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1. Case-Case Genome-Wide Analyses Identify Subtype-Informative Variants that Confer Risk for Breast Cancer

2. Association of breast cancer with quantitative mammographic density measures for women receiving contrast-enhanced mammography

3. A genome-wide association study of contralateral breast cancer in the Women’s Environmental Cancer and Radiation Epidemiology Study

4. Association of Breast Cancer Odds with Background Parenchymal Enhancement Quantified Using a Fully Automated Method at MRI: The IMAGINE Study

5. Trends in Radiation Dose to the Contralateral Breast During Breast Cancer Radiation Therapy

6. Suppl. Table 1 from Approaching a Scientific Consensus on the Association between Allergies and Glioma Risk: A Report from the Glioma International Case-Control Study

7. Supplementary Table 7 from Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma

8. Data from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

9. Supplementary Methods from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

10. Suppl. Table 1 from Approaching a Scientific Consensus on the Association between Allergies and Glioma Risk: A Report from the Glioma International Case-Control Study

11. Supplementary Table 1 from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

12. Data from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

13. Supplementary Methods from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

14. Supplementary Figure 4 from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

15. Supplementary Figure 3 from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

16. Data from Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma

17. Supplementary Table 1 from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

18. Supplementary Table 6 from Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma

19. Supplementary Table 5 from Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma

20. Supplementary Figure 1 from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

21. Supplementary Figure 1 from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

22. Supplementary Figure 3 from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

23. Supplementary Data from Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma

24. Supplementary Figure 2 from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

25. Data from Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma

26. Supplementary Figure 4 from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

27. Supplementary Data from Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma

28. Supplementary Figure 2 from A Variable Age of Onset Segregation Model for Linkage Analysis, with Correction for Ascertainment, Applied to Glioma

29. Supplementary Table 7 from Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma

35. Association of contralateral breast cancer risk with mammographic density defined at higher‐than‐conventional intensity thresholds

36. Mammographic texture features associated with contralateral breast cancer in the WECARE Study

37. Coronary Artery Disease in Young Women After Radiation Therapy for Breast Cancer

38. The predictive ability of the 313 variant–based polygenic risk score for contralateral breast cancer risk prediction in women of European ancestry with a heterozygous BRCA1 or BRCA2 pathogenic variant

41. List of Contributors

42. A case-control study of the joint effect of reproductive factors and radiation treatment for first breast cancer and risk of contralateral breast cancer in the WECARE study

43. Association of breast cancer with MRI background parenchymal enhancement: the IMAGINE case-control study

44. The emergence of networks in human genome epidemiology: challenges and opportunities

45. Genome-wide association studies, field synopses, and the development of the knowledge base on genetic variation and human diseases

46. Pathogenic ATM Mutations in Cancer and a Genetic Basis for Radiotherapeutic Efficacy

48. Cancer Risks Associated With Germline PALB2 Pathogenic Variants: An International Study of 524 Families

49. Machine learning on genome-wide association studies to predict the risk of radiation-associated contralateral breast cancer in the WECARE Study

50. The Implications of Genetic Testing on Radiation Therapy Decisions: A Guide for Radiation Oncologists

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