Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Overall Impression

Thank you for giving me the opportunity to review this manuscript. The manuscript provides a timely and comprehensive systematic review and meta-analysis of fluid biomarkers associated with cognitive impairment (CoI) following traumatic brain injury (TBI). The authors successfully categorize these biomarkers into functional groups, neural injury/repair, Alzheimer’s disease (AD)-like pathology, and inflammation, while emphasizing their temporal dynamics from acute to chronic stages. This work addresses a significant gap in the literature by integrating both cerebrospinal fluid (CSF) and blood-based evidence. My overall recommendation is accepting with minor revisions.

Suggested Changes

• Global changes:
  • The title is clear, but undersells the work. In addition to the systemic review, the authors also conducted a meta-analysis, nor does it reflect the temporal dynamics. This should be reflected in the title.
    • Alternative title suggestion: “Temporal Dynamics of Fluid Biomarkers for Cognitive Impairment Following TBI: A Systematic Review and Meta-Analysis”
  • Abbreviations
    • Regarding the use of abbreviations, the authors introduce 'CoI' to represent cognitive impairment. I would strongly recommend revising this to a more standard abbreviation, such as 'CI' or simply writing the term out. In the context of peer-reviewed literature and journal metadata, 'COI' is the standard acronym for 'Conflict of Interest'. To prevent potential reader confusion and ensure the manuscript aligns with standard neuropsychological nomenclature, a more conventional choice (e.g., 'CI' or 'MCI' for mild cognitive impairment) would be preferable.
    • Ensure every abbreviation (e.g., UCH-L1, NSE, BDNF) is defined at its first mention in both the Abstract and the Main Text
  • Abstract
    • correct IL-1b (instead of using a similar but not correct symbol
  • Introduction
    • For the discussion of the epidemiological data, put both the relative risk and confidence interval in the same set of parenthesis à (RR = 1.63; 95% CI: 1.34–1.99)
    • Gap in knowledge statement:
      • “a systematic integration of cerebrospinal fluid (CSF) and blood- based biomarker evidence is lacking”
        • Include temporal evaluation/trajectory
          • Expand this to explicitly state that prior reviews often focused on single-time-point assessments rather than thetemporal evolution from acute to chronic stages
        • Methods:
          • The number of included studies is inconsistent.
            • The methods states that there were 29 studies from 30 articles included but the discussion states 33 studies are ultimately included, please reconcile these numbers.
          • Clarify the ‘Get Data’ software procedure. Was this used for graphical data too or only to outline specific outliers?
          • How did you account for the potential absence of small negative studies?
            • Add a section for publication bias assessment (i.e funnel plot or eggers test)
          • Results & Tables:
            • Table 1 – typo from moth to month
            • In the presentation of the meta-analysis, specifically cite the SMD (standard mean difference) for NFL (0.89) and GFAP (0.88) to match the supplemental figure
            • In table 3 (subgroup analysis), could you please distinguish between mTBI and sTBI outcomes? This would reinforce your statement that Nfl and GFAP are viable across severities.
          • Discussion:
            • The TBI-AD mechanism
              • You state that TBI may exacerbate Tau-related pathways in AD. This is your most significant finding, relay this back to your finding wherein CSF Tau is significantly elevated in TBI history cohorts.
              • Figure 2 labels…

Author Response

Comment 1: The title is clear, but undersells the work. In addition to the systemic review, the authors also conducted a meta-analysis, nor does it reflect the temporal dynamics. This should be reflected in the title.Alternative title suggestion: “Temporal Dynamics of Fluid Biomarkers for Cognitive Impairment Following TBI: A Systematic Review and Meta-Analysis”

Response 1:We are profoundly grateful for your insightful suggestions regarding the title. We fully agree that the original title did not adequately reflect the inclusion of both a systematic review and meta-analysis, nor did it sufficiently accentuate the temporal characteristics of the biomarkers—a core focus of our work. Indeed, our results systematically map the temporal alignment between biomarker levels and cognitive assessments, aiming to elucidate their predictive value at distinct post-injury intervals and to identify general longitudinal patterns. However, we must acknowledge that due to significant variations in detection assays, sample types, and sampling timeframes across the included studies, the high degree of heterogeneity in the longitudinal data precludes a formal pooled analysis to construct a rigorous dynamic trajectory curve. To maintain high standards of scientific precision, we prefer to focus on the association and predictive utility within specific time windows rather than making generalized claims about dynamic evolution. We will optimize the title to explicitly incorporate the meta-analysis component and better reflect the temporal dimension of our study(Page 1,Line2).

