Cited by 195Metabolomics and Mass Spectrometry StudiesDementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

The DOI matches its Crossref record; 211 of the 215 references it cites were found in a registry or an index.

Metabolomics of Human Brain Aging and Age-Related Neurodegenerative Diseases

Jové, Mariona, Portero-Otín, Manuel, Naudí, Alba, Ferrer, Isidre, Pamplona, Reinald·2014·Journal of Neuropathology & Experimental Neurology

DOI 10.1097/nen.0000000000000091

Open this paper in CoChat — free account

Abstract

Neurons in the mature human central nervous system (CNS) perform a wide range of motor, sensory, regulatory, behavioral, and cognitive functions. Such diverse functional output requires a great diversity of CNS neuronal and non-neuronal populations. Metabolomics encompasses the study of the complete set of metabolites/low-molecular-weight intermediates (metabolome), which are context-dependent and vary according to the physiology, developmental state, or pathologic state of the cell, tissue, organ, or organism. Therefore, the use of metabolomics can help to unravel the diversity-and to disclose the specificity-of metabolic traits and their alterations in the brain and in fluids such as cerebrospinal fluid and plasma, thus helping to uncover potential biomarkers of aging and neurodegenerative diseases. Here, we review the current applications of metabolomics in studies of CNS aging and certain age-related neurodegenerative diseases such as Alzheimer disease, Parkinson disease, and amyotrophic lateral sclerosis. Neurometabolomics will increase knowledge of the physiologic and pathologic functions of neural cells and will place the concept of selective neuronal vulnerability in a metabolic context.

Integrity signals

Registry

Crossref · 10.1097/nen.0000000000000091

Cites

211 of 211 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

1 retracted

RETRACTED: Endoplasmic reticulum stress and induction of the unfolded protein response in human sporadic amyotrophic lateral sclerosis
Atkin, J. D., Farg, M. A., Walker, A. K., McLean, C., Tomas, D., & Horne, M. K. (2008) · Neurobiology of Disease · doi:10.1016/j.nbd.2008.02.009 · Cited by 350
Retracted
Free radicals in biology and medicine
Gutteridge, J. M. C. (1991) · General Pharmacology The Vascular System · doi:10.1016/0306-3623(91)90478-o · Cited by 17,178
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
HMDB: the Human Metabolome Database
Wishart, D. S., Tzur, D., Knox, C., Eisner, R., Guo, A. C., Young, N., Cheng, D., Jewell, K., Arndt, D., Sawhney, S., et al. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkl923 · Cited by 3,219
An anatomically comprehensive atlas of the adult human brain transcriptome
Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., van de Lagemaat, L. N., Smith, K. A., Ebbert, A., Riley, Z. L., et al. (2012) · Nature · doi:10.1038/nature11405 · Cited by 3,083
Uric acid provides an antioxidant defense in humans against oxidant- and radical-caused aging and cancer: a hypothesis.
Ames, B. N., Cathcart, R., Schwiers, E., & Hochstein, P. (1981) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.78.11.6858 · Cited by 2,915
HMDB 3.0—The Human Metabolome Database in 2013
Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M., Knox, C., Liu, Y., Djoumbou-Feunang, Y., Mandal, R., Aziat, F., Dong, E., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1065 · Cited by 2,845
Metabolomics: the apogee of the omics trilogy
Patti, G. J., Yanes, Ó., & Siuzdak, G. E. (2012) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3314 · Cited by 2,605
The expensive-tissue hypothesis: The brain and the digestive system in human and primate evolution
Aiello, L. C., & Wheeler, P. (1995) · Current Anthropology · doi:10.1086/204350 · Cited by 2,291
Gene regulation and DNA damage in the ageing human brain
Lu, T., Pan, Y., Kao, S.-Y., Li, C., Kohane, I., Chan, J., & Yankner, B. A. (2004) · Nature · doi:10.1038/nature02661 · Cited by 1,874

Show all 215 references

Research works printed but not linked: 4

Rasouri, 2007, [SIRT1/PGC-1: A neuroprotective axis?], Med Sci, 23, 840
Carrié, 2000, Specific phospholipid fatty acid composition of brain regions in mice, Effects of n − 3 polyunsaturated fatty acid deficiency and phospholipid supplementation. J Lipid Res, 41, 465
10.1210/en.142.1.506 · DOI
Lorenzo, 2006, Differential expression of GABAA and glycine receptors in ALS-resistant vs, ALS-vulnerable motoneurons: Possible implications for selective vulnerability of motoneurons. Eur J Neurosci, 23, 3161

