Research ArticleExpression Profiles of Long Noncoding RNAs in IntranasalLPS-Mediated Alzheimer’s Disease Model in Mice

Liang Tang ,1,2 Lan Liu,3 Guangyi Li,1,2 Pengcheng Jiang,1,2

YanWang,1,2 and Jianming Li 1,2,4

1Department of Human Anatomy, Histology and Embryology, Institute of Neuroscience, Changsha Medical University,Changsha, China

2Department of Human Anatomy, School of Basic Medical Science, Changsha Medical University, Changsha, China3Medical College, Tibet University, Lhasa, China4Department of Neurology, Xiang-ya Hospital, Central South University, Changsha, China

Correspondence should be addressed to Jianming Li; ljming0901@sina.com

Received 11 August 2018; Revised 23 October 2018; Accepted 30 December 2018; Published 21 January 2019

Academic Editor: Cristiano Capurso

Copyright © 2019 Liang Tang et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Alzheimer’s disease (AD), characterized by memory loss, cognitive decline, and dementia, is a progressive neurodegenerativedisease. Although the long noncoding RNAs (lncRNAs) have recently been identified to play a role in the pathogenesis of AD,the specific effects of lncRNAs in AD remain unclear. In present study, we have investigated the expression profiles of lncRNAsin hippocampal of intranasal LPS-mediated Alzheimer’s disease models in mice by microarray method. A total of 395 lncRNAsand 123 mRNAs was detected to express differently in AD models and controls (>2.0 folds, p<0.05). The microarray expressionwas validated by Quantitative Real-Time-PCR (qRT-PCR).The pathway analysis showed the mRNAs that correlatedwith lncRNAswere involved in inflammation, apoptosis, and nervous system related pathways. The lncRNA-TFs network analysis suggested thelncRNAs were mostly regulated by HMGA2, ONECUT2, FOXO1, and CDC5L. Additionally, lncRNA-target-TFs network analysisindicated the FOXL1, CDC5L, ONECUT2, and CDX1 to be the TFs most likely to regulate the production of these lncRNAs.This isthe first study to investigate lncRNAs expression pattern in intranasal LPS-mediated Alzheimer’s disease model in mice. And theseresults may facilitate the understanding of the pathogenesis of AD targeting lncRNAs.

1. Introduction

Alzheimer’s disease (AD), with principal clinical manifes-tations of memory loss, cognitive decline, and dementia, isa common progressive neurodegenerative disease in agingpeople worldwide [1, 2].Themain neuropathic characteristicsof AD are marked by extracellular amyloid-𝛽 (A𝛽) depo-sition, neurofibrillary tangles (NFTs), loss of neuron, andsynaptic and dystrophic neuritis [3–5]. The pathogenesis ofAD is largely unknown. Multiple factors such as genetics, freeradical injury, apoptosis, and inflammation were consideredto be involved in the development of AD [6–8]. Recently,many susceptible genes including BACE1 [9], PS1/2 [10], APP[11], APOE [12], and SORL1 [13] have been found to beassociated with the AD risk. However, the recent associated-genes could not explain the whole pathogenesis of AD.

Recent genomic studies have investigated thousands ofnoncoding RNAs (ncRNA) in both animal models andhuman beings. The long noncoding RNAs (lncRNAs),defined as the transcripts of >200bp, was considered to beone of the most important ncRNAs. Increasing evidence hasindicated that lncRNAs may participate in multiple essentialbiological processes such as genomic imprinting, immuneresponse, and disease development [14–16]. In the last decade,the role of lncRNAs in AD has gained considerable attentionand has been investigated by a multitude of studies. CertainlncRNAs such as BACE1-AS [17], 51A [18], 17A [19], NDM29[20], BC200 [21], andNAT-Rad18 [22] have been identified inhuman brain tissues with AD. Moreover, the expression pro-files of lncRNAs in AD patients [23, 24], transgenic AD micemodel [25], and AD rat model [26] have been investigated.Althoughmany studies on the expression profiles of lncRNAs

HindawiBioMed Research InternationalVolume 2019, Article ID 9642589, 14 pageshttps://doi.org/10.1155/2019/9642589

2 BioMed Research International

in AD models and human beings have been performed, theknowledge of the expression patterns and potential biologicalfunctions of lncRNAs in AD remains to be far from clear.

In the present study, we have investigated the differentexpression profiles of AD-related lncRNAs and mRNAs byusing microarray analysis in the hippocampus of intranasalLPS-mediated mice model, as well as matched controls.The results were identified by qRT-PCR. And the geneontology (GO), Kyoto Encyclopedia of Genes and Genomes(KEGG), coexpression of lncRNAs-mRNAs network, poten-tial lncRNA-TF (transcription factors) network, and lncRNA-target-TFs network were analyzed.

2. Materials and Methods

2.1. Animals and Study Design. The homozygous maleC57BL/6J mice, 20±5g, were purchased from Hunan slackscene of laboratory animal Co., Ltd. The protocols of theseanimals followed the National Institutes of Health Guide forthe Care and Use of Laboratory Animals. And the researchprocedures were approved by the Ethics Committee of theChangsha Medical University, China. The mice were housedin a room with the temperature of 22±0.8∘C, 50±10% relativehumidity, 12h light/dark cycle, and free to water and food.A total of 20 mice were randomly divided into two groups(AD group: n=10, control group: n=10). The AD group wastreated with intranasal LPS 10ul (right side, 1mg/ml), whilethe control groupwas treatedwith intranasal saline 10ul (rightside, 0.9%) with the treatment duration of 5 months.

2.2. Morris Water Maze Test. The Morris water maze testwas conducted to evaluate the change of spatial learningand memory deficits at the last six day in each month (fiveconsecutive days of escape training and one day of probetrail). The test protocol followed a previously published studyby Vorhees et al [27]. The trials and movements tracking ofthe animals were recorded by the ANY-maze video trackingsystem (Stoelting Co., USA). The swim paths, escape latency,and the frequency of crossing the target platform wererecorded and analyzed.

