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Communication

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

by
Dinesh Devadoss
1,
Juliet Akkaoui
1,
Natalia Orso
1,
Thiruselvam Viswanathan
1,
Glen M. Borchert
2,
Madepalli K. Lakshmana
1 and
Hitendra S. Chand
1,*
1
Department of Cellular and Molecular Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, FL 33199, USA
2
Department of Pharmacology, University of South Alabama, Mobile, AL 36688, USA
*
Author to whom correspondence should be addressed.
Cells 2026, 15(5), 412; https://doi.org/10.3390/cells15050412
Submission received: 22 January 2026 / Revised: 18 February 2026 / Accepted: 25 February 2026 / Published: 27 February 2026
(This article belongs to the Collection Molecular Insights into Neurodegenerative Diseases)
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Abstract

Alzheimer’s disease (AD) is an aging-associated neurodegenerative disorder in which dysregulated neuroinflammation drives disease progression. Although long noncoding RNAs (lncRNAs) are increasingly implicated in AD, their mechanistic roles remain poorly defined. Here, we identified a novel lncRNA termed LIMASI (LncRNA Inflammation and Mucous associated, Antisense to ICAM1), that is linked with AD-associated neuroinflammation. LIMASI expression is significantly elevated in postmortem AD brain tissues and in a 3xTg-AD mouse model by qPCR and RNA fluorescence in situ hybridization, and its upregulation is correlated with increased β-amyloid plaque burden, tau hyperphosphorylation, and heightened neuroinflammatory activation. Cell type-specific analyses demonstrated inflammation-inducible LIMASI expression in astrocytes and microglia. In an in vitro model of AD-associated neuroinflammation, viral mimetic poly(I:C) challenge of amyloid precursor protein (APP)-overexpressing neuroblastoma cells elicited coordinated induction of LIMASI and key inflammatory mediators. Mechanistically, we observed elevated levels of inflammatory microRNAs (miR-155-5p and miR-150-5p) in AD brain tissues, and computational modeling predicted energetically favorable interactions between these miRNAs and LIMASI. These findings support a competing endogenous RNA (ceRNA) model in which LIMASI sequesters pro-inflammatory miRNAs to modulate neuroinflammatory gene networks. Together, our data identify LIMASI as a putative ceRNA strongly associated with AD-related neuroinflammation and suggest that targeting LIMASI may represent a novel strategy to attenuate neuroinflammatory signaling and potentially slow AD-associated neurodegeneration.

1. Introduction

Alzheimer’s disease (AD) is the most common neurodegenerative disease among the aging population [1]. Although the neuropathological features and genetic determinants for familial cases of AD (FAD) are relatively well characterized, the molecular basis for sporadic late-onset Alzheimer’s disease (LOAD), the most prevalent form, remains poorly understood. Clinically, AD is marked by progressive decline in cognitive function, collectively termed as AD-related dementia (ADRD), that severely impairs a person’s ability to perform day-to-day activities [2]. With more than 25 million people affected worldwide by dementia, where most suffer from ADRD, a deeper understanding of AD pathophysiology is essential to reduce disease risk and delay or suppress the clinical onset of AD [3].
AD exhibits a strong genetic basis, with heritability estimates approaching 80% [4]. However, the known genetic variants in the four established AD genes, namely amyloid precursor protein (APP), presenilin (PS) 1, PS2, ApoE, and the newly identified nine genetic risk loci for LOAD account for less than half of familial AD cases [5], indicating the existence of additional, yet unidentified, genetic contributors. Multiple seminal studies implicate neuroinflammation as a critical driver of AD pathogenesis. For example, dysregulated inflammatory responses accelerate cognitive decline in both experimental animal models [6] and AD patients [7]. In addition, genome-wide association studies (GWASs) and meta-analyses have identified multiple inflammation-associated genes and polymorphisms that increase the AD risk [8,9]. These findings strongly suggest that immune dysregulation and chronic neuroinflammation play a central role in AD and warrant further mechanistic investigation.
Long noncoding RNAs (lncRNAs) have emerged as a new class of immunomodulators and are involved in multiple aspects of AD pathology, including β-amyloid (Aβ) plaque formation, neurofibrillary tangle (NFT) development, synaptic dysfunction, and neuronal loss [10,11,12]. LncRNAs modulate nervous system functions through diverse mechanisms, including epigenetic regulation [13] and posttranscriptional regulation [14]. For example, the lncRNA β-amyloid precursor protein cleaving enzyme 1-antisense (BACE1-AS) stabilizes BACE1 mRNA, thereby enhancing APP cleavage and Aβ production [15]. In addition, the ultraconserved enhancer lncRNA Evf2 regulates adult hippocampal neurogenesis [16], MALAT1 lncRNA modulates synaptogenesis in mouse hippocampal neurons [17], and many lncRNAs have been reported to function as competing endogenous RNAs (ceRNAs), acting as microRNA (miRNA) sponges [18,19] via miRNA response elements (MREs) to modulate AD-related molecular pathways [12,14,15].
Our studies investigating innate inflammatory mechanisms led to the identification a novel lncRNA LIMASI (LncRNA Inflammation and Mucous associated, Antisense to ICAM1), which shares overlapping genomic loci with ICAM1 [20]. Given that ICAM-1 is a well-established mediator of inflammation and infection [20,21,22], we hypothesized that LIMASI lncRNA may contribute to AD-associated neuroinflammatory responses. To test this, we examined LIMASI expression in archived AD patient brain samples and in a transgenic mouse model of AD, and further validated our findings in a stable APP-overexpressing cell culture model challenged with viral mimics. Mechanistically, LIMASI acted as a ceRNA that interacted with several microRNAs (miRNAs) to fine-tune neuroinflammatory gene networks relevant to Alzheimer’s disease. Collectively, these studies provide new insight into a lncRNA that potentially functions as a ceRNA dysregulated during AD-related neuroinflammation.

