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A Path Toward Precision Medicine for Neuroinflammatory Mechanisms in Alzheimer's Disease
Open accessAbstract
Neuroinflammation commences decades before Alzheimer’s disease (AD) clinical onset and represents one of the earliest pathomechanistic alterations throughout AD its continuum. Large-scale genome-wide association studies point out several genetic variants - TREM2, CD33, PILRA, CR1, MS4A, CLU, ABCA7, EPHA1, and HLA-DRB5-HLA-DRB1 - potentially linked to neuroinflammation. Most of these genes are involved in proinflammatory intracellular signaling, cytokines/interleukins cell turn-over, synaptic activity, lipid metabolism, and vesicle trafficking. Proteomic studies indicate that a plethora of interconnected aberrant molecular pathways, set off and perpetuated by TNF-α, TGF-β, IL-1β, and the receptor protein TREM2, are involved in neuroinflammation. Microglia and astrocytes are key cellular drivers and regulators of neuroinflammation. Under physiological conditions, they are important for neurotransmission and synaptic homeostasis. In AD, there is a turning point throughout its pathophysiological evolution where glial cells sustain an overexpressed inflammatory response that synergizes with amyloid-β and tau accumulation, and drives synaptotoxicity and neurodegeneration in a self-reinforcing manner. Despite a strong therapeutic rationale, previous clinical trials investigating compounds with anti-inflammatory properties, including non-steroidal anti-inflammatory drugs (NSAIDs) did not achieve primary efficacy endpoints. It is conceivable that study design issues, including the lack of diagnostic accuracy and biomarkers for target population identification and proof-of-mechanism may partially explain the negative outcomes. However, a recent meta-analysis indicates a potential biological effect of NSAIDs. In this regard, candidate fluid biomarkers of neuroinflammation are under analytical/clinical validation, i.e. TREM2, IL-1β, MCP-1, IL-6, TNF-α receptor complexes, TGF-β, YKL-40. PET radio-ligands are investigated to accomplish in-vivo and longitudinal regional exploration of neuroinflammation. Biomarkers tracking different molecular pathways (body fluid matrixes) along with brain neuroinflammatory endophenotypes (neuroimaging markers), can untangle temporal-spatial dynamics between neuroinflammation and other AD pathophysiological mechanisms. Robust biomarker-drug co-development pipelines are expected to enrich large-scale clinical trials testing new-generation compounds active, directly or indirectly, on neuroinflammatory targets and displaying putative disease-modifying effects: novel NSAIDs, AL002 (anti-TREM2 antibody), anti-Aβ protofibrils (BAN2401), and AL003 (anti-CD33 antibody). As a next step, taking advantage of breakthrough and multimodal techniques coupled with a systems biology approach is the path to pursue for developing individualized therapeutic strategies targeting neuroinflammation under the framework of precision medicine.
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“mitochondrial dysfunction—with reactive oxygen species (ROS) accumulation and neuroinflammation driving microglial activation—plays a central role in AD pathogenesis [56]”
From Theranostic Nanoplatforms for Alzheimer's Disease: A Critical Analysis of Conceptual Contradictions (2026) · cites this paper as [56]
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Cites
1 retracted
RETRACTED AND REPLACED: Nerve growth factor metabolic dysfunction in Down’s syndrome brains
Iulita, M. F., Carmo, S. D., Ower, A. K., Fortress, A. M., Aguilar, L. F., Hanna, M., Wısnıewskı, T., Granholm, A., Buhusi, M. C., Busciglio, J. A., et al. (2014) · Brain · doi:10.1093/brain/awt372 · Cited by 94
Self-citationRetractedMcKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657
NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease
Jack, C. R., Bennett, D. A., Blennow, K., Carrillo, M. C., Dunn, B., Haeberlein, S. B., Holtzman, D. M., Jagust, W., Jessen, F., Karlawish, J., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.02.018 · Cited by 10,537
Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., Gamst, A., Holtzman, D. M., Jagust, W. J., Petersen, R. C., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.008 · Cited by 10,152 · cited 1×
“, amnestic or non-amnestic), which significantly impacts clinical outcome (8, 179, 180), is inadequately specified in most of the studies.”