2.3. Sample Collection. The mice were anesthetized withpentobarbital sodium (0.2%, 0.1ml/10g) by intraperitonealinjection. The cerebrospinal fluid (CSF) was collected bypuncturing the cerebellomedullary cistern. And the periph-eral blood (PB) was obtained by removing the eyeball. Allthe samples were stored at 4∘C. In addition, the hippocampaltissues and whole brains were stored at -80∘C until furtheranalysis.

2.4. ELISA. The level of proinflammatory cytokines includ-ing interleukin-6 (IL6), tumor necrosis factor- (TNF-) 𝛼,IL1-𝛽, and IL10 in both CSF and PB were measured byenzyme-linked immunosorbent assay (ELISA). The ELISAkits were purchased from Shanghai Beinuo Bio Co., Ltd. Themicroplate spectrophotometer (Multiskan MK3, Finland)was applied to detect the proinflammatory cytokines. Thedata is represented by mean ± standard deviation (mean ±

SD). The t-test was applied in the intergroup comparisons(AD: CSF and PB; AD and controls). Linear correlationanalysis was used. P < 0.05 was considered statisticallysignificant. SPSS 15.0 were applied to carry out statisticalanalysis.

2.5. Immunohistochemistry. Three hippocampal tissues ofAD models and controls were disposed in parallel. Tissueswere first treated free-floating with 5% H

2O2in PBS for

30 min and 5% normal bovine serum in PBS with 0.3%Triton X-100 for 1h to lower nonspecific reactivity. The tissueswere first incubated overnight with mouse anti-GFAP (1:300;Chemicon, USA) at 4∘C, and then reacted with bovine anti-mouse immunoglobulin G (IgG) (1:400; Chemicon, USA)for 1h, incubated with avidin-biotin complex reagents (1:400;Burlingame, CA, USA) at room temperature for 1h. Theimmunoreactive product was visualized in 0.003%H

2O2and

0.05% 3, 3’-diaminobenzidine. The results were detected bylight microscope.

2.6. Western Blot Analysis. The frozen hippocampal tissuesof AD models and controls were homogenized by son-ication and centrifuged at 15,000 × g. Protein was col-lected from the supernatants and measured by BCA pro-tein assay kit (Thermo Fisher Scientific). 50 𝜇g proteinwas separated with 15% sodium dodecyl sulfate-PAGE gelsand then electrotransferred onto polyvinylidene fluoridemembranes (Millipore, Shanghai Trading Company Ltd.,Shanghai, China). Separated protein was then immunoblot-ted with mouse anti-GFAP (1:400; Wuhan Servicebio Tech-nology Co., Ltd., Wuhan, China) and mouse anti-GAPDH(1:5000; Wuhan Servicebio Technology Co., Ltd., Wuhan,China).Themembranes further reacted with anti-mouse IgG(1:20,000; Thermo Fisher Scientific). Immunoblot signalingwas visualized with the Pierce ECL-Plus Western BlottingSubstrate detection kit (Thermo Fisher Scientific), followedby X-ray film exposure and image capture in a laser scanner.Quantitative analysis of GFAP-positive dots was performedwith Image-Pro Plus software.

2.7. RNA Extraction. The total RNA was isolated from eachhippocampal tissue sample by using AMBION TRIZOLreagent kit (Invitrogen, Grand Island, NY, USA). The RNAquantity and integrity weremeasured byNanoDropND-1000(Thermo Scientific) and Agilent 2100 bioanalyzer (AgilentTechnologies).

2.8. Microarray Analysis. The total RNA was purified byRNaseyMini Kit (Qiagen p/n 74104).Then, fluorescent cRNAwith Cyanine-3-CTP was prepared by Quick Amp LabelingKit, One-Color (Agilent p/n 5190-2305).The labelled cRNAswere purified using an RNeasy Mini Kit (Qiagen p/n 74104).The labeled cRNA was hybridized onto the microarrayusing an Agilent Gene Expression Hybridization Kit (Agilentp/n 5188-5242). And then the hybridized microarrays werewashed, fixed, and scanned using an Agilent MicroarrayScanner (Agilent p/n G2505C). Data were extracted using

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Feature Extraction Software (version 10.7.1.1, Agilent Tech-nologies). All the experiments were carried out according tothe manufacturer’s standard protocols.The experiments wereperformed by OEBiotech Corporation (Shanghai, China).Agilent mouse lncRNA Microarray V3 (4∗180K, Design ID:084388) was used in the present experiment.

2.9. Differential Expression Analysis. The data analysis wasperformed by Genespring (version 13.1, Agilent, SantaClara, USA). All the raw data including original signalvalues, normalized signal values, and detailed annotationinformation were normalized by quantile method. t-testwas used to screen differentially expressed lncRNAs andmRNAs. And a fold change>= 2.0 and a P value <= 0.05between the compared two groups for lncRNAs or mRNAswas considered as differentially expressed. The hierarchicalclustering of differentially expressed lncRNAs and mRNAsbetween AD and control hippocampal samples was alsoperformed to display the distinguishable genes’ expressionpattern among samples by using the Genespring (version13.1, Agilent, Santa Clara, USA). Afterwards, Gene Ontologyenrichment analysis (GO) (http://www.geneontology.org)and Kyoto Encyclopedia of Genes and Genomes (KEGG)analysis (http://www.genome.jp/kegg/) were applied todetermine the roles of these differentially expressedmRNAs.

2.10.Quantitative Real-Time-PCR(qRT-PCR). The total RNAsamples were purified with DNase. And the cDNA weresynthesized by using a TIANscript RT Kit (Invitrogen, GrandIsland, NY, USA). The qRT-PCR was performed using theSYBR Green Premix DimerEraser kit (TaKaRa Bio Inc.,Dalian, China) on the Roche LightCycler 480 Instrument II.The relative expression levels of lncRNAs and mRNAs wereanalyzed using the 2−ΔΔCt method and were normalized toGAPDH. Student’s t-testwas used to access the significance ofdifferences. ANOVAwas performed for repeatedmeasures. Avalue of p < 0.05 was considered to be statistically significant.The statistical tests were performed using the SPSS (version19.0, SPSS, Inc., Chicago, IL, USA). The primers of randomlyselected lncRNA and mRNAs were listed in SupplementaryFile Table 1 (Table s1).

