Dear Dr. Yamada,

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.

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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?

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: I Don't Know

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The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Dr. Mitsunaga and colleagues present an excellent paper introducing a novel method for test-ing donor-derived cell-free DNA in transplantation patients.

The study provides a precise measurement method for dd-cfDNA quantification using a clus-tering system for NGS-based SNP data. A highly interesting approach. And an approach which can be used with or without pre-transplantation data.

This is a very interesting field, and the methodology and testing precision are key elements for the prospects of its clinical application. Therefore, this study is highly relevant.

I find the study extremely well formulated and presented, and I have only minor comments for the authors to consider.

Minor considerations

1. Abstract (page 3). I find that some of the content in the abstract is a little bit difficult to un-derstand, when not having read the full paper yet. Consider trying to make it more readable, although this is likely not easy.

2. Introduction (page 6, lines 88-91). Here, you provide some information about different techniques. This is perhaps a little too short. There are other strengths and weaknesses which could be mentioned beside multiplexing. Consider if you should elaborate a little on this topic.

3. Materials and Methods (page 7, lines 108-110). This is just a detail. Please specify that blood (and not plasma) is collected in Streck tubes, and that (only) plasma is stored (presum-ably in another type of tube) at -80 Degrees C.

4. Materials and Methods (page 8, lines 136-137). Here, you present the fragment sizes after treatment with fragmentase. It might be standard, but I find that the fragments are perhaps a little bit large? In any case, it would be great to include a reference for your statement on these fragments lengths being comparable to what is typically observed.

5. Materials and Methods (page 9, lines 151-156). I completely agree with the content of your note, but I think it would be ok to simply delete the note.

6. Table 2 (page 23). So, these data in Table 2 show excellent correlation as you demon-strate. But I think the data differences on day 1 are substantial between clustering 1 and 2. Consider if you should add a discussion on these differences (in the discussion).

7. Discussion / For comparison with other methods, it could be very interesting to hear about the turnaround time of the method (what is the time duration from the top to bottom of figure 1?).

Reviewer #2: 1. Clinical Correlation and Utility

The article lacks direct correlation analysis with clinical outcomes (e.g., biopsy-proven rejection, renal impairment). Given that data from over 650 samples are available, it is recommended that the authors include a preliminary analysis—such as a graph showing the dynamic changes in dd-cfDNA (as detected by this method) in one or two cases during rejection events. This would significantly enhance the article’s persuasiveness and clinical relevance.

Additionally, while Table 2 demonstrates concordance between clustering-based estimates and direct genotypic calculations, the manuscript does not compare the sensitivity and specificity of the clustering method versus traditional methods in diagnosing rejection episodes. Including such a comparison would better highlight the clinical utility of the approach.

2. Cost and Efficiency

The introduction mentions that existing NGS-based methods for estimating dd-cfDNA ratios are time-consuming. While the proposed clustering method appears to reduce analysis time, the manuscript does not discuss cost advantages over traditional approaches. Could the authors provide a comparative analysis of the costs involved in their method versus conventional techniques?

3. Population Specificity and Generalizability

The 300 SNPs selected were based on their frequencies in the Japanese population. It is unclear whether these polymorphisms are equally effective in other ethnic groups (e.g., Caucasians, Africans). The generalizability of the method and any adjustments that may be needed for its application in different populations should be discussed.

4. SNP Panel Design and Sequencing Parameters

As discussed in recent literature[1], several factors critically impact dd-cfDNA assay performance:

Nucleosome Footprinting: The authors should clarify whether their 300-SNP panel avoids regions with strong nucleosome positioning, as differential nucleosome occupancy between donor and recipient tissues can lead to significant quantification bias.

SNP Count and Sequencing Depth: The choice of 300 SNPs and the achieved sequencing depth are not thoroughly justified. The authors should reference theoretical calculations to demonstrate that their panel size and depth are sufficient to reliably detect low-frequency heterologous signals (e.g., <0.5%) with acceptable confidence intervals. A discussion on whether this number provides a stable proportion of homozygous and heterozygous informative SNPs in their target population is warranted.

5. Low-Level Detection and Accuracy

In post-transplant monitoring—particularly after lung transplantation—dd-cfDNA levels are typically below 1% in the absence of rejection. As shown in Table 1, the measured values at mixing rates of 0.5% and 1% deviate noticeably from the actual values. I recommend increasing the density of sample testing within the 0%–1% mixing range to validate the method's reliability for low-level dd-cfDNA quantification.

6. Use of Pre/Post-Transplant Difference Metric

The use of the differential allele ratio (post-transplant minus pre-transplant) for clustering is a central part of the method when baseline data are available. The authors assume this subtracts out background noise. However, this approach is highly sensitive to batch effects and technical variations between sequencing runs. The manuscript would be strengthened by providing quality control data demonstrating the technical reproducibility of the platform between runs, or by employing and validating an alternative normalization strategy.

7. Substitute for Pre-Transplant Samples

The manuscript states: "If a pre-transplant recipient sample is not available, leukocyte-derived genomic DNA or DNA from other sources can be fragmentase-treated and used as a substitute." However, cfDNA and leukocyte-derived gDNA differ significantly in fragment length, structure, and distribution. How do the authors address the potential impact of these differences on the accuracy and reliability of the results?

8. Sample Size and Statistical Power

Parent-Child Pairs: Given the limited sample size of only three parent-child pairs (n=3), conclusions drawn from this analysis should be treated with caution, and this limitation should be clearly stated in the Discussion.

Table 2: Lacks explicit indication of sample sizes, which should be added for clarity and transparency.

