The DOI matches its Crossref record; 210 of the 210 references it cites were found in a registry or an index.
Ageing as a risk factor for neurodegenerative disease
Abstract
Ageing is the primary risk factor for most neurodegenerative diseases, including Alzheimer disease (AD) and Parkinson disease (PD). One in ten individuals aged ≥65 years has AD and its prevalence continues to increase with increasing age. Few or no effective treatments are available for ageing-related neurodegenerative diseases, which tend to progress in an irreversible manner and are associated with large socioeconomic and personal costs. This Review discusses the pathogenesis of AD, PD and other neurodegenerative diseases, and describes their associations with the nine biological hallmarks of ageing: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, mitochondrial dysfunction, cellular senescence, deregulated nutrient sensing, stem cell exhaustion and altered intercellular communication. The central biological mechanisms of ageing and their potential as targets of novel therapies for neurodegenerative diseases are also discussed, with potential therapies including NAD+ precursors, mitophagy inducers and inhibitors of cellular senescence.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“The use of primary human monocytes also has several advantages: (i) their human origin enables the study of human-specific disease phenotypes and molecular mechanisms, (ii) monocytes derived from patients with AD may contain cell-intrinsic properties specific to that patient, and (iii) monocytes derived from patients with AD and age-matched controls may exhibit age-relevant phenotypes, given that”
From Understanding monocyte-driven neuroinflammation in Alzheimer’s disease using human cortical organoid microphysiological systems (2025) · cites this paper as [75]
In the citing paper
“Aging, which remains the largest risk factor for LOAD, is associated with low-grade systemic inflammation (termed “inflammaging”) [20, 21].”
From Microglial function, INPP5D/SHIP1 signaling, and NLRP3 inflammasome activation: implications for Alzheimer’s disease (2023) · cites this paper as [21]
In the citing paper
“Age‐related alterations in the brain microenvironment gradually led to increased BBB permeability and leakiness, neuronal degeneration, production of reactive oxygen species (ROS) and inflammation. 54 , 55 , 56”
From Therapeutic Properties and Pharmacological Activities of Asiaticoside and Madecassoside: A Review (2023) · cites this paper as [54]
In the citing paper
“Aging is known to be the primary driver of many neurodegenerative diseases, including Alzheimer’s disease (AD) [53].”
From Senescence-related impairment of autophagy induces toxic intraneuronal amyloid-β accumulation in a mouse model of amyloid pathology (2023) · cites this paper as [53]
In the citing paper
“This concurrence could explain the strong link between increased age and ND [83].”
From Untangling senescent and damage‐associated microglia in the aging and diseased brain (2023) · cites this paper as [83]
In the citing paper
“Aging is the predominant risk factor for cognitive dysfunction (Kalache and Gatti, 2003; Partridge et al., 2018) and several neurodegenerative disorders, including Alzheimer's disease (AD) and Parkinson's disease (PD) (Hou et al., 2019; López-Otín et al., 2013; Niccoli et al., 2017).”
