colonoscopy, 1236 (86%) completed the risk questionnaire. 110 participants (8.9%) had advanced neoplasia. The following risk factors were significantly associated with advanced neoplasia detected by colonoscopy: age (OR: 1.06 per year; 95% CI: 1.03–1.10), calcium intake (OR: 0.99 per mg; 95% CI: 0.99–1.00), positive CRC family history (OR: 1.55 per first degree family member; 95%CI: 1.11–2.16) and smoking (OR: 1.75; 95%CI: 1.09–2.82). Elderly screening participants, participants with lower calcium intake, a CRC family history, and smokers are at increased risk of harboring detectable advanced colorectal neoplasia at screening colonoscopy.     

Polymorphisms in the selenoprotein S and 15-kDa selenoprotein genes are associated with altered susceptibility to colorectal cancer

Selenium (Se), a dietary trace metal essential for human health, is incorporated into ~25 selenoproteins including selenoprotein S (SelS) and the 15-kDa selenoprotein (Sep15) both of which have functions in the endoplasmic reticulum protein unfolding response. The aim of this study was to investigate whether genetic variants in such selenoprotein genes are associated with altered risk of colorectal cancer (CRC). A Korean population of 827 patients with CRC and 733 healthy controls was genotyped for 7 SNPs in selenoprotein genes and one SNP in the gene encoding manganese superoxide dismutase using Sequenom technology. Multivariate logistic regression analysis showed that after adjustment for lifestyle factors three SNP variants were associated with altered disease risk. There was a mean odds ratio of 2.25 [95% CI 1.13,4.48] in females homozygous TT for rs34713741 in SELS with the T variant being associated with higher risk of rectal cancer, and odds ratios of 2.47 and 2.51, respectively, for rs5845 and rs5859 in SEP15 with the minor A and T alleles being associated with increased risk of male rectal cancer. The data indicate that the minor alleles for rs5845, rs5859 and rs34713741 are associated with increased rectal cancer risk and that the effects of the three SNPs are dependent on gender. The results highlight potential links between Se, the function of two selenoproteins involved in the protein unfolding response and CRC risk. Further studies are required to investigate whether the effects of the variants on CRC risk are also modulated by dietary Se intake.     

Developing Genetic Epidemiological Models to Predict Risk for Nasopharyngeal Carcinoma in High-Risk Population of China

To date, the only established model for assessing risk for nasopharyngeal carcinoma (NPC) relies on the sero-status of the Epstein-Barr virus (EBV). By contrast, the risk assessment models proposed here include environmental risk factors, family history of NPC, and information on genetic variants. The models were developed using epidemiological and genetic data from a large case-control study, which included 1,387 subjects with NPC and 1,459 controls of Cantonese origin. The predictive accuracy of the models were then assessed by calculating the area under the receiver-operating characteristic curves (AUC). To compare the discriminatory improvement of models with and without genetic information, we estimated the net reclassification improvement (NRI) and integrated discrimination index (IDI). Well-established environmental risk factors for NPC include consumption of salted fish and preserved vegetables and cigarette smoking (in pack years). The environmental model alone shows modest discriminatory ability (AUC = 0.68; 95% CI: 0.66, 0.70), which is only slightly increased by the addition of data on family history of NPC (AUC = 0.70; 95% CI: 0.68, 0.72). With the addition of data on genetic variants, however, our model’s discriminatory ability rises to 0.74 (95% CI: 0.72, 0.76). The improvements in NRI and IDI also suggest the potential usefulness of considering genetic variants when screening for NPC in endemic areas. If these findings are confirmed in larger cohort and population-based case-control studies, use of the new models to analyse data from NPC-endemic areas could well lead to earlier detection of NPC.     

Current status of genome-wide association studies in cancer

Genome-wide association studies in cancer have already identified over 150 regions associated with two dozen specific cancers. Already, a handful of multi-cancer susceptibility regions have been uncovered, providing new insights into perhaps common mechanisms of carcinogenesis. For each new susceptibility allele, investigators now face the arduous task of interrogating each region beginning with fine mapping prior to pursuing the biological basis for the direct association of one or more variants. It appears that there may be a significant number of common alleles that contribute to the heritability of a specific cancer. Since each region confers a small contribution to the risk for cancer, it is daunting to consider any single nucleotide polymorphism (SNP) as a clinical test. Since the complex genomic architecture of each cancer differs, additional genotyping and sequence analysis will be required to comprehensively catalog susceptibility alleles followed by the formidable task of understanding the interactions between genetic regions as well as the environment. It will be critical to assess the applicability of genetic tests in specific clinical settings, such as when to perform screening tests with calculable risks (e.g., biopsies or chemoprevention), before incorporating SNPs into clinical practice. To advance the current genomic observations to the clinical venue, new studies will need to be designed to validate the utility of known genetic variants in assessing risk for cancer as well as its outcomes.     