2. Materials and Methods

2.1. Brain Tissue Samples of AD and Control Subjects

The AD and normal control (NC) brain tissues (hippocampi) were obtained from the “Harvard Brain Tissue Resource Center”, which is supported in part by PHS grant number R24MH068855. Additional brain tissues (motor cortex) were obtained from the NICHD Brain and Tissue Bank for Developmental Disorders at the University of Maryland, Baltimore, MD. The frozen brain tissue samples (see Table 1 for demographics) were processed for protein and RNA isolation as described previously [23]. The archived samples were selected randomly, and the age (75.1 ± 3.6 vs. 82.2 ± 3.5 y) and gender distributions (2F/5M vs. 3F/6M) between the control and AD tissue donors were comparable, with no significant difference in the postmortem intervals of 19.2 ± 1.8 h and 16.4 ± 2.5 h, respectively. The formalin-fixed paraffin-embedded sections were processed for histochemical, immunostaining, and RNA-FISH analyses as described in the following sections.

2.2. Animal Model of AD Pathology

All animal regulations were strictly enforced as per the National Institute of Health’s “Guide for the Care and Use of Animals”, and the protocols were approved by the Institutional Animal Care and Use Committee (IACUC) at Florida International University. Brain tissues from 10-month-old male and female 3xTg-AD (MMRC stock #34830) mice were analyzed as described before [23,24]. 3xTg-AD mice are homozygous for all three mutant alleles (homozygous for the Psen1 mutation and homozygous for the co-injected APPSwe and tauP301L transgenes (Tg(APPSwe,tauP301L)1Lfa)). Brain tissues from C57BL/6j wild-type (WT) mice (Jackson Labs) from both males and females served as the controls. For brain tissue collection, the 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, and were snap frozen for protein and RNA analyses, and then the other half was fixed in formalin for histological processing and sectioning as described previously [23,25].

2.3. Cell Culture and Treatments

To generate the human neuroblastoma cell line stably expressing APP, SH-SY5Y cells (cat# CRL-2266, ATCC, Manassas, VA, USA) were transfected with the pLHCX plasmid vector (Clontech, Palo Alto, CA, USA) containing the APP751 Swedish mutation (K595N/M596L). The SH-SY5Y-APPSwe cells were cultured in a 1:1 mixture of DMEM/Nutrient Mixture F12 with 1mM L-Glutamine media (Cytiva HyClone) supplemented with 10% fetal bovine serum (FBS) and Pen–Strep and the stable cell line was selected with 50 µg/ml Hygromycin B (Invitrogen Inc., Carlsbad, CA, USA). Human primary astrocytes (cat# 1800, ScienCell, Carlsbad, CA, USA) were cultured as per the manufacturer’s instructions. The cells were challenged with polyinosine-polycytidilic acid (poly(I:C)) to mimic viral infection. To model the acute neuroinflammatory responses, the cells were treated with 0, 5, 10, 25, 50, and 100 µg/mL poly(I:C) (Invivogen Inc., San Diego, CA, USA) for 2, 24, and 48 h.

2.4. Immunostaining and Imaging

For immunohistochemical staining, the brain tissue sections (10 µ) or treated cells were fixed in 4% paraformaldehyde (PFA) and washed in 0.05% v Brij-35 in PBS (pH 7.4), and then immunostained for antigen expression as described previously [22,23]. Briefly, the sections/cells were blocked and permeabilized for an hour at RT and stained with antibodies for anti-beta Amyloid1-16 (6E10) (cat# 803001, BioLegend, San Diego, CA, USA), GFAP (cat# sc-33673), and IBA1 (cat# sc-32725) from Santa Cruz Biotech (Dallas, TX, USA). The immunolabelled cells were detected using secondary antibodies conjugated fluorescent dyes (Jackson ImmunoResearch Lab Inc., West Grove, PA, USA) and mounted with 4′,6-diamidino-2-phenylindole (DAPI) containing Fluormount-GTM (SouthernBiotech, Birmingham, AL, USA) for staining nuclei. Immunofluorescent images were captured by a BZX700 Microscopy system (Keyence Corp., Osaka, Japan) and analyzed using NIH Image J software (https://imagej.net/ij/index.html).

2.5. RNA Fluorescent In-Situ Hybridization

RNA FISH was performed using the RNAscope® Fluorescent Multiplexed reagent kit (Advanced Cell Diagnostics, Newark, CA, USA) as per the manufacturer’s protocol using custom-made probe sets for LIMASI lncRNA as described previously [20]. Briefly, cryostat brain sections/cells were hybridized with probes for 2 h at 40 °C using an HyBEZ® oven (Advanced Cell Diagnostics, Newark, CA, USA), and the signal was amplified by serial incubation in amplification buffers and HRP-tagged probe (Advanced Cell Diagnostics, Newark, CA, USA.) at 40 °C using an HyBEZ® oven. Probes were detected using Tyramide signal amplification (TSA) reaction using TSA-Plus Cy5 for LIMASI transcripts. Sections were also immunostained with GFAP or IBA1 as described above. Dual-labelled images were analyzed, and LIMASI expression was quantified by H-score analysis as reported earlier [20,22].