From Atlas of the aging mouse brain reveals white matter as vulnerable foci (2023) · cites this paper as Hou et al., 2019
Citations
Cites
2 retracted
RETRACTED ARTICLE: Parkin and PINK1 mitigate STING-induced inflammation
Sliter, D. A., Martinez, J., Hao, L., Chen, X., Sun, N., Fischer, T. D., Burman, J. L., Li, Y., Zhang, Z., Narendra, D. P., et al. (2018) · Nature · doi:10.1038/s41586-018-0448-9 · Cited by 1,287
RetractedValera, E., Spencer, B. J., Fields, J. A., Trinh, I., Adame, A., Mante, M., Rockenstein, E. M., Desplats, P., & Masliah, E. (2017) · Acta Neuropathologica Communications · doi:10.1186/s40478-016-0409-1 · Cited by 49
RetractedLópez-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2013) · Cell · doi:10.1016/j.cell.2013.05.039 · Cited by 14,982
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
Kalia, L. V., & Lang, A. E. (2015) · The Lancet · doi:10.1016/s0140-6736(14)61393-3 · Cited by 6,184
The amyloid hypothesis of Alzheimer's disease at 25 years
Selkoe, D. J., & Hardy, J. (2016) · EMBO Molecular Medicine · doi:10.15252/emmm.201606210 · Cited by 6,164
The limited in vitro lifetime of human diploid cell strains
Hayflick, L. (1965) · Experimental Cell Research · doi:10.1016/0014-4827(65)90211-9 · Cited by 5,876
Poewe, W., Seppi, K., Tanner, C. M., Halliday, G. M., Brundin, P., Volkmann, J., Schrag, A.-E., & Lang, A. E. (2017) · Nature Reviews Disease Primers · doi:10.1038/nrdp.2017.13 · Cited by 5,415
The senescence-associated secretory phenotype: the dark side of tumor suppression
Coppé, J.-P., Desprez, P.-Y., Krtolica, A., & Campisi, J. (2010) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-121808-102144 · Cited by 5,206
Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy
Liu, C.-C., Kanekiyo, T., Xu, H., & Bu, G. (2013) · Nature Reviews Neurology · doi:10.1038/nrneurol.2012.263 · Cited by 3,459
Cited by
Sorted by citations
Items 901–1,000 of 1,007
Severe COVID-19 induces molecular signatures of aging in the human brainPreprint
Mavrikaki, M., Lee, J. D., Solomon, I. H., & Slack, F. J. (2021) · medRxiv · doi:10.1101/2021.11.24.21266779 · Cited by 23
Transcription Blockage by DNA Damage in Nucleotide Excision Repair-Related Neurological Dysfunctions
Kajitani, G. S., Nascimento, L. L. D. S., Neves, M. R. D. C., Leandro, G. D. S., Garcia, C. C. M., & Menck, C. F. M. (2021) · Seminars in Cell & Developmental Biology · doi:10.1016/j.semcdb.2020.10.009 · Cited by 22
Priorities Towards Fair Allocation of Ventilators During COVID-19 Pandemic: A Delphi Study
Ghamari, S., Abbasi‐Kangevari, M., Zamani, N., Hassanian‐Moghaddam, H., & Kolahi, A. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2021.769508 · Cited by 22
Jung, H. H., Ha, J., Park, J., Kang, S., Kim, J., Jung, H. N., Kim, S., Yea, J., Lee, H., Oh, S., et al. (2023) · Advanced Functional Materials · doi:10.1002/adfm.202311436 · Cited by 22
Xu, W., Zheng, H., Yang, R., Sun, Y.-F., Peng, B., Liu, C., Song, J., Jiang, S., & Zhu, L. (2024) · Cell Biology and Toxicology · doi:10.1007/s10565-024-09854-9 · Cited by 24
A deep‐learning retinal aging biomarker for cognitive decline and incident dementia
Sim, M. A., Tham, Y. C., Nusinovici, S., Quek, T. C., Yu, M., Xue, C. C., Chee, M. L., Peng, Q., Tan, E. S. J., Chan, S. P., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.14601 · Cited by 24
Design of engineered nanoparticles for biomedical applications by computational modeling
Chaparro, D., & Goudeli, E. (2025) · Nanoscale · doi:10.1039/d4nr05199h · Cited by 22
Alrouji, M., Alshammari, M. S., Syed, T., & Shamsi, A. (2025) · Antioxidants · doi:10.3390/antiox14070774 · Cited by 21
Gao, H., Zhou, H.-Q., Ji, H., Shen, J. Z., Yin, D., & Wu, D. (2025) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2025.119114 · Cited by 27
The rise of astrocytes: are they guardians or troublemakers of the brain disorder?
