Smith-Byrne, K. | bioRxiv Science

bioRxiv2020

Integration of polygenic risk scores with modifiable risk factors improves risk prediction: results from a pan-cancer analysis

Cancer risk is determined by a complex interplay of environmental and heritable factors. Polygenic risk scores (PRS) provide a personalized genetic susceptibility profile that may be leveraged for disease prediction. Using data from the UK Biobank (413,753 individuals; 22,755 incident cancer cases), we quantify the added predictive value of integrating cancer-specific PRS with family history and modifiable risk factors for 16 cancers. We show that incorporating PRS measurably improves prediction accuracy for most cancers, but the magnitude of this improvement varies substantially. We also demonstrate that stratifying on levels of PRS identifies significantly divergent 5-year risk trajectories after accounting for family history and modifiable risk factors. At the population level, the top 20% of the PRS distribution accounts for 4.0% to 30.3% of incident cancer cases, exceeding the impact of many lifestyle-related factors. In summary, this study illustrates the potential for improving cancer risk assessment by integrating genetic risk scores.

genetics↗

bioRxiv2019

Insulin-like growth factor-1 (IGF-1), insulin-like growth factor-binding protein-3 (IGFBP-3) and breast cancer risk: observational and Mendelian randomization analyses

BackgroundEpidemiological evidence supports a positive association between circulating insulin-like growth factor-1 (IGF-1) concentrations and breast cancer risk, but both the magnitude and causality of this relationship are uncertain. We conducted observational analyses with adjustment for regression dilution bias, and Mendelian randomization (MR) analyses to allow causal inference.\n\nPatients and methodsWe investigated the associations between circulating IGF-1 concentrations and incident breast cancer risk in 206,263 women in the UK Biobank. Multivariable hazard ratios (HRs) and 95% confidence intervals (CI) were estimated using Cox proportional hazards models. HRs were corrected for regression dilution using repeat IGF-1 measures available in a subsample of 6,711 women. For the MR analyses, genetic variants associated with circulating IGF-1 and IGFBP-3 levels were identified and their association with breast cancer was examined with two-sample MR methods using genome-wide data from 122,977 cases and 105,974 controls.\n\nResultsIn the UK Biobank, after a median follow-up of 7.1 years, 4,360 incident breast cancer cases occurred. In the multivariable-adjusted models corrected for regression dilution, higher IGF-1 concentrations were associated with a greater risk of breast cancer (HR per 5 nmol/L increment of IGF-1=1.11, 95%CI=1.07-1.16). Similar positive associations were found by follow-up time, menopausal status, body mass index, and other risk factors. In the MR analyses, a 5 nmol/L increment in genetically-predicted IGF-1 concentration was associated with greater breast cancer risk (odds ratio [OR]=1.05, 95%CI=1.01-1.10; Pvalue=0.02), with a similar effect estimate for estrogen positive (ER+) tumors, but no effect found for estrogen negative (ER-) tumors. Genetically-predicted IGFBP-3 concentrations were not associated with breast cancer risk (OR per 1-SD increment=1.00, 95%CI=0.97-1.04; Pvalue=0.98).\n\nConclusionOur results support a probable causal relationship between circulating IGF-1 concentrations and breast cancer, suggesting that interventions targeting the IGF pathway may be beneficial in preventing breast tumorigenesis.\n\nDisclaimerWhere authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organization.

genetics↗