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image of Effective Analysis of Alzheimer's Disease and Mechanisms of Methyl-4-Hydroxybenzoate using Network Toxicology, Molecular Docking, and Machine Learning Strategies

Abstract

Introduction

Nowadays, the large increase in environmental pollutants has led to the occurrence and development of an increasing number of diseases. Studies have shown that exposure to environmental pollutants, such as methyl-4-hydroxybenzoate (MEP) may lead to Alzheimer's disease (AD). Therefore, the purpose of this study was to elucidate the complex effects and potential molecular mechanisms of environmental pollutants MEP on AD.

Methods

Through exhaustive exploration of databases, such as ChEMBL, STITCH, SwissTargetPrediction, and Gene Expression Omnibus DataSets (GEO DataSets), we have identified a comprehensive list of 46 potential targets closely related to MEP and AD. After rigorous screening using the STRING platform and Cytoscape software, we narrowed the list to nine candidate targets and ultimately identified six hub targets using three proven machine learning methods (LASSO, RF, and SVM): CREBBP, BCL6, CXCR4, GRIN1, GOT2, and ITGA5. The “clusterProfiler” R package was used to conduct GO and KEGG enrichment analysis. At the same time, we also constructed disease prediction models for core genes. At last, six hub targets were executed molecular docking.

Results

We derived 46 key target genes related to MEP and AD and conducted gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. MEP might play a role in AD by affecting the pathways of neuroactive ligand-receptor interaction. Nine genes were screened as pivotal targets, followed by machine learning methods to identify six hub targets. Molecular docking analysis showed a good binding ability between MEP and CREBBP, BCL6, CXCR4, GRIN1, GOT2 and ITGA5. In addition, changes in the immune microenvironment revealed a significant impact of immune status on AD.

Discussions

This study revealed that MEP may induce AD through multiple mechanisms, such as oxidative stress, neurotoxicity, and immune regulation, and identified six core targets (CREBBP, BCL6, ) and found that they are related to changes in the immune microenvironment, such as T cells and B cells, providing new molecular targets for AD intervention.

Conclusion

Overall, CREBBP, BCL6, CXCR4, GRIN1, GOT2, and ITGA5 have been identified as the crucial targets correlating with AD. Our findings provide a theoretical framework for understanding the complex molecular mechanisms underlying the effects of MEP on AD and provide insights for the development of prevention and treatment of AD caused by exposure to MEP.

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2025-07-15
2025-08-17
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References