BackgroundInflammation in atherosclerosis
Libby, P. (2002) · Nature · doi:10.1038/nature01323 · Cited by 8,315
Neurotoxic reactive astrocytes are induced by activated microglia
Liddelow, S. A., Guttenplan, K. A., Clarke, L. E., Bennett, F. C., Bohlen, C. J., Schirmer, L., Bennett, M. L., Münch, A. E., Chung, W.-S., Peterson, T. C., et al. (2017) · Nature · doi:10.1038/nature21029 · Cited by 7,971
Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Kaye, J., Montine, T. J., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.003 · Cited by 7,155
Neuroinflammation in Alzheimer's disease
Heneka, M. T., Carson, M. J., Khoury, J. E., Landreth, G. E., Brosseron, F., Feinstein, D. L., Jacobs, A. H., Wyss-Coray, T., Vitorica, J., Ransohoff, R. M., et al. (2015) · The Lancet Neurology · doi:10.1016/s1474-4422(15)70016-5 · Cited by 6,226 · cited 5×
“The pathophysiological mechanisms of multifactorial and polygenic AD are not limited to the neuronal tissue; they are related to cerebral immunological responses (12).”
BackgroundInfluentialA New Initiative on Precision Medicine
Collins, F. S., & Varmus, H. (2015) · New England Journal of Medicine · doi:10.1056/nejmp1500523 · Cited by 5,202
Astrocytes: Biology and pathology
Sofroniew, M. V., & Vinters, H. V. (2010) · Acta Neuropathologica · doi:10.1007/s00401-009-0619-8 · Cited by 5,196 · cited 1×
“Moreover, remodeling of astrocytes promotes neuroprotection and recovery of injured neural tissue (80, 81).”
Background
Flagged first, then by citations
Research works printed but not linked: 1
- Presented at the 11thClinical Trials on Alzheimer's Disease (CTAD) Conference October 24–272018
Cited by
Sorted by citations
Items 301–360 of 360
Oluwadahunsi, G., Akinwotu, S., Fadipe, T. M., Akintoye, O. P., Omoyajowo, T. J., Ologuntere, E. T., & Abdullah, Z. (2022) · International Journal of Biochemistry Research & Review · doi:10.9734/ijbcrr/2022/v31i130299
Scassellati, C., & Bonvicini, C. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-819641-0.00103-1
Azimpour, M., Fathi, M., & Dezfulian, O. (2021) · Armaghane Danesh · doi:10.52547/armaghanj.26.3.307
Role of Buccal Cells in Neurodegeneration
Gonidi, M., Kontara, N., Vrahatis, A. G., Exarchos, T., & Vlamos, P. (2023) · Springer eBooks · doi:10.1007/978-3-319-75479-6_13-1
A neuroinflamação da Doença de Alzheimer e sua correlação anatômica
Netto, F. D. F., Santos, A. A., Gesser, G. T., Perreto, L., Pironatto, M. L. D. M., Andreassa, P. S., & Batista, T. Y. (2023) · Brazilian Journal of Health Review · doi:10.34119/bjhrv6n1-133
Du, Y., Zhang, Q., Zhang, X., Song, Y., Zheng, J., An, Y., & Lu, Y. (2023) · Research Square · doi:10.21203/rs.3.rs-2255566/v1
Investigating a Mechanistic Link between Mindful Music-Listening and Regulation of NeuroinflammationPreprint
Page, N., & Loui, P. (2023) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/7sde5 · Cited by 1
Role of Buccal Cells in Neurodegeneration
Gonidi, M., Kontara, N., Vrahatis, A. G., Exarchos, T. P., & Vlamos, P. (2023) · Springer eBooks · doi:10.1007/978-3-319-75922-7_13
THE PROMISING ROLE OF iNOS INHIBITORS IN ALZHEIMERS DISEASE
Ahmed, S. R., Tugcu, G., & Köksal, M. (2023) · Ankara Universitesi Eczacilik Fakultesi Dergisi · doi:10.33483/jfpau.1314900
Immunogenetics of Alzheimer’s disease: the human leukocyte antigen
Costescu, C., Vică, L. M., Bâlici, Ș., Nicula, G. Z., Nemeş, B., Coman, H. G., & Matei, H. V. (2023) · Psihiatru ro · doi:10.26416/psih.75.4.2023.8928
温, 涛. (2023) · Medical Diagnosis · doi:10.12677/md.2023.134067
Investigating CR1 as an indicated Gene for mild cognitive impairment in type 2 diabetes mellitus
Zhou, X., Wang, S., Yu, D., & Niu, T. (2024) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-024-01449-y
“Prior studies have indicated that CR1 significantly impacts AD pathology, primarily influencing Aβ deposition, immune response modulation, neuroinflammation, brain structure changes, and glucose metabolism throughout AD progression [33–36].”
