PONE-D-23-31393Epigenetic aging differentially impacts breast cancer risk by self-reported ancestryPLOS ONE

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: In the manuscript “Epigenetic aging differentially impacts breast cancer risk by self-reported ancestry,” Wu et al. perform a case-control study of newly-diagnosed breast cancer patients and cancer free controls with two DNA methylation (DNAm) based metrics of biological age. The investigators report positive associations between age acceleration metrics (both adjusted an unadjusted for blood cell composition) and breast cancer risk. In a stratified analysis by self-reported race, the association between age acceleration and breast cancer risk appeared to vary, with stronger associations observed in White women. Overall, the paper is a bit sophomoric and narrow in focus. However, it is well written and advances our understanding of the association between the GrimAge epigenetic clock and breast cancer using a small, but racially diverse, population. Although I believe the manuscript is worthy of publication in this journal, the authors should address the following points:

Major concerns

There seems to be some confusion about the role of self-reported race in the analysis of GrimAge and breast cancer. The results from the stratified models and the significant interaction term suggest that race is a modifier of the association, not a confounder or a mediator as suggested by the authors.

It is perhaps not surprising that the association of intrinsic GrimAge and breast cancer is attenuated compared to the unadjusted model; Kresovich et al (2020, JAMA Network open) previously reported that blood cell composition is a marker of breast cancer risk suggesting that biological age and blood cell composition appear to detect overlapping, although not entirely, signals of breast cancer risk. This point should be made clear to readers.

The authors should report breast cancer associations with the DNAm proteins that comprise the GrimAge epigenetic clock. This would provide more of a basis to the comments made in the discussion where the authors suggest their associations are due to the underlying associations with cystatin C and leptin. (see Kresovich et al, Aging 2019)

Although using the MethylationEPIC BeadChip information for biological age is interesting, there is a bit of a missed opportunity to perform an epigenome-wide association study of breast cancer at the individual CpG site resolution. A challenge would be replicating associations, but many EWASs of breast cancer have been performed, so the investigators could present an external validation of known CpG and BC associations.

Similarly, the associations between other epigenetic clocks (Horvath, PhenoAge) and DNAm-based metrics of aging rates (DunedinPACE) should be at a minimum reported in supplemental material. There do not appear to be any papers between aging rates (DunedinPACE) and breast cancer, which would greatly strengthen the impact of this manuscript.

Minor concerns

There is some incorrect information about GrimAge in the discussion: the GrimAge clock is based on 7 DNAm-predicted plasma protein concentrations (not 88) and a DNAm predictor of smoking status, combined with chronological age and sex. The authors may need to revisit the original clock manuscripts to make sure their descriptions of the development procedures are correct.

The intrinsic GrimAge metric does not consider “white blood cell count” (line 200); instead, it accounts for “white blood cell composition” which is represented by the circulating proportion of different leukocyte subsets. Unfortunately, it is not possible to obtain reliable cell count information from methylation arrays.

The description of the figures seems to be incorrect. Please revise the figure images so the cases are pink and the disease-free controls are orange (opposite to what is noted in the figure legend).

Please do not confuse self-reported race with ancestry. Ancestry is commonly measured using genetic data whereas race is often based on identity. Unless genetic data were used to inform the ancestry of the participants, please refer to the data as how the participants “self-identified” themselves.

Reviewer #2: Yanning Wu and colleagues analyzed epigenetic clock data from 209 women of the Cleveland Medical Center with respect to an association with breast cancer. Statistically significant differences in age acceleration were found between cases and controls and this association persisted after adjustment for known confounder in a logistic regression model. The role of self-reported race was analyzed in subgroup analyses.

This paper is an interesting and important contribution to the field and the available data as well as the statistical analyses employed seem fit to answer the author’s research question. The study is well designed and the data seems to be of a high scientific quality. However, some issues remain and I hope the authors will find my comments helpful.

First, I found the nomenclature sometimes confusing. I would suggest using the convention in the field as this would make it much easier to comprehend the information presented. Namely, the abbreviation AA_GrimAge and AA_GrimAge_In seem weird to me. In most studies you would find the following abbreviations:

- DNA methylation age: DNAmA

- DNA methylation age acceleration: DNAmAA

- GrimAge acceleration: GrimAA

- Intrinsic epigenetic age acceleration: IEAA

- Extrinsic epigenetic age acceleration: EEAA

Also, it is necessary to distinct better between methylation age and methylation age acceleration. Both are used interchangeably in the manuscript which is not correct (methylation age is the “raw” biological age measure and methylation age acceleration refers to the “gap” between chronological and biological age).