2.11. Coexpression Network Analysis. The normalized signalintensities of specific mRNA and lncRNA expression levelswere used to construct coexpression network. Pearson’scorrelation coefficients (PCC)(≥0.7) were used to identify thecoexpression of lncRNAs and mRNAs. A p < 0.05 indicatedstatistically significant correlation. In addition, the correla-tions between lncRNA-TFs and lncRNA-target mRNA-TFswere detected by hypergeometric distribution analysis. Themost recent data released by the Encyclopedia of DNAElements (ENCODE) on TFs and their targets were used inthe present analysis. The co expression of lncRNA-mRNA,lncRNA-TFs, and lncRNA-target mRNA-TFs networks wereconstructed by using Cytoscape software (The CytoscapeConsortium, San Diego, CA, USA).

3. Results

3.1. Animal Models Construction

(1) Behavioral Alterations in AD Models and Controls. Todetect the spatial learning and memory deficits after LPStreatment in the mice, Morris water maze test was performedat the last six days of each month. As shown in Figures1(a) and 1(b), in visible platform tests mice with chronicintranasal LPS instillation exhibited a longer latency andswimming distances to escape onto the visible platform thanthat in controls treated with saline, indicating weaker spatiallearning ability in AD models than controls. In the probetrial, mice with chronic intranasal LPS instillation spentsignificantly more time to travel into the fourth quadrant,where the hidden platform was previously placed, thanthe controls did (Figures 1(c) and 1(d)), which revealedweaker spatial memory ability in the AD model thancontrols.

(2) Immune Response in Mice with Chronic Intranasal LPSInstillation. To examine further the influence of intranasalLPS instillation in inducing systemic or locus immuneresponse, we detected the levels of IL1-𝛽, IL6, IL10, andTNF-𝛼 in peripheral blood of AD models and controls,as well as in CSF and PB of AD models. As shown inFigure 2(a), no significant difference in serum IL1-𝛽, IL6,IL10, and TNF-𝛼 between AD models and controls wasfound. In addition, significant differences were detected forthe levels of IL1-𝛽, IL6, IL10, and TNF-𝛼 between CSF andPB in ADmodels.These results may reveal that the intranasalLPS instillation could only induce locus immune responsein central nervous system (CNS), but not systemic immuneresponses (Figure 2(b)).

(3) Activation of Astrocyte in AD and Control in Mice. GFAPis a characteristic marker of astrocytes. When the body isstimulated, the astrocytes in certain parts of the centralnervous system appear positive for GFAP. We next definedwhether GFAP accumulation was involved in our modelby immunohistochemistry and western blots. As shown inFigures 3(a)–3(f), the expression of GFAP in AD modelstreated with LPS instillation was found to be elevated com-pared with saline treated controls. Notably, the expressionlevel of GFAP decreased along the olfactory bulb to thehippocampus, whichmay indicate a potential role of the nasalpassage in the pathogenesis of AD. The number of GFAP-positive dots in AD models treated with LPS instillation wassignificantly increased compared with saline treated controls(Figures 3(g) and 3(h), p<0.05).

3.2. Differentially Expressed LncRNAs and MRNAs in In-tranasal LPS-Mediated AD Mice. The normalized raw datafrom array image were used to assess the expression levels oflncRNAs andmRNAs in ADmice and controls. A total of 395significantly dysregulated (172 upregulated and 223 down-regulated) lncRNAs were identified. NONMMUT034127.2,with a FC of 9.95, was the most upregulated lncRNA. And,

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Figure 1: Testing of spatial learning and memory in AD models and controls by Morris water maze. (a) The swim paths and time of findingthe hidden platform in the control group was significantly shorter than that of the AD group, indicating that intranasal LPS impairs spatiallearning and memory (n = 10/group). (b) Significant difference of escape latency between AD and control groups was observed at the lastthree days in the fourth and fifth months (∗ p<0.05) (n = 10/group). (c) Significant difference of the frequency of crossing the target platformbetweenAD and control groups (∗ p<0.05). Data are expressed as themean ± standard error of themean (SEM)(n = 10/group). (d)The imageshows the control group had a crossing frequency approximately 2 times the AD group (n = 10/group).

NONMMUT079254.1, with a FC of 7.51, was the most down-regulated lncRNA. In addition, 123 significantly dysregulated(43 up-regulated and 80 downregulated) mRNAs were alsodetected. The most upregulated and downregulated mRNAswere XM 006514426 and NM 146439, with FCs of 9.53 and4.52 respectively (Figures 4(a) and 4(b), Table s2, and Tables3).

With regard to the AD mouse model conducted byintranasal LPS instillation, 34 mRNAs related to neurons/nervous system diseases, inflammation, and olfactory path-waywere selected for further analysis. Among the 34mRNAs,the most up- and downregulated mRNAs were AK080003(Cd274) and ENSMUST00000137938 (Itpr2), with FCs of3.06 and 2.96 separately. A total of 24 lncRNAs coexpressedwith the selected 34 mRNAs with the highest Pearson’scorrelation coefficients were chosen. For the selected 24lncRNAs, AK158273 (FC=4.89) and NONMMUT079247.1(FC=2.98) were the most up- and downregulated lncRNAs(Figure s1a and s1b and Table s4). The hierarchical clustering

was performed to display the distinguishable lncRNAs andmRNAs expression patterns among AD mice and controls.

The results of microarray were verified by using qRT-PCR. Four lncRNAs and mRNAs were randomly selectedand the results were consistent with the microarray chip data(Figures 4(c) and 4(d)).

3.3. Coexpression Network and Potential Functions Identifi-cation. The correlation between top100 (100 up- and 100downregulated) dysregulated lncRNAs and mRNAs werepredicted. The p value of each lncRNA-mRNA correlationwas ranked. The coexpression network was conducted withthe selected lncRNA-mRNA correlations with the highestPearson correlation coefficient (Figure 5). A total of 13246network nodes and 548607 connections (269022 negativeand 279585 positive interactions) were involved in the net-work. Furthermore, the correlation between the selected 34mRNAs and their coexpressed lncRNAs were predicted. A

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Figure 2:The expression levels of inflammatory factors inADand control groups. (a)No significant differencewas detected for the expressionlevels of IL6, TNF-𝛼, IL1-𝛽, and IL10 in peripheral blood of AD and control groups (p>0.05) (n = 6/group). (b) The expression levels of IL6,TNF-𝛼, IL1-𝛽, and IL10 in cerebrospinal fluid were significantly different from that in peripheral blood of AD group (p>0.05) (n = 6/group).Data are expressed as the mean ± standard error of the mean (SEM).

total of 359 lncRNAs, 5948 connections(3173 negative and2775 positive interactions) were involved in the network(Figure s2).