Comment 2:Abbreviations. Regarding the use of abbreviations, the authors introduce 'CoI' to represent cognitive impairment. I would strongly recommend revising this to a more standard abbreviation, such as 'CI' or simply writing the term out. In the context of peer-reviewed literature and journal metadata, 'COI' is the standard acronym for 'Conflict of Interest'. To prevent potential reader confusion and ensure the manuscript aligns with standard neuropsychological nomenclature, a more conventional choice (e.g., 'CI' or 'MCI' for mild cognitive impairment) would be preferable. Ensure every abbreviation (e.g., UCH-L1, NSE, BDNF) is defined at its first mention in both the Abstract and the Main Text

Response 2: We appreciate your professional advice regarding the terminology. As CoI is conventionally used to denote 'Conflict of Interest,' we agree that its use for 'cognitive impairment' could lead to unnecessary confusion. Accordingly, we have standardized the abbreviation to CI throughout the entire manuscript. Furthermore, we have conducted a comprehensive review of all abbreviations (including UCH-L1, NSE, and BDNF) to ensure that each is fully defined upon its first appearance in both the abstract and the main text, consistent with standard academic reporting guidelines.

Comment 3:Abstract,correct IL-1b (instead of using a similar but not correct symbol. Introduction，For the discussion of the epidemiological data, put both the relative risk and confidence interval in the same set of parenthesis à (RR = 1.63; 95% CI: 1.34–1.99)

Response 3: Thank you for your suggestion. This has been revised accordingly(Page4, Line97-99;Page 2,Line 37).

Comment 4：Gap in knowledge statement:“a systematic integration of cerebrospinal fluid (CSF) and blood- based biomarker evidence is lacking” in Introduction. Please include temporal evaluation/trajectory and expand this to explicitly state that prior reviews often focused on single-time-point assessments rather than the temporal evolution from acute to chronic stages.

Response 4: Thank you for your constructive comments. We concur that prior literature often lacks a systematic overview of the temporal progression of biomarkers following TBI. To address this, we have updated the Introduction to clearly define the research lacuna: the absence of a consolidated analysis of CSF and blood-based markers, as well as the neglect of their time-dependent trends in relation to cognitive impairment.Our review specifically addresses these deficiencies by adopting a multidimensional framework that categorizes findings by post-injury phases (acute, subacute, and chronic), injury severity, and biomarker origin. By systematically mapping the temporal patterns of key biomarkers against cognitive outcomes, we offer a more nuanced understanding of the disease progression. These updates are now reflected in the revised abstract and the corresponding chapters(Page 6, Line 124-135).

Comment 5：Methods:The number of included studies is inconsistent.The methods states that there were 29 studies from 30 articles included but the discussion states 33 studies are ultimately included, please reconcile these numbers. Clarify the ‘Get Data’ software procedure. Was this used for graphical data too or only to outline specific outliers?

Response 5:Thank you for noting the discrepancy in our study count. A thorough re-verification confirms that our review includes 30 publications derived from 29 independent studies (with two articles sharing the same primary trial). We have corrected all instances of inconsistent reporting to ensure a unified narrative(Page 2, Line 31; Page 6, Line 138; Page 16, Line 392; Page 26,Figure1).Furthermore, we have clarified the methodology for Get Data Graph Digitizer. The software served strictly as a data retrieval tool for digitizing graphical information into numerical formats (Mean/SD), with no role in outlier filtering. To ensure the objectivity of our meta-analysis, the extraction was conducted systematically across all eligible figures without selection bias. This process was performed independently and in duplicate by two investigators to guarantee the accuracy and reproducibility of the extracted datasets.

