Alzheimer's disease (AD) is an advancing neurodegenerative disorder distinguished by the formation of amyloid plaques and neurofibrillary tangles in the human brain. Nevertheless, the lack of peripheral biomarkers that can detect the development of AD remains a significant limitation.
Objective
The main aim of this work was to discover the molecular markers associated with AD.
Methods
We conducted a comprehensive microarray analysis of gene expression data from hippocampus tissue in AD patients and control samples using three microarray datasets (GSE1297, GSE28146, and GSE29378) collected from Gene Expression Omnibus (GEO). The datasets were pre-processed and normalized, revealing 346 significant genes, 103 of which were upregulated and 243 downregulated. The PPI network of significant genes was constructed to detect the top 50 hub genes, which were then further analyzed using Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes pathway (KEGG), and GSEA, revealing 47 key genes involved in AD-related pathways. These key genes were then subjected to feed forward loop (FFL) motif analysis for the prediction of transcriptional factors (TFs) and microRNAs (miRNAs) mediated gene regulatory networks.
Results
The interaction of AD-associated TFs HNF4A, SPI1, EGR1, STAT3, and MYC and miRNAs hsa-miR-155-5p and hsa-miR-16-5p in the transcriptional and post-transcriptional events of 3 upregulated and 10 downregulated genes: H2AFZ, MCM3, MYO1C, AXIN1, CCND1, ETS2, MYH9, RELA, RHEB, SOCS3, TBL1X, TBP, TXNIP, and YWHAZ, respectively, has been identified. The miRNA/TF-mediated three types of the FFL motifs, i.e., miRNA-FFL, TF-FFL, and composite-FFL, were constructed, and seven common genes among these FFL were identified: CCND1, MYH9, SOCS3, RHEB, MYO1C, TXNIP, AXIN1, and TXNIP.
Conclusions
These findings may provide insights into the development of potential molecular markers for therapeutic management of AD.
BehlC. Alzheimer’s disease research: What has guided research so far and why it is high time for a paradigm shift. Cham, Switzerland: Springer Nature, 2023.
UlepMGLienardP. Free-listing and semantic knowledge: a diagnostic tool for detecting Alzheimer’s disease?Cogn Behav Neurol2024; 37: 117–143.
4.
YamadaYYokogawaNKatoS, et al.Effects of dementia on outcomes after cervical spine injuries in elderly patients: evaluation of 1512 cases in a nationwide multicenter study in Japan. J Clin Med2023; 12: 1867.
5.
ThakralSYadavASinghV, et al.Alzheimer's disease: molecular aspects and treatment opportunities using herbal drugs. Ageing Res Rev2023; 88: 101960.
6.
MadnaniRS. Alzheimer’s disease: a mini-review for the clinician. Front Neurol2023; 14: 1178588.
7.
GhanbariMLiGHsuLM, et al.Accumulation of network redundancy marks the early stage of Alzheimer's disease. Hum Brain Mapp2023; 44: 2993–3006.
8.
OcalDMcCarthyIDPooleT, et al.Effects of the visual environment on object localization in posterior cortical atrophy and typical Alzheimer's disease. Front Med2023; 10: 1102510.
9.
AmanollahiMJameieMHeidariA, et al.The dialogue between neuroinflammation and adult neurogenesis: mechanisms involved and alterations in neurological diseases. Mol Neurobiol2023; 60: 923–959.
10.
YuZTengYYangJ, et al.The role of exosomes in adult neurogenesis: implications for neurodegenerative diseases. Neural Regen Res2024; 19: 282–288.
11.
NorevikCSHuuhaAMRøsbjørgenRN, et al.Exercised blood plasma promotes hippocampal neurogenesis in the Alzheimer's disease rat brain. J Sport Health Sci2024; 13: 245–255.
12.
KolbBGibbR. Brain plasticity and behaviour in the developing brain. J Can Acad Child Adolesc Psychiatry2011; 20: 265.
13.