2.6. Protein Isolation and Western Blot Analysis

The tissue/cell lysates were prepared using RIPA lysis buffer (cat #89990, ThermoFisher Scientific, Waltham, MA, USA) with 400nM microcystine-LR, 0.5 mM sodium vanadate, and 5% protease inhibitor cocktail. Protein concentration was determined by a BCA assay (Pierce; Rockford, IL, USA), and 30 µg protein was analyzed by Western blotting as described previously [24]. The antibodies used for detecting Tau (HT7) (cat# MN1000) and pTau Thr231 (cat# MN1040) were from Invitrogen, and those for pTau S396 (cat# 2934-1) and for total Tau-5 (cat# MAB361) were from Epitomics (Burlingame, CA, USA) and Millipore Sigma (Burlington, MA, USA), respectively; those for APP (cat# 751-770) were from Calbiochem (San Diego, CA, USA), those for GFAP (Cat# G3893) were from Sigma (Saint Louis, MO, USA), and those for IBA1 (Cat# 17198) were from Cell Signaling Technology (Danvers, MA, USA). Immunolabeled protein bands were detected using an ECL kit and visualized by chemiluminescence (Perkin Elmer, Waltham, MA, USA) using the BioRad Chemidoc Imaging system (Hercules, CA, USA). The signals were quantified by using Image J software, and β-actin (cat# A5441) from Sigma was used to normalize the protein levels in each sample.

2.7. Cytokine Proteome Array

The brain tissue inflammatory and tissue remodeling factors were analyzed using the Proteome Profiler Human XL (hXL) Cytokine Array Kit (cat-# ARY022B; R&D Systems, Minneapolis, MN, USA) according to the manufacturer’s instructions. Equal protein amounts of AD and NC brain tissue lysates were incubated with the array membranes separately, and the immunolabelled protein blots were detected using the ECL kit (Perkin Elmer, Waltham, MA, USA). The densitometric analysis of each protein spot was determined using the Image J software after background subtraction, and relative expression for the NC tissue was quantified.

2.8. Real-Time Quantitative PCR for mRNAs, lncRNAs and miRNAs

Total RNA was isolated from the brain tissues and treated cells using the RNeasy kit (Qiagen, Germantown, MD, USA) as per the manufacturer’s instructions. The FAM-based primer/probe sets for LIMASI were obtained from Applied Biosystems (ThermoFisher Inc., Waltham, MA, USA), and the SYBR green-based primer sets for ICAM-1, IL-6, IL-1β, and TNF mRNA were obtained from BioRad (Hercules, CA, USA). RNA expression levels were quantified by qRT-PCR using the iTaq SYBR-green Master Mix (BioRad) in the CFX96 Real-Time PCR System (BioRad). Relative RNA quantities were calculated by normalizing the data to u6 for LIMASI and GAPDH for all the mRNAs as described previously [20]. To quantify the miRNA expression levels, cDNA was synthesized from total RNA preparations with a TaqMan® Advanced miRNA cDNA Synthesis Kit (Applied Biosystems, ThermoFisher Inc.). TaqMan® Advanced miRNA assays for hsa-miR-150-5p and hsa-miR-155-5p were obtained from Applied Biosystems (ThermoFisher Inc.), and the expression levels were quantified by qRT-PCR using the TaqMan® Fast Advanced Master Mix (ThermoFisher Inc.). Relative quantities were calculated by normalizing the data to U6 snRNA (Applied Biosystems, ThermoFisher Inc.) as described previously [22].

2.9. Modeling of Potential miRNA Interaction Site Prediction

The IntaRNA 2.0 webserver [26] was used to predict potential RNA-RNA binding sites between LIMASI and the miRNAs miR-150-5p, miR-155-5p, miR-122-5p, and miR-1915-3p.

2.10. Statistical Analysis

The data is expressed as means ± SEM and was analyzed using GraphPad Prism Software v10.6.1 (GraphPad Software, Inc., San Diego, CA, USA). The grouped results were analyzed using one-way analysis of variance. When significant main effects were detected (p < 0.05), Student’s t-test was used to determine differences between the two groups.

3. Results

3.1. Classical Alzheimer’s Disease Neuropathology Is Associated with Robust Neuroinflammatory Activation

We first verified hallmark AD pathology in the archived postmortem brain tissues from AD patients (Braak stage IV or higher) and compared these findings with the normal control (NC) subjects. In contrast to the NC brain sections, immunostaining for β-amyloid (Aβ) in the AD brain tissues revealed markedly elevated Aβ expression with prominent plaque aggregation (Supplementary Figure S1A). Consistently, the Aβ40 monomer levels were more than two-fold higher in the AD brain homogenates, as quantified by specific ELISA (Supplementary Figure S1B). Analysis of tau pathology demonstrated increased hyperphosphorylation at serine residues S396/S404 (Supplementary Figure S1C), and S396 (Supplementary Figure S1E), and threonine T231 (Supplementary Figure S1D), along with a significant increase in total tau protein levels in the AD subjects (Supplementary Figure S1F).
Next, multiplex protein array analysis of brain tissue lysates from the AD and NC subjects revealed robust neuroinflammatory activation in the AD subjects (Supplementary Figure S2). Compared with the NC tissues, the quantities of innate immune-associated cytokines and chemokines—including CD14, Lipocalin-2, IL-19, IL-1β, IL-6, IL-10, IL-15, IL-34, MCP-1, CXCL-10, and TNF-α—were elevated by approximately three-fold in the AD brains (Figure 1A). Additionally, brain tissue remodeling and vascular inflammatory markers, including BDNF, CHI3L-1, uPAR, MMP9, CRP, ICAM-1 and VCAM1, were significantly increased in the AD subjects (Figure 1B). Gene expression analysis further showed significantly higher mRNA levels of ICAM-1 (1.5-fold, Figure 1C) and TNF (three-fold, Figure 1F) in the AD tissues compared to the NC controls, with trends toward increased IL-6 and IL-1β mRNA expression (approximately two-fold, p = 0.07, Figure 1D,E). Thus, these findings confirm the presence of classical AD neuropathology in our archived brain samples and demonstrate a strong association with elevated neuroinflammatory gene and protein expression.