BackgroundA Neuroinflammatory View of Alzheimer’s Disease
Anisman, H., Hayley, S. P., & Kusnecov, A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-23565-8.00005-3
(2024) · Elsevier eBooks · doi:10.1016/b978-0-443-23565-8.09996-8
Decreased interleukin-8 levels in the peripheral blood of Alzheimer’s patientsPreprint
Ros‐Bernal, F., Lozano, M. D. M., Arnau, J., Martínez‐López, J., Vericat, A., Sánchez, R., & Burgos, J. S. (2024) · medRxiv · doi:10.1101/2024.12.12.24318919
Qi, P., Huang, M., & Zhu, H. (2025) · Combinatorial Chemistry & High Throughput Screening · doi:10.2174/0113862073322931241030104813
Untangling the Genetic Threads of Alzheimer's: Insights into Risk Factors and Biomarkers
Naiyeri, A., Moqadami, A., & Khalaj‐Kondori, M. (2025) · Current Gene Therapy · doi:10.2174/0115665232338503241227111640
Review: New strategies for early dietary intervention in Alzheimer's disease
Huang, J. (2025) · Nutrition Clinique et Métabolisme · doi:10.1016/j.nupar.2024.11.002
Zhang, L., Liu, S., Zhao, Q., Liu, X.-Y., Liu, T., Zhang, Q., Liu, M.-H., & Zhao, W. (2025) · World Journal of Hepatology · doi:10.4254/wjh.v17.i2.102328
Dong, X., Wu, G., Zhang, L., Li, Q., Li, Y., Jin, F., Li, R., Ling, Y., & Xu, Y. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.01.651665
Wen, G., Niu, S., Mei, S., & Wang, S. (2025) · Scientific Reports · doi:10.1038/s41598-025-00585-3
“…better prognosis 52 , and the interaction of HLA-DPB1 and HLA-DRB5 can accelerate neuroinflammation, such as activation of proinflammatory intracellular signaling, release of cytokines/interleukins (TNF-α, TGF-β and IL-1β) in Alzheimer’s disease 53 , but the reports of HLA-DPB1 in LUAD are lacking.”
