Dear Dr. David,

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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?

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

Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: This manuscript presents a conceptual essay proposing the Genomic Equity Accessibility Formula (GEAF), a mathematical framework for evaluating and improving the affordability and equitable distribution of genomic and regenerative therapies. The paper addresses important topics — CRISPR gene editing ethics, synthetic embryo models, stem cell research regulation, and health equity in genomic medicine — and proposes policy frameworks including Ethical Enhancement Councils (EECs), a Tiered Moral Framework (TMF), and International Stem Cell Accords (ISCAs). The ambition to bridge bioethics with quantitative modeling is commendable. However, the manuscript suffers from significant methodological and presentational shortcomings that substantially limit its scholarly contribution. The GEAF formula, while mathematically simple, lacks rigorous derivation, validation against empirical data, and sensitivity analysis. The manuscript reads more as a policy opinion piece than a research article, and the connection between the qualitative ethical discussion (which constitutes the majority of the text) and the quantitative GEAF model is insufficiently developed.

The Introduction broadly surveys CRISPR, synthetic embryos, stem cell regulation, and health equity challenges. The authors should consider acknowledging the intersection between genomics policy and the food-medicine homology paradigm, where natural products are increasingly studied using genomic and multi-omics approaches. The review by Zhang et al. (DOI: 10.26599/FMH.2025.9420059) on Panax ginseng for medicinal and edible value demonstrates how genomic tools are being applied to characterize complex botanical therapeutics — an application domain that raises parallel questions about equitable access to traditionally-used medicinal resources. The review by Li et al. (DOI: 10.26599/FMH.2025.9420120) on food and medicine homology in disease treatment provides a conceptual framework relevant to how regulatory frameworks and equitable access policies in one domain (traditional medicine/food-medicine homology) may inform approaches in another (personalized genomic medicine).

1. The most significant concern is the GEAF formula itself, which constitutes the claimed methodological contribution. The formula GEAF = ((A × E) − (C × I)) / (P + R) × 100 lacks rigorous theoretical justification. Several fundamental issues must be addressed: (a) The linear additive/multiplicative structure is arbitrary — why multiply A×E rather than using a weighted sum? Why subtract C×I rather than dividing by it? The authors must provide a principled derivation, potentially grounded in multi-attribute utility theory, health economics frameworks, or established equity metrics; (b) Dimensional analysis reveals internal inconsistencies — A (percentage, 0-100) multiplied by E (0-1) yields units incompatible with C (cost in thousands of USD) multiplied by I (Gini-like coefficient, 0-1). The subtraction of incommensurate quantities is mathematically improper; (c) The normalization approach is unclear — C is described as "normalized USD value" but the method of normalization is not specified; (d) The formula produces negative values (e.g., GEAF = -105.63) which are interpreted as "inequities," but the meaningful range and interpretation thresholds are not established — at what GEAF value is equity considered "acceptable"?

2. The study is presented as a "Research Article" with defined Methods, Results, and Discussion sections. However, it does not meet the methodological standards of empirical research. The "Methods" describe a "conceptual and mathematical modeling approach" using "manual calculations and scenario-based simulations without specialized software." No empirical data were collected, no statistical analyses were performed, and the seven "scenarios" consist of manually chosen input values with no systematic approach to parameter space exploration. The authors should either: (a) substantially strengthen the GEAF framework with formal derivation, empirical calibration against real-world health equity datasets (e.g., global gene therapy access statistics, WHO health equity indicators, country-level pharmaceutical expenditure data), systematic sensitivity analysis (e.g., Monte Carlo simulation), and validation against known equity outcomes; or (b) reclassify the manuscript as a Perspective/Opinion piece and reframe the GEAF as a conceptual heuristic rather than a validated quantitative model.

3. The ethical discussion sections (covering CRISPR, synthetic embryos, stem cell regulation) are written in an essayistic style without systematic literature review methodology. Major concerns include: (a) Key ethical frameworks are mentioned superficially — deontology, consequentialism, and procreative beneficence are each discussed in only 1-2 sentences without substantive analysis of how these frameworks reach divergent conclusions on specific applications; (b) The proposed policy innovations (EECs, TMF, ISCAs) are described at a high level of abstraction without operational detail. For example, the Tiered Moral Framework proposes that "pre-implantation models can be used freely" while "post-gastrulation models need justification" — but what constitutes "justification"? Who adjudicates? What criteria apply?; (c) The ISSCR 2025 guidelines are referenced multiple times but the specific provisions relevant to the authors' proposals are not analyzed in detail; (d) Many claims lack supporting citations.