3.2. Elevated lncRNA LIMASI Expression in AD Patients and an AD Transgenic Mouse Model

Modulation of innate immune responses and neuroinflammation has been shown to reduce or delay the onset of AD [27]. Increasing evidence indicates that long noncoding RNAs (lncRNAs) play important roles in regulating innate inflammatory pathways. We previously identified an immunomodulatory lncRNA associated with ICAM-1 termed LIMASI, which regulates the expression of multiple innate inflammatory mediators [20,22,28]. Analysis of postmortem human brain tissues revealed that compared to the NC tissues, the LIMASI expression level was more than 5-fold higher in the AD tissues (Figure 2A). To validate these findings and determine cell-specific expression of LIMASI, we performed RNA-FISH analysis (Figure 2B). Quantitative analysis demonstrated approximately 5-fold higher LIMASI transcript levels in the AD brain sections compared with the NC controls (Figure 2C). Co-immunostaining of the RNA-FISH sections showed LIMASI was expressed in both GFAP+ astrocytes (Supplementary Figure S3A) and IBA1+ microglia (Supplementary Figure S3B). 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 S3).
To extend these findings to an experimental model, we performed bioinformatic analysis to identify a murine analog of human LIMASI and identified a homologous sequence on mouse chromosome 9 (GenBank: CM001002.2) with substantial sequence identity. Using RNA-FISH probes targeting human LIMASI, we analyzed brain sections from a 3xTg-AD mouse model, which develops neurofibrillary tangles, tauopathy, and other AD-like pathologies [29]. Age-matched (10 months) male and female C57/BL6 wild-type (WT) and 3xTg-AD mice were examined. Compared with the WT brain sections, the 3xTg-AD mice exhibited markedly elevated LIMASI expression (Figure 2D). Consistently, qPCR analysis revealed a 1.5-fold increase in LIMASI transcripts (Figure 2E), a 5-fold increase in Icam1 (Figure 2F), and a striking 30-fold increase in Il-6 mRNA expression (Figure 2G) in the 3xTg-AD mice relative to the WT controls. These data collectively demonstrate that LIMASI expression is elevated in both human AD brains and this transgenic mouse model of AD and is associated with a primed neuroinflammatory network, supporting a potential link between LIMASI upregulation and AD-associated neuroinflammation.

3.3. Cell Culture Models of AD-Associated Neuroinflammation Show Increased lncRNA LIMASI Expression

To establish a cell culture model of AD-associated neuroinflammation, we used the APPSwe-overexpressing human neuroblastoma cell line (SH-SY5Y-APPSwe) and challenged the cells with the viral mimetic poly(I:C) to simulate viral infections known to exacerbate AD neuropathology [30]. The SH-SY5Y-APPSwe cells were treated with increasing concentrations of poly(I:C) (0, 5, 25, 50, and 100 µg/mL) for 2 h based on our prior observations that lncRNAs regulate early inflammatory gene expression [20,22]. No significant toxicity was observed under any treatment conditions, as assessed by viable cell count analysis. Quantitative PCR analysis revealed a dose-dependent induction in the LIMASI transcript levels (Figure 3A), accompanied by increased expression of neuroinflammatory mediators, including the ICAM1, IL-6, IL-1β, and TNF mRNA levels (Figure 3B–E).
To examine the temporal dynamics, the SH-SY5Y-APPSwe cells were treated with 50 µg/mL of poly(I:C) and incubated for 2, 24, and 48 h and compared the changes in gene expression with the non-treated (NT) controls. LIMASI and inflammatory gene expression peaked at 2 h post-treatment. The expression levels returned toward the baseline by 24 h, whereas the quantities of LIMASI and TNF were again elevated at 48 h (Figure 3F–J). RNA-FISH analysis further validated poly(I:C)-induced LIMASI upregulation, demonstrating increased LIMASI levels following 10 µg/mL poly(I:C) treatment compared to the NT controls (Figure 3K,L).
In a separate experiment, the SH-SY5Y-APPSwe cells treated with 50 µg/mL poly(I:C) for 48 h exhibited a more than 50% increase in APP protein levels (Supplementary Figure S4A,B). To extend these findings to a non-neuronal cell type, human primary astrocytes (HPAs) were treated with 10 µg/mL poly(I:C) for 24 h, resulting in increased expression of the inflammatory markers ICAM1, IL-6, and IL-1β, along with concomitant induction of the LIMASI transcripts (Supplementary Figure S5A–D). These elevated LIMASI expression levels were further confirmed by RNA-FISH in GFAP-positive astrocytes (Supplementary Figure S5E,F). Thus, these cell culture models recapitulate key features of AD-associated neuroinflammation and demonstrate strong correlation between neuroinflammatory activation and increased LIMASI expression.

3.4. Elevated LIMASI-Associated miRNAs in AD and Evidence for a ceRNA Model

Analysis of the lncRNA-miRNA interactome provides important insights into gene regulatory mechanisms operating under pathological conditions. LncRNAs function as ceRNAs that could act as miRNA sponges/decoys, compete with miRNAs for shared mRNA targets, and serve as precursors for miRNA biogenesis [31,32,33,34]. In a separate earlier study, we performed small RNA sequencing to identify the miRNAs associated with LIMASI during viral infection. Notably siRNA-mediated knock down of LIMASI resulted in reversal of several differentially expressed miRNAs [22], suggesting a functional regulatory relationship.
Among the LIMASI-associated miRNAs, miR-1915-3p, miR-122-5p, miR-155-5p, and miR-150-5p have previously been identified in serum and brain tissues of AD patients. We quantified the miRNA expression levels in the archived brain tissue samples and found that compared with NC brains, the AD patients exhibited markedly elevated expressions of miR-150-5p (approximately ten-fold increase, Figure 4A) and miR-155-5p (more than three-fold increase, Figure 4B). To predict potential interaction sites between LIMASI and these miRNAs, we used the IntaRNA web server. Computational modeling predicted that nucleotides 6-20 of miR-1915-3p’s interact with the exon 1 region of LIMASI spanning nucleotides 64-78 (Figure 4C). Both miR-122-5p and miR-155-5p were predicted to bind LIMASI exon 2. Specifically, miR-122-5p was predicted to bind with the LIMASI nucleotides 171-204 (Figure 4D), whereas miR-155-5p’s nucleotides 13-21 were predicted to bind with the LIMASI nucleotides 324-332 (Figure 4E). In addition, the miR-150-5p nucleotides 1-16 were predicted to pair with the LIMASI nucleotides 797-806 within exon 3 (Figure 4F). All the predicted LIMASI–miRNA interactions exhibited energetically favorable minimum free energies (ranging from approximately −9.24 to −14.8 kcal/mol), supporting the feasibility of stable RNA–RNA interactions. Collectively, these findings suggest that LIMASI harbors multiple miRNA binding sites and may function as a competing endogenous RNA by sequestering inflammation-associated miRNAs relevant to AD-associated neuroinflammation.