  1. Tiwari S. Atluri V. Kaushik A. Yndart A. Nair M. Alzheimer’s disease: Pathogenesis, diagnostics, and therapeutics. Int. J. Nanomedicine 2019 14 5541 5554 10.2147/IJN.S200490 31410002
    [Google Scholar]
  2. Lane C.A. Hardy J. Schott J.M. Alzheimer’s disease. Eur. J. Neurol. 2018 25 1 59 70 10.1111/ene.13439 28872215
    [Google Scholar]
  3. Tahami Monfared A.A. Byrnes M.J. White L.A. Zhang Q. Alzheimer’s disease: Epidemiology and clinical progression. Neurol. Ther. 2022 11 2 553 569 10.1007/s40120‑022‑00338‑8 35286590
    [Google Scholar]
  4. Scheltens P. De Strooper B. Kivipelto M. Holstege H. Chételat G. Teunissen C.E. Cummings J. van der Flier W.M. Alzheimer’s disease. Lancet 2021 397 10284 1577 1590 10.1016/S0140‑6736(20)32205‑4 33667416
    [Google Scholar]
  5. Sheppard O. Coleman M. Alzheimer’s disease: Etiology, neuropathology and pathogenesis. Alzheimer’s Disease: Drug Discovery Huang X. Brisbane (AU) Exon Publications 2020
    [Google Scholar]
  6. Mir R.H. Sawhney G. Pottoo F.H. Mohi-ud-din R. Madishetti S. Jachak S.M. Ahmed Z. Masoodi M.H. Role of environmental pollutants in Alzheimer’s disease: A review. Environ. Sci. Pollut. Res. Int. 2020 27 36 44724 44742 10.1007/s11356‑020‑09964‑x 32715424
    [Google Scholar]
  7. Ma Y.H. Chen H.S. Liu C. Feng Q.S. Feng L. Zhang Y.R. Hu H. Dong Q. Tan L. Kan H.D. Zhang C. Suckling J. Zeng Y. Chen R.J. Yu J.T. Association of long-term exposure to ambient air pollution with cognitive decline and Alzheimer’s disease–related amyloidosis. Biol. Psychiatry 2023 93 9 780 789 10.1016/j.biopsych.2022.05.017 35953319
    [Google Scholar]
  8. Vasefi M. Ghaboolian-Zare E. Abedelwahab H. Osu A. Environmental toxins and Alzheimer’s disease progression. Neurochem. Int. 2020 141 104852 10.1016/j.neuint.2020.104852 33010393
    [Google Scholar]
  9. Manivannan B. Yegambaram M. Supowit S. Beach T.G. Halden R.U. Assessment of persistent, bioaccumulative and toxic organic environmental pollutants in liver and adipose tissue of Alzheimer’s disease patients and age-matched controls. Curr. Alzheimer Res. 2019 16 11 1039 1049 10.2174/1567205016666191010114744 31660829
    [Google Scholar]
  10. Dhapola R. Sharma P. Kumari S. Bhatti J.S. HariKrishnaReddy D. Environmental toxins and Alzheimer’s disease: A comprehensive analysis of pathogenic mechanisms and therapeutic modulation. Mol. Neurobiol. 2024 61 6 3657 3677 10.1007/s12035‑023‑03805‑x 38006469
    [Google Scholar]
  11. Olloquequi J. Díaz-Peña R. Verdaguer E. Ettcheto M. Auladell C. Camins A. From inhalation to neurodegeneration: Air pollution as a modifiable risk factor for Alzheimer’s disease. Int. J. Mol. Sci. 2024 25 13 6928 10.3390/ijms25136928 39000036
    [Google Scholar]
  12. Kuntić M. Hahad O. Münzel T. Daiber A. Crosstalk between oxidative stress and inflammation caused by noise and air pollution—implications for neurodegenerative diseases. Antioxidants 2024 13 3 266 10.3390/antiox13030266 38539800
    [Google Scholar]
  13. Song H. Zhou H. Yang S. He C. Combining mendelian randomization analysis and network toxicology strategy to identify causality and underlying mechanisms of environmental pollutants with glioblastoma: A study of Methyl-4-hydroxybenzoate. Ecotoxicol. Environ. Saf. 2024 287 117311 10.1016/j.ecoenv.2024.117311 39536568
    [Google Scholar]