4. The GEAF scenario analysis (Section Results) relies entirely on "hypothetical data based on real-world estimates," yet the sources and derivation of these parameter values are not documented. For example, in the "Baseline Scenario": A=20 — what is the empirical basis for this value? Is it derived from WHO data on gene therapy coverage in LMICs?; E=0.6 — how is this quantified from real-world regulatory data?; I=0.7 — how is this "Gini-like coefficient" computed from actual health access disparities? Without transparent parameter derivation, the scenarios are essentially numerical illustrations of the formula's algebraic properties rather than meaningful policy analyses. Each parameter must be anchored to citable empirical data or a documented estimation protocol.

5. The manuscript claims that "targeted actions...could lower therapy costs by up to 70% for low-income groups" (Abstract). This claim appears in the Abstract and Discussion as a key finding, but the Methods do not describe how this 70% figure was derived. The sensitivity analysis consists only of adjusting cost (C) by ±20% in the baseline scenario, which is insufficient to support the 70% cost reduction claim. Either: (a) provide a detailed economic model demonstrating the cost reduction mechanisms with quantitative estimates grounded in health economics literature; or (b) remove unsupported quantitative claims and present cost reduction as a conceptual aspiration.

6. The manuscript is presented as having a single author with affiliations listed across eight institutions spanning the US, UK, and Nigeria. This unusual affiliation pattern requires clarification: (a) Which institution(s) provided the primary intellectual environment for this work? (b) What is the nature of the author's relationship with each listed entity? (c) Several affiliations appear unrelated to the manuscript's content. The journal's authorship and affiliation policies should be reviewed to ensure compliance.

7. The manuscript would benefit from a structured comparison with existing health equity frameworks and quantitative models. The authors mention cost-effectiveness models (ICERs) and multi-attribute utility theory in passing but do not systematically compare GEAF against: (a) the WHO health equity assessment framework; (b) extended cost-effectiveness analysis (ECEA) methods used in global health; (c) the fair innings approach and other distributive justice frameworks for healthcare resource allocation; and (d) existing equity-weighted QALY/DALY models.

Minor points:

The title "Revolutionizing the Genome" is hyperbolic for a conceptual modeling paper and does not accurately describe the content.

The Abstract contains grammatical errors and imprecise language (e.g., "fostering a kinder and more inclusive future"). Scientific manuscripts should maintain professional, objective language.

A "LLM NOTE" stating "No large language model use in preparation of this research paper" appears in the manuscript front matter. If required by the journal, the format should comply with journal policy. If not required, it should be removed.

The manuscript contains numerous typographical, formatting, and grammatical errors throughout that require thorough proofreading.

The reference formatting is inconsistent. Some citations use numbered references while others use author-date format.

The manuscript organization is unconventional for a research article: the Methods section is embedded within the Discussion narrative rather than appearing as a standalone section before Results.

The seven GEAF scenarios in Table 1 are presented without a systematic rationale for the parameter choices.

The manuscript states "No datasets were generated or analysed during the current study" which is appropriate for a conceptual paper but should be clearly reflected in the Methods section.

Consider adding a limitations section that frankly acknowledges: the conceptual nature of GEAF, the lack of empirical validation, and the need for prospective testing against real-world policy outcomes.

Reviewer #2: Revolutionizing the Genome: Ethical Innovations, Equitable Policies, and a

Mathematical Framework for Affordable Regenerative Medicine

1. The research questions and main hypotheses are not clear enough. Currently, various topics such as non-treatment gene editing, synthetic embryo models, stem cell regulation, global health equity, and payment policies are being discussed simultaneously, which is too broad and lacks a testable central issue. It is suggested to clearly define the main research questions, secondary questions, research subjects, analysis units, and testable hypotheses in the introduction section, and to delete the general ethical descriptions that are not directly related to GEAF.

2. The 7 figures in the text only provide basic conceptual displays, without original quantitative analysis charts; there is a lack of multi-scenario comparison line graphs of GEAF, tornado charts of sensitivity analysis, and bar charts of fair benefits from different policy interventions. The visual support is seriously insufficient. It is suggested to add 4 types of original quantitative charts: ① Comparison charts of GEAF scores for 7 scenarios; ② Dual-factor tornado charts of sensitivity analysis of cost C and inequality factor I; ③ Prediction charts of global accessible population changes before and after EGI intervention; ④ Comparison charts of GEAF and traditional ICER evaluation results, which should be placed in the main text or supplementary materials.