Sorted by citations

Items 101–195 of 195

Blood-Based Biomarkers of Alzheimers Disease: Diagnostic Algorithms and New Technologies
Carmona, P., Molina, M., & Tolédano, A. (2016) · Current Alzheimer Research · doi:10.2174/1567205013666151116130301 · Cited by 21
Temporal lobe in human aging: A quantitative protein profiling study of samples from Chinese Human Brain Bank
Xu, B., Xiong, F., Tian, R., Zhan, S., Gao, Y., Qiu, W., Wang, R., Ge, W., & Ma, C. (2015) · Experimental Gerontology · doi:10.1016/j.exger.2015.11.016 · Cited by 21
Toll Like Receptor 4 Affects the Cerebral Biochemical Changes Induced by MPTP Treatment
Conte, C., Roscini, L., Sardella, R., Mariucci, G., Scorzoni, S., Beccari, T., & Corte, L. (2017) · Neurochemical Research · doi:10.1007/s11064-016-2095-6 · Cited by 20
Rapid Solution-Phase Hydrogen/Deuterium Exchange for Metabolite Compound Identification
Majuta, S. N., Li, C., Jayasundara, K. U., Karanji, A. K., Attanayake, K., Ranganathan, N., Li, P., & Valentine, S. J. (2019) · Journal of the American Society for Mass Spectrometry · doi:10.1007/s13361-019-02163-0 · Cited by 19
Identification of candidate biomarkers of brain damage in a mouse model of closed head injury: a metabolomic pilot study
Bahado-Singh, R. O., Graham, S. F., Türkoğlu, O., Beauchamp, K. M., Bjorndahl, T. C., Han, B., Mandal, R., Pantane, J., Kowalenko, T., Wishart, D. S., et al. (2016) · Metabolomics · doi:10.1007/s11306-016-0957-1 · Cited by 18
Alterations in Urine Metabolomics Following Sport-Related Concussion: A 1H NMR-Based Analysis
Wanner, Z. R., Southam, C., Sanghavi, P., Boora, N. S., Paxman, E., Dukelow, S. P., Benson, B. W., Montina, T., Metz, G. A. S., & Debert, C. T. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.645829 · Cited by 17
Nicotinamide riboside and caffeine partially restore diminished NAD availability but not altered energy metabolism in Alzheimer's disease
Ryu, W., Shen, M., Lee, Y., Healy, R. A., Bormann, M. K., Cohen, B. M., & Sonntag, K. (2022) · Aging Cell · doi:10.1111/acel.13658 · Cited by 18
Plasma and cerebrospinal fluid nonenzymatic protein damage is sustained in Alzheimer's disease
Dakterzada, F., Jové, M., Cantero, J. L., Pamplona, R., & Piñoll‐Ripoll, G. (2023) · Redox Biology · doi:10.1016/j.redox.2023.102772 · Cited by 17
Self-citation
Age-related changes in the metabolic profiles of rat hippocampus, medial prefrontal cortex and striatum
Durani, L. W., Hamezah, H. S., Ibrahim, N. F., Yanagisawa, D., Makpol, S., Damanhuri, H. A., & Tooyama, I. (2017) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2017.09.164 · Cited by 17
Quantitativein vivoneurochemical profiling in humans: where are we now?
McKay, J. A., & Tkáč, I. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw235 · Cited by 16
UPLC-QTOFMS-based metabolomic analysis of the serum of hypoxic preconditioning mice
Liu, J., Zhang, G., Chen, D., Chen, J., Yuan, Z., Zhang, E., Gao, Y., Xu, G., Sun, B.-D., Liao, W., et al. (2017) · Molecular Medicine Reports · doi:10.3892/mmr.2017.7493 · Cited by 16
Toward defining the anatomo‐proteomic puzzle of the human brain: An integrative analysis
Fernández‐Irigoyen, J., Labarga, A., Zabaleta, A., de Morentin, X. M., Pérez‐Valderrama, E., Zelaya, M. V., & Santamaría, E. (2014) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201400127 · Cited by 16
UHPLC-QTOFMS-Based Metabolomic Analysis of the Hippocampus in Hypoxia Preconditioned Mouse
Liao, W., Liu, J., Zhou, S.-M., Xu, G., Gao, Y., & Liu, W. (2019) · Frontiers in Physiology · doi:10.3389/fphys.2018.01950 · Cited by 16
Urinary Biomarkers for Lupus Nephritis: A Systems Biology Approach
Omer, M. H., Shafqat, A., Ahmad, O., Nadri, J., AlKattan, K. M., & Yaqinuddin, A. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13082339 · Cited by 15