  14. Sharfalddin A. Davaasuren B. Emwas A.H. Jaremko M. Jaremko Ł. Hussien M. Single crystal, Hirshfeld surface and theoretical analysis of methyl 4-hydroxybenzoate, a common cosmetic, drug and food preservative—Experiment versus theory. PLoS One 2020 15 10 0239200 10.1371/journal.pone.0239200 33021975
    [Google Scholar]
  15. Xiang J. Lv B.R. Shi Y. Chen W. Zhang J. Environmental pollution of paraben needs attention: A study of methylparaben and butylparaben co-exposure trigger neurobehavioral toxicity in zebrafish. Environ. Pollut. 2024 356 124370 10.1016/j.envpol.2024.124370 38876377
    [Google Scholar]
  16. Seymore T.N. Rivera-Núñez Z. Stapleton P.A. Adibi J.J. Barrett E.S. Phthalate exposures and placental health in animal models and humans: A systematic review. Toxicol. Sci. 2022 188 2 153 179 10.1093/toxsci/kfac060 35686923
    [Google Scholar]
  17. Comeche A. Martín-Villamil M. Picó Y. Varó I. Effect of methylparaben in Artemia franciscana. Comp. Biochem. Physiol. C Toxicol. Pharmacol. 2017 199 98 105 10.1016/j.cbpc.2017.04.004 28428009
    [Google Scholar]
  18. da Silveira F.F.C.L. Porto V.A. de Sousa B.L.C. de Souza E.V. Lo Nostro F.L. Rocha T.L. de Jesus L.W.O. Bioaccumulation and ecotoxicity of parabens in aquatic organisms: Current status and trends. Environ. Pollut. 2024 363 Pt 2 125213 10.1016/j.envpol.2024.125213 39477001
    [Google Scholar]
  19. Hu C. Bai Y. Li J. Sun B. Chen L. Endocrine disruption and reproductive impairment of methylparaben in adult zebrafish. Food Chem. Toxicol. 2023 171 113545 10.1016/j.fct.2022.113545 36470324
    [Google Scholar]
  20. Nowak K. Jabłońska E. Garley M. Radziwon P. Ratajczak-Wrona W. Methylparaben-induced regulation of estrogenic signaling in human neutrophils. Mol. Cell. Endocrinol. 2021 538 111470 10.1016/j.mce.2021.111470 34606965
    [Google Scholar]
  21. Mushtaq G. Greig N. Khan J. Kamal M. Status of acetylcholinesterase and butyrylcholinesterase in Alzheimer’s disease and type 2 diabetes mellitus. CNS Neurol. Disord. Drug Targets 2014 13 8 1432 1439 10.2174/1871527313666141023141545 25345511
    [Google Scholar]
  22. McGleenon B.M. Dynan K.B. Passmore A.P. Acetylcholinesterase inhibitors in Alzheimer’s disease. Br. J. Clin. Pharmacol. 1999 48 4 471 480 10.1046/j.1365‑2125.1999.00026.x 10583015
    [Google Scholar]
  23. Aloui M. El fadili M. Mujwar S. Er-rajy M. Abuelizz H.A. Er-rahmani S. Zarougui S. Menana E. In silico design of novel pyridazine derivatives as balanced multifunctional agents against Alzheimer’s disease. Sci. Rep. 2025 15 1 15910 10.1038/s41598‑025‑98182‑x 40335607
    [Google Scholar]
  24. Liu S. Wang Z. Zhu R. Wang F. Cheng Y. Liu Y. Three differential expression analysis methods for RNA sequencing: Limma, EdgeR, DESeq2. J. Vis. Exp. 2021 175 2021-09-18 10.3791/62528
    [Google Scholar]
  25. Wu T. Hu E. Xu S. Chen M. Guo P. Dai Z. Feng T. Zhou L. Tang W. Zhan L. Fu X. Liu S. Bo X. Yu G. ClusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation 2021 2 3 100141 10.1016/j.xinn.2021.100141 34557778
    [Google Scholar]
  26. Tian L. Wu W. Yu T. Graph random forest: A graph embedded algorithm for identifying highly connected important features. Biomolecules 2023 13 7 1153 10.3390/biom13071153 37509188
    [Google Scholar]
  27. Xu L. Shi M. Qin G. Lin X. Huang B. Environmental pollutant Di-(2-ethylhexyl) phthalate induces asthenozoospermia: New insights from network toxicology. Molec. Divers. 2025 29 3 2179 2192 10.1007/s11030‑024‑10976‑9
