In this study, we evaluated the clinical utility of genetic markers in PCa risk prediction for Chinese men. Using 33 SNPs identified in populations of European descent, we demonstrated that the genetic markers were effective in discriminating Chinese PCa cases from Chinese controls, with AUCs above 0.60. Although these results need to be confirmed, our study shows these genetic markers may be useful for PCa risk prediction in Chinese men and might be informative for guiding prevention and screening of PCa in China.
In contrast to the traditional risk factors for PCa, such as family history, or biomarkers such as serum prostate specific antigen levels, genetic scores derived from inherited genetic variations have an advantage in that the genetic variants are stable throughout the life of the individuals. Family history information may change over time, and is strongly dependent on other factors including family size, age of relatives, healthcare access within the family, and the level of family communication. PSA levels change over time, and must be measured repeatedly.
With the cost of genotyping declining, genetic testing represents a cost-efficient method to predict PCa risk. Further efficiency can be obtained by simultaneously estimating the risk of multiple diseases, based on a single sample of DNA obtained from blood or saliva, by integrating multiple disease risk prediction markers. In addition, it is important to stress that the potential benefit of using genetic markers in PCa risk prediction may be stronger in Chinese men than western men for at least two reasons: 1) family history of PCa is very rare among the Chinese population, thus precluding its utility for PCa risk prediction in Chinese men; 2) the majority of PCa cases in Chinese men have advanced stage disease because most PCa diagnoses in China are based on symptoms rather than PSA screening.
We calculated AUCs based on ORs from studies of populations of European descent as well as from the association results observed in subjects of the current study. We used the European ORs because estimates of ORs based on a large Chinese population for those 33 SNPs were not available. As expected, the AUC was higher for either model that we developed based on ORs from all 33 SNPs or just the 11 significant SNPs in these Chinese cases and controls, compared with a lower AUC when using the risk model derived from ORs in the European population,. However, at this time, we are not able to conclude that the risk model derived from Chinese ORs actually performed better than that derived from European ORs; over-fitting of the genetic models might have occurred because we used the effect sizes that were calculated from the same set of subjects. In addition, a higher AUC was observed for all 33 SNPs than for the 11 significant SNPs, which suggests the SNPs that were not significantly associated with PCa risk in this study contribute additional information to the prediction model. Further studies with larger sample sizes may be helpful to confirm our results and further refine the list of SNPs related to PCa risk in Chinese men.
Given the substantial heterogeneity of genetic determinants between populations of Chinese (relatively homogenous) versus those of European descent (relatively heterogeneous), it may be imprecise to assess the performance of 33 SNPs on risk prediction in Chinese men based on the SNP effects (ORs) estimated from studies among populations of European descent. In fact, if the effect sizes of the 33 SNPs were not available in this Chinese population, then ORs for 33 SNPs from the European population might be an alternative approach for the assessment of the genetic markers. At least twofactors may support our approach. First, in populations of European descent these 33 SNPs were all identified from GWAS and have been reproducibly replicated [4
]; these SNPs might be causal or good surrogates for their respective causal variants. In populations of non-European descent, these genetic markers, might be modifiers for PCa risk. At least 11 of these 33 loci were observed to be significantly associated with PCa risk in our study of 1,108 cases and 1,525 controls. In addition, suggestive evidence for association with PCa risk was also found for 6 additional SNPs for which the reported risk alleles were more common in cases than controls (P
< 0.20). Second, some of these SNPs may be important in European populations but not in Chinese populations. We recognize that such loci might have resulted in noise for the genetic risk model and therefore may have decreased the efficiency of this study. However, such noise should be random and have a net neutral effect, and thus should not substantially increase or decrease the performance of the genetic model.
Limitations of this study should be noted. First, utilization of an existing case-control study was a cost-efficient approach to build and evaluate the risk prediction model, although potential bias may have been introduced. It is also challenging to assess the value of genetic markers in addition to PSA for PCa risk prediction. Further prospective cohort studies are required to formally evaluate the findings of this study. Second, we did not obtain detailed epidemiologic information from all participants, which limited our ability to compare the genetic model versus risk prediction models based on family history. Finally, this study was focused on the SNPs identified in populations of European descent. Additional genetic risk factors, particularly those unique to the Chinese population, need to be identified and evaluated in future studies, and may further improve the discriminatory accuracy of risk prediction based on genotyping data.
In summary, our results show that genetic scores, an aggregate measure of the combined effect of multiple genetic risk factors, based on PCa risk variants identified in populations of European descent are potential predictors for PCa risk in Chinese men. This study extends the previous findings from European populations to the Chinese population and provides additional support for the clinical utility of genetic markers. Although the genetic risk scores had moderate discriminatory accuracy, they showed promise for assessing PCa risk in Chinese men, and this may help identify men who would obtain the most benefit from PCa prevention and screening strategies. Nevertheless, further efforts should be focused on the discovery of genetic risk variants that are specific to the Chinese population, so they may be used as risk predictors to improve the discriminatory accuracy of genetic risk models.