Comment 6 :How did you account for the potential absence of small negative studies?Add a section for publication bias assessment (i.e funnel plot or eggers test) in Methods?

Response 6:Thank you for highlighting this critical issue. We agree that publication bias remains a concern, as missing negative data may inflate the observed effect sizes.In the revised manuscript, we have added a publication bias assessment protocol to the Methods(Page 24,Line 562-566), utilizing funnel plots and Egger’s tests for primary outcomes. While a new subsection in the Results now presents these evaluations, we have clarified that funnel plot visualization was not feasible for most metrics due to the limited number of studies per outcome(Page 15, Line 354-355). To address this, we have supplemented the Discussion by acknowledging that the potential for publication bias exists, and our findings should be interpreted judiciously alongside this limitation (Page 21, Line 512-514).

Comment 7:

Results & Tables: Table 1 – typo from moth to month

In the presentation of the meta-analysis, specifically cite the SMD (standard mean difference) for NFL (0.89) and GFAP (0.88) to match the supplemental figure

In table 3 (subgroup analysis), could you please distinguish between mTBI and sTBI outcomes? This would reinforce your statement that Nfl and GFAP are viable across severities.

Response 7: Thank you for pointing out these details. The spelling error in Table 1 has been corrected from 'moth' to 'month.'(Page 30). Furthermore, the SMD values for NfL (0.89) and GFAP (0.88) have been integrated into the main text to align perfectly with the supplementary data (Page 8, Line 185; Page 10, Line 236). In response to your comment on Table 3, we have revised the subgroup analysis to provide a clear distinction between mTBI and sTBI outcomes. This stratified approach offers a more nuanced view of the biomarker associations across different injury severities, as summarized below:In mTBI, acute-phase plasma NfL, UCH-L1, and S100B, as well as CRP levels during the subacute phase, have been associated with long-term cognitive outcomes. In the chronic phase, a reduced CSF Aβ42 or Aβ40 levels is linked to CI, particularly in individuals aged ≥45 years in some cohorts, whereas findings for tau-related biomarkers remain inconsistent. In sTBI, acute-phase NSE, S100B, and BDNF have been associated with memory outcomes and recovery, while plasma NfL, GFAP, UCH-L1, NCAM, T-tau, and inflammatory markers have been associated with structural brain changes and cognitive decline, although considerable heterogeneity across studies has been observed. Notably, NfL, GFAP, and UCH-L1 demonstrate relatively consistent associations across studies with cognitive outcomes in both mTBI and sTBI cohorts, suggesting their potential utility as prognostic and predictive biomarkers for TBI-CI across different injury severities. In contrast, exosomal P-tau181, Aβ42, and several other biomarkers show promising but still preliminary evidence(Page 14 ,Line 332-344).

Comment 8: In Discussion(The TBI-AD mechanism),you state that TBI may exacerbate Tau-related pathways in AD. This is your most significant finding, relay this back to your finding wherein CSF Tau is significantly elevated in TBI history cohorts.

Figure 2 labels…

Response 8: Thank you for this insightful suggestion. In Section 4.2 of the revised Discussion, we have reinforced the link between our findings and the underlying pathology. Specifically, we noted that the significantly higher CSF tau levels in AD patients with a history of TBI lend support to the theory that TBI acts as a catalyst for tau-mediated neurodegeneration. 'The significantly elevated CSF tau in AD patients with past TBI underscores the biological plausibility of TBI as a driver of accelerated tau pathology and subsequent AD development.' (Page 17, Line 451-455).Furthermore, Figure 2 and its legend have been revised to clearly define the depicted post-injury temporal patterns of biomarkers relevant to TBI-CI(Page 26).

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript addresses a clinically relevant and timely topic: the potential role of fluid biomarkers in predicting or characterizing cognitive impairment after traumatic brain injury (TBI). The topic is important, and the attempt to organize biomarkers by pathophysiological domain and temporal phase is potentially valuable. The manuscript also includes a PRISMA-based approach and summarizes a broad literature base. However, in its current form, the paper has substantial methodological, interpretive, and presentation-related weaknesses that limit its reliability and suitability for publication. Several key inconsistencies and overstatements should be resolved before the manuscript can be considered further. 