Yuan, S., Gaamouch, F. E., Cho, S., Kuncewicz, K., Nada, H., & Gabr, M. T. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.22.660908
Dong, X., Wu, G., Zhang, L., Li, Q., Li, Y., Jin, F., Li, R., Ling, Y., & Xu, Y. (2025) · Research Square · doi:10.21203/rs.3.rs-7047737/v1
Neuroinflammation links the neurogenic and neurodegenerative phenotypes of Nrmt1 -/- micePreprint
Catlin, J. P., Fraher, S., Alexander, J. J., & Tooley, C. E. S. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.02.673860
Xue, L., Yang, Y.-Q., Du, R., Gan, Z., Zhao, Y., Wang, W., Bi, N., Wang, Q., Wang, T., & Xiong, L. (2025) · The Journals of Gerontology Series A · doi:10.1093/gerona/glaf193
Che, Y., Qin, C., & Cui, Y. (2025) · Research Square · doi:10.21203/rs.3.rs-7522220/v1
Nordengen, K., Kirsebom, B.-E., Richter, G., Pålhaugen, L., Gísladóttir, B., Siafarikas, N., Nakling, A. E., Rongve, A., Bråthen, G., Grøntvedt, G. R., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26653528
Hok‐A‐Hin, Y. S., Hoozemans, J. J. M., Hu, W. T., Wouters, D., Howell, J. C., Rábano, A., van der Flier, W. M., Pijnenburg, Y. A. L., Teunissen, C. E., & del Campo, M. (2022) · Figshare · doi:10.6084/m9.figshare.20374647
Hok‐A‐Hin, Y. S., Hoozemans, J. J. M., Hu, W. T., Wouters, D., Howell, J. C., Rábano, A., van der Flier, W. M., Pijnenburg, Y. A. L., Teunissen, C. E., & del Campo, M. (2022) · Figshare · doi:10.6084/m9.figshare.20374653
Nordengen, K., Kirsebom, B.-E., Richter, G., Pålhaugen, L., Gísladóttir, B., Siafarikas, N., Nakling, A. E., Rongve, A., Bråthen, G., Grøntvedt, G. R., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26653531
Nordengen, K., Kirsebom, B.-E., Richter, G., Pålhaugen, L., Gísladóttir, B., Siafarikas, N., Nakling, A. E., Rongve, A., Bråthen, G., Grøntvedt, G. R., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26653534
Tomar, M., Dwivedi, S., & Darwhekar, G. (2025) · Premier Journal of Biomedical Science · doi:10.70389/pjs.100185
Mechanistic modeling of amyloid dynamics relating to Alzheimer's disease progression
Przekwas, A. J., Norris, C., & Garimella, H. T. (2026) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2026.1730480 · Cited by 1
“…Continued integration of complex models into a single framework has the potential to support a forthcoming revolution in personalized precision neurology (Hampel et al., 2020, 2018), enabling pre-symptomatic AD diagnosis, and development of early preventive and optimal therapeutic interventions.”
InfluentialPuente-Sanz, A., Mazzantini, C., Venturini, M., Mainolfi, F., Herrero-González, A., Pugliese, A. M., Fernández‐López, A., Pellegrini-Giampietro, D. E., & Landucci, E. (2026) · Brain Research · doi:10.1016/j.brainres.2026.150225
Decreased interleukin-8 levels in the peripheral blood of Alzheimer's disease patients
Ros, F., Lozano, M. D. M., Arnau, J., Martínez, J., Vericat, A., Sánchez, R. M., & Burgos, J. S. (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877261428052
Hemonnot-Girard, A.-L. (2021) · theses.fr (ABES) · doi:10.70675/9c8a4775zd774z494ez9bbazf7566faefa8f
Li, L., Yan, X., Cui, M. A., Yuting, W., Dou, T., & Xie, W. (2026) · Journal of Acupuncture and Tuina Science · doi:10.1007/s11726-026-1567-8
Microglia crosstalk with T cells in neurodegenerative diseases: pathogenesis and treatment targets
Chen, G., Zhao, C., Wang, C., Chen, G., Shi, J., & Chen, H. (2026) · International Immunopharmacology · doi:10.1016/j.intimp.2026.116781
Microglial advances in psychiatric disorders
de Jesus, J. R., Ribeiro, I. S., Pereira, M. V. S., Aquino, W. C. P., & Alfredo, L. H. M. (2026) · Advances in immunology · doi:10.1016/bs.ai.2026.04.007
Astrocyte subtype dynamics in mood disorders: Current insights and future directions
Chen, D., Wang, J., Zhu, G., & Yang, S. (2026) · Brain Network Disorders · doi:10.1016/j.bnd.2026.04.003
Functional Pathological Features and Molecular Markers in Alzheimer’s Disease
Park, M.-N., Kim, H. W., Hong, J., Kim, J. K., Lee, S.-B., Baek, H. S., Kwak, S., Kwon, Y. J., Park, K., Jeon, J., et al. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27114720
“Instead, AD is increasingly viewed as a disorder involving multiple interacting functional pathological processes that converge with these primary proteinopathies to drive neurodegeneration [7,8].”
Toothache and Alzheimer’s Disease: A Mendelian Randomization Study of the NAAG-CD33 Neuroimmune Axis
Qing, W., Xie, Y., Wu, X., Jin, S., Zhen, W., Yu, S., Sun, Y., Sun, W., Xu, J., & Zhang, H. (2026) · Journal of Pain Research · doi:10.2147/jpr.s603587
“56,57 Current evidence underscores CD33 as a pivotal neuroimmune checkpoint in the pathogenesis of AD.”
Guo, H., Yang, Z., & Cheng, L. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1837643 · Cited by 2
Wu, H., Xia, J., Shi, Z., Zhang, C., Chen, S., Dai, L., & He, L. (2026) · Neurochemical Research · doi:10.1007/s11064-026-04831-6
Neuroinflammation: molecular mechanisms, triggers, and biomarkers for clinical stratification
Khyzhnyak, M. V., Vasylieva, I. G., & Gafiychuk, Y. (2026) · Ukrainian Neurosurgical Journal · doi:10.25305/unj.350308
“In this context, PRRs and their downstream signaling cascades are considered key pathogenetic mechanisms, as well as promising therapeutic targets and biomarkers of neuroinflammatory activity [6, 7].”
InfluentialPiłat, D., Baranger, K., & Rivera, S. (2026) · Cytokine & Growth Factor Reviews · doi:10.1016/j.cytogfr.2026.07.004
Sheikh, S., Mollah, F., Chowdhury, R., Oni, M. I. J., Khatun, M. M., Shadin, M., Bhuia, M. S., Hoque, M. A., Alfaifi, M., Altemani, F. H., et al. (2026) · ChemistrySelect · doi:10.1002/slct.73819
JOVANOVIC, S., Rafiei, F., & Hackney, M. E. (2026) · Springer eBooks · doi:10.1007/978-3-032-21528-4_4
Environmental determinants of neurotoxicity: role of heavy metals in neurological disorders
Mandal, S., Dipa, P., Neha, Chatterjee, D., & Maparu, K. (2026) · Frontiers in Neurology · doi:10.3389/fneur.2026.1867856
“Future mechanistic and clinical studies are needed to elucidate specific inflammatory pathways and to develop precision therapeutic strategies to protect the integrity of the nervous system under environmental stress (51).”
Xu, L., Zhang, Y., Jiang, L., Xing, J. F., Hu, J., Lan, T., & Ta, G. (2026) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2026.1902577
Precision medicine: personalizing treatments for improved outcomes
Papadopoulou, P., & Stratakis, C. A. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-40572-3.00015-0
Dipu, M., Richi, S. N., Saha, S., Islam, M. M., Chakma, P., Ibnat, N., & Rahman, M. A. (2026) · Food and Humanity · doi:10.1016/j.foohum.2026.101490
Zhou, B., Zhong, Y., Meng, X., Xu, B., & Jia, L. (2026) · Pharmaceuticals · doi:10.3390/ph19101512
“Neuroinflammation, oxidative stress, mitochondrial dysfunction, metabolic disturbance, and progressive neuronal loss all contribute to disease onset and progression [4–7].”