3. The 7 figures in the text only provide basic conceptual displays, without original quantitative analysis charts; there is a lack of multi-scenario comparison line graphs of GEAF, tornado charts of sensitivity analysis, and bar charts of fair benefits from different policy interventions. The visual support is seriously insufficient. It is suggested to add 4 types of original quantitative charts: ① Comparison charts of GEAF scores for 7 scenarios; ② Dual-factor tornado charts of sensitivity analysis of cost C and inequality factor I; ③ Prediction charts of global accessible population changes before and after EGI intervention; ④ Comparison charts of GEAF and traditional ICER evaluation results, which should be placed in the main text or supplementary materials.

4. The ethical statement is too general. Although the study does not involve human or animal subjects, it involves issues of human genome equity, vulnerable groups, and data governance. It is not sufficient to simply use "N/A" to replace the ethical position explanation. It is suggested to clearly state in the methods or discussion section that this study does not contain individual-level data, and to explain the ethical principles and potential risks followed when involving genomic data sharing and policy recommendations.

5. The first appearance of some professional term abbreviations in the full text is not marked with the full name, such as DCEA, HTA, SCBEM; the long sentences are excessively piled up, and the paragraph logic jumps abruptly; some policies and mathematical formulas are expressed in colloquial language, which does not conform to the academic writing norms of PLOS One. It is suggested to uniformly check all abbreviations in the full text, mark the full English names for the first appearance; split extremely long paragraphs, and rationalize the internal argument logic of the paragraphs; revise the formulas and policy explanations to use more formal language, eliminate redundant background scientific explanations, and focus on the original research analysis.

6. The inequality of medical accessibility only lists the bar charts of prices for high-income/LMIC regions, lacking real epidemiological data support for specific diseases and regions, such as the gap in diagnosis and treatment of sickle cell anemia in Africa, and the coverage rate of rare disease gene therapies in Asia without specific population statistics. It is suggested to supplement large continent and disease-specific statistical tables of genomic diagnosis accessibility; cite the 2024–2025 WHO African genomic report and the real data from the Nigerian sickle cell anemia survey to quantify the scale of unmet medical needs.

7. It is suggested to add references: Wang, Y., Huang, B., Wei, X., Guan, Y., Li, L.*, Zheng, Y., Sun, W. Gut Microbiota Metabolic Reprogramming Drives the Development of Metabolic Diseases in the Host. Gut Microbes, 2026, 18 (1), 2644681. This document is an authoritative review in the field of intestinal microbiota in 2026, systematically explaining the complete molecular pathway by which the metabolic reprogramming of the intestinal microbiota induces host metabolic diseases. It is highly consistent with the research topic of this article, providing a cutting-edge literature support for the discussion of mechanisms, and completing the core research progress in the field this year, enhancing the completeness of the discussion.

8. Suggested supplementary citation: Yimao Wu, Zichang Chen, Yinting Hu, Gokhan Zengin, Qian Zhang*, Meng-Yao Li*, Wenlong Sun*. SUMOylation Regulates Tumorigenesis and Progression: Molecular Mechanisms and Therapeutic Applications, Interdisciplinary Medicine, 2026;e70120. This document is a latest interdisciplinary review in 2026, systematically summarizing the complete molecular pathway of SUMOylation modification regulating tumor occurrence and progression and its therapeutic potential. It is highly compatible with the research topic of this article, providing a cutting-edge literature support for the discussion of mechanisms, completing the core research progress in the field this year, and enhancing the timeliness and completeness of the discussion.

9. Suggested supplementary citation: Potential effects of functional foods and dietary supplements on metabolic-associated fatty liver disease and the underlying mechanisms: a narrative review with a focus on the modulation of the gut microbiota. This review focuses on the complete action pathway of functional foods and dietary supplements in modulating metabolic-associated fatty liver disease (MAFLD) and systematically summarizes the lipid metabolism and inflammatory regulation mechanisms mediated by the gut-liver axis, which is highly compatible with the core direction of this research. It can supplement the latest consensus in the field, improve the literature support for the mediation of dietary intervention through the intestinal microbiota in improving fatty liver, and enhance the completeness and timeliness of the discussion.

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what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #2: No

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The Genomic Equity Accessibility Framework (GEAF): A Dimensionally Consistent Framework for Modeling Affordability and Equity in Genomic and Regenerative Therapies.

PONE-D-26-32218R1

Dear Dr. David,

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,

Kangkang Ji, Ph.D., M.D.

Academic Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

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

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

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

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

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

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

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

Reviewer #1: Yes

Reviewer #2: (No Response)

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Reviewer #1: After careful review of this manuscript, I have gone through the full text, I recommend that this manuscript be accepted.

Reviewer #2: (No Response)

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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

Reviewer #2: No

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