A critical appraisal of the scientific basis of commercial genomic profiles used to assess health risks and personalize health interventions

Predictive genomic profiling used to produce personalized nutrition and other lifestyle health recommendations is currently offered directly to consumers. By examining previous meta-analyses and HuGE reviews, we assessed the scientific evidence supporting the purported gene-disease associations for genes included in genomic profiles offered online. We identified seven companies that offer predictive genomic profiling. We searched PubMed for meta-analyses and HuGE reviews of studies of gene-disease associations published from 2000 through June 2007 in which the genotypes of people with a disease were compared with those of a healthy or general-population control group. The seven companies tested at least 69 different polymorphisms in 56 genes. Of the 56 genes tested, 24 (43%) were not reviewed in meta-analyses. For the remaining 32 genes, we found 260 meta-analyses that examined 160 unique polymorphism-disease associations, of which only 60 (38%) were found to be statistically significant. Even the 60 significant associations, which involved 29 different polymorphisms and 28 different diseases, were generally modest, with synthetic odds ratios ranging from 0.54 to 0.88 for protective variants and from 1.04 to 3.2 for risk variants. Furthermore, genes in cardiogenomic profiles were more frequently associated with noncardiovascular diseases than with cardiovascular diseases, and though two of the five genes of the osteogenomic profiles did show significant associations with disease, the associations were not with bone diseases. There is insufficient scientific evidence to conclude that genomic profiles are useful in measuring genetic risk for common diseases or in developing personalized diet and lifestyle recommendations for disease prevention.     

Association analysis of miRNA-related genetic polymorphisms in miR-143/145 and KRAS with colorectal cancer susceptibility and survival

Background: There is accumulating evidence of aberrant expression of miR-143 and miR-145 and their target gene KRAS in colorectal cancer (CRC). We hypothesize that single nucleotide polymorphisms (SNPs) within or near mRNA–microRNA (miRNA) binding sites may affect miRNA/target gene interaction, resulting in differential mRNA/protein expression and promoting the development and progression of CRC. Methods: We conducted a case–control study of 507 patients with CRC recruited from a tertiary hospital and 497 population-based controls to assess the association of genetic polymorphisms in miR-143/145 and the KRAS 3′ untranslated region (3′UTR) with susceptibility to CRC and patients’ survival. In addition, genetic variations of genomic regions located from 500 bp upstream to 500 bp downstream of the miR-143/miR-145 gene and the 3′UTR of KRAS were selected for analysis using the Haploview and HaploReg software. Results: Using publicly available expression profiling data, we found that miR-143/145 and KRAS expression were all reduced in rectal cancer tissue compared with adjacent non-neoplastic large intestinal mucosa. The rs74693964 C/T variant located 65 bp downstream of miR-145 genomic regions was observed to be associated with susceptibility to CRC (adjusted odds ratio (OR): 2.414, 95% CI: 1.385–4.206). Cumulative effects of miR-143 and miR-145 on CRC risk were observed (P_trend=0.03). Patients having CRC carrying variant genotype TT of KRAS rs712 had poorer survival (log-rank P=0.044, adjusted hazard ratio (HR): 4.328, 95% CI: 1.236–15.147). Conclusions: Our results indicate that miRNA-related polymorphisms in miR-143/145 and KRAS are likely to be deleterious and represent potential biomarkers for susceptibility to CRC and patients’ survival.     