    [Google Scholar]
  28. Darbre P.D. Byford J.R. Shaw L.E. Hall S. Coldham N.G. Pope G.S. Sauer M.J. Oestrogenic activity of benzylparaben. J. Appl. Toxicol. 2003 23 1 43 51 10.1002/jat.886 12518336
    [Google Scholar]
  29. Gindorf M. Storck S.E. Ohler A. Scharfenberg F. Becker-Pauly C. Pietrzik C.U. Meprin β: A novel regulator of blood–brain barrier integrity. J. Cereb. Blood Flow Metab. 2021 41 1 31 44 10.1177/0271678X20905206 32065075
    [Google Scholar]
  30. Reitz C. Brayne C. Mayeux R. Epidemiology of Alzheimer disease. Nat. Rev. Neurol. 2011 7 3 137 152 10.1038/nrneurol.2011.2 21304480
    [Google Scholar]
  31. Go W. Ishak I.H. Zarkasi K.Z. Azzam G. Salvianolic acids modulate lifespan and gut microbiota composition in amyloid-β-expressing Drosophila melanogaster. World J. Microbiol. Biotechnol. 2024 40 11 358 10.1007/s11274‑024‑04163‑z 39428437
    [Google Scholar]
  32. Martins F.C. Oliveira M.M. Gaivão I. A Videira R. Peixoto F. The administration of methyl and butyl parabens interferes with the enzymatic antioxidant system and induces genotoxicity in rat testis: Possible relation to male infertility. Drug Chem. Toxicol. 2024 47 3 322 329 10.1080/01480545.2023.2176512 36756703
    [Google Scholar]
  33. Sears S.M.S. Hewett S.J. Influence of glutamate and GABA transport on brain excitatory/inhibitory balance. Exp. Biol. Med. 2021 246 9 1069 1083 10.1177/1535370221989263 33554649
    [Google Scholar]
  34. Wang Y. Xia J. Shen M. Zhou Y. Wu Z. Shi Y. Xu J. Hou L. Zhang R. Qiu Z. Xie Q. Chen H. Zhang Y. Wang H. Effects of BIS-MEP on reversing amyloid plaque deposition and spatial learning and memory impairments in a mouse model of β-amyloid peptide- and ibotenic acid-induced Alzheimer’s disease. Front. Aging Neurosci. 2019 11 3 10.3389/fnagi.2019.00003 30723404
    [Google Scholar]
  35. Farina M. Aschner M. Rocha J.B.T. Oxidative stress in MeHg-induced neurotoxicity. Toxicol. Appl. Pharmacol. 2011 256 3 405 417 10.1016/j.taap.2011.05.001 21601588
    [Google Scholar]
  36. Polunas M. Halladay A. Tjalkens R.B. Philbert M.A. Lowndes H. Reuhl K. Role of oxidative stress and the mitochondrial permeability transition in methylmercury cytotoxicity. Neurotoxicology 2011 32 5 526 534 10.1016/j.neuro.2011.07.006 21871920
    [Google Scholar]
  37. Kandimalla R. Reddy P.H. Therapeutics of neurotransmitters in Alzheimer’s disease. J. Alzheimers Dis. 2017 57 4 1049 1069 10.3233/JAD‑161118 28211810
    [Google Scholar]
  38. Yang Z. Zou Y. Wang L. Neurotransmitters in prevention and treatment of Alzheimer’s disease. Int. J. Mol. Sci. 2023 24 4 3841 10.3390/ijms24043841 36835251
    [Google Scholar]
  39. Wang R. Reddy P.H. Role of glutamate and NMDA receptors in Alzheimer’s disease. J. Alzheimers Dis. 2017 57 4 1041 1048 10.3233/JAD‑160763 27662322
    [Google Scholar]
  40. Conn K.A. Borsom E.M. Cope E.K. Implications of microbe-derived ɣ-aminobutyric acid (GABA) in gut and brain barrier integrity and GABAergic signaling in Alzheimer’s disease. Gut Microbes 2024 16 1 2371950 10.1080/19490976.2024.2371950 39008552
    [Google Scholar]
  41. Kocahan S. Doğan Z. Mechanisms of Alzheimer’s disease pathogenesis and prevention: The brain, neural pathology, n-methyl-d-aspartate receptors, tau protein and other risk factors. Clin. Psychopharmacol. Neurosci. 2017 15 1 1 8 10.9758/cpn.2017.15.1.1 28138104