Kim, H. Y., Kim, S., Akaydin, A. N., Kim, S. S., Hyeon, S. J., Lee, J.-H., & Ryu, H. (2026) · Experimental & Molecular Medicine · doi:10.1038/s12276-025-01627-6 · Cited by 28
Yu, C.-C., Wang, J., Ye, S.-S., Gao, S., Li, J., Wang, L., Jiang, T., Wang, X., Li, B., Shu, Q., et al. (2020) · Evidence-based Complementary and Alternative Medicine · doi:10.1155/2020/1428752 · Cited by 23
Identifying Blood Transcriptome Biomarkers of Alzheimer’s Disease Using Transgenic Mice
Ochi, S., Iga, J., Funahashi, Y., Yoshino, Y., Yamazaki, K., Kumon, H., Mori, H., Ozaki, Y., Mori, T., & Ueno, S. (2020) · Molecular Neurobiology · doi:10.1007/s12035-020-02058-2 · Cited by 23
COllaborative Neuropathology NEtwork Characterizing ouTcomes of TBI (CONNECT-TBI)
Smith, D. H., Dollé, J.-P., Ameen‐Ali, K. E., Bretzin, A. C., Cortes, E. P., Crary, J. F., Dams-O’Connor, K., Diaz-Arrastia, R. R., Edlow, B. L., Folkerth, R. D., et al. (2021) · Acta Neuropathologica Communications · doi:10.1186/s40478-021-01122-9 · Cited by 23
Griñán‐Ferré, C., Bellver‐Sanchís, A., Olivares-Martín, M., Bañuelos, Ó., & Pallàs, M. (2021) · Nutrients · doi:10.3390/nu13072411 · Cited by 22
Fatal attraction – The role of hypoxia when alpha-synuclein gets intimate with mitochondria
Burtscher, J., Syed, M. M. K., Keller, M. A., Lashuel, H. A., & Millet, G. P. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.07.017 · Cited by 25
Nies, S. H., Takahashi, H., Herber, C. S., Huttner, A. J., Chase, A., & Strittmatter, S. M. (2021) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2021.101159 · Cited by 25
Astrocytic MicroRNA in Ageing, Inflammation, and Neurodegenerative Disease
Chu, A. J., & Williams, J. M. (2022) · Frontiers in Physiology · doi:10.3389/fphys.2021.826697 · Cited by 22
Giampietri, L., Belli, E., Beatino, M. F., Giannoni, S., Palermo, G., Campese, N., Tognoni, G., Siciliano, G., Ceravolo, R., Luca, C. D., et al. (2022) · Diagnostics · doi:10.3390/diagnostics12040796 · Cited by 22
Practices and Patterns of Hourly Neurochecks: Analysis of 8,936 Patients With Neurological Injury
LaBuzetta, J. N., Hirshman, B. R., Malhotra, A., Owens, R. L., & Kamdar, B. B. (2021) · Journal of Intensive Care Medicine · doi:10.1177/08850666211029220 · Cited by 23
Li, X., Cao, G., Liu, X., Tang, T.-S., Guo, C., & Liu, H. (2022) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2022.852002 · Cited by 22
Bahlakeh, G., Rahbarghazi, R., Abedelahi, A., Sadigh‐Eteghad, S., & Karimipour, M. (2022) · Stem Cell Research & Therapy · doi:10.1186/s13287-022-03024-6 · Cited by 22
Lu, J., Wang, M., Wu, P., Yakushev, I. Y., Zhang, H., Ziegler, S. I., Jiang, J., Förster, S., Wang, J., Schwaiger, M., et al. (2022) · Phenomics · doi:10.1007/s43657-022-00079-6 · Cited by 22
Therapeutic potential of melatonin and its derivatives in aging and neurodegenerative diseases
Verma, A. K., Singh, S., & Rizvi, S. I. (2022) · Biogerontology · doi:10.1007/s10522-022-10006-x · Cited by 23
Aguayo, G., Zhang, L., Vaillant, M., Ngari, M. M., Perquin, M., Moran, V., Huiart, L., Krüger, R., Azuaje, F. J., Ferdynus, C., et al. (2023) · BMC Medical Research Methodology · doi:10.1186/s12874-023-01837-4 · Cited by 23
Yu, M., Ye, H., De-Paula, R. B., Mangleburg, C. G., Wu, T., Lee, T. V., Li, Y., Duong, D. M., Phillips, B., Cruchaga, C., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010760 · Cited by 22
McMurran, C. E., Wang, Y., Mak, J. K. L., Karlsson, I., Tang, B., Ploner, A., Pedersen, N. L., & Hägg, S. (2023) · Brain · doi:10.1093/brain/awad252 · Cited by 21
Cyclophilin D in Mitochondrial Dysfunction: A Key Player in Neurodegeneration?