Altered Plasma Acylcarnitines and Amino Acids Profile in Spinocerebellar Ataxia Type 7
Nambo-Venegas, R., Valdez-Vargas, C., Cisneros, B., Palacios-González, B., Vela-Amieva, M., Ibarra-González, I., Cerecedo-Zapata, C. M., Martínez-Cruz, E., Cortés, H., Reyes-Grajeda, J. P., et al. (2020) · Biomolecules · doi:10.3390/biom10030390 · Cited by 15
Metabolic profiling reveals dysregulated lipid metabolism and potential biomarkers associated with the development and progression of Fragile X‐Associated Tremor/Ataxia Syndrome (FXTAS)
Zafarullah, M., Palczewski, G., Rivera, S. M., Hessl, D. R., & Tassone, F. (2020) · The FASEB Journal · doi:10.1096/fj.202001880r · Cited by 15
Interconnections of insulin/IGF‐1 signaling and autophagy abnormalities in Alzheimer's disease
Liao, W., Xuan, J., Ryu, W., Bormann, M. K., Lee, Y., Dion, H., Evangelista, E., Li, R., Trambaiolli, L. R., Liu, J., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70099 · Cited by 14
Assessing Causal Relationship Between Human Blood Metabolites and Five Neurodegenerative Diseases With GWAS Summary Statistics
Chen, H., Qiao, J., Wang, T., Shao, Z., Huang, S., & Zeng, P. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.680104 · Cited by 14
Effects of Moxibustion and Moxa Smoke on Behavior Changes and Energy Metabolism in APP/PS1 Mice
Ha, L., Yu, M., Yan, Z., Rui, Z., & Zhao, B. (2019) · Evidence-based Complementary and Alternative Medicine · doi:10.1155/2019/9419567 · Cited by 14
Anti‐ageing effect of red ginseng revealed by urinary metabonomics using RRLC‐Q‐TOF‐MS
Sun, J., Jiao, C., Ma, Y., Chen, J., Wu, W., & Liu, S. (2018) · Phytochemical Analysis · doi:10.1002/pca.2758 · Cited by 14
Rapamycin improves sevoflurane‑induced cognitive dysfunction in aged rats by mediating autophagy through the TLR4/MyD88/NF‑κB signaling pathway
Li, Y., Liu, L., Tian, Y., & Zhang, J. (2019) · Molecular Medicine Reports · doi:10.3892/mmr.2019.10541 · Cited by 14
Metabolite signatures of diabetes with cardiovascular disease: a pilot investigation
Reddivari, L., Sapkota, B. R., Rudraraju, A., Liang, Y., Aston, C. E., Sidorov, E. V., Vanamala, J., & Sanghera, D. K. (2017) · Metabolomics · doi:10.1007/s11306-017-1278-8 · Cited by 13
Dynamic metabolic patterns tracking neurodegeneration and gliosis following 26S proteasome dysfunction in mouse forebrain neurons
Geiszler, P. C., Ugun‐Klusek, A., Lawler, K., Pardon, M., Ding, Y., Bai, L., Daykin, C. A., Auer, D. P., & Bedford, L. (2018) · Scientific Reports · doi:10.1038/s41598-018-23155-2 · Cited by 14
A prospective pilot study using metabolomics discloses specific fatty acid, catecholamine and tryptophan metabolic pathways as possible predictors for a negative outcome after severe trauma
Serviá, L., Jové, M., Sol, J., Pamplona, R., Badía, M., Montserrat, N., Portero‐Otín, M., & Trujillano, J. (2019) · Scandinavian Journal of Trauma Resuscitation and Emergency Medicine · doi:10.1186/s13049-019-0631-5 · Cited by 13
Self-citation
Hypothesis and Theory: Characterizing Abnormalities of Energy Metabolism Using a Cellular Platform as a Personalized Medicine Approach for Alzheimer’s Disease
Ryu, W., Cohen, B. M., & Sonntag, K. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.697578 · Cited by 14
Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients
Atya, H. B., Ali, S. A. E.-M., Hegazy, M. I., & Sharkawi, F. Z. E. (2017) · Indian Journal of Clinical Biochemistry · doi:10.1007/s12291-017-0661-6 · Cited by 12
Phenotypic molecular features of long-lived animal species
Jové, M., Mota‐Martorell, N., Fernàndez‐Bernal, A., Portero‐Otín, M., Barja, G., & Pamplona, R. (2023) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2023.09.023 · Cited by 11
Self-citation
Targeted quantitative metabolic profiling of brain-derived cell cultures by semi-automated MEPS and LC-MS/MS
