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PONE-D-22-06423Interaction-based Mendelian randomization with measured and unmeasured gene-by-covariate interactionsPLOS ONE

Dear Dr. Spiller:

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. Best wishes, Momiao Xiong

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Momiao Xiong

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. 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 #1: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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3. 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 #1: Yes

Reviewer #2: Yes

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4. 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 #1: Yes

Reviewer #2: Yes

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5. 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 #1: The paper discusses the relative strengths and limitations of interaction-MR approaches for both MR-GxE and MR-GENIUS methods, which is a great contribution to the field. I have a few comments below:

1. For simulation settings, could you please provide more details how the variables in equations are generated (i.e. what are the distributions they come from and the associated parameters)?

2. For simulation results, could you make it clear what type of outcomes they are (seems the results are for continuous exposure and outcome).

3. Have you tried to extend the simulations to other types of outcomes (i.e. binary outcome)?

Thanks.

Reviewer #2: Spiller et al explore the performance of two Mendelian randomization approaches that rely on genotype x environment interactions (MR-GxE and MR-GENIUS) to correct for the pervasive problem of genetic pleiotropy in ordinary MR analyses. The authors review both methods, propose a new formulation of MR-GxE in the two stage least squares framework, propose a series of sensitivity analyses to evaluate the robustness of the methods to violations of underlying assumptions, and then finally explore the (known) causal relationship between BMI and systolic blood pressure in the UK Biobank.

General comments:

-This is an exceptionally well written manuscript that I thoroughly enjoyed reading. The background material in the Materials and Methods was very useful - providing intuition for understanding the mechanics of the approaches and without sacrificing intellectual rigour. I do not have any major concerns with the paper, but do have a number of suggestions for improving its clarity in certain parts, and some additional points that the author might want to consider.

Line 110 Page 5: The notation is confusing here. I assume this is meant to be epsilon_hat_subscript_X_i but it could also be read as epsilon_hat multiplied by X_subscript_i.

Line 138 Page 5: “First, when using a single interaction the F-statistic cannot be related to the magnitude of relative bias, as at least three instruments would be required for the asymptotic formula to be valid.”. This sentence is not clear to me.

Top of page 6: Scale dependency- obviously scale dependent interactions may also be present in the absence of transformation (i.e. when the variables are on their original scale).

Line 159 Page 6: “Specifically, MR-GENIUS relies upon the residual error in a regression of the exposure upon the genetic IV to be heteroskedastic, such that (X|G) = E(ϵ2X|G) [13]. This is evaluated using a Breusch-Pagan test for heteroskedasticity [13].” Again, I find this a little unclear especially the equation. My understanding is that in a Breusch-Pagan test the square of the first stage residuals is regressed on the IV (here genotype). I assume you are saying that the expected value of the squared residuals given G doesn’t change across levels of G- but is this the correct way to say this using an equation?

Line 163-171. I assume that these analyses to identify gene x covariate interactions are based on polygenic risk scores, rather than individual variants. I suggest you make this clear, especially since single variants are unlikely to show large GxE for most traits.

Line 173 (page 6) “In previous work we show how assumption GxE2 is potentially violated when certain confounding structures exist, specifically, where Gi and Zki are simultaneously downstream of a confounder Ui or where there is an open path between the two variables through Ui”. Could the authors please discuss the intuition for this result perhaps with the aid of a path diagram (or description)? Do you need both paths to be present (i.e. a path from U to G AND a path from U to Z, or is only one sufficient to produce bias?). Why? Maybe this could be pointed out to the reader?

“Relating assumption GxE2 to the MR-GENIUS approach, associations violating GxE2 would imply associations vary across values of the unmeasured confounders violating the second MR-GENIUS assumption [13]. However, this problem can be mitigated by incorporating additional interaction covariates within the MR-GENIUS model, as described in Tchetgen Tchetgen et al, 2021 [13].” Please expand on this.

“The third MR-GxE assumption requires pleiotropic effects of Gi upon Yi to remain

constant across values of Zki, with the gene-by-covariate interaction being independent

of Yi when conditioning on Xi.”. I would put in parentheses after this statement (i.e. beta_4 equals zero)

Some further thoughts:

A table summarizing the core assumptions, the consequences for violating them, and methods of testing them might be useful for readers.

One of the difficulties in ordinary MR studies is whether the SNPs chosen to be instruments are primarily associated with the exposure, or the outcome. Various methods (e.g. Steiger filtering) have been proposed to get a handle on this problem. My question is whether the addition of SNP*covariate terms in GZ where the SNP is primarily an outcome associated SNP is problematic? My guess would be yes (it implies beta_4 is not null). Do the authors think that this would be a common problem? If so, could they recommend procedures to guide against this possible source of bias?

Sex seems an obvious candidate for a genotype x “environment” interaction. Was this included in the list of covariates and results not presented because the evidence for interaction was so low?

You have a “positive empirical control” in this paper (i.e. we know BMI causes SBP) would it be worth also including a negative empirical control? (i.e. two phenotypes where we are pretty sure the exposure doesn’t cause the outcome). I realize that this may potentially be a substantial amount of work so would be happy for the paper to be accepted without it, but i think it is something worth considering.

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Reviewer #1: No

Reviewer #2: No

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Interaction-based Mendelian randomization with measured and unmeasured gene-by-covariate interactions

PONE-D-22-06423R1

Dear Dr.Spiller ,

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.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Momiao Xiong

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

You have address all the issues  which the reviewers are concerned.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (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 #1: (No Response)

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

Reviewer #1: (No Response)

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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 #1: (No Response)

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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 #1: (No Response)

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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 #1: (No Response)

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

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