Coluccino, G., Muraca, V. P., Corazza, A., & Lippe, G. (2023) · Biomolecules · doi:10.3390/biom13081265 · Cited by 23
The gut microbiome: an important role in neurodegenerative diseases and their therapeutic advances
Li, S., Zhao, L., Xiao, J., Guo, Y., Fu, R., Zhang, Y., & Xu, S. (2023) · Molecular and Cellular Biochemistry · doi:10.1007/s11010-023-04853-6 · Cited by 23
Chitosan – An alternative drug delivery approach for neurodegenerative diseases
Iyer, M., Elangovan, A., Ramya, S., Babu, H. W. S., Saranya, T., Krishnan, J., Yadav, M., Gopalakrishnan, A. V., Narayanasamy, A., & Vellingiri, B. (2024) · Carbohydrate Polymer Technologies and Applications · doi:10.1016/j.carpta.2024.100460 · Cited by 23
Mesecar, M. E., Duffy, M. F., Acri, D. J., Ding, J., Langston, R. G., Shah, S. I., Nalls, M. A., Reed, X., Scholz, S. W., Whitaker, D. T., et al. (2026) · npj Aging · doi:10.1038/s41514-026-00391-9 · Cited by 28
FoxO3 transcription factor promotes autophagy after oxidative stress injury in HT22 cells
Deng, A., Ma, L., Zhou, X., Wang, X., Wang, S., & Chen, X. (2020) · Canadian Journal of Physiology and Pharmacology · doi:10.1139/cjpp-2020-0448 · Cited by 22
Emotion Regulation in Couples Across Adulthood
Haase, C. M. (2023) · Annual Review of Developmental Psychology · doi:10.1146/annurev-devpsych-120621-043836 · Cited by 29
Etxebeste-Mitxeltorena, M., Niza, E., Fajardo, C. M., Gil, C., Gómez‐Gómez, L., Martı́nez, A., & Ahrazem, O. (2024) · Natural Products and Bioprospecting · doi:10.1007/s13659-023-00425-9 · Cited by 21
Patel, V. R., Liu, M., Worsham, C. M., & Jena, A. B. (2024) · BMJ · doi:10.1136/bmj-2024-082194 · Cited by 21
Clinical biomarkers of perioperative neurocognitive disorder: initiation and recommendation
Liu, J., Li, C., Yao, J., Zhang, L., Zhao, X., Lv, X., Liu, Z., Miao, C., Wang, Y., Jiang, H., et al. (2025) · Science China Life Sciences · doi:10.1007/s11427-024-2797-x · Cited by 21
Augusto‐Oliveira, M., Arrifano, G. D. P., Leal-Nazaré, C. G., Chaves-Filho, A. J. M., Santos-Sacramento, L., Lopes-Araújo, A., Tremblay, M., & Lopez, M. E. C. (2025) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2025.106091 · Cited by 28
The Complementary Role of Morphology in Understanding Microglial Functional Heterogeneity
Godeanu, S., & Cătălin, B. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26083811 · Cited by 22
Mayer, M. G., & Fischer, T. (2025) · American Journal Of Pathology · doi:10.1016/j.ajpath.2025.03.011 · Cited by 22
Advances in research on mitochondrial dysfunction in neurodegenerative diseases
Zhang, Y., Li, X., Zhang, Y., & Li, X. (2025) · Journal of Neurology · doi:10.1007/s00415-025-13101-4 · Cited by 25
Extracellular vesicles in age-related diseases: disease pathogenesis, intervention, and biomarker
Putri, P. H. L., Alamudi, S. H., Dong, X., & Fu, Y. L. (2025) · Stem Cell Research & Therapy · doi:10.1186/s13287-025-04374-7 · Cited by 25
He, Z., Zhang, H., Hu, G., Qiao, Y., Yin, C., Li, J., Lin, H., Wu, A., Qin, D., Law, B. Y. K., et al. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1583339 · Cited by 29