9. Comparison with Existing Methods

Although other methods are mentioned in the Introduction, it would be best to more directly compare this method with the gold standard in this field (such as ArcherDX’s LiquidIQ or Natera’s Prospera), highlighting its advantages and potential disadvantages in terms of process simplification, cost, and speed.

Moreover, the authors present their clustering method as a novel solution for dd-cfDNA quantification without donor genotype. However, the study fails to benchmark its performance against established donor-independent algorithms, such as:

Maximum likelihood estimation-based method using a binomial model [2]. A direct comparison on the same dataset(s) is essential to demonstrate the relative advantages, disadvantages, and potential improvements offered by the clustering approach in terms of accuracy, precision, and robustness, especially at low dd-cfDNA fractions.

10. Graphical Enhancements

It is recommended that trend lines or confidence intervals be added to the scatter plots in Figures 2, 3, and 4 to make the correlations more intuitive.

The time series diagram in Figure 5 suggests connecting the results of different methods with points of different shapes to more clearly observe the differences and consistencies among the three methods (direct method, clustering method 1, and clustering method 2). Additionally, Figure 5 lacks a clear legend to distinguish the different data series—adding one would significantly improve readability.

Reference

1. Cao C, Yuan L, Wang Y, Liu H, Cuello Garcia H, Huang H, et al. Analysis of the primary factors influencing donor derived cell-free DNA testing in kidney transplantation. Front Immunol. 2024;15: 1435578. doi:10.3389/fimmu.2024.1435578

2. Zhou Y, Yang G, Liu H, Chen Y, Li X, Ge J, et al. A Noninvasive and Donor-independent Method Simultaneously Monitors Rejection and Infection in Patients With Organ Transplant. Transplant Proc. 2019;51: 1699–1705. doi:10.1016/j.transproceed.2019.04.051

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Reviewer #1: Yes: Frederik Banch Clausen

Reviewer #2: No

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Dear Dr. Yamada,

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.

The authors have done significant improvement of this submission, however, they need to highlight the cost effectiveness of this method as compared to existing methods, including addressing the minor comments from the second reviewer.

Please submit your revised manuscript by Dec 26 2025 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.

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We look forward to receiving your revised manuscript.

Kind regards,

Elingarami Sauli, PhD

Academic Editor

PLOS ONE

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If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

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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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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

Reviewer #1: Yes

Reviewer #2: Partly

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

Reviewer #1: I find that the manuscript is ready for accept. The authors have provided a comprehensive and thorough response to the concerns and suggestions raised by the reviewers and satisfactorily amended the manuscript accordingly. I have no further comments.

Reviewer #2: 1. Clinical Correlation and Utility

I appreciate that the authors added a clinical case (S4 Fig) illustrating dd-cfDNA changes. However, in this figure, the orange line (w/o pre-data) lacks data points where dd-cfDNA levels exceed 10%, especially around the event biopsy time point. Since rejection is a dynamic process, missing data at these clinically relevant points limits interpretation. The authors are encouraged to supplement these data if available.

In addition, the figure currently lacks axis labels for both x- and y-axes. Each figure should be self-explanatory so that readers can understand its meaning even without referring to the caption.

Finally, while I understand that a direct comparison with existing dd-cfDNA assays was beyond the current scope, such a comparison would be highly valuable for future work, as it would strengthen the clinical relevance and translational potential of this new method.

2. Cost and Efficiency

I would like to update the authors’ understanding regarding existing methods: commercially available dd-cfDNA assays that do not require donor genotyping are already in widespread use.

In the Discussion, the authors briefly mention relative cost and efficiency advantages, but I could not find detailed information about cost aspects in the revised manuscript. Since cost and reliability are key determinants for clinical adoption, a short discussion on the economic feasibility or expected cost differences compared to existing commercial assays would be appreciated.

3. Population Specificity and Generalizability

Thank you for your clarification.

4. SNP Panel Design and Sequencing Parameters

Thank you for your clarification.

5. Low-Level Detection and Accuracy

While I understand the authors’ rationale, the potential measurement error in the 0–1% dd-cfDNA range remains clinically concerning. For example, in lung transplantation, a 1% threshold is often used to indicate possible rejection. In Table 1, when the actual mixing rate is 0.5%, the measured value is 1.0%, which could lead to significant clinical misinterpretation. This limitation should be clearly discussed, as small inaccuracies around this threshold can greatly influence clinical decision-making.

6–8. Use of Pre/Post-Transplant Difference Metric, Substitute for Pre-Transplant Samples, Sample Size and Statistical Power

Thank you for your responses.

9. Comparison with Existing Methods

Our earlier comment was intended to encourage comparison with existing commercial dd-cfDNA platforms to highlight the advantages and limitations of the new method. Although the authors indicated that direct comparison was difficult, I still suggest that, if feasible in future work, they test a subset of samples using a commercial platform to compare turnaround time and measurement concordance. This would significantly strengthen the paper’s translational impact.

10. Graphical Enhancements

Thank you for your response.

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Reviewer #1: Yes: Frederik Banch Clausen

Reviewer #2: No

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Dear Dr. Yamada,

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.

Please address reviewer 2's comments from the previous decision letter.

Please submit your revised manuscript by Jan 29 2026 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.

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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,

Elingarami Sauli, PhD

Academic Editor

PLOS One

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If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

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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A SNP-Based Capture and Clustering Workflow to Assess Donor-Derived Cell-Free DNA in Transplantation

PONE-D-25-42729R3

Dear Dr. Yamada,

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Academic Editor

PLOS One

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