Major Comments

1. The manuscript reports different totals in different sections. The abstract states that 30 clinical studies were included, the Results section states that 29 studies published in 30 articles were included, and the Discussion later states that 33 studies were ultimately included. These discrepancies are serious because they create uncertainty about the actual evidence base used for synthesis and meta-analysis. The authors must carefully reconcile the PRISMA flowchart, abstract, Results, tables, supplementary figures, and Discussion so that the reported number of included studies and articles is fully consistent throughout. 
2. 2. Across the Results, subgroup analysis, and Tables 2–3, observational associations are frequently described as if they establish predictive performance or clinical applicability. Phrases such as “could predict cognitive dysfunction,” “predictive value,” and “dependable biological marker” are often too strong for the cited evidence, especially when many included studies are cross-sectional or have modest sample sizes and when more than half of the included studies were rated moderate-to-low quality. The wording should be made much more cautious and should distinguish clearly between association, discrimination, prognosis, and mechanistic inference. 
3. 3. The manuscript begins with TBI-related cognitive impairment, but later blends this with Alzheimer’s disease diagnosis, AD-like pathology, and biomarker behavior in cohorts with AD plus remote TBI history. These are related but not equivalent constructs. The inclusion of studies in AD populations may be informative, but it should not be used interchangeably with evidence on TBI-related cognitive impairment.
4. 4. The figure on longitudinal biomarker trajectories presents smooth temporal curves for multiple biomarkers, implying a unified kinetic model. However, the manuscript does not explain how these curves were generated, whether they were quantitatively derived from pooled longitudinal data, or whether they are purely schematic. Because the included studies differ substantially in sampling schedules, severity groups, and assay methods, this figure may create a false impression of precision and comparability. If it is conceptual, it should be explicitly labeled as a schematic summary and described as such in the legend and Methods. If it is data-derived, the derivation must be explained in detail. 

Minor Comments

1. Although the overall meaning is understandable, the paper contains many grammatical, stylistic, and typographical problems. Examples include:

• “Characteristic of the included studies” instead of “Characteristics”
• “the reminder focused on TBI-CoI” instead of “the remainder”
• “published in different journal” instead of “published in different journals”
• “outcomes was evaluated” instead of “outcomes were evaluated”
• “could have a predicative value” instead of “predictive value”
• “blood predict cognitive impairment” instead of “blood levels predicted” or similar
• a duplicated period in “strategies..”
• inconsistent spacing and punctuation throughout. 

2. The manuscript alternates among “CoI,” “TBI-CoI,” “cognitive dysfunction,” “cognitive decline,” and “post-traumatic cognitive deficits.” These may overlap, but they are not necessarily interchangeable. One preferred term should be selected and used consistently, with others defined when needed. 
3. There are multiple formatting problems, including split words, inconsistent abbreviations, odd spacing, and apparent typographic errors such as “Sioma” instead of “Simoa,” “moth” instead of “month,” and “Slavoaca D 20200.” These issues reduce readability and create doubts about editorial accuracy. 
4. The claim that this is the “first” review of its kind should be softened unless rigorously substantiated. The Introduction and Abstract make strong novelty claims. Given the rapidly evolving literature on TBI biomarkers and cognition, this wording should be more cautious unless the authors clearly define what makes this review uniquely first. 
5. The authors should more clearly distinguish serum, plasma, CSF, and exosomal biomarkers in the interpretation.These are not interchangeable biological compartments, and the manuscript sometimes discusses them together in ways that blur biological and analytical differences. 

Author Response

Comment 1:The manuscript reports different totals in different sections. The abstract states that 30 clinical studies were included, the Results section states that 29 studies published in 30 articles were included, and the Discussion later states that 33 studies were ultimately included. These discrepancies are serious because they create uncertainty about the actual evidence base used for synthesis and meta-analysis. The authors must carefully reconcile the PRISMA flowchart, abstract, Results, tables, supplementary figures, and Discussion so that the reported number of included studies and articles is fully consistent throughout.