Jadhav, V. S., & Khatri, D. K. (2025) · Ageing Research Reviews · doi:10.1016/j.arr.2025.102872 · Cited by 22
Spatial and single-cell transcriptomics reveal the reorganization of cerebellar microglia with aging
Tsai, A. P., Henze, D. E., Lopez, E. R., Haberberger, J., Dong, C., Lu, N., Atkins, M., Costa, E. K., Farinas, A., Oh, H. S., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116624 · Cited by 23
A review of nardosinone for pharmacological activities
Wen, J., Liu, L., Li, J., & He, Y. (2021) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2021.174343 · Cited by 22
Biomonitoring of Mycotoxins in Plasma of Patients with Alzheimer’s and Parkinson’s Disease
Arce-López, B., Alvarez‐Erviti, L., Santis, B. D., Izco, M., López-Calvo, S., Marzo-Sola, M. E., Debegnach, F., Lizarraga, E., de Ceráin, A. L., González‐Peñas, E., et al. (2021) · Toxins · doi:10.3390/toxins13070477 · Cited by 21
Ying, F., Lin, S., Li, J., Zhang, X., & Chen, G. (2021) · Food Bioscience · doi:10.1016/j.fbio.2021.101355 · Cited by 21
Zhang, Y., Zhang, Y., Shi, X., Han, J., Lin, B., Peng, W., Mei, Z., & Yang, L. (2022) · Diabetic Medicine · doi:10.1111/dme.14821 · Cited by 22
Chen, S., Hu, N., Wang, H., & Li, G. (2022) · Journal of Functional Foods · doi:10.1016/j.jff.2022.105104 · Cited by 21
Rosell‐Cardona, C., Amat, C., Griñán‐Ferré, C., Polo, J., Pallàs, M., Pérez‐Bosque, A., Moretó, M., & Miró, L. (2022) · Nutrients · doi:10.3390/nu14112211 · Cited by 22
Anselmi, C., Kowarsky, M., Gasparini, F., Caicci, F., Ishizuka, K. J., Palmeri, K. J., Raveh, T., Sinha, R., Neff, N. F., Quake, S. R., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2203032119 · Cited by 22
Zhang, H., Fu, Y., Chen, M., & Si, L. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.942911 · Cited by 21
Overview of the role of big data in mental health: A scoping review
Ahmed, A., Agus, M., Alzubaidi, M. S., Aziz, S., Abd-Alrazaq, A. A., Giannicchi, A., & Househ, M. S. (2022) · Computer Methods and Programs in Biomedicine Update · doi:10.1016/j.cmpbup.2022.100076 · Cited by 21
Malis, V., Bae, W. C., Yamamoto, A., McEvoy, L. K., McDonald, M. A., & Miyazaki, M. (2022) · Magnetic Resonance in Medical Sciences · doi:10.2463/mrms.mp.2022-0117 · Cited by 21
Vascular endothelial cells: a fundamental approach for brain waste clearance
Wei, H., Jiang, H., Zhou, Y., Xiao, X., Zhou, C., & Ji, X. (2022) · Brain · doi:10.1093/brain/awac495 · Cited by 20
Yu, Y., Wang, Y., Dong, Y. C., Shu, S., Zhang, D., Xu, J., Zhang, Y., Shi, W., & Wang, S. (2023) · Environmental Science and Pollution Research · doi:10.1007/s11356-023-25729-8 · Cited by 22
Feng, Z., Wu, J., Liu, W., Ren, H., Zheng, X., Zhang, W., Lee, C., & Wang, P. (2023) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2023.133668 · Cited by 22
Karami, F., Jamaati, H., Coleman‐Fuller, N., Zeini, M. S., Hayes, A. W., Gholami, M., Salehirad, M., Darabi, M., & Motaghinejad, M. (2023) · Pharmacological Reports · doi:10.1007/s43440-023-00469-1 · Cited by 21
Chepisheva, M. (2023) · PeerJ · doi:10.7717/peerj.15040 · Cited by 25
