Review Reports - A Novel Competing Endogenous RNA Linked to Dysregulated Neuroinflammation in Alzheimer’s Disease

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Major Comments

The work is interesting and relevant; however, the authors should clarify whether the study primarily focuses on ceRNA regulation, neuroinflammation, or cell-type-specific mechanisms in AD, as the current scope appears broad. Further, there are several points that need to be addressed before publication.
The introduction provides a good background; however, the authors should more clearly justify why LIMASI was selected as the primary ceRNA of interest and how it advances current understanding beyond existing lncRNA studies in AD.
Elaborating and relating early biomarker for AD would be interesting to strengthen the introduction eg miRNA and others. https://pubmed.ncbi.nlm.nih.gov/37833762/ https://pubmed.ncbi.nlm.nih.gov/39046584/
In Methods. Human Brain Samples, more details are needed regarding sample selection, demographic variability, and clinical characterization of NC and AD brain tissues (e.g., age range, sex distribution, post-mortem interval), as these factors can influence neuroinflammatory readouts.
Animal section, please elaborate how animal being dissected and how tissue was collected. I would be helpful for the reader to follow.
The authors should carefully verify whether astrocytic activation has been sufficiently quantified. Although astrocytes are visualized, inclusion of additional quantitative parameters such as GFAP protein or transcript levels would strengthen conclusions regarding astrocyte-mediated neuroinflammation. If already performed (e.g., shown in supplementary data), this should be clearly emphasized and discussed in the main text.
Although IBA1 staining is presented, the authors should consider whether microglial activation states (e.g., M1/M2-like markers or inflammatory cytokines) were assessed, as this would provide deeper mechanistic insight into the inflammatory phenotype.
Results sections remain largely descriptive. The authors should improve interpretation by explicitly linking changes in LIMASI expression with downstream inflammatory signaling and AD-related pathology (Aβ, tau, cytokines).
In Vitro experiment. The poly(I:C) astrocyte experiments are relevant; however, the authors should discuss how well this model reflects chronic neuroinflammation in AD and acknowledge its limitations compared to in vivo or co-culture systems.
The Discussion should better integrate findings into a unified mechanistic model, explaining how LIMASI-mediated ceRNA regulation influences astrocyte-microglia crosstalk, neuroinflammation, and disease progression rather than discussing each result in isolation.

Author Response

We sincerely thank the reviewers for their thoughtful and constructive comments. We have carefully addressed each point raised and have revised the manuscript accordingly. All changes have been incorporated into the revised version, and we have uploaded both a marked manuscript (with modifications highlighted in red) and a clean version for clarity.

We believe that these revisions have substantially strengthened the manuscript and improved its clarity and overall quality for the journal’s readership. Below, we provide a detailed, point-by-point response to all reviewer comments, organized as R1, R2, etc.

C1. The work is interesting and relevant; however, the authors should clarify whether the study primarily focuses on ceRNA regulation, neuroinflammation, or cell-type-specific mechanisms in AD, as the current scope appears broad. Further, there are several points that need to be addressed before publication.

R1: Thank you for this important feedback. The present manuscript identifies the association between a long noncoding RNA (lncRNA) LIMASI and Alzheimer’s disease-linked neuroinflammation. We demonstrate that LIMASI is upregulated in human AD brain tissues, a transgenic AD mouse model, and in β-amyloid-linked inflammatory cell culture systems. Mechanistically, our data posits that LIMASI functions as a competing endogenous RNA (ceRNA) that sequesters AD-associated inflammatory microRNAs, thus linking a ceRNA-mediated regulation of neuroinflammation and neurodegeneration. We have emphasized this throughout the manuscript. As this is a very novel finding, we would like to share the findings with the scientific community as a ‘Communication’ section of this journal and the future studies will focus on delineating the cell-type-specific underlying mechanisms and molecular regulation of neuroinflammation by this lncRNA.

C2. The introduction provides a good background; however, the authors should more clearly justify why LIMASI was selected as the primary ceRNA of interest and how it advances current understanding beyond existing lncRNA studies in AD.

R2: Thank you for appreciating the background information. As per suggestion, now we have modified the introductory statement to emphasize the rationale for focusing on the role of LIMASI lncRNA in the current study. This has been incorporated in the revised manuscript (line 70 onwards) to state that,

“Our studies investigating innate inflammatory mechanisms led to the identification a novel lncRNA LIMASI (LncRNA Inflammation and Mucous associated, Antisense to ICAM1), which shares the overlapping genomic loci with ICAM1. Given that ICAM-1 is well-established mediator of inflammation and infection, we hypothesized that LIMASI lncRNA may contribute to AD-associated neuroinflammatory responses.”

