PREreview of Functional Antibody-Dependent Enhancement as an Immune Assessment Platform: Development, Standardization, and Translational Interpretation in Flavivirus Research

Manuscript titled "Functional Antibody-Dependent Enhancement as an Immune Assessment Platform: Development, Standardization, and Translational Interpretation in Flavivirus Research," provides a comprehensive and timely synthesis of how Antibody-Dependent Enhancement (ADE) assays have evolved from specialized mechanistic tools into standardized, multi-site platforms for vaccine evaluation and population-level surveillance.

The manuscript is well-structured, shifting the focus from viewing ADE as a binary "risk" to a dynamic "functional state" that can be quantitatively mapped to inform clinical and regulatory decisions.

1. General Strengths

• Conceptual Clarity: The paper excellently articulates the shift from "single-readout" experiments to "integrated assessment platforms." The distinction between ADE as a functional state versus an intrinsic antibody property is a critical conceptual framework for the field.

• Timeliness: Given the ongoing challenges in developing safe and effective vaccines for Dengue and other flaviviruses, the focus on standardized immune assessment is highly relevant for both academic researchers and vaccine developers.

• High-Quality Visuals: Figures 1 through 4 are exceptional. They effectively summarize complex timelines, modular architectures, terminology, and longitudinal immune trajectories, making the concepts accessible and reproducible.

• Regulatory Relevance: Explicitly mentioning the WHO Expert Committee on Biological Standardization (ECBS) evaluations grounds the review in real-world application and policy.

2. Content-Specific Comments and Suggestions

Section 2: Conceptual Foundations

• Cell System Comparison: In section 2.4, the author discusses various assay architectures. While the trade-offs between engineered cell lines (e.g., BHK-FcγRIIA) and primary cells are mentioned, a more explicit "pros and cons" table or a deeper discussion on when to choose one over the other based on the research question (e.g., high-throughput screening vs. deep mechanistic inquiry) would be a valuable addition for laboratories looking to adopt these platforms.

• Viral Input Maturation: The mention of "maturation state (e.g., prM cleavage)" as a hidden confounder is excellent. Expanding slightly on how different cell lines used for virus production (e.g., C6/36 vs. Vero) affect this maturation and subsequently influence ADE readouts would further strengthen the standardization guidelines.

Section 3: Applications across Research and Translational Context

• Systems Immunology Examples: The review mentions the integration of ADE profiling with systems immunology and computational modeling (Fig. 4D). To provide even more depth, the author could briefly cite or describe 1-2 specific examples of how machine learning or predictive models have successfully utilized ADE platform data to stratify risk in clinical cohorts.

• "Disease X" Preparedness: The inclusion of pandemic preparedness is a strong point. It might be worth explicitly mentioning how these standardized platforms could be rapidly adapted for non-flavivirus emerging pathogens (as hinted in the abbreviations/references regarding SARS-CoV-2 and Ebola).

Section 4: Methods and Reporting Standards

• Inter-laboratory Transfer Challenges: While reproducibility challenges are mentioned, Section 4.2 could benefit from a short "Common Pitfalls" paragraph regarding the actual process of protocol transfer between sites (e.g., differences in CO2 incubator calibration, serum heat-inactivation protocols, or plate-reader sensitivities).

• Terminology Box (Figure 3): This is a standout feature. Standardizing terms like Emax and EAUC​ is vital for cross-study meta-analyses.

3. Minor Technical/Formatting Points

• Abbreviations: The list of abbreviations is comprehensive. Ensure that all abbreviations (like "SRIP" or "FFU") are defined at their first mention in the main text as well as in the list.

• Figure 4 Legend: The legend is very detailed; however, in Figure 4C, the transition from "transient enhancement phase" to "protective dominance" is a core takeaway. Explicitly linking this to the "stoichiometric coverage" mentioned in the text would help tie the visual and textual data together more tightly.

Overall Recommendation

This is a high-quality review that serves as both a "state-of-the-field" summary and a practical guide for standardization. It is highly recommended for publication as it addresses a significant gap in the harmonization of functional immunoassays. The forward-looking integration of ADE platforms with multi-omic data (Figure 2, Module G) sets a clear and ambitious direction for future flavivirus research.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.