Diagnosis of neurodegenerative diseases with a refined Lempel–Ziv complexity
Zhao, H., Xie, J., Chen, Y., Cao, J., Liao, W., & Cao, H. (2023) · Cognitive Neurodynamics · doi:10.1007/s11571-023-09973-9 · Cited by 21
Microglia in brain aging: An overview of recent basic science and clinical research developments
Fan, H., Zhang, M., Wen, J., Wang, S., Yuan, M., Sun, H., Shu, L., Xu, Y., Pu, Y., & Cai, Z. (2023) · Journal of Biomedical Research · doi:10.7555/jbr.37.20220220 · Cited by 23
Finley, J. A., Cladek, A., Gonzalez, C., & Brook, M. A. (2023) · The Clinical Neuropsychologist · doi:10.1080/13854046.2023.2241190 · Cited by 23
Healthy brain aging and delayed dementia in Texas rural elderly
Basu, T., Sehar, U., Malhotra, K., Culberson, J. W., Khan, H. M. R., Morton, H., Orlov, E., Brownell, M., & Reddy, P. H. (2023) · Ageing Research Reviews · doi:10.1016/j.arr.2023.102047 · Cited by 24
Wu, A., Yong, Y.-Y., He, C., Li, Y.-P., Zhou, X., Yu, L., Chen, Q., Lan, C., Liu, J., Yu, C., et al. (2024) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2024.111901 · Cited by 21
Neuroprotective Roles of the Biliverdin Reductase-A/Bilirubin Axis in the Brain
Paul, B. D., & Pieper, A. A. (2024) · Biomolecules · doi:10.3390/biom14020155 · Cited by 21
Liu, Y., Meng, X.-K., Shao, W.-Z., Liu, Y.-Q., Tang, C., Deng, S.-S., Tang, C., Zheng, L., & Guo, W. (2024) · Neurochemical Research · doi:10.1007/s11064-024-04108-w · Cited by 22
Hypoxia Sensing and Responses in Parkinson’s Disease
Burtscher, J., Duderstadt, Y., Gatterer, H., Burtscher, M., Vozdek, R., Millet, G. P., Hicks, A. A., Ehrenreich, H., & Kopp, M. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25031759 · Cited by 24
Lutein and the Underlying Neuroprotective Promise against Neurodegenerative Diseases
Iyer, S., Bhat, I., & Sheshappa, M. B. (2024) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.202300409 · Cited by 22
Gou, R., Yang, J., Guo, M., Chen, Y., & Xue, W. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c00504 · Cited by 21
Suppressing UBE2N ameliorates Alzheimer's disease pathology through the clearance of amyloid beta
Zhang, C., Jia, Q., Zhu, L., Hou, J., Wang, X., Li, D., Zhang, J., Zhang, Y., Su, Y., Tu, Z., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14122 · Cited by 19
Immunosenescence: A new direction in anti-aging research
Li, H., Lin, S., Wang, Y., Shi, Y., Fang, X., Wang, J., Cui, H., Bian, Y., & Qi, X. (2024) · International Immunopharmacology · doi:10.1016/j.intimp.2024.112900 · Cited by 21
Săndulescu, V., Ianculescu, M., Valeanu, L., & Alexandru, A. (2024) · Algorithms · doi:10.3390/a17090376 · Cited by 21
Neurodegeneration trajectory in pediatric and adult/late DM1: A follow‐up MRI study across a decade
Labayru, G., Jiménez-Marín, A., Fernández, E., Villanúa, J., Zulaica, M., Cortés, J. M., Diez, I. P., Sepulcre, J., de Munaín, A. L., & Sistiaga, A. (2020) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51163 · Cited by 24
Wang, Y., Kang, Y., Qi, C., Zhang, T., Zhao, H., Ji, X., Yan, W., Huang, Y., Cui, R., Zhang, G., et al. (2020) · Aging · doi:10.18632/aging.104155 · Cited by 23