Protti, M., Cirrincione, M., Palano, S., Poeta, E., Babini, G., Magnifico, M. C., Barile, S. N., Balboni, N., Massenzio, F., Mahdavijalal, M., et al. (2023) · Journal of Pharmaceutical and Biomedical Analysis · doi:10.1016/j.jpba.2023.115757 · Cited by 11
Do age and sex impact on the absolute cell numbers of human brain regions?
de Oliveira-Pinto, A. V., Andrade-Moraes, C. H., Oliveira, L. M., Rayêe, D., Santos, R. M., Coutinho, R., Alho, A. T. D. L., Leite, R. E. P., Suemoto, C. K., Grinberg, L. T., et al. (2015) · Brain Structure and Function · doi:10.1007/s00429-015-1118-4 · Cited by 11
Future perspectives: Moving towards NCL treatments
Cotman, S. L., Mole, S., & Kohan, R. (2015) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2015.04.001 · Cited by 11
Metabolomic Estimation of the Diagnosis and Onset Time of Permanent and Transient Cerebral Ischemia
Cambray, S., Portero‐Otín, M., Jové, M., Torreguitart, N., Campàs, L. C., Sanz‐Alcázar, A., Benabdelhak, I., Yemişçi, M., Dalkara, T., Dönmez‐Demir, B., et al. (2017) · Molecular Neurobiology · doi:10.1007/s12035-017-0827-5 · Cited by 12
Self-citation
Viewpoint on the role of tissue maintenance in ageing: focus on biomarkers of bone, cartilage, muscle, and brain tissue maintenance
van der Spoel, E., van Vliet, N. A., & van Heemst, D. (2019) · Ageing Research Reviews · doi:10.1016/j.arr.2019.100964 · Cited by 11
Convergent synthesis and characterization of fatty acid-conjugated poly(ethylene glycol)-block-poly(epsilon-caprolactone) nanoparticles for improved drug delivery to the brain
Li, H. Y., Zhang, B., Chan, P. S., Weng, J., Tsang, C. K., & Lee, T. W.-Y. (2017) · European Polymer Journal · doi:10.1016/j.eurpolymj.2017.11.038 · Cited by 10
Determinants of Vitamin B6 Status in Community-Dwelling Older Adults: A Longitudinal Study Over a Period of 18 Years
Jungert, A., & Neuhäuser‐Berthold, M. (2019) · The Journals of Gerontology Series A · doi:10.1093/gerona/glz010 · Cited by 10
Explainable Brain Age Prediction using coVariance Neural Networks.Preprint
Sihag, S., Mateos, G., McMillan, C. T., & Ribeiro, A. (2023) · PubMed · Cited by 10
Sleep deprivation and aging are metabolically linked across tissues
Sengupta, A., Tudor, J. C., Cusmano, D. M., Baur, J. A., Abel, T. G., & Weljie, A. M. (2023) · SLEEP · doi:10.1093/sleep/zsad246 · Cited by 9
The Potential of Metabolomics to Find Proper Biomarkers for Addressing the Neuroprotective Efficacy of Drugs Aimed at Delaying Parkinson’s and Alzheimer’s Disease Progression
Franco, R., Garrigós, C., Lillo, J., & Rivas‐Santisteban, R. (2024) · Cells · doi:10.3390/cells13151288 · Cited by 9
Retrospection on the Role of Soluble Guanylate Cyclase in Parkinson's Disease.
Ghanta, M. K., Panchanathan, E., Bhaskar, L. V., & Narayanaswamy, A. S. (2017) · Europe PMC (PubMed Central) · doi:10.4103/jpp.jpp_45_17 · Cited by 10
GC-MS Based Metabolic Profiling of Parkinson’s Disease with Glutathione S-transferase M1 and T1 Polymorphism in Tunisian Patients
Rebai, A., Reçber, T., Nemutlu, E., Chbili, C., Kurbanoğlu, S., Kır, S., Amor, S. B., Özkan, S. A., & Saguem, S. (2020) · Combinatorial Chemistry & High Throughput Screening · doi:10.2174/1386207323666200428082815 · Cited by 8
Pharmacotherapeutic Potential of Garlic in Age-Related Neurological Disorders
Ahangar‐Sirous, R., Poudineh, M., Ansari, A., Nili, A., Dana, S. M. M. A., Nasiri, Z., Hosseini, Z., Karami, D., Mokhtari, M., & Deravi, N. (2021) · CNS & Neurological Disorders - Drug Targets · doi:10.2174/1871527320666210927101257 · Cited by 8
Preventive Effect of Soybean on Brain Aging and Amyloid-β Accumulation: Comprehensive Analysis of Brain Gene Expression
Unno, K., & Konishi, T. (2015) · Recent Patents on Food Nutrition & Agriculture · doi:10.2174/2212798407666150629140132 · Cited by 7
Confounders in metabolomics
Tokarz, J., & Adamski, J. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-812784-1.00002-5 · Cited by 7
