Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology
In this issue, Kresovich and colleagues have published a hallmark paper in Molecular, Environmental, Genetic and Analytic Epidemiology. By applying artificial intelligence to the Sister Study they created a new methylation‐based breast cancer risk score (mBCRS) based on blood DNA methylation. Using...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Molecular Oncology |
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| Online Access: | https://doi.org/10.1002/1878-0261.13117 |
| _version_ | 1818967905557020672 |
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| author | John L. Hopper Tuong L. Nguyen Shuai Li |
| author_facet | John L. Hopper Tuong L. Nguyen Shuai Li |
| author_sort | John L. Hopper |
| collection | DOAJ |
| description | In this issue, Kresovich and colleagues have published a hallmark paper in Molecular, Environmental, Genetic and Analytic Epidemiology. By applying artificial intelligence to the Sister Study they created a new methylation‐based breast cancer risk score (mBCRS) based on blood DNA methylation. Using a prospective design and after accounting for age and questionnaire‐based breast cancer risk factors, the Odds PER Adjusted standard deviation (OPERA) for mBCRS and polygenic risk score (PRS) was 1.58 (95% CI: 1.38, 1.81) and 1.58 (95% CI: 1.36, 1.83), respectively, and the corresponding area under the receiver operating curve was 0.63 for both. Therefore, mBCRS could be as powerful as the current best PRS in differentiating women of the same age in terms of their breast cancer risk. These risk scores are among the strongest known breast cancer risk‐stratifiers, shaded only by new mammogram risk scores based on measures other than conventional mammographic density, such as Cirrocumulus and Cirrus, which when combined have an OPERA as high as 2.3. The combination of PRS and mBCRS with the other measured risk factors gave an OPERA of 2.2. OPERA has many advantages over changes in areas under the receiver operator curve because the latter depend on the order in which risk factors are considered. Although more replication is needed using prospective data to protect against reverse causation, there are many novel molecular and analytic aspects to this paper which uncovers a potential mechanism for how genetic and environmental factors combine to cause breast cancer. |
| first_indexed | 2024-12-20T13:56:10Z |
| format | Article |
| id | doaj.art-63642af7198b42fd9597447078124229 |
| institution | Directory Open Access Journal |
| issn | 1574-7891 1878-0261 |
| language | English |
| last_indexed | 2024-12-20T13:56:10Z |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Molecular Oncology |
| spelling | doaj.art-63642af7198b42fd95974470781242292022-12-21T19:38:26ZengWileyMolecular Oncology1574-78911878-02612022-01-0116181010.1002/1878-0261.13117Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiologyJohn L. Hopper0Tuong L. Nguyen1Shuai Li2Centre for Epidemiology and Biostatistics University of Melbourne Melbourne Vic AustraliaCentre for Epidemiology and Biostatistics University of Melbourne Melbourne Vic AustraliaCentre for Epidemiology and Biostatistics University of Melbourne Melbourne Vic AustraliaIn this issue, Kresovich and colleagues have published a hallmark paper in Molecular, Environmental, Genetic and Analytic Epidemiology. By applying artificial intelligence to the Sister Study they created a new methylation‐based breast cancer risk score (mBCRS) based on blood DNA methylation. Using a prospective design and after accounting for age and questionnaire‐based breast cancer risk factors, the Odds PER Adjusted standard deviation (OPERA) for mBCRS and polygenic risk score (PRS) was 1.58 (95% CI: 1.38, 1.81) and 1.58 (95% CI: 1.36, 1.83), respectively, and the corresponding area under the receiver operating curve was 0.63 for both. Therefore, mBCRS could be as powerful as the current best PRS in differentiating women of the same age in terms of their breast cancer risk. These risk scores are among the strongest known breast cancer risk‐stratifiers, shaded only by new mammogram risk scores based on measures other than conventional mammographic density, such as Cirrocumulus and Cirrus, which when combined have an OPERA as high as 2.3. The combination of PRS and mBCRS with the other measured risk factors gave an OPERA of 2.2. OPERA has many advantages over changes in areas under the receiver operator curve because the latter depend on the order in which risk factors are considered. Although more replication is needed using prospective data to protect against reverse causation, there are many novel molecular and analytic aspects to this paper which uncovers a potential mechanism for how genetic and environmental factors combine to cause breast cancer.https://doi.org/10.1002/1878-0261.13117breast cancerDNA methylationMEGA epidemiologyOPERApolygenic risk scorerisk prediction |
| spellingShingle | John L. Hopper Tuong L. Nguyen Shuai Li Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology Molecular Oncology breast cancer DNA methylation MEGA epidemiology OPERA polygenic risk score risk prediction |
| title | Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology |
| title_full | Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology |
| title_fullStr | Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology |
| title_full_unstemmed | Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology |
| title_short | Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology |
| title_sort | blood dna methylation score predicts breast cancer risk applying opera in molecular environmental genetic and analytic epidemiology |
| topic | breast cancer DNA methylation MEGA epidemiology OPERA polygenic risk score risk prediction |
| url | https://doi.org/10.1002/1878-0261.13117 |
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