Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology. Issue 1 (3rd November 2021)
- Record Type:
- Journal Article
- Title:
- Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology. Issue 1 (3rd November 2021)
- Main Title:
- Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology
- Authors:
- Hopper, John L.
Nguyen, Tuong L.
Li, Shuai - Abstract:
- Abstract : 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 aAbstract : 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. Abstract : This commentary highlights the introduction of a new DNA methylation‐based breast cancer risk score (mBCRS). Unlike genetic events, DNA methylation is an epigenetic process influenced by lifestyle factors, and changes the way the DNA code is read. The statistical approach called OPERA shows that mBCRS is as good as the current best genetic risk score in determining a woman's breast cancer risk. … (more)
- Is Part Of:
- Molecular oncology. Volume 16:Issue 1(2022)
- Journal:
- Molecular oncology
- Issue:
- Volume 16:Issue 1(2022)
- Issue Display:
- Volume 16, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 16
- Issue:
- 1
- Issue Sort Value:
- 2022-0016-0001-0000
- Page Start:
- 8
- Page End:
- 10
- Publication Date:
- 2021-11-03
- Subjects:
- breast cancer -- DNA methylation -- MEGA epidemiology -- OPERA -- polygenic risk score -- risk prediction
Cancer -- Molecular aspects -- Periodicals
616.994005 - Journal URLs:
- http://www.journals.elsevier.com/molecular-oncology/ ↗
http://febs.onlinelibrary.wiley.com/hub/journal/10.1002/(ISSN)1878-0261/issues/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1002/1878-0261.13117 ↗
- Languages:
- English
- ISSNs:
- 1574-7891
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5900.817993
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- 20552.xml