4. Discussion

In this study, we demonstrate a strong association between the lncRNA LIMASI and AD-associated neuroinflammation in human postmortem brain tissues, a transgenic mouse model of AD, and complementary in vitro models. 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. Using a viral mimic, poly (I:C), we further showed that APPSwe-overexpressing SH-SY5Y neuroblastoma cells exhibited robust induction of these inflammatory factors in parallel with LIMASI upregulation, supporting a functional link between LIMASI expression and inflammatory signaling. Computational analyses indicate that LIMASI contains multiple energetically favorable binding sites for AD-associated inflammatory miRNAs, including miR-1915-3p, miR-122-5p, miR-155-5p, and miR-150-5p, supporting its role as a competing endogenous RNA that sequesters these miRNAs and modulates neuroinflammatory gene regulation. Collectively, these findings identify LIMASI as a potential mediator of AD-associated neuroinflammation and pathology.
Neuroinflammation is increasingly recognized as a central and early contributor to AD pathogenesis, facilitating and exacerbating both Aβ and NFT pathologies, and potentially bridging early Aβ deposition with later tau aggregation. Recent high-resolution PET imaging studies have identified neuroinflammation as one of the earliest detectable biomarkers of AD [35]. 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 cytokine 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—highlighting their potential value as diagnostic or prognostic biomarkers. ICAM-1, a cell surface glycoprotein expressed by neurons, glia, and endothelial cells, plays a critical role in immune cell adhesion and trafficking; its dysregulation can profoundly alter brain immune homeostasis. Previous studies have shown strong ICAM-1 expression in AD brain regions enriched with amyloid plaques and activated microglia [36,37], supporting its relevance in AD-related neuroinflammation.
Pro-inflammatory cytokines are pivotal contributors to AD pathology. TNF-α, primarily secreted by macrophages and microglia, regulates microglial activation and synaptic dysfunctions and is elevated in serum of AD patients [38,39]. IL-6, a multifunctional cytokine essential for neuronal tissue homeostasis, promotes chronic neuroinflammation when overproduced and correlates with cognitive decline and AD disease severity [40,41,42,43]. IL-1β further amplifies the inflammatory cascade by regulating APP synthesis, Aβ plaque deposition, mild cognitive impairment and AD pathophysiology [44,45,46,47]. Further, IL-1β regulates the expression of downstream cytokines such as IL-6 and TNF-α [48]. In our study, the AD brain tissues exhibited increased levels of TNF-α, CXCL-10, MCP-1, CXCL1, IL-34, IL-15, IL-10, IL-6, IL-1β, IL-19, Lipocalin-2, and CD14. Although elevated levels of pro-inflammatory mediators were observed, no significant changes were observed in the IBA1 levels. In contrast, the GFAP levels showed a trend toward increased expression, which may reflect reactive astrogliosis [49]. These data underscore the extensive inflammatory milieu associated with AD pathology and reinforce the need to understand the upstream regulatory mechanisms governing these responses.
Growing evidence highlights lncRNAs as key regulators of neuroinflammation and neurodegeneration, and the temporal regulation of lncRNAs and miRNAs is a major contributor in the adaptation of cells and the host immune system [50,51]. Several lncRNAs including BACE1-AS, MALAT1, BDNF-AS, and MAGI2-AS3 have been implicated in APP processing, synaptic regulation, neuronal apoptosis, and amyloid secretion [12,17,52,53,54]. LncRNAs are often dysregulated in pathological states and restoration of their expression has shown therapeutic benefits in multiple disease models [55,56]. Our immunohistological and molecular analyses demonstrate that LIMASI is expressed in both microglia and astrocytes and is strongly associated with AD-related neuroinflammation. Most notably, the induction of LIMASI by poly(I:C) further suggests that this lncRNA may participate in viral infection-augmented neuroinflammation, potentially involving TLR3/7-dependent pathways in APPSwe-overexpressing cells [57,58]. Importantly, experiments using human primary astrocytes confirmed that LIMASI is directly inducible during astrocytic inflammatory responses, highlighting astrocytes as a key cellular course of LIMASI-induced inflammatory responses in AD. 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. Further studies are needed to investigate the molecular pathways by which LIMASI regulates neuroinflammation, including developing a suitable co-culture model of human induced-pluripotent stem cell (hiPSC)-derived cells to study the contribution of glial cells and other neurons.
Mechanistically, our bioinformatic and expression analyses support a competing endogenous RNA (ceRNA) model in which LIMASI regulates neuroinflammation through interactions with multiple disease-relevant miRNAs. As discussed earlier, lncRNAs often act as ceRNAs and influence gene regulation by sequestering proteins and coding and noncoding RNAs [59]. Several LIMASI-associated miRNAs, including miR-1915-3p, miR-122-5p, miR-155-5p, and miR-150-5p, have previously reported as being dysregulated in neurodegenerative diseases, including AD [60,61,62,63,64]. Among these, miR-155-5p and miR-150-5p play distinct, yet complementary roles in AD, linking neuroinflammatory regulation, disease pathology, and clinical relevance. miR-155-5p functions as a context-dependent pro-inflammatory mediator with both detrimental and protective effects; its early upregulation in AD mouse models promotes microglial and astrocytic activation and inflammatory cytokine production (e.g., IL-6 and IFN-β) prior to overt amyloid plaque formation [65], while mechanistically enhancing amyloid pathology through pathways such as the miR-155-5p/SKP2/IKKβ axis [66]. Conversely, microglia-specific deletion of miR-155-5p induces a pre-neurodegenerative microglial phenotype that enhances amyloid plaque compaction and reduces neuritic damage, yet paradoxically increases neuronal hyperexcitability and seizure susceptibility due to altered synaptic pruning [67,68]. These findings place miR-155-5p at the intersection of innate immune signaling, amyloid processing, synaptic regulation, and viral response pathways relevant to late-onset AD [69]. In contrast, miR-150-5p has emerged as a robust and clinically validated blood-based biomarker for AD with elevated levels correlating strongly with cognitive decline, reduced CSF Aβ42, increased CSF total tau, and brain atrophy within default mode and executive control networks [70]. Mechanistically, miR-150-5p targets components of the Wnt signaling pathway, including PDCD4, which is downregulated in AD patients [70]. Consistent with these findings, our analysis of archived AD brain tissues revealed increased expression of both miR-155-5p and miR-150-5p. Future studies should examine the spatial and cell-type-specific expression of these miRNAs in relation to their cytological localization in conjunction with the lncRNA interactome to better define their regulatory relationships in AD pathology. Together, these miRNAs exemplify how small noncoding RNAs contribute to AD pathogenesis, biomarker development, and ceRNA-based regulatory networks implicated in disease progression [70,71].
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.
Overall, this proof-of-concept study strongly suggests that LIMASI mediates amyloid-associated neuroinflammation following viral mimic challenges. Despite these insights, several limitations should be acknowledged while drawing conclusions. First, the postmortem human brain samples analyzed represent late-stage disease, limiting our insight into early pathogenic events. Second, the relatively small sample size warrants validation in larger, independent cohorts. Finally, although animal and cell culture models provide valuable mechanistic insight, they incompletely recapitulate the complexity of human AD, so better experimental models are needed that recapitulate the complex AD disease spectrum [72].
In conclusion, this proof-of-concept study identifies LIMASI as a novel ceRNA associated with AD-related neuroinflammation and supports a ceRNA-based mechanism linking LIMASI, miRNAs, and ICAM-1 signaling. These findings provide new avenues for understanding AD pathogenesis and highlight LIMASI as a potential biomarker and therapeutic target for modulating neuroinflammation and slowing disease progression.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cells15050412/s1. Figure S1: Increased accumulation of β-amyloid plaques and hyperphosphorylation of tau in the brain tissues of AD patients (Braak stage IV or higher) compared to non-diseased brain tissues (NC). Figure S2: Micrographs showing the hXL array blot expressions of non-diseased controls (NC) and AD patients brain tissue homogenates. Figure S3: Astrocyte and microglia associated LIMASI lncRNA expression, and GFAP and IBA1 protein levels in archived brain tissues. Figure S4: A cell culture model of neuroinflammation induced by poly(I:C) challenge results in increased amyloid precursor protein (APP) expression. Figure S5: Viral mimetic stimulation upregulates LIMASI lncRNA and cytokine mRNA expression in human astrocytes.