Generation of RRMS and PPMS specific iPSCs as a platform for modeling Multiple Sclerosis
Mutukula, N., Man, Z., Takahashi, Y., Martinez, F. I., Morales, M., Guarnizo, E. C., Clares, R. H., García‐Bernal, D., Martinez, L. M., Lajara, J., et al. (2021) · Stem Cell Research · doi:10.1016/j.scr.2021.102319 · Cited by 19
Age-Related Adaptive Immune Changes in Parkinson’s Disease
Kouli, A., & Williams-Gray, C. H. (2022) · Journal of Parkinson's Disease · doi:10.3233/jpd-223228 · Cited by 20
Ma, Y., Wang, X., Li, X., Chen, X., Teng, Z., Yang, J., Yang, J., & Liu, G. (2024) · Molecular Neurobiology · doi:10.1007/s12035-024-03976-1 · Cited by 20
Deformability of Heterogeneous Red Blood Cells in Aging and Related Pathologies
Prudinnik, D. S., Kussanova, A., Vorobjev, I. A., Tikhonov, A., Ataullakhanov, F. I., & Barteneva, N. S. (2024) · Aging and Disease · doi:10.14336/ad.2024.0526 · Cited by 21
Multifunctional PLGA nanosystems: enabling integrated diagnostic and therapeutic strategies
Li, Y., Tao, T., Xiong, Y., Guo, W., & Liang, Y. (2025) · Frontiers in Pharmacology · doi:10.3389/fphar.2025.1670397 · Cited by 24
D’Errico, M., Parlanti, E., Pascucci, B., Filomeni, G., Mastroberardino, P. G., & Dogliotti, E. (2021) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2021.108977 · Cited by 20
Wu, S., Chen, M., Liao, X., Huang, R., Wang, J., Xie, Y., Hu, H., Zhang, J., Wu, Q., & Ding, Y. (2021) · Journal of Food Biochemistry · doi:10.1111/jfbc.13879 · Cited by 20
Peng, H.-R., Yu, S., Zhang, Y., Yin, Y., & Zhou, J. (2022) · Neuroscience Bulletin · doi:10.1007/s12264-022-00848-3 · Cited by 20
Haynes, E. M., Ulland, T. K., & Eliceiri, K. W. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2022.867010 · Cited by 24
Scarian, E., Bordoni, M., Fantini, V., Jacchetti, E., Raimondi, M. T., Diamanti, L., Carelli, S., Cereda, C., & Pansarasa, O. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23105344 · Cited by 21
The Role of Sesamin in Targeting Neurodegenerative Disorders: A Systematic Review
Ghaderi, M. A., Emami, S. A., Olia, M. D. B., & Javadi, B. (2022) · Mini-Reviews in Medicinal Chemistry · doi:10.2174/1389557522666220523112027 · Cited by 21
Prasuhn, J., Kunert, L., & Brüggemann, N. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23137263 · Cited by 20
Mitophagy: An Emergence of New Player in Alzheimer’s Disease
Sharma, B., Pal, D., Sharma, U., & Kumar, A. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2022.921908 · Cited by 21
Athanasiou, E., Gargalionis, A. N., Anastassopoulou, C. G., Tsakris, A., & Boufidou, F. (2022) · Brain Sciences · doi:10.3390/brainsci12081010 · Cited by 20
Characteristic Hallmarks of Aging and the Impact on Carcinogenesis
Fiore, M., Terracina, S. A., Ferraguti, G., Petrella, C., Bruno, S. M., Blaconà, G., Certo, M. G. D., Minni, A., Greco, A., Musacchio, A., et al. (2022) · Current Cancer Drug Targets · doi:10.2174/1568009622666220816120353 · Cited by 21
Preclinical Alzheimer’s dementia: a useful concept or another dead end?