    [Google Scholar]
  42. Brodin L. Shupliakov O. Retromer in synaptic function and pathology. Front. Synaptic Neurosci. 2018 10 37 10.3389/fnsyn.2018.00037 30405388
    [Google Scholar]
  43. Lamas J.A. Selyanko A.A. Brown D.A. Effects of a cognition-enhancer, linopirdine (DuP 996), on M-type potassium currents (IK(M)) and some other voltage- and ligand-gated membrane currents in rat sympathetic neurons. Eur. J. Neurosci. 1997 9 3 605 616 10.1111/j.1460‑9568.1997.tb01637.x 9104602
    [Google Scholar]
  44. Hu C. Bai Y. Sun B. Zhou X. Chen L. Exposure to methylparaben at environmentally realistic concentrations significantly impairs neuronal health in adult zebrafish. J. Environ. Sci. 2023 132 134 144 10.1016/j.jes.2022.07.012 37336604
    [Google Scholar]
  45. Li S. Xiao J. Huang C. Sun J. Identification and validation of oxidative stress and immune-related hub genes in Alzheimer’s disease through bioinformatics analysis. Sci. Rep. 2023 13 1 657 10.1038/s41598‑023‑27977‑7 36635346
    [Google Scholar]
  46. Zhang J. Mohamad F.H. Wong J.H. Mohamad H. Ismail A.H. Mohamed Yusoff A.A. Osman H. Wong K.T. Idris Z. Abdullah J.M. The effects of 4-hydroxybenzoic acid identified from bamboo (Dendrocalamus asper) shoots on kv1.4 channel. Malays. J. Med. Sci. 2018 25 1 101 113 10.21315/mjms2018.25.1.12 29599640
    [Google Scholar]
  47. Winter A.N. Brenner M.C. Punessen N. Snodgrass M. Byars C. Arora Y. Linseman D.A. Comparison of the neuroprotective and anti-inflammatory effects of the anthocyanin metabolites, protocatechuic acid and 4-hydroxybenzoic acid. Oxid. Med. Cell. Longev. 2017 2017 1 6297080 10.1155/2017/6297080 28740571
    [Google Scholar]
  48. Wang Q. Qiao W. Zhang H. Liu B. Li J. Zang C. Mei T. Zheng J. Zhang Y. Nomogram established on account of Lasso-Cox regression for predicting recurrence in patients with early-stage hepatocellular carcinoma. Front. Immunol. 2022 13 1019638 10.3389/fimmu.2022.1019638 36505501
    [Google Scholar]
  49. Dai P. Chang W. Xin Z. Cheng H. Ouyang W. Luo A. Retrospective study on the influencing factors and prediction of hospitalization expenses for chronic renal failure in China based on random forest and LASSO regression. Front. Public Health 2021 9 678276 10.3389/fpubh.2021.678276 34211956
    [Google Scholar]
  50. Silva G.F.S. Fagundes T.P. Teixeira B.C. Chiavegatto Filho A.D.P. Machine learning for hypertension prediction: A systematic review. Curr. Hypertens. Rep. 2022 24 11 523 533 10.1007/s11906‑022‑01212‑6 35731335
    [Google Scholar]
  51. Alamro H. Thafar M.A. Albaradei S. Gojobori T. Essack M. Gao X. Exploiting machine learning models to identify novel Alzheimer’s disease biomarkers and potential targets. Sci. Rep. 2023 13 1 4979 10.1038/s41598‑023‑30904‑5 36973386
    [Google Scholar]
  52. Zhao S. Ye B. Chi H. Cheng C. Liu J. Identification of peripheral blood immune infiltration signatures and construction of monocyte-associated signatures in ovarian cancer and Alzheimer’s disease using single-cell sequencing. Heliyon 2023 9 7 17454 10.1016/j.heliyon.2023.e17454 37449151
    [Google Scholar]
  53. Dong Y. Li T. Ma Z. Zhou C. Wang X. Li J. HSPA1A, HSPA2, and HSPA8 are potential molecular biomarkers for prognosis among HSP70 family in Alzheimer’s disease. Dis. Markers 2022 2022 1 16 10.1155/2022/9480398 36246562
    [Google Scholar]