Author Contributions

Conceptualization, H.S.C.; methodology, D.D.; software, T.V.; validation, D.D., J.A. and N.O.; formal analysis, D.D. and H.S.C.; investigation, D.D., J.A. and N.O.; resources, H.S.C. and M.K.L.; data curation, D.D. and G.M.B.; writing—original draft preparation, D.D. and H.S.C.; writing—review and editing, D.D., J.A., N.O., T.V., G.M.B. and M.K.L.; visualization, D.D., T.V. and H.S.C.; supervision, H.S.C.; project administration, D.D. and H.S.C.; funding acquisition, M.K.L. and H.S.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by NIH, grant numbers R21AI152937 and 3R21AI152937-02S1.

Institutional Review Board Statement

This animal study was approved by Institutional Animal Care and Use Committee of Florida International University (FIU). The deidentified archived human brain tissues were from ‘Harvard Brain Tissue Resource Center’ at McLean Hospital, Belmont, MA, and the ‘NICHD Brain and Tissue Bank for Developmental Disorders’ at the University of Maryland, Baltimore, MD, which are now part of the ‘NIH NeuroBioBank’. This study was conducted in accordance with the local legislation and FIU’s institutional guidelines and regulations.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding author(s).

Acknowledgments

Authors would like to thank Arianne Chung for technical support, and Mohan KM Karuppan, for help with the mouse study and brain tissue sectioning.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
ADAlzheimer’s disease
ADRDAlzheimer’s disease-related dementia
ApoEApolipoprotein E
APPAmyloid Precursor Protein
APPSweAPP with Swedish mutation (K595N/M596L)
AβAmyloid-beta
BACE1Beta-site Amyloid Precursor Protein Cleaving Enzyme
BACE1-ASBACE1-Antisense RNA
BDNF-ASBrain-Derived Neurotrophic Factor Antisense RNA
ceRNAcompeting endogenous RNA
CHI3L-1Chitinase-3-like protein 1
CRPC-reactive protein
CSFCerebrospinal fluid
CXCL-10C-X-C motif chemokine ligand 10
DAPI4′,6-diamidino-2-phenylindole
FADfamilial cases of Alzheimer’s disease
FBSFetal Bovine Serum
FISHFluorescence In Situ Hybridization
GFAPGlial Fibrillary Acidic Protein
IBA1Ionized calcium-binding adaptor molecule 1
ICAM1intercellular adhesion molecule-1
IKKβInhibitor of nuclear factor kappa B kinase subunit beta
IL-1βInterleukin-1β
IL-6Interleukin-6
LIMASILncRNA Inflammation and Mucous associated, Antisense to ICAM1
lncRNAslong noncoding RNAs lncRNAs
LOADLate-onset Alzheimer’s disease
MAGI2-AS3Membrane Associated Guanylate Kinase, WW And PDZ Domain Containing 2-Antisense RNA 3
MALAT1Metastasis Associated Lung Adenocarcinoma Transcript 1
MCP-1Monocyte Chemoattractant Protein-1
miRNAsmicroRNAs
MMP9Matrix metalloproteinase-9
NFTsNeurofibrillary tangles
PBSPhosphate-Buffered Saline
PDCD4Programmed cell death protein 4
PS1presenilin 1
PS1presenilin 2
qPCRQuantitative Polymerase Chain Reaction
RIPARadioimmunoprecipitation Assay buffer
RNARibonucleic Acid
SKP2S-phase kinase-associated protein 2
TLR3/7Toll-like receptors3/7
TNFαTumor necrosis factor α
uPARUrokinase-type Plasminogen Activator Receptor
VCAM1Vascular cell adhesion protein 1