Mark, R. E., & Brehmer, Y. (2022) · European Journal of Ageing · doi:10.1007/s10433-022-00735-w · Cited by 20
Targeting amyloid proteins for clinical diagnosis of neurodegenerative diseases
Zhang, S., Dong, H., Bian, J., Li, D., & Liu, C. (2022) · Fundamental Research · doi:10.1016/j.fmre.2022.10.009 · Cited by 23
Norouzkhani, N., Karimi, A. G., Badami, N., Jalalifar, E., Mahmoudvand, B., Ansari, A., Sariyarighan, N. P., Alijanzadeh, D., Aghakhani, S., Shayestehmehr, R., et al. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.960037 · Cited by 24
Zhao, X., Lin, Y., Liou, B., Fu, W., Jian, J., Fannin, V., Zhang, W., Setchell, K. D. R., Grabowski, G. A., Sun, Y., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2210442120 · Cited by 22
Wu, J., Wang, L., Ervin, J. F., Wang, S. J., Soderblom, E. J., Ko, D. C., & Yan, D. (2022) · Science Advances · doi:10.1126/sciadv.adc9236 · Cited by 17
Pérez-Arancibia, R., Cisternas-Olmedo, M., Sepúlveda, D., Troncoso-Escudero, P., & Vidal, R. L. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.1084493 · Cited by 21
Rhythms in barriers and fluids: Circadian clock regulation in the aging neurovascular unit
Skapetze, L., Owino, S., Lo, E. H., Arai, K., Merrow, M. W., & Harrington, M. E. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106120 · Cited by 20
Soleymani, T., Chen, T.-Y., Gonzalez‐Kozlova, E., & Dogra, N. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1156821 · Cited by 22
Ravenhill, S. M., Evans, A. H., & Crewther, S. G. (2023) · Antioxidants · doi:10.3390/antiox12051117 · Cited by 22
Zhang, J., Chen, K., Yin, J.-Y., Zheng, Y., Chen, R., Liu, W., Tang, S., Zhang, J., Zhang, M., Wang, Z., et al. (2023) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2023.175824 · Cited by 23
Sollmann, N., Hoffmann, G., Schramm, S., Reichert, M., Petzsche, M. R. H., Strobel, J., Nigris, L., Kloth, C., Roßkopf, J., Börner, C., et al. (2023) · RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren · doi:10.1055/a-2119-5574 · Cited by 19
An enquiry to the role of CB1 receptors in neurodegeneration
Fernández‐Moncada, I., Eraso‐Pichot, A., Tor, T. D., Fortunato-Marsol, B., & Marsicano, G. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106235 · Cited by 23
Metadata
- Authors
- Hou, Y., Dan, X., Babbar, M., Wei, Y., Hasselbalch, S. G., Croteau, D. L., & Bohr, V. A.
- Affiliations
- National Institute on Aging (US)
- University of Copenhagen (DK)
- Corresponding author
- Bohr, Vilhelm A.
- ORCID
- Venue
- Nature Reviews Neurology
- Published
- 2019-09-09
- Volume
- 15
- Issue
- 10
- Pages
- 565-581
- ISSN
- 1759-4758 (ISSN-L)
- 1759-4766
- OpenAlex
- W2972368830
- Semantic Scholar
- 4f2aec225c7ce5314a73bd30acc5348f6086766b
- Cited by
- 3,310
- References
- 209
- Citations by year
- 2026: 441 · 2025: 639 · 2024: 675 · 2023: 534 · 2022: 474 · 2021: 359 · 2020: 178 · 2019: 8
- FWCI
- 22.06
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nature Reviews Neurology (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Funders
- National Institute on Aging
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- 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
- aging, neurodegenerative diseases, Alzheimer's disease, Parkinson's disease, genomic instability, telomere shortening, epigenetic modifications, proteostasis, mitochondrial dysfunction, cellular senescence, nutrient sensing, stem cell exhaustion, intercellular communication, NAD+ precursors, mitophagy, senolytics, therapeutic target
- MeSH terms
- Aging, Brain, DNA Damage, Humans, Risk Factors, Neurodegenerative Diseases, Epigenesis, Genetic, Mitophagy
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