3.4. KEGG+GO. For function prediction of lncRNAs, thecoexpressed mRNAs for each differentiated lncRNAs werefirst calculated. And then a functional enrichment analysisof this set of coexpressed mRNAs was conducted. Theenriched functional terms were used as the predicted func-tional term of given lncRNA. The coexpressed mRNAs oflncRNAs were identified by calculating Pearson correlationwith correlation P value <0.05. Then, the hypergeometriccumulative distribution function was used to calculate theenrichment of functional terms in annotation of coexpressedmRNAs.

As shown in Figure 6(d) and Table s5, the KEGGanalysis indicated that the lncRNA were involved in theinflammation progress (NF-kappa B signaling pathway, TNFsignaling pathway, Inflammatory mediator regulation ofTRP channels, and cell adhesion molecules (CAMs)) andneuronal function or nervous system diseases (Alzheimer’sdisease, Huntington’s disease, neuroactive ligand-receptorinteraction, and synaptic vesicle cycle). Furthermore, theGOenrichment analysis indicated the differentially expressedlncRNAsweremostly enriched in keratinocyte differentiationin its Biological process (Figure 6(c)), contractile ring in itsCellular Component (Figure 6(b)), and calcium ion bindingin its molecular function (Figure 6(a)).

3.5. LncRNA-TFs Network Analysis. The TFs were consid-ered to regulate the production of lncRNAs. Thus, the200 most differentially regulated lncRNAs (100 upregulated

and 100 downregulated) were selected and predicted theTFs. These 200 lncRNAs were indicated to be regulatedby 248 TFs. The lncRNA-TFs network was conducted onthe most 5 related lncRNA-TFs pairs according to the Pvalue. The results showed that these lncRNAs were mostlyregulated by HMGA2, ONECUT2, FOXO1, CDC5L, TFDP2,ZBTB16, E2F1, NKX3-1, and FOXJ2 (Figure 7). We addi-tionally predicted lncRNA-TFs pairs with the selected 24lncRNAs related to neuron function/nervous systemdiseases,inflammation, and olfactory pathway.These 24 lncRNAswereindicated to be regulated by 179 TFs and mostly regulatedby TFDP2, ONECUT2, NKX3-1, FOXL1, CDC5L, and FOXJ2(Figure s3).

3.6. LncRNA-Target-TFs Network Analysis. To investigate thefunctions of each lncRNA in AD, we analyzed the top 20mostly differentially expressed lncRNAs (10 upregulated and10 downregulated) between AD mice and controls. A total of119 TFs and 5698 mRNAs were predicted to regulate or bethe target of these lncRNAs.The lncRNA-target-TFs networkwas conducted on the most 2 related lncRNA-mRNA andlncRNA-TFs pairs according to the p value (Figure 8). Amongthese TFs, E2F1, E2F4, and TFDP1 were predicted to regulateseveral lncRNAs. For example, E2F1 and E2F4 were pre-dicted to regulate AK013093, NONMMUT136363.1, NONM-MUT101632.1, NONMMUT085451.1, NONMMUT080699.1,NONMMUT080006.1, NONMMUT037057.2, and NONM-MUT025624.2. TFDP1 was predicted to regulate AK013093,NONMMUT080699.1, NONMMUT101632.1, and NONM-MUT136363.1.

In addition, we analyzed the selected 24 lncRNAs. A totalof 183 TFs and 6652 mRNAs were predicted to regulate or bethe target of these lncRNAs (Figure s4). Among these TFs,

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Figure 3: Light microscopic images show the distribution of GFAP immunolabeling across the brain of Intranasal LPS mice and controls.(a)–(f) The images revealed that the GFAP was expressed higher in Intranasal LPS mice than in control mice. And the GFAP expressiondecreased along the olfactory bulb to the hippocampus. Scale bar= 1000 𝜇m in (a) and (d), 200 𝜇m in (b) and (e), and 50 𝜇m in (c) and (f).(g) Western blot images from Intranasal LPS mice and controls. (h) Quantitative summaries of the protein levels relative to GAPDH as aninternal control, expressed as a percentage of GAPDH optical density (o.d.) for the groups (n = 3/group). The ∼ 50 kDa GFAP band is notreadily seen in control mice compared with Intranasal LPS mice. Statistical results (Kruskal–Wallis nonparametric test with Dunn’s multiplepost hoc comparison) are shown in the bar graphs, with “∗” indicating significant intergroup differences.

FOXL1, CDC5L, ONECUT2, and CDX1 were predicted toregulate several lncRNAs. CDC5L was predicted to regulateAK045227, AK045590, AK149638, and AK158273. CDX1 waspredicted to regulate NONMMUT135177.1, AK045227, and

NONMMUT104720.1. ONECUT2 was predicted to regu-late NONMMUT099169.1, NONMMUT102111.1, and NON-MMUT115705.1. Moreover, most of these TFs were relatedwith inflammation or apoptosis processes.

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Figure 4:Thehierarchical clusteringof the differentially expressed lncRNAs (a) andmRNAs (b) in AD(n= 3/group) and control(n = 3/group)hippocampal tissues. (c) and (d) The quantitative real-time PCR (qRT-PCR) validated 4 randomly selected lncRNAs and mRNAs. The qRT-PCR results were consistent with the microarray data. (c) lncRNAS. (d) mRNAs.

4. Discussion

In the present study, we investigated the expression profilesof lncRNAs in intranasal LPS-mediated Alzheimer’s diseasemodel in mice. A total of 395 lncRNAs (172 upregulated and223 downregulated) and 123 mRNAs (43 upregulated and 80downregulated) were identified to be differently expressedbetween ADmice and control. The results ofmicroarray wereidentified by qRT-PCR.