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Figure 1. Robust neuroinflammatory activation in AD brain tissues (Braak stage IV or higher). Heat map showing multiplex protein array of select innate immune-associated cytokines and chemokines (A) and tissue remodeling factors (B) in NC and AD brain tissue homogenates (n = 3). Total RNA isolated from NC and AD brain tissues were analyzed by qPCR for relative expression of inflammatory markers (C) ICAM1 (D) IL-6, (E) IL-1β, (F) TNF mRNA (n = 4). * p < 0.05, ** p < 0.01, and *** p < 0.001 as analyzed by Student’s t-test.
Figure 1. Robust neuroinflammatory activation in AD brain tissues (Braak stage IV or higher). Heat map showing multiplex protein array of select innate immune-associated cytokines and chemokines (A) and tissue remodeling factors (B) in NC and AD brain tissue homogenates (n = 3). Total RNA isolated from NC and AD brain tissues were analyzed by qPCR for relative expression of inflammatory markers (C) ICAM1 (D) IL-6, (E) IL-1β, (F) TNF mRNA (n = 4). * p < 0.05, ** p < 0.01, and *** p < 0.001 as analyzed by Student’s t-test.
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Figure 2. Elevated LncRNA LIMASI expression in brain tissues of AD patients (Braak stage IV or higher) and 3xTg-AD mice brains. Total RNA isolated from NC and AD brain tissues were analyzed by qPCR for relative expression of (A) LIMASI transcript (n = 4). (B) Representative micrographs of brain cortex regions of NC and AD brain tissues stained for LIMASI transcripts (in red; scale −10 µ), along with DAPI-stained nuclei (blue) by RNA-FISH analysis. Inner panels show magnified images of inset regions; arrows indicate LIMASI transcripts. (C) LIMASI transcript levels were quantified as histo-score (H-score). (n = 3). ** p < 0.01, *** p < 0.001 as analyzed by Student’s t-test. (D) Representative micrographs of mouse brain tissues from wild-type (WT) C57BL/6 and 3xTg-AD mice for LIMASI (red) by RNA-FISH. Lower panels display magnified inset images of hippocampus brain regions immunostained for GFAP (green) to mark astrocytes and arrows indicate LIMASI expression (red). Scales: 250 µ (upper panels) and 5 µ (lower panels). Total RNA isolated from WT and 3xTg mice brain tissues were analyzed by qPCR for relative expression of (E) LIMASI transcripts, (F) Icam1, and (G) Il-6 mRNA (n = 3; ** p < 0.01, *** p < 0.001 as analyzed by Student’s t-test).
Figure 2. Elevated LncRNA LIMASI expression in brain tissues of AD patients (Braak stage IV or higher) and 3xTg-AD mice brains. Total RNA isolated from NC and AD brain tissues were analyzed by qPCR for relative expression of (A) LIMASI transcript (n = 4). (B) Representative micrographs of brain cortex regions of NC and AD brain tissues stained for LIMASI transcripts (in red; scale −10 µ), along with DAPI-stained nuclei (blue) by RNA-FISH analysis. Inner panels show magnified images of inset regions; arrows indicate LIMASI transcripts. (C) LIMASI transcript levels were quantified as histo-score (H-score). (n = 3). ** p < 0.01, *** p < 0.001 as analyzed by Student’s t-test. (D) Representative micrographs of mouse brain tissues from wild-type (WT) C57BL/6 and 3xTg-AD mice for LIMASI (red) by RNA-FISH. Lower panels display magnified inset images of hippocampus brain regions immunostained for GFAP (green) to mark astrocytes and arrows indicate LIMASI expression (red). Scales: 250 µ (upper panels) and 5 µ (lower panels). Total RNA isolated from WT and 3xTg mice brain tissues were analyzed by qPCR for relative expression of (E) LIMASI transcripts, (F) Icam1, and (G) Il-6 mRNA (n = 3; ** p < 0.01, *** p < 0.001 as analyzed by Student’s t-test).
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Figure 3. Cell culture model of neuroinflammation using viral mimetic poly (I:C) challenge recapitulates increased LIMASI lncRNA expression. SH-SY5Y-APPSwe cells were treated with different doses (0, 5, 10, 25, 50 and 100 µg/mL) and incubation times (2, 24, and 48 h) of poly(I:C). Total RNA isolated from poly(I:C) treated cells were analyzed by qPCR for relative expression of LIMASI (A,F), ICAM1 (B,G), IL-6 (C,H), IL-1β (D,I) and TNF (E,J). (n = 3) * p < 0.05, ** p < 0.01, and *** p < 0.001, as analyzed by one-way ANOVA. (K) Micrographs of SH-SY5Y-APPSwe cells showing LIMASI transcripts (red) as stained by RNA-FISH. Scale −10 µm. (L) LIMASI transcripts expression per cell as quantified by H-score analysis. (n = 4). * p < 0.05, ** p < 0.01, and *** p < 0.001, as analyzed by Student’s t-test.