Kobro-FlatmoenABattistinCNairRR, et al.Lowering levels of reelin in entorhinal cortex layer II-neurons results in lowered levels of intracellular amyloid-β. Brain Commun2023; 5: fcad115.
14.
AksmanLMOxtobyNPScelsiMA, et al.A data-driven study of Alzheimer's disease related amyloid and tau pathology progression. Brain2023; 146: 4935–4948.
15.
RajmohanRReddyPH. Amyloid-beta and phosphorylated tau accumulations cause abnormalities at synapses of Alzheimer’s disease neurons. J Alzheimers Dis2017; 57: 975–999.
16.
HangerDPSeereeramANobleW. Mediators of tau phosphorylation in the pathogenesis of Alzheimer’s disease. Expert Rev Neurother2009; 9: 1647–1666.
17.
JoelZIzquierdoPSalihDA, et al.Improving mouse models for dementia. Are all the effects in tau mouse models due to overexpression?Cold Spring Harb Symp Quant Biol2018; 83: 151–161.
18.
CulbersonJWKopelJSeharU, et al.Urgent needs of caregiving in ageing populations with Alzheimer’s disease and other chronic conditions: support our loved ones. Ageing Res Rev2023; 90: 102001.
19.
ListaSGonzález-DomínguezRLópez-OrtizS, et al.Integrative metabolomics science in Alzheimer’s disease: relevance and future perspectives. Ageing Res Rev2023; 89: 101987.
20.
EdgarRBarrettT. NCBI GEO standards and services for microarray data. Nat Biotechnol2006; 24: 1471–1472.
21.
BlalockEMGeddesJWChenKC, et al.Incipient Alzheimer's disease: microarray correlation analyses reveal major transcriptional and tumor suppressor responses. Proc Natl Acad Sci U S A2004; 101: 2173–2178.
22.
BlalockEMBuechelHMPopovicJ, et al.Microarray analyses of laser-captured hippocampus reveal distinct gray and white matter signatures associated with incipient Alzheimer's disease. J Chem Neuroanat2011; 42: 118–126.
23.
MillerJAWoltjerRLGoodenbourJM, et al.Genes and pathways underlying regional and cell type changes in Alzheimer's disease. Genome Med2013; 5: 48.
24.
HeberleHMeirellesGVda SilvaFR, et al.Interactivenn: a web-based tool for the analysis of sets through venn diagrams. BMC Bioinformatics2015; 16: 169.
25.
AllaireJ. RStudio: integrated development environment for R (Version 0.96.122). Boston, MA: RStudio, 2012.
26.
LiuSWangZZhuR, et al.Three differential expression analysis methods for RNA sequencing: limma, EdgeR, DESeq2. J Vis Exp2021. doi: https://doi.org/10.3791/62528.
27.
SnelBLehmannGBorkP, et al.STRING: a web-server to retrieve and display the repeatedly occurring neighbourhood of a gene. Nucleic Acids Res2000; 28: 3442–3444.
28.
ShannonPMarkielAOzierO, et al.Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res2003; 13: 2498–2504.
29.
ChinC-HChenS-HWuH-H, et al.Cytohubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol2014; 8: S11.
30.
JiaAXuLWangY. Venn diagrams in bioinformatics. Brief Bioinform2021; 22: bbab108.
31.
ConsortiumGO. The Gene Ontology (GO) database and informatics resource. Nucleic Acids Res2004; 32: D258–D261.
32.
KanehisaMGotoS. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res2000; 28: 27–30.
33.
SubramanianATamayoPMoothaVK, et al.Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A2005; 102: 15545–15550.
34.
KoopmansFvan NieropPAndres-AlonsoM, et al.SynGO: an evidence-based, expert-curated knowledge base for the synapse. Neuron2019; 103: 217–234.e214.
35.
DennisGShermanBTHosackDA, et al.DAVID: database for annotation, visualization, and integrated discovery. Genome Biol2003; 4: P3.
36.
JiangQWangYHaoY, et al.Mir2disease: a manually curated database for microRNA deregulation in human disease. Nucleic Acids Res2009; 37: D98–D104.