  54. Rahman M.R. Islam T. Turanli B. Zaman T. Faruquee H.M. Rahman M.M. Mollah M.N.H. Nanda R.K. Arga K.Y. Gov E. Moni M.A. Network-based approach to identify molecular signatures and therapeutic agents in Alzheimer’s disease. Comput. Biol. Chem. 2019 78 431 439 10.1016/j.compbiolchem.2018.12.011 30606694
    [Google Scholar]
  55. Bellenie B.R. Cheung K.M.J. Varela A. Pierrat O.A. Collie G.W. Box G.M. Bright M.D. Gowan S. Hayes A. Rodrigues M.J. Shetty K.N. Carter M. Davis O.A. Henley A.T. Innocenti P. Johnson L.D. Liu M. de Klerk S. Le Bihan Y.V. Lloyd M.G. McAndrew P.C. Shehu E. Talbot R. Woodward H.L. Burke R. Kirkin V. van Montfort R.L.M. Raynaud F.I. Rossanese O.W. Hoelder S. Achieving in vivo target depletion through the discovery and optimization of benzimidazolone BCL6 degraders. J. Med. Chem. 2020 63 8 4047 4068 10.1021/acs.jmedchem.9b02076 32275432
    [Google Scholar]
  56. Baron B.W. Baron R.M. Baron J.M. The ITM2B (BRI2) gene is a target of BCL6 repression: Implications for lymphomas and neurodegenerative diseases. Biochim. Biophys. Acta Mol. Basis Dis. 2015 1852 5 742 748 10.1016/j.bbadis.2014.12.018 25557390
    [Google Scholar]
  57. Baron B.W. Pytel P. Expression pattern of the BCL6 and itm2b proteins in normal human brains and in Alzheimer disease. Appl. Immunohistochem. Mol. Morphol. 2017 25 7 489 496 10.1097/PAI.0000000000000329 26862951
    [Google Scholar]
  58. Kim K. Wang X. Ragonnaud E. Bodogai M. Illouz T. DeLuca M. McDevitt R.A. Gusev F. Okun E. Rogaev E. Biragyn A. Therapeutic B-cell depletion reverses progression of Alzheimer’s disease. Nat. Commun. 2021 12 1 2185 10.1038/s41467‑021‑22479‑4 33846335
    [Google Scholar]
  59. Bezzi P. Domercq M. Brambilla L. Galli R. Schols D. De Clercq E. Vescovi A. Bagetta G. Kollias G. Meldolesi J. Volterra A. CXCR4-activated astrocyte glutamate release via TNFα: Amplification by microglia triggers neurotoxicity. Nat. Neurosci. 2001 4 7 702 710 10.1038/89490 11426226
    [Google Scholar]
  60. Parachikova A. Agadjanyan M.G. Cribbs D.H. Blurton-Jones M. Perreau V. Rogers J. Beach T.G. Cotman C.W. Inflammatory changes parallel the early stages of Alzheimer disease. Neurobiol. Aging 2007 28 12 1821 1833 10.1016/j.neurobiolaging.2006.08.014 17052803
    [Google Scholar]
  61. Parachikova A. Cotman C.W. Reduced CXCL12/CXCR4 results in impaired learning and is downregulated in a mouse model of Alzheimer disease. Neurobiol. Dis. 2007 28 2 143 153 10.1016/j.nbd.2007.07.001 17764962
    [Google Scholar]
  62. Ragnarsson L. Zhang Z. Das S.S. Tran P. Andersson Å. des Portes V. Desmettre Altuzarra C. Remerand G. Labalme A. Chatron N. Sanlaville D. Lesca G. Anggono V. Vetter I. Keramidas A. GRIN1 variants associated with neurodevelopmental disorders reveal channel gating pathomechanisms. Epilepsia 2023 64 12 3377 3388 10.1111/epi.17776 37734923
    [Google Scholar]
  63. Korinek M. Candelas Serra M. Abdel Rahman F.E.S. Dobrovolski M. Kuchtiak V. Abramova V. Fili K. Tomovic E. Hrcka Krausova B. Krusek J. Cerny J. Vyklicky L. Balik A. Smejkalova T. Disease-associated variants in GRIN1, GRIN2A and GRIN2B genes: Insights into NMDA receptor structure, function, and pathophysiology. Physiol. Res. 2024 73 Suppl. 1 S413 S434 10.33549/physiolres.935346 38836461
    [Google Scholar]
  64. Mitra S. Bp K. C R S. Saikumar N.V. Philip P. Narayanan M. Alzheimer’s disease rewires gene coexpression networks coupling different brain regions. NPJ Syst. Biol. Appl. 2024 10 1 50 10.1038/s41540‑024‑00376‑y 38724582