A Multi‐Organ Atlas Links Gut Microbial Metabolites to Systemic Redox Changes in Aging Mice
Sajid, S., Huang, J., Kong, S., Lai, C., Tan, Z., Shao, Y., & Guo, L. (2026) · Aging Cell · doi:10.1111/acel.70433 · Cited by 7
Exploring the Link Between the Gut Mycobiome and Neurological Disorders
Yetgin, A. (2024) · Advanced Gut & Microbiome Research · doi:10.1155/2024/9965893 · Cited by 6
A Urinary Metabolomics Analysis Based on UPLC-MS and Effects of Moxibustion in APP/PS1 Mice
He, R., Liu, J., Huang, C., Liu, J., Cui, H., & Zhao, B. (2020) · Current Alzheimer Research · doi:10.2174/1567205017666201109091759 · Cited by 6
Metabolic variation in Caribbean giant barrel sponges: Influence of age and sea-depth
Bayona, L. M., Kim, M. S., Swierts, T., Hwang, G., de Voogd, N. J., & Choi, Y. H. (2021) · Marine Environmental Research · doi:10.1016/j.marenvres.2021.105503 · Cited by 6
2-Year-Old and 3-Year-Old Italian ALS Patients with Novel ALS2 Mutations: Identification of Key Metabolites in Their Serum and Plasma
Gautam, M., Carratore, R. D., Helmold, B., Tessa, A., Gözütok, Ö., Chandel, N. S., Idrısoğlu, H. A., Bongioanni, P., Battini, R., & Özdi̇nler, P. H. (2022) · Metabolites · doi:10.3390/metabo12020174 · Cited by 6
Ischemia preconditioning induces an adaptive response that defines a circulating metabolomic signature in ischemic stroke patients
Sol, J., Campàs, L. C., Mauri, G., Molina‐Seguin, J., Galo‐Licona, J. D., Torres-Querol, C., Aymerich, N., Ois, Á., Roquer, J., Tur, S., et al. (2022) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x221116288 · Cited by 6
Self-citation
Transferability of coVariance Neural Networks
Sihag, S., Mateos, G., McMillan, C. T., & Ribeiro, A. (2024) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2024.3378887 · Cited by 6
Impaired mitochondrial energy metabolism
Das, B. B., Ray, P., & Raut, S. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819621-2.00004-8 · Cited by 6
Multilayer metabolomic integration reveals bioenergetic disruption in Long COVID
García‐Hidalgo, M. C., Mota‐Martorell, N., González, J., Benitez, I. D., Jové, M., Barbé, F., Amigó, N., Pamplona, R., de Gonzalo‐Calvo, D., & Torres, G. (2026) · Journal of Translational Medicine · doi:10.1186/s12967-026-07684-3 · Cited by 4
Self-citation
Metabolomics and Risk of Dementia: A Systematic Review of Prospective Studies
Flores, A. C., Zhang, X., Kris‐Etherton, P. M., Sliwinski, M. J., Shearer, G. C., Gao, X., & Na, M. (2024) · Journal of Nutrition · doi:10.1016/j.tjnut.2024.01.012 · Cited by 7
Advances in metabolomics profiling of pediatric kidney diseases: A review
Huang, G. (2024) · Biomolecules and Biomedicine · doi:10.17305/bb.2024.10098 · Cited by 5
Growth of Malignant Non-CNS Tumors Alters Brain Metabolome
KOVALCHUK, A. V., Nersisyan, L., Mandal, R., Wishart, D. S., Mancini, M., Sidransky, D., Kolb, B. E., & Kovalchuk, O. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00041 · Cited by 5
Metabolome of the Brain
Dryagina, N. V., Kondratyeva, E., Dubrovskii, Y. A., & Kondratyev, A. N. (2020) · Russian neurological Journal · doi:10.30629/2658-7947-2020-25-1-4-12 · Cited by 4
Studies on metabolic alterations due to hypobaric hypoxia in serum using NMR spectroscopy
Koundal, S., Gandhi, S., & Khushu, S. (2022) · Biomarkers · doi:10.1080/1354750x.2022.2076152 · Cited by 4
Targeted Metabolomic Analysis of the Eye Tissue of Triple Transgenic Alzheimer’s Disease Mice at an Early Pathological Stage
Shen, L., Tang, X., Zhang, H., Zhuang, H., Jing, L., Zhao, Y., & Liu, X. (2023) · Molecular Neurobiology · doi:10.1007/s12035-023-03533-2 · Cited by 4
Reducing subspace models for large‐scale covariance regression
Franks, A. M. (2021) · Biometrics · doi:10.1111/biom.13531 · Cited by 5
Ether lipids and sphingolipids drive sex-specific human aging dynamics
