Polygenic Risk Score in Follicular Lymphoma Risk and Prognosis in a Population-Based Case-Control Study in Los Angeles County

Background: Although several prognostic factors are regularly utilized for follicular lymphoma (FL) - e.g., extent of disease, presence of B-symptoms, and the FL international prognostic index (IPI) - they do not fully account for the heterogeneity in patient outcomes. Etiologic risk factors may influence the heterogeneity of prognostic outcomes, but relatively few risk factors for FL have been identified and subsequently confirmed. Recent epidemiologic studies have uncovered genetic risk loci associated with FL risk. To date, the association between these risk alleles with FL prognosis remains unknown. We therefore sought to evaluate whether identified genetic risk loci specific to FL also play a role in FL prognosis. Methods: We previously conducted a population-based case-control study of primary, incident Non-Hodgkin Lymphoma (NHL) among women in Los Angeles County diagnosed from 2006 to 2009. A total of 230 FL cases were enrolled in the study along with 246 age- and race- matched controls. To ascertain treatment and follow-up information, medical records were retrieved and abstracted, and data linkages to the California hospitalization discharge records and SEER-Medicare were conducted. Based on abstracted data, we constructed a surrogate to the FL IPI. Genotyping for FL genetic risk alleles identified in the National Human Genome Research Institute-European Bioinformatics Institute genome wide association study catalog (rs12195582, rs13254990, rs17749561, rs4245081, and rs4938573) was conducted and used to construct a polygenic risk score (PRS). The PRS was computed by taking a weighted average of the five alleles and the log of their reported odds ratio and creating tertiles based on the values of our control. To confirm the risk association, we first evaluated the association between our PRS and FL risk, adjusted for demographic characteristics and potential confounders (e.g., smoking status, BMI, and family history of hematologic malignancies). We subsequently confirmed the prognostic performance of our reconstructed IPI and then evaluated the association between the PRS and FL outcomes, including overall survival (OS), defined as date of initial diagnosis to date of death or last known follow-up; and event-free survival at 12 months (EFS12) and 24 months (EFS24), where events consisted of progression, refractory disease, or death. Results: In case-control analysis, we confirmed an increased FL risk associated with the third tertile PRS (OR=2.19, 95% CI=1.22-3.94), compared to the first tertile. The median follow-up time among FL cases was 8.5 years (IQR: 7.1-10.1) after initial diagnosis: 50 (22%) FL cases had died, 198 (86%) achieved EFS12 and 186 (81%) achieved EFS24. The re-constructed FL-IPI in our case population was statistically significantly associated with overall survival (HR=4.00, 95% CI=1.32-12.16). In our multivariate model that included the PRS, we observed a marginally significant risk for longer overall survival (HR=0.39, 95% CI=0.15, 1.01), but no association with EFS12 or EFS24. No statistically significant associations of individual risk alleles and prognostic outcomes were observed. Race-specific results and evaluation of demographic and other risk factors on risk and survival will also be presented in relation to the PRS. Conclusion: In our population sample of FL cases identified from the Los Angeles County Cancer Registry and initially recruited for a case-control study, we confirmed the association between a PRS and FL risk. We further report a potential association between the PRS and improved overall survival, suggesting an opposite effect for the PRS on risk versus survival. Larger studies on FL with genetic data and prognostic outcomes are warranted to replicate this finding. Disclosures Chao: Seattle Genetics: Research Funding.