A unifying framework for evaluating the predictive power of genetic variants based on the level of heritability explained

An increasing number of genetic variants have been identified for many complex diseases. However, it is controversial whether risk prediction based on genomic profiles will be useful clinically. Appropriate statistical measures to evaluate the performance of genetic risk prediction models are required. Previous studies have mainly focused on the use of the area under the receiver operating characteristic (ROC) curve, or AUC, to judge the predictive value of genetic tests. However, AUC has its limitations and should be complemented by other measures. In this study, we develop a novel unifying statistical framework that connects a large variety of predictive indices together. We showed that, given the overall disease probability and the level of variance in total liability (or heritability) explained by the genetic variants, we can estimate analytically a large variety of prediction metrics, for example the AUC, the mean risk difference between cases and non-cases, the net reclassification improvement (ability to reclassify people into high- and low-risk categories), the proportion of cases explained by a specific percentile of population at the highest risk, the variance of predicted risks, and the risk at any percentile. We also demonstrate how to construct graphs to visualize the performance of risk models, such as the ROC curve, the density of risks, and the predictiveness curve (disease risk plotted against risk percentile). The results from simulations match very well with our theoretical estimates. Finally we apply the methodology to nine complex diseases, evaluating the predictive power of genetic tests based on known susceptibility variants for each trait.     

Population aspects of cancer genetics

A number of relatively rare, high-risk genes have been identified which predispose to common cancers such as breast, colon, and melanoma. Although these are clearly important in the clinical setting, it is also relevant to discuss the impact of these genes at the population level and to contrast these with that which could be ascribed to more common genetic variants which only confer a modest increased risk of cancer. In this review, we examine inferences about the role of genetics in cancer from ecological studies of incidence patterns from a number of population-based studies of familial and attributable risk. The relationship between the genetic model (genotypic risk, allele frequency, mode of inheritance) and the expected impact in the population in terms of both attributable risk and familial risk is presented. The advantages and limitations of using cancer occurrence in twins to measure the genetic contribution to specific cancer sites is discussed. The potential role of lower-penetrance genes in the overall cancer burden may be significant but may pose significant problems in the public health arena.     

Using Lifetime Risk Estimates in Personal Genomic Profiles: Estimation of Uncertainty

Personal genome tests are now offered direct-to-consumer (DTC) via genetic variants identified by genome-wide association studies (GWAS) for common diseases. Tests report risk estimates (age-specific and lifetime) for various diseases based on genotypes at multiple loci. However, uncertainty surrounding such risk estimates has not been systematically investigated. With breast cancer as an example, we examined the combined effect of uncertainties in population incidence rates, genotype frequency, effect sizes, and models of joint effects among genetic variants on lifetime risk estimates. We performed simulations to estimate lifetime breast cancer risk for carriers and noncarriers of genetic variants. We derived population-based cancer incidence rates from Surveillance, Epidemiology, and End Results (SEER) Program and comparative international data. We used data for non-Hispanic white women from 2003 to 2005. We derived genotype frequencies and effect sizes from published GWAS and meta-analyses. For a single genetic variant in FGFR2 gene (rs2981582), combination of uncertainty in these parameters produced risk estimates where upper and lower 95% simulation intervals differed by more than 3-fold. Difference in population incidence rates was the largest contributor to variation in risk estimates. For a panel of five genetic variants, estimated lifetime risk of developing breast cancer before age 80 for a woman that carried all risk variants ranged from 6.1% to 21%, depending on assumptions of additive or multiplicative joint effects and breast cancer incidence rates. Epidemiologic parameters involved in computation of disease risk have substantial uncertainty, and cumulative uncertainty should be properly recognized. Reliance on point estimates alone could be seriously misleading.     

Improving genetic risk prediction by leveraging pleiotropy

An important task of human genetics studies is to predict accurately disease risks in individuals based on genetic markers, which allows for identifying individuals at high disease risks, and facilitating their disease treatment and prevention. Although hundreds of genome-wide association studies (GWAS) have been conducted on many complex human traits in recent years, there has been only limited success in translating these GWAS data into clinically useful risk prediction models. The predictive capability of GWAS data is largely bottlenecked by the available training sample size due to the presence of numerous variants carrying only small to modest effects. Recent studies have shown that different human traits may share common genetic bases. Therefore, an attractive strategy to increase the training sample size and hence improve the prediction accuracy is to integrate data from genetically correlated phenotypes. Yet, the utility of genetic correlation in risk prediction has not been explored in the literature. In this paper, we analyzed GWAS data for bipolar and related disorders and schizophrenia with a bivariate ridge regression method, and found that jointly predicting the two phenotypes could substantially increase prediction accuracy as measured by the area under the receiver operating characteristic curve. We also found similar prediction accuracy improvements when we jointly analyzed GWAS data for Crohn’s disease and ulcerative colitis. The empirical observations were substantiated through our comprehensive simulation studies, suggesting that a gain in prediction accuracy can be obtained by combining phenotypes with relatively high genetic correlations. Through both real data and simulation studies, we demonstrated pleiotropy can be leveraged as a valuable asset that opens up a new opportunity to improve genetic risk prediction in the future.     