Response 1: Thank you for your pointing out this critical inconsistency in the reported study numbers.. After carefully double-checking our literature screening data, In total, 30 eligible articles were included, but two of them were published from the same clinical trial, For this reason, the actual number of independent studies is 29.We have now revised and standardized all relevant content throughout the paper. The abstract, Results, Discussion, PRISMA flow diagram, tables,and supplementary materials, have all been checked and updated uniformly to clearly state 29 independent studies from 30 articles. We apologize for this confusing discrepancy in our original writing(Page 2,Line 31; Page 6,Line 138; Page 16,Line 392; Page 26,Figure1).

 

Comment 2: Across the Results, subgroup analysis, and Tables 2–3, observational associations are frequently described as if they establish predictive performance or clinical applicability. Phrases such as “could predict cognitive dysfunction,” “predictive value,” and “dependable biological marker” are often too strong for the cited evidence, especially when many included studies are cross-sectional or have modest sample sizes and when more than half of the included studies were rated moderate-to-low quality. The wording should be made much more cautious and should distinguish clearly between association, discrimination, prognosis, and mechanistic inference.

Response 2: Thank you for your valuable comments. We fully agree with your concern that the original wording in the Results section, subgroup analyses, and Tables 2–3 may have risked overinterpreting observational associations as predictive performance or clinical applicability. In response, we have undertaken a comprehensive revision of the manuscript. First, in the Results section (including the detailed descriptions in Tables 2 and 3), we have clearly distinguished between “statistical associations,” “discriminative ability,” and “prognostic value,” and have reserved predictive terminology only for studies employing validated predictive modeling approaches(Page 8,Line 184-190, Line 193-194;Page 9,Line 214-218, Line 222;Page 10,Line 237, Line 244-247;Page 11,Line 259-262;Page12 ,Line 286-288; Page 13,Line 320-322; Page 14,Line 324-325; Page 14, Line 332-343; Page 31 and 32, Table 2 and Table 3).

Second, we have added a specific statement in Section 2.3.6 (Page 15, Lines 351–353) to emphasize that the current evidence is largely derived from cross-sectional or small-sample studies, and that most biomarkers demonstrate statistical associations with cognitive outcomes rather than validated predictive performance. Accordingly, their clinical applicability should be interpreted with caution. Additionally, we have further elaborated on the limitations related to study design in the Discussion section (Page 21, Lines 496–500), explicitly avoiding overinterpretation of causal relationships or clinical utility.

 

Comment 3: The manuscript begins with TBI-related cognitive impairment, but later blends this with Alzheimer’s disease diagnosis, AD-like pathology, and biomarker behavior in cohorts with AD plus remote TBI history. These are related but not equivalent constructs. The inclusion of studies in AD populations may be informative, but it should not be used interchangeably with evidence on TBI-related cognitive impairment.

Response 3:Thank you for highlighting this important conceptual issue. We fully acknowledge that the original manuscript did not clearly distinguish between TBI-related cognitive impairment (TBI-CI) and AD, which may have led to conceptual overlap. Although TBI-CI and AD share certain pathological features, they represent distinct clinical and research entities and should not be considered interchangeable. In this study, we included studies enrolling participants with a history of TBI and CI, encompassing a spectrum of conditions such as MCI, dementia, and clinically diagnosed AD. However, we recognize that some of the included studies did not provide detailed classification of cognitive impairment subtypes. In response, we have systematically revised the Results and Discussion sections to clearly differentiate between populations with primary TBI-CI and those with AD accompanied by a prior TBI history. Existing evidence suggests that TBI is considered a potential risk factor for sporadic AD. Therefore, including AD cohorts and examining the influence of prior TBI on biomarker profiles may help explore whether TBI may contribute to or accelerate AD-related pathological processes. We have also added explicit clarification in the Discussion that cognitive impairment following TBI is highly heterogeneous(Page 19,Line 468-471). The findings related to AD-associated biomarkers in this study are applicable specifically to AD-spectrum populations with a history of TBI and may not be directly generalizable to all forms of TBI-CI.In addition, we have revised and streamlined statements throughout the manuscript that could potentially lead to misinterpretation regarding TBI-associated AD, ensuring a clearer distinction between these two conditions and improving overall conceptual clarity(Page 19,Line 448-461).