Figure 3. Cell culture model of neuroinflammation using viral mimetic poly (I:C) challenge recapitulates increased LIMASI lncRNA expression. SH-SY5Y-APPSwe cells were treated with different doses (0, 5, 10, 25, 50 and 100 µg/mL) and incubation times (2, 24, and 48 h) of poly(I:C). Total RNA isolated from poly(I:C) treated cells were analyzed by qPCR for relative expression of LIMASI (A,F), ICAM1 (B,G), IL-6 (C,H), IL-1β (D,I) and TNF (E,J). (n = 3) * p < 0.05, ** p < 0.01, and *** p < 0.001, as analyzed by one-way ANOVA. (K) Micrographs of SH-SY5Y-APPSwe cells showing LIMASI transcripts (red) as stained by RNA-FISH. Scale −10 µm. (L) LIMASI transcripts expression per cell as quantified by H-score analysis. (n = 4). * p < 0.05, ** p < 0.01, and *** p < 0.001, as analyzed by Student’s t-test.
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Figure 4. In silico modeling analysis of potential miRNA interaction sites within lncRNA LIMASI using IntaRNA web server. Total RNA isolated from NC and AD brain tissues were analyzed by qPCR for relative expression of miRNAs (A) miR-150-5p and (B) miR-155-5p (n = 4). (C) Predicted base pairing interaction between miR-1915-3p (nucleotides 6–20, in red font) and exon 1 region of LIMASI (nucleotides 64–78, blue font). (D) Predicted interaction of miR-122-5p (red) with LIMASI exon 2 (blue), spanning nucleotides 171–204. (E) Predicted binding of miR-155-5p (nucleotides 13–21, red) to exon 2 region of LIMASI (nucleotides 324–332, blue). (F) Predicted interaction between miR-150-5p (nucleotides 1–16, red) and LIMASI exon 3 (nucleotides 797–806, blue).
Figure 4. In silico modeling analysis of potential miRNA interaction sites within lncRNA LIMASI using IntaRNA web server. Total RNA isolated from NC and AD brain tissues were analyzed by qPCR for relative expression of miRNAs (A) miR-150-5p and (B) miR-155-5p (n = 4). (C) Predicted base pairing interaction between miR-1915-3p (nucleotides 6–20, in red font) and exon 1 region of LIMASI (nucleotides 64–78, blue font). (D) Predicted interaction of miR-122-5p (red) with LIMASI exon 2 (blue), spanning nucleotides 171–204. (E) Predicted binding of miR-155-5p (nucleotides 13–21, red) to exon 2 region of LIMASI (nucleotides 324–332, blue). (F) Predicted interaction between miR-150-5p (nucleotides 1–16, red) and LIMASI exon 3 (nucleotides 797–806, blue).
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Table 1. Demographics of the non-diseased controls (NC) and AD brain tissue donors.
Table 1. Demographics of the non-diseased controls (NC) and AD brain tissue donors.
SamplesGender (M/F)Age (Y)Avg. Age (Y)PMI (h)Avg. PMI (h)Pathology
Non-Diseased ControlsC-1F8875.1 ± 3.6017.0619.20 ± 1.82Control
C-2M7614.6Control
C-3M7717.06Control
C-4M8314.7Control
NC-5F7728.00Control
NC-6M6121.00Control
NC-7M6422.00Control
NC-11NANANAControl
NC-12NANANAControl
AD patientsAD-1F8382.22 ± 3.556.9216.38 ± 2.50AD Braak 5
AD-2M8610.92AD Braak 4
AD-3F5928.33AD Braak 6
A-5M9515.00AD Braak 6
A-6M8717.45AD Braak 5
A-7M7216.08AD Braak 6
A-8M846.66AD Braak 6
AD-11M9024.00AD Braak 4
AD-12F8422.08AD Braak 4
The gender distribution of male/female (M/F), age in years (Y), and the postmortem interval (PMI) for tissue collection in hours (h); NA—not available.
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Devadoss, D.; Akkaoui, J.; Orso, N.; Viswanathan, T.; Borchert, G.M.; Lakshmana, M.K.; Chand, H.S. A Novel Competing Endogenous RNA Linked to Dysregulated Neuroinflammation in Alzheimer’s Disease. Cells 2026, 15, 412. https://doi.org/10.3390/cells15050412

AMA Style

Devadoss D, Akkaoui J, Orso N, Viswanathan T, Borchert GM, Lakshmana MK, Chand HS. A Novel Competing Endogenous RNA Linked to Dysregulated Neuroinflammation in Alzheimer’s Disease. Cells. 2026; 15(5):412. https://doi.org/10.3390/cells15050412

Chicago/Turabian Style

Devadoss, Dinesh, Juliet Akkaoui, Natalia Orso, Thiruselvam Viswanathan, Glen M. Borchert, Madepalli K. Lakshmana, and Hitendra S. Chand. 2026. "A Novel Competing Endogenous RNA Linked to Dysregulated Neuroinflammation in Alzheimer’s Disease" Cells 15, no. 5: 412. https://doi.org/10.3390/cells15050412

APA Style

Devadoss, D., Akkaoui, J., Orso, N., Viswanathan, T., Borchert, G. M., Lakshmana, M. K., & Chand, H. S. (2026). A Novel Competing Endogenous RNA Linked to Dysregulated Neuroinflammation in Alzheimer’s Disease. Cells, 15(5), 412. https://doi.org/10.3390/cells15050412

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