37.
HuangZShiJGaoY, et al.HMDD V3. 0: a database for experimentally supported human microRNA–disease associations. Nucleic Acids Res2019; 47: D1013–D1017.
38.
TakousisPSadlonASchulzJ, et al.Differential expression of microRNAs in Alzheimer's disease brain, blood, and cerebrospinal fluid. Alzheimers Dement2019; 15: 1468–1477.
39.
ChangLZhouGSoufanO, et al.miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology. Nucleic Acids Res2020; 48: W244–W251.
40.
XieG-YXiaMMiaoY-R, et al.FFLtool: a web server for transcription factor and miRNA feed forward loop analysis in human. Bioinformatics2020; 36: 2605–2607.
41.
SajadMAhmedMMThakurSC.An integrated bioinformatics strategy to elucidate the function of hub genes linked to Alzheimer's Disease. Gene Reports2022; 26: 101534.
42.
JiangTYuJ-TTianY, et al.Epidemiology and etiology of Alzheimer’s disease: from genetic to non-genetic factors. Curr Alzheimer Res2013; 10: 852–867.
43.
BallMHachinskiVFoxA, et al.A new definition of Alzheimer's disease: a hippocampal dementia. Lancet1985; 325: 14–16.
44.
Van HoesenGWHymanBT. Hippocampal formation: anatomy and the patterns of pathology in Alzheimer's disease. Prog Brain Res1990; 83: 445–457.
45.
AlsopDCCasementMde BazelaireC, et al.Hippocampal hyperperfusion in Alzheimer's disease. Neuroimage2008; 42: 1267–1274.
46.
VisuttijaiKPetterssonJMehrbani AzarY, et al.Lowered expression of tumor suppressor candidate MYO1C stimulates cell proliferation, suppresses cell adhesion and activates AKT. PLoS One2016; 11: e0164063.
47.
NevzorovISidorenkoEWangW, et al.Myosin-1C uses a novel phosphoinositide-dependent pathway for nuclear localization. EMBO Rep2018; 19: 290–304.
48.
BondLMBrandstaetterHKendrick-JonesJ, et al.Functional roles for myosin 1c in cellular signaling pathways. Cell Signal2013; 25: 229–235.
49.
SansonRLazzaraSLCuneD, et al.Axin1 protects colon carcinogenesis by an immune-mediated effect. Cell Mol Gastroenterol Hepatol2023; 15: 689–715.
50.
TerhalPVenhuizenAJLesselD, et al.AXIN1 bi-allelic variants disrupting the C-terminal DIX domain cause craniometadiaphyseal osteosclerosis with hip dysplasia. Am J Hum Genet2023; 110: 1470–1481.
51.
XieRYiDZengD, et al.Specific deletion of Axin1 leads to activation of β-catenin/BMP signaling resulting in fibular hemimelia phenotype in mice. Elife2022; 11: e80013.
52.
WhelanCDMattssonNNagleMW, et al.Multiplex proteomics identifies novel CSF and plasma biomarkers of early Alzheimer’s disease. Acta Neuropathol Commun2019; 7: 169.
53.
AliashrafiMNasehiMZarrindastM, et al.Association of microbiota-derived propionic acid and Alzheimer’s disease; bioinformatics analysis. J Diabetes Metab Disord2020; 19: 783–804.
54.
BesliNSarikamisBCakmakRK, et al.Exosomal circular ribonucleic acid–microribonucleic acid expression profile from plasma in Alzheimer’s disease patients by bioinformatics and integrative analysis. Eurasian J Med2023; 55: 218.
55.
WicikZCzajkaPEyiletenC, et al.The role of miRNAs in regulation of platelet activity and related diseases-a bioinformatic analysis. Platelets2022; 33: 1052–1064.
56.
NingZZhongXWuY, et al.β-asarone improves cognitive impairment and alleviates autophagy in mice with vascular dementia via the cAMP/PKA/CREB pathway. Phytomedicine2024; 123: 155215.