 

Comment 4: The figure on longitudinal biomarker trajectories presents smooth temporal curves for multiple biomarkers, implying a unified kinetic model. However, the manuscript does not explain how these curves were generated, whether they were quantitatively derived from pooled longitudinal data, or whether they are purely schematic. Because the included studies differ substantially in sampling schedules, severity groups, and assay methods, this figure may create a false impression of precision and comparability. If it is conceptual, it should be explicitly labeled as a schematic summary and described as such in the legend and Methods. If it is data-derived, the derivation must be explained in detail.

Response 4:Among the nine studies included in this analysis, longitudinal changes in several biomarkers, including NfL, tau, UCH-L1, GFAP, NSE, and S100B, were reported following TBI. This figure is not a simple schematic illustration, nor does it attempt to quantitatively combine heterogeneous data. The time-course trajectories presented were derived from two studies with complete longitudinal sampling data [1,2].Specifically, values at each time point were extracted using GetData, followed by log-normalization (LN). The processed data were then fitted using R software to generate smooth temporal trajectories, which approximate the dynamic patterns of biomarker changes over time.The remaining included studies exhibited substantial heterogeneity in sampling time points, disease stratification, assay methods, and measurement units, thereby precluding meaningful quantitative synthesis. These studies were therefore summarized qualitatively, focusing on overall trends.Overall, most biomarkers appeared to peak within 24 hours after TBI; however, their longitudinal dynamic profiles differed considerably (Page 15–16, Lines 359–377). We have added a clarification in the figure legend(Page 26,Figure 2) stating that the smooth curves represent fitted data derived from two studies with complete longitudinal sampling, processed using log-normalization and generated in R. This clarification is intended to avoid misinterpretation regarding the comparability and integration of heterogeneous data.

[1] Graham N, Zimmerman KA, Moro F, et al. Axonal marker neurofilament light predicts long-term outcomes and progressive neurodegeneration after traumatic brain injury. Sci Transl Med. 2021. 13(613): eabg9922.doi:10.1126/scitranslmed.abg9922

[2] Shahim P, Politis A, van der Merwe A, et al. Time course and diagnostic utility of NfL, tau, GFAP, and UCH-L1 in subacute and chronic TBI. Neurology. 2020. 95(6): e623-e636.doi:10.1212/WNL.0000000000009985

 

Comment 5: Although the overall meaning is understandable, the paper contains many grammatical, stylistic, and typographical problems. There are multiple formatting problems, including split words, inconsistent abbreviations, odd spacing, and apparent typographic errors such as “Sioma” instead of “Simoa,” “moth” instead of “month,” and “Slavoaca D 20200.” These issues reduce readability and create doubts about editorial accuracy.Such as,Characteristic of the included studies” instead of “Characteristics”;“the reminder focused on TBI-CoI” instead of “the remainder”;“published in different journal” instead of “published in different journals”;“outcomes was evaluated” instead of “outcomes were evaluated”;“could have a predicative value” instead of “predictive value”;“blood predict cognitive impairment” instead of “blood levels predicted” or similar;a duplicated period in “strategies..”;inconsistent spacing and punctuation throughout.

Response 5: Thank you for your valuable feedback. We have thoroughly checked the entire text word by word and corrected all grammar, spelling, punctuation, spacing, and layout errors (such as "Sioma" → "Simoa", "moth" → "month", "reminder" → "remainder", subject-verb agreement, singular/plural, repeated full stops, etc.). At the same time, we have standardized the abbreviation format throughout the text. For example, it is correctly marked as "single-molecule array (Simoa)" for the first occurrence and uniformly uses "Simoa" thereafter. All abnormal reference citation formats (such as "Slavoaca D 20200") have been corrected according to the journal requirements. Additionally, the manuscript has been professionally edited by an English editor to ensure clarity and formatting compliance. All modifications have been implemented in the revised version. (Page 6, Line 140 and 143; Page 7,Line 148,Line 162 and 167; Page 28, Table 1)

 

Comment 6: The manuscript alternates among “CoI,” “TBI-CoI,” “cognitive dysfunction,” “cognitive decline,” and “post-traumatic cognitive deficits.” These may overlap, but they are not necessarily interchangeable. One preferred term should be selected and used consistently, with others defined when needed.