Dysregulated expression of lncRNAs has been detectedin postmortem human brains with AD or late-onset AD[23, 24]. In addition, the expression profiles of lncRNAs inADmodels including triple transgenic mice and A𝛽 intracerebral

injection rats were also reported [25–27]. The transgenicmodel studies have mainly focused on several special genesincluding APP, PS1/2 [28, 29], and Tau [30]. However, noneof these genes can replicate the pathogenesis affected bymultiple factors in AD. The A𝛽 infusion model stronglycomplements the use of animal models in exploring the roleof inflammatory and immune response in the developmentof AD. However, the A𝛽 could not explain all aspects ofAD pathogenesis [31], especially for the chronic and long-term endotoxin exposure such as LPS. LPS has been usedin building AD models by intraperitoneal injection or brainstereotaxic injection [32, 33]. The former might result insystemic inflammation and the latter might simulate acute or

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Iqcf6

Rpl39l

Klk1b11 Prl7a2

Cldn7

Smg8

NONMMUT117663.1

Hoxc11

Nkx1-2

Khk

4930548H24Rik

Prl8a9

NONMMUT086230.1

D16Ertd472e

Scgb2b12

Vmn1r38

Izumo3

NovelTID_00001515

Defb1

Lctl

Ankk1

Olfr160

Gm5346

Olfr876

Tchhl1

Mixl1

Ear7

NONMMUT077667.1

Ube4a

Myrfl

Ankrd16

Ace3

Lrrc2

NONMMUT101632.1

NONMMUT136363.1

Lce1k

NONMMUT080006.1

NovelTID_00000350

Klhl12Cluh

XR_396660

Lrrc25 Il1rap

NONMMUT091542.1 NONMMUT075062.1AK038790

Gm40556

NONMMUT089483.1

Brwd1

NONMMUT082935.1 NONMMUT083571.1

Olfr324 Slc7a12 Pdzd7

NONMMUT104645.1 NONMMUT104720.1

Ltbp4

NONMMUT125608.1 NONMMUT126056.1NONMMUT119214.1 XR_376908 XR_384963

NONMMUT088599.1 NONMMUT136499.1NONMMUT094117.1

AU044856 LOC102632383Olfr770

NONMMUT115688.1

Irak4

NONMMUT092631.1

Wdr82

Zscan10

Nlrp4b

NONMMUT114722.1

Ncbp1

NONMMUT082660.1

NONMMUT131563.1

Psg27

XR_393617

Gskip

Fam228a

NONMMUT132898.1

Osgin1Olfr372Ablim3 Mdh1b Sema3dC920025E04Rik

NONMMUT129203.1 BB617541AK077539NONMMUT126530.1

Stx3

NONMMUT123605.1

Birc6 Mical2 Dcun1d2

Gm32204Olfr648 Arhgef7Aunip Ttc3

NR_045801

Cep131

XR_378948

NONMMUT072621.2AK013093

Cpne4

NONMMUT129577.1

Gdap9

NONMMUT028103.2NONMMUT096777.1AK020655

C030009H01Rik

NONMMUT124161.1NONMMUT093474.1

Tsn

A230046K03Rik

NONMMUT038394.2NONMMUT037057.2

Prdm11H2-M10.3

NONMMUT132449.1 NovelTID_00003643

LOC102642104

NONMMUT089419.1

H2-M9Olfr1180

NONMMUT111921.1

Dcdc2b

Stk4

NONMMUT134128.11700125H20Rik

Gm17689

Olfr724

NONMMUT137442.1

Gimap7

2810021J22Rik

BC053393

AK045227

NONMMUT098003.1

NONMMUT098363.1NONMMUT095214.1 NR_040645NONMMUT119191.1 NONMMUT130006.1AK037071 NONMMUT105185.1 NONMMUT134190.1 NONMMUT020270.2

2900076A07Rik Acrv1 Epha6 A130010J15RikMsx2Adam28Olfr1020 Cma1 Ugt8a

AK041433NONMMUT127241.1 XR_883967NONMMUT079416.1 AK033130XR_884158 AK089745AK020434 NONMMUT111826.1

Rfpl4Fbln1 Rnf213Nisch Tmcc3 1700066B19RikTmem181a Nol11 Cd5

NovelTID_00000467 NONMMUT008894.2NONMMUT076015.1XR_875106NONMMUT025195.2 NONMMUT108479.1 NONMMUT117382.1CJ204422 AK087177

AK019930 AK043355 NONMMUT097621.1AK143372 NR_040748NONMMUT102257.1 NONMMUT129492.1NONMMUT134941.1 NONMMUT093066.1

Olfr69 Olfr965Crct1Slc25a37 Rpl7 Ren1 Pag1Sult5a1 Brd4

Tead1 Tbx6 Olfr301 Olfr394

NONMMUT129607.1 NONMMUT117752.1NONMMUT105303.1 NONMMUT127336.1

Vmn1r192Hbb-bh1 Hook3 Pcdh9 Slit2 Cbfa2t3 AU014756

NONMMUT082031.1 NovelTID_00002453 AK033243

Notch4

AK041536

Rassf4 Zfp345 Plekhg3

Rpl7l1 Bicd1

Vmn1r171Slamf1

Pkn1Hsph1

Ntrk3Wdr38Krtap19-2Slc5a1

NONMMUT118845.1

Itpr2

NONMMUT088292.1

Rbm44

Olfr137

Olfr1010

Olfr1497 4933425L06Rik

NONMMUT098187.1

Cyc1NONMMUT132232.1 Mog

Gm14393

NONMMUT080699.1

Mroh1

NONMMUT107764.1Loxhd1

AK046497

Cep89

Ift46

Olfr1313

Prss40

Olfr1446

Nudt8

Phlda2Slc12a1

Drg2 Gm13124

NONMMUT137392.1

Ablim2

Dcaf6 Fbxw13

NONMMUT121570.1

Plcb3

AK013746

Ilkap

Cipc

Zswim8

NONMMUT124781.1

Thoc2

AK089564

NONMMUT023216.2

NONMMUT107145.1Fam135a

NONMMUT109302.1

Gm648

4930504O13Rik

BU962357

Lars2

Cyp2d26Adam34

Adgrg54930435E12Rik

Olfr873

Parp12

Dirc2

AK051481

Actg2

1190003K10Rik

Olfr225

NONMMUT076455.1

Dkk4

Cypt3H2-Ea-ps

4-Sep

Olfr1221

ElnOlfr1328

Olfr1462 Vmn1r44Vmn2r23

Figure 5: LncRNA-mRNA-network analysis. Purple squares represent dysregulated mRNAs, green arrows represent dysregulated lncRNAs.The dotted lines between lncRNAs and mRNAs indicate a negative correlation, while the solid lines indicate a positive correlation.