C3. Elaborating and relating early biomarker for AD would be interesting to strengthen the introduction eg miRNA and others. https://pubmed.ncbi.nlm.nih.gov/37833762/ https://pubmed.ncbi.nlm.nih.gov/39046584/

R3: Thank you for pointing this out and we would like to clarify that this project has not attempted to assess or identify early biomarkers of AD pathogenesis. The present manuscript just describes the association of brain tissue lncRNA LIMASI with Alzheimer’s disease-linked neuroinflammation. The study demonstrates that LIMASI is upregulated in human AD brain tissues, a transgenic AD mouse model, and in β-amyloid-linked inflammatory cell culture model. Mechanistically, we observe elevated levels of inflammatory microRNAs (miR-155-5p and miR-150-5p) in AD brain tissues, and computational modeling predicts energetically favorable binding of these inflammatory miRNAs to LIMASI. Further studies are needed to assess whether the identified brain-resident lncRNA and miRNAs are also detectable in circulation, and to validate them as AD biomarkers, which are beyond the scope of current study. More importantly, this manuscript has been submitted for consideration as a ‘Communication’ and not as a full ‘Original article’.

C4. In Methods. Human Brain Samples, more details are needed regarding sample selection, demographic variability, and clinical characterization of NC and AD brain tissues (e.g., age range, sex distribution, post-mortem interval), as these factors can influence neuroinflammatory readouts.

R4: In our manuscript, we have provided all the characterization of brain tissues used in this study along with the demographics of donors as summarized in the revised Table 1. “The archived samples were selected randomly and age (75.1±3.6 vs 82.2±3.5 y) and gender distribution (2F/5M vs 3F/6M) between control and AD tissue donors was comparable with no significant difference in post-mortem interval, 19.2±1.8 and 16.4±2.5 h, respectively.” This has been added to the revised methods section (ln line 89 onwards).

C5. Animal section, please elaborate how animal being dissected and how tissue was collected. It would be helpful for the reader to follow.

R5: Based on this suggestion, we have now included the description for animal dissection to state that, “For brain tissue collection, mice were euthanized by carbon dioxide overdose, decapitated immediately, and one-half of the brain tissue was dissected into specific brain regions i.e., cortex, hippocampus, brainstem, and cerebellum, were snap frozen for protein and RNA analyses and other half was fixed in formalin for histological processing and sectioning as described previously (23, 25).”

This has been added to the revised methods section (ln line 109 onwards).

C6. The authors should carefully verify whether astrocytic activation has been sufficiently quantified. Although astrocytes are visualized, inclusion of additional quantitative parameters such as GFAP protein or transcript levels would strengthen conclusions regarding astrocyte-mediated neuroinflammation. If already performed (e.g., shown in supplementary data), this should be clearly emphasized and discussed in the main text.

R6: As per suggestion, we assessed the expression levels of GFAP in the whole brain tissue homogenates of AD patients and control subjects, and the data has been added to the revised manuscript (ln 255 onwards) and under the Online data supplement (Supplementary Figure S3C-E). The immunoblot analysis revealed that, “Although no significant differences were observed in IBA1 expression, immunoblot analysis of brain tissue homogenates revealed a trend toward increased GFAP protein levels (Supplementary Figure S3C-E).”

We modified the text in the revised results (ln 162 onwards) and discussion (ln 408 onwards) section accordingly.

C7. Although IBA1 staining is presented, the authors should consider whether microglial activation states (e.g., M1/M2-like markers or inflammatory cytokines) were assessed, as this would provide deeper mechanistic insight into the inflammatory phenotype.

R7: Similar to the response to comment #6, we assessed the expression levels of IBA1 in the whole brain tissue homogenates of AD patients and control subjects, and the data has been added to the revised manuscript (ln 255 onwards) and under the Online data supplement (Supplementary Figure S3C-E). The immunoblot analysis revealed that, “Although no significant differences were observed in IBA1 expression, immunoblot analysis of brain tissue homogenates revealed a trend toward increased GFAP protein levels (Supplementary Figure S3C-E).”

We modified the text in the revised results (ln 162 onwards) and discussion (ln 408 onwards) section accordingly.

C8. Results sections remain largely descriptive. The authors should improve interpretation by explicitly linking changes in LIMASI expression with downstream inflammatory signaling and AD-related pathology (Aβ, tau, cytokines).

R8: We have summarized the observed correlation between LIMASI expression levels and the AD-related neuroinflammation very explicitly under the discussion section, line 360 onwards to state that, “Elevated LIMASI expression consistently correlated with increased levels of key inflammatory mediators, including ICAM-1, IL-6, IL-1β and TNF, which are known drivers of neuroinflammation and brain tissue remodeling.”

However, based on this suggestion, we now revised the discussion section to state the observed correlation between LIMASI expression levels and AD-related pathology at line 387 onwards to state that, “In agreement with these observations, our analysis confirmed classical AD neuropathology in the archived brain tissues that showed elevated LIMASI expression along with markedly elevated innate immune cytokines and tissue remodeling factors. Notably, we identified increased expression of CHI3L-1, uPAR, MMP9, CRP, ICAM-1, and VCAM1 – molecules implicated in immune cell recruitment, extracellular matrix remodeling, and vascular inflammation...."

C9. In Vitro experiment. The poly(I:C) astrocyte experiments are relevant; however, the authors should discuss how well this model reflects chronic neuroinflammation in AD and acknowledge its limitations compared to in vivo or co-culture systems.