57.
PedrazaNMonserratMVFerrezueloF, et al.Cyclin D1—Cdk4 regulates neuronal activity through phosphorylation of GABAA receptors. Cell Mol Life Sci2023; 80: 280.
58.
MaSWangDXieD. Identification of disulfidptosis-related genes and subgroups in Alzheimer’s disease. Front Aging Neurosci2023; 15: 1236490.
59.
LuZHShvartsmanMBLeeAY, et al.Mammalian target of rapamycin activator RHEB is frequently overexpressed in human carcinomas and is critical and sufficient for skin epithelial carcinogenesis. Cancer Res2010; 70: 3287–3298.
60.
ShamsRItoYMiyatakeH. Evaluation of the binding kinetics of RHEB with mTORC1 by in-cell and in vitro assays. Int J Mol Sci2021; 22: 8766.
61.
ZhongYZhouXGuanK-L, et al.Rheb regulates nuclear mTORC1 activity independent of farnesylation. Cell Chem Biol2022; 29: 1037–1045.e1034.
62.
MoonGJKimSJeonM-T, et al.Therapeutic potential of AAV1-rheb (S16H) transduction against Alzheimer’s disease. J Clin Med2019; 8: 2053.
63.
KimJLimJYooID, et al.TXNIP Contributes to induction of pro-inflammatory phenotype and caspase-3 activation in astrocytes during Alzheimer’s diseases. Redox Biol2023; 63: 102735.
64.
GaoWKongWWangS, et al.Biomarker genes discovery of Alzheimer’s disease by multi-omics-based gene regulatory network construction of microglia. Brain Sci2022; 12: 1196.
65.
SuLChenSZhengC, et al.Meta-analysis of gene expression and identification of biological regulatory mechanisms in Alzheimer's disease. Front Neurosci2019; 13: 633.
66.
LeeD-HParkS-HAhnJ, et al.Mir214-3p and Hnf4a/Hnf4α reciprocally regulate Ulk1 expression and autophagy in nonalcoholic hepatic steatosis. Autophagy2021; 17: 2415–2431.
67.
ChuY-BLiJJiaP, et al.Irf1-and Egr1-activated transcription plays a key role in macrophage polarization: a multiomics sequencing study with partial validation. Int Immunopharmacol2021; 99: 108072.
68.
AlamroHThafarMAAlbaradeiS, et al.Exploiting machine learning models to identify novel Alzheimer’s disease biomarkers and potential targets. Sci Rep2023; 13: 4979.
69.
CulpanDKehoePGLoveS. Tumour necrosis factor-α (TNF-α) and miRNA expression in frontal and temporal neocortex in Alzheimer's disease and the effect of TNF-α on miRNA expression in vitro. Int J Mol Epidemiol Genet2011; 2: 156.
70.
ZhaoYBhattacharjeeSJonesBM, et al.Regulation of TREM2 expression by an NF-κB-sensitive miRNA-34a. Neuroreport2013; 24: 318.
71.
HébertSSWangW-XZhuQ, et al.A study of small RNAs from cerebral neocortex of pathology-verified Alzheimer's disease, dementia with Lewy bodies, hippocampal sclerosis, frontotemporal lobar dementia, and non-demented human controls. J Alzheimers Dis2013; 35: 335–348.
72.
LeitnerFKrallingerMTripathiS, et al.Mining cis-regulatory transcription networks from literature. Proc BioLINK SIG2013; 2013: 5–12.
73.
KanitzA. Tools and strategies for the unraveling of post-transcriptional gene regulatory networks. PhD Thesis, ETH Zurich, Switzerland, 2012.
74.
ShalgiRBroshROrenM, et al.Coupling transcriptional and post-transcriptional miRNA regulation in the control of cell fate. Aging (Albany NY)2009; 1: 762.
75.
SunJGongXPurowB, et al.Uncovering microRNA and transcription factor mediated regulatory networks in glioblastoma. PLoS Comput Biol2012; 8: e1002488.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