BioMed Research International 9

0 0.5 1 1.5 2 2.5

calcium ion bindingintegrin binding

dolichyl pyrophosphate Glc1Man9GlcNAc2 alpha-1,3-glucosyltransferase activitysalicylic acid glucosyltransferase (glucoside-forming) activity

beta-1,4-mannosyltransferase activitylipopolysaccharide-1,5-galactosyltransferase activity

UDP-glucose:glycoprotein glucosyltransferase activitydolichyl pyrophosphate Man7GlcNAc2 alpha-1,3-glucosyltransferase activity

cellulose synthase activitychondroitin hydrolase activity

-log10(Pvalue)

Molecular Function

(a)

0 0.5 1 1.5 2 2.5 3 3.5

contractile ringcornified envelopeplasma membrane

keratin filamentanchored component of membrane

zonula adherensextracellular matrix

inner dynein armflotillin complex

dystrophin-associated glycoprotein complex

-log10(Pvalue)

Cellular Component

(b)

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

keratinocyte differentiationpatterning of blood vessels

morphogenesis of a branching structureepidermis development

negative regulation of axon extensionpositive regulation of cell-matrix adhesion

negative regulation of extrinsic apoptotic signaling pathwaykeratinization

positive regulation of cell-substrate adhesionnegative regulation of neuron projection development

-log10(Pvalue)

Biological Process

(c)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

Cell adhesion molecules (CAMs)Thyroid hormone synthesis

Viral myocarditisPancreatic secretionCholinergic synapse

Leukocyte transendothelial migrationHTLV-I infection

Vascular smooth muscle contractionUbiquitin mediated proteolysis

alpha-Linolenic acid metabolism

-log10(Pvalue)

KEGG

(d)

Figure 6: KEGG pathway and GO enrichment analysis of differentially expressed lncRNAs. The top 10 most enriched GO categories andpathways were calculated and plotted. (a) Molecular function; (b) cellular component; (c) biological process; (d) KEGG pathway.

subacute response in models. Neither model could replicatethe chronic and local inflammatory and progressive degen-eration in AD. In addition, LPS was a component of the airpollutants PM2.5 [34], which can be absorbed via the noseand bypass the blood brain barrier. Research has shown thatpatients with AD and PD have smell loss and olfactory bulbpathology after being exposed in LPS in long terms [35, 36].In present study, we successfully generated an AD modelvia unilateral intranasal instillation of LPS, which provided a

tool in investigating the intracephalic chronic inflammation-mediated pathogenesis in AD. To our knowledge, this is thefirst study to investigate the expression profiles of lncRNAsin the hippocampus in LPS-mediated AD model, whichmay facilitate the understanding of lncRNAs related to theintracephalic chronic inflammation-mediated pathogenesisin AD.

Neuroinflammation induced by A𝛽, Tau, and microgliaactivity in AD has been widely reported [37, 38]. Genes