Second, in some parts of the manuscripts the authors use causal language although causality is hard to deduct from this kind of (cross-section and observational) data. To confidently assume a causal effect, much more analyses and theoretical considerations need to be included (directed acyclic graph and others). Therefore, I would suggest rewriting the respective passages, e.g. exchange “results in” with “is associated with”.

Third, although it is understandable that the authors focus on GrimAge in this manuscript, it still would be interesting to see how the other epigenetic clocks (e.g. Horvath, Hannum, PhenoAge, DundinPACE) are associated with breast cancer. Additionally, this would increase comparability to other studies and substantially improve the impact of the study. I therefore suggest the authors provide these additional analyses as Supplementary Material and briefly discuss potential differences in the results. Since the authors used Steve Horvath’s website the other clocks should already be available.

Minor concerns:

Line 39: I think the convention is to use “intrinsic epigenetic age acceleration” when referring to the cell-type adjusted residuals. “GrimAge intrinsic clocks” sounds unfamiliar to me.

Line 44/45 “GrimAge intrinsic accelearion”: The same applies here. I think it would be better to stick to “intrinsic epigenetic age acceleration”.

Line 101: “intrinsic epigenetic age”: I think it should state “intrinsic epigenetic age acceleration”.

Line 103 “intrinsic epigenetic age” -> “intrinsic epigenetic age acceleration”

Line 106: “intrinsic age” -> “intrinsic age acceleration”

Line 137: Since you calculated a regression please exchange “correlated” with “associated”.

Line 138-140: I find this sentence confusing. The measure AA_Grim_In is per definition an cell-type adjusted residual of a regression of epigenetic age on chronological age. It therefore would not make sense to adjust any regression including AA_Grim_in for blood cell composition. I therefore would suggest that this sentence is rephrased, e.g. “similar effect size was found for the leukocyte cell type adjusted AA_Grim_In as well”.

Line 142: The word “impact” implies causation as well as a direction of the causal association. Neither can be deducted from cross-sectional data only. Please rephrase. Also this sentence is somewhat redundant to the second sentence in this paragraph.

Line 145: “effect” implies causation. Additionally, a potential effect of one variable on the other stays always the same. Only the effect size estimated from a statistical analysis changes.

Line 148 and 149: Please write “percentage points” instead of “%” if you are referring to the numerical difference between the risk.

Line 158: I am not sure whether self-reported race would “confound” the association. It certainly is as effect measure modifier (EMM) but whether if fulfils the criteria for a confounder should be checked.

Discussion: It is a frequently observed phenomenon that women have lower epigenetic age than chronological age (while men often have a higher epigenetic age). This is described frequently in the literature and might be important to mention in the discussion as this might not be known to all readers. Without context it could be confusing that the disease-free women are all epigenetically younger.

Line 294: What do you mean by “imputed”? Were they measured and the missing values were imputed? Or were they estimated from the methylation data? Please clarify.

Line 274: “Data was processed for downstream analyses”: Please elaborate which quality control measures were used and how data was processed (software, packages).

Statistical Analysis: Please report which statistical software was used to conduct the analyses.

Figure 1 and S1: Please use boxplots instead of dynamite plots as a lot of information is lost. If possible, please show individual datapoints to illustrate the distribution.

Table 1: Please include the epigenetic age estimations in your table one (AA_GrimAge and AA_GrimAge_In).

Table 3: Which of the models in Table 2 was used here? I think it would be interesting to show all three models of Table 2 also stratified by self-reported race.

List of abbreviations: IEAA and EEAA are noted but never used in the manuscript (although I would suggest to use these abbreviations instead of AA_GrimAge and AA_GrimAge_In).

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Reviewer #1: No

Reviewer #2: Yes: Valentin Vetter

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PONE-D-23-31393R1Epigenetic aging differentially impacts breast cancer risk by self-reported racePLOS ONE

Dear Dr. Schumacher,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

here is one issue with the analysis that has not been addressed. The differences in age acceleration being greater in the breast cancer patients appears real but the authors must take into account the effect of chemotherapy on age acceleration as this would skew any results in favor of greater age acceleration which is not due to breast cancer per se. So, in the analysis this must be controlled for.

==============================

Please submit your revised manuscript by Jun 03 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Abdul Rauf Shakoori

Academic Editor

PLOS ONE

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Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Comments to the Author

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Reviewer #3: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: There is one issue with the analysis that has not been addressed. The differences in age acceleration being greater in the breast cancer patients appears real but the authors must take into account the effect of chemotherapy on age acceleration as this would skew any results in favor of greater age acceleration which is not due to breast cancer per se. So, in the analysis this must be controlled for.

**********

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Reviewer #3: No

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Epigenetic aging differentially impacts breast cancer risk by self-reported race

PONE-D-23-31393R2

Dear Dr. Schumacher,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Abdul Rauf Shakoori

Academic Editor

PLOS ONE

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