Sol, J., Fernàndez‐Bernal, A., Mota‐Martorell, N., Martin‐Garí, M., Òbis, È., Juanes-Casado, A., Ayala, V., Mayneris‐Perxachs, J., Ramos, R., Pineda, V., et al. (2025) · Redox Biology · doi:10.1016/j.redox.2025.103779 · Cited by 3
Self-citation
Loliolide combats glutamate-induced neurotoxicity by oxidative stress through MAPK/Nrf2 pathway in hippocampal neuronal cells
Kim, H., Cheon, J., Kirindage, K. G. I. S., Jayasinghe, A. M. K., Han, E. J., Park, S.-M., Ahn, G., & Cha, S. (2024) · Algal Research · doi:10.1016/j.algal.2024.103866 · Cited by 3
Constraint-based modeling of bioenergetic differences between synaptic and non-synaptic components of dopaminergic neurons in Parkinson’s disease
Luo, X., Assal, D. C. E., Liu, Y., Ranjbar, S., & Fleming, R. M. T. (2025) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2025.1594330 · Cited by 3
Biochemical Markers in Parkinson's Disease
Čeprnja, M., & Vuletić, V. (2020) · Neurology - Research & Surgery · doi:10.33425/2641-4333.1032 · Cited by 3
Explainable Brain Age Gap Prediction in Neurodegenerative Conditions Using Covariance Neural Networks
Sihag, S., Mateos, G., & Ribeiro, A. (2025) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi60581.2025.10980674 · Cited by 3
Human Derived Dermal Fibroblasts as in Vitro Research Tool to Study Circadian Rhythmicity in Psychiatric Disorders
Palm, D., Uzoni, A., Kronenberg, G., Thome, J., & Faltraco, F. (2023) · Pharmacopsychiatry · doi:10.1055/a-1147-1552 · Cited by 4
The relationship between the brain and spirituality with respect to aging and neurodegenerative diseases: clinical and research implications
Datta, S., & Newberg, A. B. (2020) · Journal of Religion Spirituality & Aging · doi:10.1080/15528030.2020.1773372 · Cited by 5
Bidirectional Causal Associations Between Plasma Metabolites and Parkinson’s Disease
Zhao, M., Li, T., Shen, H., Baranova, A. V., Chandhoke, V., & Zhang, F. (2025) · Molecular Neurobiology · doi:10.1007/s12035-025-05306-5 · Cited by 2
Cognitive processes affect the gait of subjects with Parkinson’s and Alzheimer’s disease in dual tasks
Christofoletti, G., Felippe, L. A., Müller, P. D. T., Beinotti, F., & BORGES, G. A. (2015) · Jornal Brasileiro de Psiquiatria · doi:10.1590/0047-2085000000071 · Cited by 2
Artificial intelligence approaches in biological age prediction: current status and challenges
Wang, G., Ding, P., Li, Z., Tang, Q., Tu, L., Jiang, T., Zhang, L., Su, B., Xu, J., & An, H. (2026) · British Journal of Biomedical Science · doi:10.3389/bjbs.2026.16141 · Cited by 1
Concepts in Pharmacogenomics: Tools and Applications
Vemula, D., Singothu, S., & Bhandari, V. (2023) · Springer eBooks · doi:10.1007/978-981-99-2302-1_2 · Cited by 1
Lipoxidation
Pamplona, R., Jové, M., Pradas, I., Mota‐Martorell, N., & Ferrer, I. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-817990-1.00008-1 · Cited by 1
Self-citation
Personalized Management of Neurological Disorders
Jain, K. K. (2015) · Springer eBooks · doi:10.1007/978-1-4939-2553-7_12
Single-Cell Metabolomics
Bunawan, H., & Baharum, S. N. (2016) · Series in bioengineering · doi:10.1007/978-3-662-49118-8_11
1H NMR metabolomics of stress
Kiss, D. (2016)
ORBIS-Met: Optimization of R based integrative statistics for metabolome analyses
Culleré, J. S. (2017) · The Oberta in Open Access (Universitat Oberta de Catalunya)
Nontargeted Brain Lipidomic Profiling Performed by UPLC-ESI-qToF-MS/MS
Naudí, A., Cabré, R., Jové, M., & Pamplona, R. (2017) · Neuromethods · doi:10.1007/978-1-4939-7119-0_6
Self-citation
Sisyphus in Neverland
Ferrer, I. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-170609
Self-citation
Determinação de fosfolípides plasmáticos nas doenças neuropsiquiátricas
Costa, A. C. (2017) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/d.5.2017.tde-11092017-115142