10 BioMed Research International

PLAU

NONMMUT085451.1AK013093

NONMMUT080699.1

NONMMUT038318.2

ATF4

NONMMUT115705.1

NRF1

LMO2

NONMMUT094861.1

AK037309NONMMUT117382.1

E2F1

NONMMUT132788.1

CREB1

AK033130TFDP1

NR_040530

E2F2

BU962357

E2F5

NovelTID_00004006

HLF

NONMMUT119214.1

XR_376460

NONMMUT079197.1

NONMMUT118845.1

NONMMUT080006.1

E2F4CJ204422

NONMMUT020270.2

NFE2L1

NovelTID_00002453

AK020434

NONMMUT105185.1

AK020499

NONMMUT116280.1

NFYB

VSX2

NFYA

NR_003632

NONMMUT075094.1

NONMMUT131563.1

AK136421

AK078214

ATF1

PITX2

TFDP2

SRF

NONMMUT008412.2

NONMMUT083658.1

NONMMUT084129.1

NFATC2

NONMMUT008894.2NR_029384

NFATC1

IRF1

NONMMUT025195.2

AK132561

MEF2A

ALX4NONMMUT096824.1

AK021040

NONMMUT126821.1

NONMMUT106228.1

NONMMUT130006.1

NONMMUT121011.1

NONMMUT092631.1NONMMUT123605.1

BB617541

NONMMUT079247.1

CDC5L

NONMMUT095214.1

AK080003

NR_040748

NONMMUT129712.1

AK037071

XR_376908

XR_883967

NONMMUT130805.1

AK041027NONMMUT108606.1

AK136376

FOXO3

NONMMUT122559.1

DDIT3

NONMMUT077307.1

OTX2

AK019930

NONMMUT125606.1

NONMMUT100626.1

AK138315

ZFP238

POU2F1 NONMMUT101001.1

XR_378948TC1716772

NONMMUT132449.1

NONMMUT112097.1

NKX6-2

NONMMUT115882.1 NONMMUT129577.1

TC1618330

NONMMUT081769.1

AK034598

NONMMUT090819.1

AK013746

AK051864

FOXJ2

NONMMUT088599.1

NONMMUT110464.1

NONMMUT096777.1

AK038790

NONMMUT028103.2

NONMMUT105303.1

SRY

NONMMUT079254.1

NONMMUT128608.1 ENSMUST00000200625.1

NONMMUT124251.1

NONMMUT078519.1

NKX6-1

TC1730998

NONMMUT089027.1

NONMMUT024086.2

ENSMUST00000124085XR_393617

NONMMUT089419.1

NONMMUT122952.1

NovelTID_00000032

NONMMUT099169.1

NONMMUT106474.1

AK145170

NONMMUT100399.1

FOXD3

IL10

NONMMUT115842.1

AK037371

NONMMUT069685.2NONMMUT101293.1

NovelTID_00003643AK019603

NONMMUT072621.2

NONMMUT060812.2

NR_045952 NONMMUT082971.1NovelTID_00003634

NONMMUT121748.1

AK089564

NONMMUT126890.1

NONMMUT075062.1

AK037738

AK045590

NONMMUT084642.1NovelTID_00005703AK148487

ZBTB16

NONMMUT088292.1

NONMMUT134128.1

NONMMUT127241.1

NONMMUT077446.1AK019580

NONMMUT098003.1

AK158273

NONMMUT135177.1

FOXP3

AK016022

TC1640282

NONMMUT120391.1

FOXF1A

NONMMUT078535.1

AIRE

XR_397005

NONMMUT113638.1

SOX5

NONMMUT101796.1

NONMMUT111826.1

NONMMUT132898.1FOXL1

AK043355

NONMMUT115594.1NONMMUT127336.1

AK157082

NONMMUT102257.1

ENSMUST00000210247.1

NONMMUT119537.1

AK006537

NONMMUT109302.1

TBP

NONMMUT103064.1

NR_046026

NONMMUT130301.1

NONMMUT083571.1

NONMMUT105466.1

NONMMUT028028.2

ONECUT2

NovelTID_00000350

NONMMUT108085.1

NONMMUT102111.1AK048935

NONMMUT125608.1

NR_045469

NONMMUT125795.1

NovelTID_00003476

NONMMUT103408.1AK149638

AK041536

AK081868

NONMMUT119191.1

NONMMUT131689.1

NONMMUT094154.1

NovelTID_00006350

NONMMUT134190.1

FOXF2

AK156546

XR_385767

NovelTID_00003273

NR_015587 LHX3

NONMMUT084527.1

IRF2XR_386591NONMMUT086528.1

BM894561

NONMMUT117065.1

NONMMUT122911.1

XR_382256

NONMMUT009557.2

NONMMUT095457.1

AK136879

NONMMUT122003.1

AK053300

HMGA2

NKX3-1

NONMMUT112958.1

NONMMUT115688.1

NONMMUT132232.1

NONMMUT092424.1

AK149001NONMMUT080044.1NKX2-2

NONMMUT111829.1

AK139336

NONMMUT111613.1

FOXO1NONMMUT098363.1

NONMMUT125698.1

NONMMUT125630.1

AK135646

NONMMUT086926.1

NONMMUT103122.1

Figure 7: Network of the top 200 most related LncRNA-TFs pairs (the most 5 related lncRNA-TFs pairs according to the P value). Orangearrow: TFs; blue diamonds: lncRNAs.

involved in pathways associated with neuroinflammatoryhave also been identified. According to the KEGG pathwayanalyses, genes associated with dysregulated lncRNAs in ADmodels are involved in several inflammation-related path-ways such as NF-kappa B signaling pathway, TNF signalingpathway, Jak-STAT signaling pathway, and MAPK signalingpathway. In addition, genes associated with dysregulatedlncRNAs in AD models are also involved in synaptic vesi-cle cycle, cholinergic synapse, dopaminergic synapse, andneuroactive ligand-receptor interaction, which were shownto play an important role in neuronal function and thepathogenesis of neurodegenerative diseases including ADand PD [39, 40]. GO analyzes revealed that these lncRNAswere involved in inflammatory-related biological processes(regulation of p38MAPK cascade, interleukin-1 beta produc-tion, and acute inflammatory response to antigenic stimulus)and neuron-related biological processes (negative regulationof axon extension, negative regulation of neuron projectiondevelopment, and negative regulation of neuronmaturation),which are important in learning and memory [41], as well asthe development of AD. Compared with the previous studyon the expression profiles of lncRNAs in A𝛽 intracerebralinjection AD rat models, several similar KEGG pathwayssuch as insulin signaling pathway, synaptic vesicle cycle, cell

adhesion molecules, and neuroactive ligand-receptor inter-action were predicted [26], which may indicate an importantrole of these signaling pathways in neural system, as well asin the pathogenesis of AD.

Furthermore, we identified the ENSMUST00000137938and ENSMUST00000115299 in the cholinergic synapse path-way. A line of evidence has suggested that the selective lossof cholinergic neurons and decreased synthesis and releaseof acetyl choline (ACH) were the most important cause ofmemory loss, cognitive decline, and dementia inAD [42–44].The lncRNA ENSMUST00000137938 is significantly asso-ciated with abundant pathways including apoptosis, long-term potentiation, serotonergic synapse, and dopaminergicsynapse, which are shown to be associated with memory andcognition, as well as the development of AD. In addition,ENSMUST00000115299 was found to be only significantlyassociated with the cholinergic synapse pathway, whichmay reveal a key role of this lncRNA in the pathogenesisof AD. To confirm this hypothesis, functional identifica-tion of ENSMUST00000115299 in AD is necessary in thefuture.

The lncRNA-TFs network was predicted via hyperge-ometric distribution analysis. The mostly correlated TFswith top 100 lncRNAs were HMGA2, ONECUT2, FOXO1,

BioMed Research International 11

Sergef

Hspe1

Tubg1

Arrdc5

Cnot1

Bcor

Lrrc51

Nbeal2

Cops3Ptch1Cbx8Sass6

Dlx2

Tle2

Zfp526

Trmt61a

Ogfr

Psmb3Chd7

Dopey1Zbtb32

Usp19

Tbc1d10b

Hnrnpd

Fam65a

Cpne5Mgat4a

Nubp2 2610028H24Rik

Golga1

Atad5

Tesc

Hgs

Coro1b

Calhm2Epm2aip1

E2F4Sgce

E2F1TFDP1

Hcrt

Socs2

Znrf1

Csrp2bp

Bad

Cacnb3 Nfatc2ip

Asxl2

Bbs9

Samd4

Zfp628

Hist1h1bCamkk2

Ctbp1NONMMUT080006.1

NONMMUT080699.1

Hook2

NONMMUT025624.2

AK013093

NONMMUT136363.1

NONMMUT037057.2

NONMMUT085451.1

Zfp110

Hspa2Pdgfb

Rpl17

Epb4.1l2

Rps5

Stx5aDpy19l3

Zfp384

Mef2d

Ptdss2 NONMMUT101632.1

Slc17a7

Gjc2 Gsk3a

Cpsf1

Dpagt1

Taok2

Figure 8: LncRNA-target-TFs network of 20 most differentially expressed lncRNAs. Red arrow: lncRNAs; green round: target mRNAs; bluediamond: TFs.