Response 6:We appreciate your comment on the use of inconsistent terminology. Although terms such as CoI, TBI-CoI, cognitive dysfunction, cognitive decline, and post-traumatic cognitive deficits overlap, they differ in conceptual scope and should not be used interchangeably.As this study focuses on the overarching phenotype of post-traumatic cognitive impairment, we have standardized the terminology by adopting “cognitive impairment (CI)” as the primary descriptor throughout the revised manuscript. This approach enhances conceptual clarity and reduces potential ambiguity for readers.Where specific dimensions are discussed,such as functional impairment, progressive decline, or domain-specific deficits, we provide explicit qualifiers to ensure both terminological consistency and conceptual precision

[1]Petersen RC, Caracciolo B, Brayne C, Gauthier S, Jelic V, Fratiglioni L. Mild cognitive impairment: a concept in evolution. J Intern Med. 2014;275(3):214-228. doi:10.1111/joim.12190

 

Comment 7:The claim that this is the “first” review of its kind should be softened unless rigorously substantiated. The Introduction and Abstract make strong novelty claims. Given the rapidly evolving literature on TBI biomarkers and cognition, this wording should be more cautious unless the authors clearly define what makes this review uniquely first.

Response 7: Thank you for your valuable comment. We fully agree with your concern. In the rapidly evolving field of TBI biomarkers and cognitive function, the use of absolute expressions such as “first” or “the first” may be overly definitive and insufficiently cautious. Accordingly, in the revised manuscript, we have removed all such expressions from the Abstract, Introduction, Discussion, and Conclusion, and replaced them with more balanced and objective statements. Specifically, we now state: “To our knowledge, there is currently a lack of systematic reviews specifically examining the relationship between TBI biomarkers and cognitive function.”(Page 2,Line 43;Page 6, Line 129-135；Page 24,Section 5. Line 568).

 

Comment 8: The authors should more clearly distinguish serum, plasma, CSF, and exosomal biomarkers in the interpretation.These are not interchangeable biological compartments, and the manuscript sometimes discusses them together in ways that blur biological and analytical differences.

Response 8: Thank you for highlighting this important issue. We agree that serum, plasma, cerebrospinal fluid, and exosome-derived biomarkers represent distinct biological compartments, with different biological significance and analytical characteristics, and should not be interpreted interchangeably. In the revised manuscript, we have systematically distinguished biomarkers according to their biological sample sources in both the main text(Page 8, Line 184,188,193;Page 9,Line 205,213 and 217;Page 10,Line 228,235,244;Page 13,Line 305, 315 and 319) and tables. Specifically, we now explicitly indicate the sample type (e.g., serum, plasma, cerebrospinal fluid, or exosomes) in all relevant descriptions and no longer aggregate data from different sources in a generalized manner. In addition, we have included a dedicated explanation in the Results section (Page 14-15, Line 345-353) to clarify the biological differences across sample types. Tables 2 and 3 have also been revised and optimized to better present the distinct characteristics of biomarkers derived from different sources, thereby strengthening the biological interpretability and analytical rigor of our findings.

Reviewer 3 Report

Comments and Suggestions for Authors

This review of biomarker analysis of traumatic brain injury addresses a fairly relevant topic and will undoubtedly be of interest to readers. It is well written, but requires a number of clarifications:

1. The review clearly lacks a deeper molecular biological interpretation. The authors group markers into fairly broad blocks, but barely address their cellular origin, biogenesis, pathways into the bloodstream, their relationship with BBB damage, kinetics, and analytical specificity. The importance of this issue stems from the fact that the same increase in concentration can indicate different processes, such as acute axonal injury, a secondary glial reaction, barrier disruption, or simply systemic inflammatory noise. This aspect requires more thorough examination.