Molecular insights into the effects of cancer and chemotherapy on the brain
Kovalchuk, A. (2017)
Morphology of GFAP-Positive Cells in Male and Female Rats’ Cerebral Cortex during the Cerebral Hypoxia Development according to the Stress Tolerance Level
Chrishtop, V. V., Rumyantseva, T. А., & Пожилов, Д. А. (2019) · RUDN Journal of Medicine · doi:10.22363/2313-0245-2019-23-4-397-404
Detection of Alzheimer’s Disease in Brain MR Images Using Hybrid Local Graph Structure
Srinivasan, A., Prasad, I. A., Mounya, V., Bhattacharjee, P., & Sanyal, G. (2020) · Springer eBooks · doi:10.1007/978-3-030-41862-5_91
Improving Characterization of Small Molecules using Enhanced Molecular Reaction and Ionization Techniques
Majuta, S. N. (2021) · The Research Repository @ WVU (West Virginia University) · doi:10.33915/etd.8113
Principles of Management of Drug-Induced Neurological Disorders
Jain, K. K. (2021) · Springer eBooks · doi:10.1007/978-3-030-73503-6_6
Biomarker discovery
Scalbert, A., & Ferrari, P. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-812784-1.00010-4
MORPHOLOGICAL CHANGES IN RAT CORTICAL CELLS DURING CEREBRAL HYPOPERFUSION WITH SHORT-TERM PHYSICAL EXERCISE AS A FUNCTION OF SEX AND STRESS TOLERANCE
Криштоп, В. В., Rumyantseva, T. А., & Nikonorova, V. G. (2022) · Russian Biomedical Research · doi:10.56871/8132.2022.26.86.002
Protective effects of tiger milk mushroom (lignosus rhinocerus) extracts on oxidative stress-induced neurotoxicity and aging in HT22 cells and C. elegans
Kittimongkolsuk, P. (2020) · doi:10.58837/chula.the.2020.115
A study of work ability and associated factors in aging office workers with non-communicable diseases and musculoskeletal disorders
Rawdeng, S. (2021) · doi:10.58837/chula.the.2021.317
Marcadores periféricos de metabolismo de membrana: caracterização de indivíduos com alto risco para psicose
Costa, A. C. (2023) · doi:10.11606/t.5.2023.tde-14092023-143128
Ameliorating Effect of Black Chia (Salvia Hispanica L.) Oil and/ or Peppermint (Mentha Piperita L.) Oil on Neurological Effects Induced by Lead Acetate in Growing Albino Rats
Ali, A., Mohamed, K. E., El-Fattah, B. A., & Helal, H. (2023) · Egyptian Journal of Chemistry · doi:10.21608/ejchem.2023.240111.8705
Gender - and age-related differences in plasma metabolic fingerprinting of healthy populationsPreprint
Xie, Y., Tao, Q., Li, J., Wu, Y., Liu, Z., Chen, Y., & Zeng, C. (2023) · Research Square · doi:10.21203/rs.3.rs-3673972/v1
The Effect of Self-Designed Anti-Aging and Prolonging Life Formula on Learning, Memory, and Inflammatory Factors in D-Galactose-Induced Aging Rats
熊, 彤. (2024) · Pharmacy Information · doi:10.12677/pi.2024.132014
Treating Lafora Disease with an Antibody-Enzyme Fusion
Gentry, M. S., Markussen, K. H., Sun, R. C., & Kooi, C. W. V. (2024) · Oxford University Press eBooks · doi:10.1093/med/9780197549469.003.0055
The Research of Proteomics in Neurodegenerative Diseases Based on Bibliometric Analysis
An, X., He, J., Yu, W., & Ren, Z. (2025) · Brain and Behavior · doi:10.1002/brb3.70964
Cftr nominates a novel therapeutic target for Alzheimer's disease: Evidence from integrative omics and in vitro validation
Li, H., Shi, J.-Z., Zhang, M.-J., Yun, L.-Y., Zhou, Y., He, Y.-Y., Li, X., Du, G.-H., Pang, X., Wang, M., et al. (2025) · Neuropharmacology · doi:10.1016/j.neuropharm.2025.110808
Toward clinical implementation of a metabolic blood biomarker for Parkinson’s disease differential diagnosisPreprint
Millasseau, V., Mallet, D., Carnicella, S., Barbier, E., Sauvée, M., Gouëllec, A. L., Cannet, C., Pompe, N., Boulet, S., & Fauvelle, F. (2026) · medRxiv · doi:10.64898/2026.04.02.26349497
Metabolomic Biomarkers of Cellular Senescence in Neurodegenerative Disease
Slocum, D. L., Duka, D., Antonelli, L., & Logan, R. (2026) · IntechOpen eBooks · doi:10.5772/intechopen.1018049