CDC5L, TFDP2, ZBTB16, E2F1, NKX3-1, and FOXJ2. More-over, the TFDP2, ONECUT2, NKX3-1, FOXL1, CDC5L,and FOXJ2 were the mostly related TFs that regulated theproduction of the 24 selected lncRNAs. Previous studieshave shown that TFDP2, NKX3-1, CDC5L, and FOXJ2 wereassociated with diseases through inducing cell apoptosis, cellcycle regulation, and inflammation [45–47]. Interestingly,HMGA2was previously focused on enhancing the expressionof proinflammatory cytokines including TNF-𝛼, IL-6, andIL-1𝛽, which is also one of the most important pathogenicmechanisms in AD. However, it is necessary to investigatefurther how it acts in AD.

We also analyzed the relationship between the top 20mostly dysregulated lncRNAs with TFs and their mRNAsand found the most likely TFs regulating these lncRNAswere E2F1, E2F4, and TFDP1. Further analysis indicatedthe AK013093, NONMMUT136363.1, NONMMUT101632.1,NONMMUT085451.1, NONMMUT080699.1, NONMMU-T080006.1, NONMMUT037057.2, and NONMMUT02-5624.2 were predicted to be regulated by both E2F1 andE2F4. As for the selected 24 lncRNAs, the most likely TFsregulating these lncRNAs were FOXL1, CDC5L, ONECUT2,and CDX1. And the AK045227, NONMMUT104720.1, andNONMMUT135177.1 were predicted to be regulated by bothCDC5L and CDX1. Notably, the lncRNAswere mostly related

to inflammatory and apoptosis process. And the TFs (E2F1,E2F4, CDC5L, and CDX1) were also shown to have functionon cell apoptosis [48, 49]. Thus, we presumed that theselncRNAs together with the 4 TFs might affect inflammatoryand apoptosis processes and then the pathogenesis of AD.

5. Conclusion

We have identified a number of dysregulated lncRNAs andmRNAs that might be potential biomarkers or targets refer-ring to AD. Further investigation is needed to elucidate thedetailed mechanisms underlying the regulation of differentlyexpressed lncRNAs.

Data Availability

The data used to support the findings of this study areincluded within the article.

Additional Points

Highlights. (1) An intranasal LPS-mediated Alzheimer’s dis-ease model in mice was firstly conducted. (2) The expres-sion profiles of lncRNAs in hippocampal showed that 395

12 BioMed Research International

lncRNAs and 123 mRNAs were detected to be significantlydifferently expressed between AD models and controls. (3)The significantly differently expressedmRNAs that correlatedwith lncRNAs were involved in inflammation, apoptosis, andnervous system related pathways.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Authors’ Contributions

Liang Tang and Lan Liu conceived and designed the work andhelped to coordinate support and funding. Liang Tang andJianming Liwrote themanuscript. Guangyi Li andPengchengJiang performed the animal experiments and helped collectthe samples. Yan Wang, participated in the acquisition,analysis, and interpretation of the data. Liang Tang and YiZhu coworked on associated data collection and analysis. Allauthors reviewed and approved the final manuscript. LiangTang and Lan Liu contributed equally to this work.

Acknowledgments

Theauthors thank Prof. Xiaoxin Yan (Department of Neurol-ogy, Xiang-ya Hospital, Central South University) for analyz-ing the Immunohistochemistry,Dr. YZhu from the first affili-ated hospital of Jiaxing University for data analysis, and Prof.Peter R. Patrylo (Departments of Physiology and Anatomy,Southern Illinois University, School of Medicine) for Lan-guage polishing. This study was funded by the Foundationof the Education Department of Hunan (13C1115, 16A027,and 16B035), the Foundation of the Health Department ofHunan (B2017041),TheNational Natural Science Foundationof China (81873780), the Foundation of Research CultivationProgram Growth Project of Tibet University (ZDCZJH18-18), The central support for the reform and developmentof local colleges and universities: Rescue protection andconstruction of tissue culture platform for endangered andprecious Tibetan Medicinal materials, and the constructprogram of the key discipline in Hunan province.

Supplementary Materials

Supplementary Figure 1 (Figure s1). The hierarchical clus-tering of the 34 mRNAs related to neurons/nervous systemdiseases, inflammation, and olfactory pathway and the 24lncRNAs coexpressed with the 34 mRNAs with the highestPearson’s correlation coefficients in AD and control hip-pocampal tissues. a. lncRNAs. b. mRNAs. SupplementaryFigure 2 (Figure s2). lncRNA-mRNA-network analysis on 34selected mRNAs and their coexpressed lncRNAs. Red arrow:lncRNAs; green round: mRNAs. The dotted lines betweenlncRNAs and mRNAs indicate a negative correlation, whilethe solid lines indicate a positive correlation. SupplementaryFigure 3 (Figure s3) LncRNA-TFs Network of the selected24 lncRNAs (the most 5 related lncRNA-TFs pairs accordingto the P value). Orange arrow: lncRNAs; blue diamonds:

TFs. Supplementary Figure 4 (Figure s4) lncRNA-target-TFsnetwork of the selected 24 lncRNAs (the most 5 relatedlncRNA-TFs pairs according to the P value). Orange arrow:lncRNAs; purple square: target mRNAs; Blue diamond: TFs.Supplementary File Table 1 Primers designed for qRT-PCRvalidation of candidate lncRNAs andmRNAs SupplementaryFile Table 2. The characters of differently expressed lncRNAsin AD and control. Supplementary File Table 3. The char-acters of differently expressed mRNAs in AD and control.Supplementary File Table 4. Characters of 34 mRNAs thatrelated to neurons/nervous system diseases, inflammation,and olfactory pathway, and 24 lncRNAs that correlated with34mRNAs with the highest Pearson’s correlation coefficients.Supplementary File Table 5. The KEGG pathways predictedfor differently expressed mRNAs. (Supplementary Materials)

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