    [Google Scholar]
  65. Han Y. Chen K. Yu H. Cui C. Li H. Hu Y. Zhang B. Li G. Maf1 loss regulates spinogenesis and attenuates cognitive impairment in Alzheimer’s disease. Brain 2024 147 6 2128 2143 10.1093/brain/awae015 38226680
    [Google Scholar]
  66. Li Y. Li B. Xu Y. Qian L. Xu T. Meng G. Li H. Wang Y. Zhang L. Jiang X. Liu Q. Xie Y. Cheng C. Sun B. Yu D. GOT2 silencing promotes reprogramming of glutamine metabolism and sensitizes hepatocellular carcinoma to glutaminase inhibitors. Cancer Res. 2022 82 18 3223 3235 10.1158/0008‑5472.CAN‑22‑0042 35895805
    [Google Scholar]
  67. Kang S. Lee Y. Lee J.E. Metabolism-centric overview of the pathogenesis of Alzheimer’s disease. Yonsei Med. J. 2017 58 3 479 488 10.3349/ymj.2017.58.3.479 28332351
    [Google Scholar]
  68. Ezkurdia A. Ramírez M.J. Solas M. Metabolic syndrome as a risk factor for Alzheimer’s disease: A focus on insulin resistance. Int. J. Mol. Sci. 2023 24 5 4354 10.3390/ijms24054354 36901787
    [Google Scholar]
  69. Chen Z. Balachandran Y.L. Chong W.P. Chan K.W.Y. Roles of cytokines in Alzheimer’s disease. Int. J. Mol. Sci. 2024 25 11 5803 10.3390/ijms25115803 38891990
    [Google Scholar]
  70. Goel P. Chakrabarti S. Goel K. Bhutani K. Chopra T. Bali S. Neuronal cell death mechanisms in Alzheimer’s disease: An insight. Front. Mol. Neurosci. 2022 15 937133 10.3389/fnmol.2022.937133 36090249
    [Google Scholar]
  71. Gao C. Jiang J. Tan Y. Chen S. Microglia in neurodegenerative diseases: Mechanism and potential therapeutic targets. Signal Transduct. Target. Ther. 2023 8 1 359 10.1038/s41392‑023‑01588‑0 37735487
    [Google Scholar]
  72. Liang C. Yuan Z. Yang S. Zhu Y. Chen Z. Can D. Lei A. Li H. Leng L. Zhang J. Mannose promotes β-amyloid pathology by regulating BACE1 glycosylation in Alzheimer’s disease. Adv. Sci. 2025 12 9 2409105 10.1002/advs.202409105 39807036
    [Google Scholar]
  73. Li S. Zhang N. Liu S. Zhang H. Liu J. Qi Y. Zhang Q. Li X. ITGA5 is a novel oncogenic biomarker and correlates with tumor immune microenvironment in gliomas. Front. Oncol. 2022 12 844144 10.3389/fonc.2022.844144 35371978
    [Google Scholar]
  74. Mahzarnia A. Lutz M.W. Badea A. A continuous extension of gene set enrichment analysis using the likelihood ratio test statistics identifies vascular endothelial growth factor as a candidate pathway for Alzheimer’s disease via ITGA5. J. Alzheimers Dis. 2024 97 2 635 648 10.3233/JAD‑230934 38160360
    [Google Scholar]
  75. Burgaletto C. Munafò A. Di Benedetto G. De Francisci C. Caraci F. Di Mauro R. Bucolo C. Bernardini R. Cantarella G. The immune system on the TRAIL of Alzheimer's disease. J. Neuroinflamm. 2020 17 1 298 2020-10-13 10.1186/s12974‑020‑01968‑1
    [Google Scholar]
  76. Kinney J.W. Bemiller S.M. Murtishaw A.S. Leisgang A.M. Salazar A.M. Lamb B.T. Inflammation as a central mechanism in Alzheimer’s disease. Alzheimers Dement. 2018 4 1 575 590 10.1016/j.trci.2018.06.014 30406177
    [Google Scholar]
  77. Linzhu Z. Zhang J. Fan W. Su C. Jin Z. Influence of immune cells and inflammatory factors on Alzheimer’s disease axis: Evidence from mediation Mendelian randomization study. BMC Neurol. 2025 25 1 49 10.1186/s12883‑025‑04057‑z 39910474
    [Google Scholar]
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