Authors: Jové, M., Portero-Otín, M., Naudí, A., Ferrer, I., & Pamplona, R.
Affiliations: Universitat de Lleida (ES)
Corresponding author: Pamplona, Reinald
ORCID: Jové, Mariona
Naudí, Alba
Pamplona, Reinald
Venue: Journal of Neuropathology & Experimental Neurology
Publisher: Oxford University Press (OUP)
Published: 2014-07
Volume: 73
Issue: 7
Pages: 640-657
ISSN: 0022-3069 (ISSN-L)
1554-6578
DOI: 10.1097/nen.0000000000000091
OpenAlex: W2317167530
Cited by: 195
References: 215
Citations by year: 2026: 5 · 2025: 8 · 2024: 13 · 2023: 15 · 2022: 12 · 2021: 21 · 2020: 19 · 2019: 18 · 2018: 20 · 2017: 22 · 2016: 19 · 2015: 20 · 2014: 3
FWCI: 2.01
Type: journal article
Language: en
Open access: closed
Locations: Journal of Neuropathology & Experimental Neurology (publishedVersion)
PubMed (publishedVersion)
Topics: 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
Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
Keywords: brain aging, age-related neurodegenerative diseases, Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, cerebrospinal fluid metabolites, plasma metabolites, aging biomarkers, selective neuronal vulnerability, central nervous system metabolism
MeSH terms: Aged, Aged, 80 and over, Aging, Alzheimer Disease, Amyotrophic Lateral Sclerosis, Brain, Energy Metabolism, Female, Humans, Male, Neurons, Parkinson Disease, Species Specificity, Biomarkers, Neurodegenerative Diseases, Metabolomics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Metabolomics of Human Brain Aging and Age-Related Neurodegenerative Diseases

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks