Deciphering metabolic abnormalities associated with Alzheimer's disease in the APP/PS1 mouse model using integrated metabolomic approaches
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The transgenic mouse APP/PS1 is widely employed by neuroscientists because reproduces well some of the neuropathological and cognitive deficits observed in human Alzheimer's disease. In this study, serum samples from APP/PS1 mice (n = 30) and wild-type controls (n = 30) were analyzed using a metabolomic multiplatform based on the combination of gas chromatography-mass spectrometry and ultra-high performance liquid chromatography-mass spectrometry, in order to obtain wide information about serum metabolome. Metabolic profiles showed significant differences between the groups of study, and numerous metabolites were identified as potential players in the development of Alzheimer-type disorders in this transgenic model. Pathway analysis revealed the involvement of multiple metabolic networks in the underlying pathology, such as deficiencies in energy metabolism, altered amino acid homeostasis, abnormal membrane lipid metabolism, and other impairments related to the integrity of the central nervous system. It is noteworthy that some of these metabolomic markers are in accordance with pathological alterations observed in human Alzheimer's disease, while others have not been previously described. Therefore, these results demonstrate the potential of metabolomics and the use of transgenic animal models to understand the pathogenesis of Alzheimer's disease.
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Members of Lactobacillus have previously been shown to modulate mouse behavioral performance via vagal nerve innervation.
“Members of Lactobacillus have previously been shown to modulate mouse behavioral performance via vagal nerve innervation65,66.”
From Integrated analysis of behavioral, epigenetic, and gut microbiome analyses in AppNL-G-F, AppNL-F, and wild type mice (2021) · cites this paper as [66]
The Methods (p. 2) describe serum collection from APP/PS1 and control mice, and the Discussion (p. 6) addresses Alzheimer-related cognitive deficits and metabolic changes. Searches for Lactobacillus, vagal innervation, and microbiota-related effects on mouse behavior found no passage addressing the attributed claim. (LLM, conf=0.77)
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Self-citationRaber, J., Perez, R., Torres, E. R. S., Krenik, D., Boutros, S. W., Patel, E. M., Chlebowski, A. C., Torres, E. R., Perveen, Z., Penn, A. L., et al. (2021) · Environmental Health Perspectives · doi:10.1289/ehp8428 · Cited by 19 · see citing works
González‐Domínguez, Á., & González‐Domínguez, R. (2023) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2023.166910 · Cited by 22 · see citing works
Self-citationShen, L., Han, B., Geng, Y., Wang, J., Wang, Z., & Wang, M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0174763 · Cited by 19 · see citing works
García‐Barrera, T., Rodríguez‐Moro, G., Leblic, B. C., Arias‐Borrego, A., & Gómez‐Ariza, J. L. (2017) · Analytica Chimica Acta · doi:10.1016/j.aca.2017.10.019 · Cited by 17 · see citing works
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Self-citationWang, X., Yang, X., Hou, Z., Tian, S., Xu, G., Li, J., Wen, L., Bi, D., Gao, F., Shen, Y., et al. (2022) · Talanta · doi:10.1016/j.talanta.2022.124046 · Cited by 14 · see citing works
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Wei, M., Liu, Y., Pi, Z., Yue, K., Li, S., Hu, M., Liu, Z., Song, F., & Liu, Z. (2019) · RSC Advances · doi:10.1039/c9ra00302a · Cited by 10 · see citing works
High-Throughput Metabolomics Based on Direct Mass Spectrometry Analysis in Biomedical Research
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Analysis and Annotation of Phospholipids by Mass Spectrometry-Based Metabolomics
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Self-citationGonzález‐Domínguez, Á., Jurado‐Sumariva, L., Sayago, A., Schwarz, M., Fernández‐Recamales, Á., Durán, E., & González‐Domínguez, R. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-19116-9.00012-9
Self-citationXing, B., Xiaoqing, P., & Yan, Z. (2026) · Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · doi:10.1017/cjn.2025.10495
The Environmental Contribution to Health and Disease: Analytical Tools for Monitoring and Diagnosis
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Self-citation
- Authors
- González-Domínguez, R., García-Barrera, T., Vitorica, J., & Gómez-Ariza, J. L.
- Venue
- Biochimie
- Publisher
- Elsevier BV
- Published
- 2015-03
- Volume
- 110
- Pages
- 119-128
- ISSN
- 0037-9042 (ISSN-L)
- 0300-9084
- OpenAlex
- W2064380271
- Cited by
- 49
- References
- 70
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 3 · 2023: 6 · 2022: 2 · 2021: 6 · 2020: 3 · 2019: 3 · 2018: 7 · 2017: 9 · 2016: 1 · 2015: 4
- FWCI
- 5.17
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Biochimie (publishedVersion)
- PubMed (publishedVersion)
- Repositorio Institucional de la Universidad de Huelva (Universidad de Huelva) (submittedVersion)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion)
- Hispana (submittedVersion, cc-by-nc-nd)
- Deposito de Investigacion Universidad de Sevilla (University of Seville) (submittedVersion, cc-by-nc-nd)
- Repositorio Institucional de la Universidad de Huelva (Universidad de Huelva) (submittedVersion, cc-by-nc-nd)
- Funders
- Ministerio de Ciencia e Innovación (CTM2012-38720-C03-01)
- Consejería de Innovación
- Ciencia y Empresa (P009-FQM-4659)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- Alzheimer's disease, serum metabolome, metabolic abnormalities, energy metabolism, amino acid homeostasis, membrane lipid metabolism, metabolomic biomarkers, Alzheimer's disease pathogenesis
- MeSH terms
- Alzheimer Disease, Animals, Disease Models, Animal, Female, Male, Mice, Transgenic, Biomarkers, Multivariate Analysis, Amyloid beta-Protein Precursor, Mice, Presenilin-1, Metabolomics
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