2. The insufficient analytical and pre-analytical critique of the measurement methods is also questionable. Although the authors reviewed a fairly broad range of tests, it is important to discuss how comparable the results are between the platforms mentioned, the impact of tube type, delay before centrifugation, hemolysis, multiple freeze-thaw cycles, normalization for exosome fractions, and differences between serum and plasma.

3. The Discussion clearly seeks to demonstrate a compelling translational model important for the practical application of the group of markers discussed. Which biomarker is better for screening? Which is better for prognosis, which for monitoring, and which for differential diagnosis?

Author Response

Comment 1: The review clearly lacks a deeper molecular biological interpretation. The authors group markers into fairly broad blocks, but barely address their cellular origin, biogenesis, pathways into the bloodstream, their relationship with BBB damage, kinetics, and analytical specificity. The importance of this issue stems from the fact that the same increase in concentration can indicate different processes, such as acute axonal injury, a secondary glial reaction, barrier disruption, or simply systemic inflammatory noise. This aspect requires more thorough examination.

Response 1:We appreciate your constructive feedback. We acknowledge that our initial interpretation of biomarker mechanisms was overly generalized. The revised manuscript now offers a much more granular analysis of cellular provenance, secretory pathways, and their relationship with BBB damage and kinetic profiles.Consistent with your suggestion that similar trends may mask divergent pathologies, we have implemented the following improvements:

Results now specifies the cellular origin and metabolic background of each marker and features explicit cellular localization data(Page 8,Line 177-181,Line 195-199; Page 9,Line 203,Line 207-209, Line 221; Page10,Line 227-228, Line 232-234,Line 241; Page 11,Line 254-255,Line 260,Line 264-267;Page 12,Line 294-296). The updated temporal trajectory diagrams highlight the mechanistic differences between markers; notably, how NfL’s delayed surge signals axonal loss while GFAP’s late-phase increase characterizes reactive gliosis. This ensures that the diverse pathophysiological drivers behind biomarker fluctuations are accurately differentiated (Page 16,Line 378-389).

Comment 2: The insufficient analytical and pre-analytical critique of the measurement methods is also questionable. Although the authors reviewed a fairly broad range of tests, it is important to discuss how comparable the results are between the platforms mentioned, the impact of tube type, delay before centrifugation, hemolysis, multiple freeze-thaw cycles, normalization for exosome fractions, and differences between serum and plasma.

Response 2: Thank you for your insightful feedback. We acknowledge that addressing measurement methodologies and pre-analytical influences is crucial for this research. As suggested, we have updated the Limitations(Page 21,Line 505-512) to systematically address potential impacts on the stability of our detection results and conclusions. Specifically, we have discussed the comparability of platforms, collection tube types, pre-centrifugation intervals, hemolysis, freeze-thaw stability, exosome normalization, and the disparities between serum and plasma. This comprehensive revision ensures a more robust evaluation of our study's findings

Comment 3: The Discussion clearly seeks to demonstrate a compelling translational model important for the practical application of the group of markers discussed. Which biomarker is better for screening? Which is better for prognosis, which for monitoring, and which for differential diagnosis?

Response 3: Thank you for your insightful feedback. In the revised Discussion, we have incorporated a clinical application framework to categorize the utility of biomarkers for screening, monitoring, and diagnosis.Specifically, we noted that GFAP and UCH-L1 offer more robust evidence for early screening within 72 hours, while S100B serves only as an adjunct marker due to its lower specificity. For long-term outcomes, plasma NfL (reflecting ongoing axonal loss) and chronic-phase GFAP are proposed as a combined panel to predict cognitive decline and brain atrophy. Furthermore, we have candidly discussed the current lack of evidence for using these markers to distinguish between different cognitive impairment subtypes, identifying this as a limitation(Page16-17,Line393-401).

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors answered all questions and made appropriate changes to the manuscript. I believe the manuscript can be accepted for publication.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors made adjustments based on the comments and the article can be published.