Imbimbo, B. P., Pomara, N., Pini, L., & Frederiksen, K. S. (2026) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2026.119943
Self-citationSynthetic Protein Mimetic Modulators of Tau Aggregation
Lacambra, D. (2026) · Digital Commons - DU (University of Denver) · doi:10.56902/etdcrp.2026.169
Basile, S., Schipper, F., Zimbone, S., Vermorgen, S., Bellia, F., Parisi, C., Sortino, S., Walter, J., Giuffrida, M. L., Rozemüller, A. J. M., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-10769225/v1
Jacquier‐Sarlin, M. R., Seignobos, M., Rauzier, L., Schaack, B., Laurin, D., & Buisson, A. (2026) · Frontiers in Neuroscience · doi:10.3389/fnins.2026.1963040
“Precision medicine has considerably improved the diagnosis and management of AD by integrating genetic background, fluid biomarkers and neuropathological signatures (Hampel et al., 2020; Bellenguez et al., 2022).”
Chang, Y., Stavrides, P. H., Pidikiti, H., Ibrahim, K. W., Lee, J., Berg, M. J., Sachdeva, K. S., & Ginsberg, S. D. (2026) · Brain Sciences · doi:10.3390/brainsci16111152
Poonam, Rana, R., Thakur, M., Sharma, A., Pannu, S., Sharma, S., Naman, S., Rani, S., Devi, D., Kumar, V., et al. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2026.1908830
Metadata
- Authors
- Hampel, H., Caraci, F., Cuello, A. C., Caruso, G., Nisticò, R., Corbo, M., Baldacci, F., Toschi, N., Garaci, F., Chiesa, P. A., Verdooner, S. R., Akman-Anderson, L., Hernández, F., Ávila, J., Emanuele, E., Valenzuela, P. L., Lucía, A., Watling, M., Imbimbo, B. P., Vergallo, A., & Lista, S.
- Affiliations
- Sorbonne Université (FR)
- University of Catania (IT)
- University of Oxford (GB)
- I.R.C.C.S. Oasi Maria SS (IT)
- University of Rome Tor Vergata (IT)
- University of Pisa (IT)
- Centre National de la Recherche Scientifique (FR)
- Consejo Superior de Investigaciones Científicas (ES)
- Universidad de Alcalá (ES)
- Research Institute Hospital 12 de Octubre (ES)
- Chiesi (Italy) (IT)
- Corresponding author
- Hampel, Harald
- ORCID
- Venue
- Frontiers in Immunology
- Publisher
- Frontiers Media SA
- Published
- 2020-03-31
- Volume
- 11
- Pages
- 456-456
- ISSN
- 1664-3224 (ISSN-L)
- PMC
- PMC7137904
- OpenAlex
- W3014540555
- Cited by
- 360
- References
- 297
- Citations by year
- 2026: 43 · 2025: 53 · 2024: 53 · 2023: 66 · 2022: 69 · 2021: 49 · 2020: 22
- FWCI
- 5.13
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Immunology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by)
- Cineca Institutional Research Information System (Tor Vergata University) (submittedVersion, cc-by)
- Biblos-e Archivo (Universidad Autónoma de Madrid) (submittedVersion, cc-by)
- ABACUS. Repositorio de Producción Científica (Universidad Europea) (submittedVersion, cc-by-nc-nd)
- CINECA IRIS Institutial research information system (University of Pisa) (submittedVersion, other-oa)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion, cc-by)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Hispana (submittedVersion)
- Funders
- AXA Research Fund
- Eisai
- Sorbonne Université
- Fondation pour la Recherche sur Alzheimer
- Topics
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- Alzheimer's disease, neuroinflammation, TREM2, microglia, astrocytes, amyloid-beta, tau protein, synaptotoxicity, neurodegeneration, genetic risk variants, cytokines, TNF-α, IL-1β, TGF-beta, biomarkers, positron emission tomography, nonsteroidal anti-inflammatory drugs, disease-modifying therapy, precision medicine
- MeSH terms
- Cell Self Renewal, Alzheimer Disease, Animals, Humans, Signal Transduction, Cytokines, Neurogenic Inflammation, Proteomics, Systems Biology, Lipid Metabolism, Genome-Wide Association Study, Precision Medicine
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