Association of 10q23 with colorectal cancer in a Chinese population

Recently, a genome-wide association study of gastric cancer (GC) reported the significant association of seven genetic variants (rs4072037 and rs4460629 on 1q22; rs753724, rs11187842, rs3765524, rs2274223, and rs3781264 on 10q23) with GC in a Chinese population. These findings were confirmed in a subsequent independent study. However, it remains unknown whether these loci are associated with an increased risk of colorectal cancer (CRC). This study was to test whether the seven single nucleotide polymorphisms (SNPs) associated with GC were also associated with CRC in a Chinese population. The seven SNPs were genotyped using MassARRAY system. Allelic, genotypic, and haplotypic associations of the SNPs with CRC were investigated using χ(2) tests and logistic regression analysis. The SNPs rs3765524 and rs2274223, located on 10q23, were found to have significant protective effects against CRC, with equal odds ratios per allele. The two SNPs located on 1q22 (rs4072037 and rs4460629) showed a weak association with CRC. No significant association was identified with CRC for the remaining three SNPs located on 10q23 (rs753724, rs11187842, and rs3781264). These results suggest that rs3765524 and rs2274223 on 10q23 are associated with a protective effect against CRC in a Chinese population.     

Population Genomics of Cardiometabolic Traits: Design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium

Substantial advances have been made in identifying common genetic variants influencing cardiometabolic traits and disease outcomes through genome wide association studies. Nevertheless, gaps in knowledge remain and new questions have arisen regarding the population relevance, mechanisms, and applications for healthcare. Using a new high-resolution custom single nucleotide polymorphism (SNP) array (Metabochip) incorporating dense coverage of genomic regions linked to cardiometabolic disease, the University College-London School-Edinburgh-Bristol (UCLEB) consortium of highly-phenotyped population-based prospective studies, aims to: (1) fine map functionally relevant SNPs; (2) precisely estimate individual absolute and population attributable risks based on individual SNPs and their combination; (3) investigate mechanisms leading to altered risk factor profiles and CVD events; and (4) use Mendelian randomisation to undertake studies of the causal role in CVD of a range of cardiovascular biomarkers to inform public health policy and help develop new preventative therapies.     

Body mass index and screening for colorectal cancer: gender and attitudinal factors

Background: Overweight/obese women and men are at increased risk for colorectal cancer (CRC) incidence and mortality. Research examining body mass index (BMI) and CRC screening has had mixed results. A clearer understanding of the extent to which high-BMI subgroups are screened for CRC is needed to inform planning for CRC screening promotions targeting BMI. Methods: Data were obtained from a random, population-based sample of women and men at average-risk for CRC (aged 50–75 years) during 2004 (n = 1098). Multiple logistic regression analyses were conducted to evaluate whether BMI category was significantly associated with the probability of reporting recent CRC screening and with the probability of agreeing with statements denoting attitudes/perceptions about CRC and screening. Attitudes/perceptions about CRC and screening were evaluated as potential mediators and moderators of the association between BMI category and CRC screening. Results: After controlling for characteristics associated with CRC screening, overweight and obese women were each 40% less likely to have CRC screening than women with normal-BMI (OR = 0.6, 95% CI:0.4–0.9 and OR = 0.6, 95% CI:0.3–0.9). BMI category was unrelated to screening among men. Obese women (but not men) were less aware than normal-BMI women that obesity increased risk for CRC (OR = 0.5, 95% CI:0.3–0.9) and less worried about CRC (OR = 0.5, 95% CI:0.3–0.8). However, findings suggest that attitudes/perceptions about CRC and screening did not mediate or moderate the association between BMI category and CRC screening. Conclusion: Overweight/obese women are at increased risk for CRC because of their greater BMI and their propensity not to screen for CRC. Study findings suggest that potentially modifiable perceptions, e.g., lack of awareness of risk for CRC and less worry about CRC, in this subgroup may not explain the relationship between BMI category and reduced screening.     