R9: Thank you for this important point. We did state the limitations of our in-vitro model in the manuscript, however, as per reviewer’s suggestion, we now have revised the discussion section at line 428 onwards to state that, “The cell culture model used in this study only captures the APP-associated inflammatory responses and does not recapitulate all the complex pathways and cell systems of AD pathophysiology.”

C10. The Discussion should better integrate findings into a unified mechanistic model, explaining how LIMASI-mediated ceRNA regulation influences astrocyte-microglia crosstalk, neuroinflammation, and disease progression rather than discussing each result in isolation.

R10: Thank you for this suggestion and we have now expanded our discussion section to include the astrocyte-microglia crosstalk with neuroinflammation and disease progression. We have made changes to the discussion section in the revised version of the manuscript by modifying and rewriting it to highlight a unified mechanistic model, line 465 onwards to state that, “The current findings support a unified mechanistic model in which LIMASI functions as a ceRNA regulator that amplifies and sustains neuroinflammatory signaling in AD. In this model, inflammatory stimuli and amyloid-associated stress induce LIMASI expression in astrocytes and microglia, two key CNS cells modulating brain innate immune responses. Elevated LIMASI then acts as a ceRNA, sequestering inflammatory miRNAs such as miR-155-5p and miR-150-5p, thereby relieving repression of genes involved in cytokine production, immune activation, and cell-cell adhesion, including ICAM-1 and other inflammatory mediators. This miRNA sequestration results in pro-inflammatory signaling, promoting astrocyte-microglia crosstalk through enhanced cytokine and chemokine signaling. Activated microglia further potentiate astrocytic reactivity, establishing a feed-forward inflammatory loop that exacerbates β-amyloid accumulation, tau hyperphosphorylation, and synaptic dysfunction. Over time, this sustained LIMASI-driven ceRNA network may contribute to chronic neuroinflammation and progressive neurodegeneration, although to be validated in a larger clinical and longitudinal study. Thus, LIMASI-mediated RNA-RNA interactions could provide a novel molecular bridge linking glial activation, inflammatory amplification, and disease progression in AD pathology.”

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript by Devadoss et al., found that a novel LncRNA (LIMASI) is linked with AD-associated neuroinflammation. Increased LIMASI expression is observed in postmortem AD brain tissues and 3XTg-AD mouse model. The authors performed cell-type-specific analysis to demonstrated inflammation-inducible LIMASI expression. They further performed RNA-RNA interaction modeling to predict multiple AD-associated inflammatory microRNAs. The following are the concerns that need to be improved.

Major points.

It is acceptable that LIMASI expression is elevated many AD-associated condition including mouse model, cell type-specific analysis and in vitro model. However, They did not show any function of LIMASI in AD.
Figure 4, RNA-RNA prediction should be supported by experiments. Furthermore, what are the roles of these interactions?

Author Response

Major points.

C1. It is acceptable that LIMASI expression is elevated many AD-associated condition including mouse model, cell type-specific analysis and in vitro model. However, they did not show any function of LIMASI in AD.

R1: Thank you for this important feedback. This manuscript reports the novel observation that elevated expression of lncRNA LIMASI is associated with Alzheimer’s disease-linked neuroinflammation. As this is a very novel finding, we aim to share the findings with the scientific community as a ‘Communication’ section of this journal and the future studies will focus on delineating the cell-type-specific underlying mechanisms and molecular regulation of neuroinflammation by this lncRNA. Just to reiterate, we demonstrate that LIMASI is upregulated in human AD brain tissues, a transgenic AD mouse model, and in β-amyloid-linked inflammatory cell culture systems. Mechanistically, our data posits that LIMASI functions as a competing endogenous RNA (ceRNA) that sequesters AD-associated inflammatory microRNAs, thus linking a ceRNA-mediated regulation of neuroinflammation and neurodegeneration. We emphasized this throughout our manuscript.

C2. Figure 4, RNA-RNA prediction should be supported by experiments. Furthermore, what are the roles of these interactions?

R2: As per suggestion, we analyzed the expression levels of select miRNAs in the archived brain tissues of AD patients and control subjects, and the data has been added to the revised manuscript (ln 340 onwards) under the revised Results section now titled “3.4. Elevated LIMASI-associated miRNAs in AD and evidence for a ceRNA Model” with data on new Figures 4A and 4B.

We have now revised the results section to state that, “We quantified miRNA expression levels in archived brain tissue samples, and found that compared with NC brains, AD patients exhibited markedly elevated expression of miR-150-5p (approximately ten-fold increase, Figure 4A) and miR-155-5p (more than three-fold increase, Figure 4B).”

We modified the text in the revised methods section to include miRNA qPCR analysis (line 187 onwards) and the discussion section (line 457 onwards) accordingly.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The author has revised the manuscript meticulously and I would recommend it for publication.

Reviewer 2 Report

Comments and Suggestions for Authors

The authors responded to all of my concerns well. Now the manuscript is acceptable to cells.