Vitamin D receptor polymorphism and colorectal cancer-specific and all-cause mortality

BackgroundThe vitamin D receptor (VDR) gene is present in colorectal cancer (CRC) cells and its genetic variants have been associated with an increased risk of CRC. The association with colorectal cancer prognosis remains widely unexplored.Methods1397 colorectal cancer patients participating in two cancer cohorts (ESTHER II and VERDI) and in a population-based case–control study (DACHS) were followed for 5 years. Unadjusted and adjusted hazard ratios for all-cause mortality (469 events) and CRC-specific mortality (336 events) were estimated for VDR variants rs731236 (TaqI), rs2228570 (FokI), rs11568820 (Cdx2), and rs1989969 (VDR-5132).ResultsNo association was found between VDR polymorphism and CRC specific and all-cause mortality. Adjusted hazard ratios ranged from 0.79 (95% CI 0.57–1.12) to 1.14 (95% CI 0.89–1.46) for CRC-specific mortality and from 0.89 (95% CI 0.67–1.18) to 1.22 (95% CI 0.99–1.50) for all-cause mortality. All 95% confidence intervals included the null value.ConclusionsOur findings do not support the hypothesis that the common VDR gene variants investigated in this study are of clinical relevance with respect to CRC prognosis.     

Baseline alcohol consumption,type of alcoholic beverage and risk of colorectal cancer in the European Prospective Investigation into Cancer and Nutrition-Norfolk study

Excessive alcohol consumption has been associated with increased risk of colorectal cancer (CRC). However, the effect of modest alcohol consumption or of particular types of beverages on CRC risk remains unclear. We examined whether consumption of total alcohol or specific types of alcoholic beverages relate to overall or site-specific CRC risk in a prospective population study of 24,244 participants and 407 incident CRC cases after 11 years of follow-up. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models. Consumption of specific alcoholic beverages at baseline was collected using a detailed health and lifestyle questionnaire. Total alcohol consumption was not associated with CRC risk before or after adjustment for age, sex, weight, height, and smoking status (HR: 0.80, 95% CI: 0.51–1.26 for alcohol consumption of ≥21 units/week compared with non-drinkers), and further adjustment for education level, exercise, family history of CRC, and dietary factors did not significantly alter the risk estimates (HR: 0.70, 95% CI: 0.44–1.13). No significant associations were observed between consumption of specific alcoholic beverages (beer, sherry, or spirits) and CRC risk when compared with non-drinkers after adjustment for lifestyle and dietary factors. Daily consumption of ≥1 unit of wine appeared inversely related to CRC risk (HR: 0.61, 95% CI: 0.40–0.94). No evidence was found for sex-specific relationships, and further exclusion of cases incident within 3 years of baseline did not change the associations observed. In this population-based UK cohort, we did not find any significant adverse effect of alcohol over the moderate range of intake on colorectal cancer risk.     

Genome-Wide Diet-Gene Interaction Analyses for Risk of Colorectal Cancer

Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3) and processed meat consumption (OR = 1.17; p = 8.7E-09), which was consistently observed across studies (p heterogeneity = 0.78). The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively) and null among those with the GG genotype (OR = 1.03). Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.     

Performance of an adipokine pathway-based multilocus genetic risk score for prostate cancer risk prediction

Few biomarkers are available to predict prostate cancer risk. Single nucleotide polymorphisms (SNPs) tend to have weak individual effects but, in combination, they have stronger predictive value. Adipokine pathways have been implicated in the pathogenesis. We used a candidate pathway approach to investigate 29 functional SNPs in key genes from relevant adipokine pathways in a sample of 1006 men eligible for prostate biopsy. We used stepwise multivariate logistic regression and bootstrapping to develop a multilocus genetic risk score by weighting each risk SNP empirically based on its association with disease. Seven common functional polymorphisms were associated with overall and high-grade prostate cancer (Gleason≥7), whereas three variants were associated with high metastatic-risk prostate cancer (PSA≥20 ng/mL and/or Gleason≥8). The addition of genetic variants to age and PSA improved the predictive accuracy for overall and high-grade prostate cancer, using either the area under the receiver-operating characteristics curves (P<0.02), the net reclassification improvement (P<0.001) and integrated discrimination improvement (P<0.001) measures. These results suggest that functional polymorphisms in adipokine pathways may act individually and cumulatively to affect risk and severity of prostate cancer, supporting the influence of adipokine pathways in the pathogenesis of prostate cancer. Use of such adipokine multilocus genetic risk score can enhance the predictive value of PSA and age in estimating absolute risk, which supports further evaluation of its clinical significance.