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 601–700 of 1,007
Liu, X., Shen, L., Wan, M., Xie, H., & Wang, Z. (2024) · Journal of Nanobiotechnology · doi:10.1186/s12951-024-02428-1 · Cited by 33
Nuclear pore complex maintenance and implications for age-related diseases
Liu, J., & Hetzer, M. W. (2021) · Trends in Cell Biology · doi:10.1016/j.tcb.2021.10.001 · Cited by 35
Zacharias, H. U., Kaleta, C., Cossais, F., Schaeffer, E., Berndt, H., Best, L., Dost, T., Glüsing, S., Groussin, M., Poyet, M., et al. (2022) · Metabolites · doi:10.3390/metabo12121222 · Cited by 38
Acteoside palliates d-galactose induced cognitive impairment by regulating intestinal homeostasis
Li, M., Zhu, M., Quan, W., Huang, W., Liu, X., Zhang, C., Lu, B., Xiao, X., & Liu, Z. (2023) · Food Chemistry · doi:10.1016/j.foodchem.2023.135978 · Cited by 35
Lemaître, P., Tareen, S. H. K., Pasciuto, E., Mascali, L. G., Martirosyan, A., Callaerts‐Vegh, Z., Poovathingal, S. K., Dooley, J., Holt, M. G., Yshii, L., et al. (2023) · EMBO Molecular Medicine · doi:10.15252/emmm.202216805 · Cited by 31
Multimodal Precision Prevention - A New Direction in Alzheimer's Disease
Barbera, M., Perera, D., Matton, A., Mangialasche, F., Rosenberg, A., Middleton, L. T., Ngandu, T., Solomon, A., & Kivipelto, M. (2023) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2023.114 · Cited by 38
Ungvari, A., Gulej, R., Csík, B., Mukli, P., Negri, S., Tarantini, S., Yabluchanskiy, A., Benyó, Z., Csiszár, A., & Ungvari, Z. I. (2023) · Nutrients · doi:10.3390/nu15214662 · Cited by 34
Spatially resolved transcriptome of the aging mouse brain
Wu, C., Tu, T., Xie, M., Wang, Y., Yan, B., Gong, Y., Zhang, J., Zhou, X., & Xie, Z. (2024) · Aging Cell · doi:10.1111/acel.14109 · Cited by 33
Olloquequi, J., Díaz‐Peña, R., Verdaguer, E., Ettcheto, M., Auladell, C., & Camins, A. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25136928 · Cited by 40
Splicing accuracy varies across human introns, tissues, age and disease
García-Ruiz, S., Zhang, D., Gustavsson, E. K., Rocamora-Perez, G., Grant‐Peters, M., Fairbrother-Browne, A., Reynolds, R. H., Brenton, J., Gil-Martínez, A. L., Chen, Z., et al. (2025) · Nature Communications · doi:10.1038/s41467-024-55607-x · Cited by 33
Chiral Inorganic Nanomaterial‐Based Diagnosis and Treatments for Neurodegenerative Diseases
Dong, J., Xu, L., Qu, A., Hao, C., Sun, M., Xu, C., Hu, S., & Kuang, H. (2025) · Advanced Materials · doi:10.1002/adma.202418723 · Cited by 35
Stress granules: emerging players in neurodegenerative diseases
Yuan, L., Mao, L.-H., Huang, Y.-Y., Outeiro, T. F., Li, W., Vieira, T. C. R. G., & Li, J. (2025) · Translational Neurodegeneration · doi:10.1186/s40035-025-00482-9 · Cited by 48
Enhancing mitophagy as a therapeutic approach for neurodegenerative diseases
Aman, Y., Ryan, B. J., Torsetnes, S. B., Knapskog, A., Watne, L. O., McEwan, W. A., & Fang, E. F. (2020) · International review of neurobiology · doi:10.1016/bs.irn.2020.02.008 · Cited by 36
Fei, D., Wang, Y., Zhai, Q., Zhang, X., Zhang, Y., Wang, Y., Li, B., & Wang, Q. (2021) · Stem Cell Research & Therapy · doi:10.1186/s13287-021-02164-5 · Cited by 34
Crosstalk between Different DNA Repair Pathways Contributes to Neurodegenerative Diseases
Gupta, S., You, P., SenGupta, T., Nilsen, H. L., & Sharma, K. (2021) · Biology · doi:10.3390/biology10020163 · Cited by 37
Reprogramming: Emerging Strategies to Rejuvenate Aging Cells and Tissues
Alle, Q., Le Borgne, E., Milhavet, O., & Lemaitre, J.-M. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22083990 · Cited by 35
Common Principles and Specific Mechanisms of Mitophagy from Yeast to Humans
Kumar, R., & Reichert, A. S. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22094363 · Cited by 33
Are the Acute Effects of THC Different in Aging Adults?
Mueller, R. L., Ellingson, J. M., Bidwell, L. C., Bryan, A. D., & Hutchison, K. E. (2021) · Brain Sciences · doi:10.3390/brainsci11050590 · Cited by 32
An NRF2 Perspective on Stem Cells and Ageing
Dodson, M. B., Anandhan, A., Zhang, D. D., & Madhavan, L. (2021) · Frontiers in Aging · doi:10.3389/fragi.2021.690686 · Cited by 35
Engineered neural circuits for modeling brain physiology and neuropathology
Bang, S., Hwang, K. S., Jeong, S., Cho, I., Choi, N., Kim, J., & Kim, H. N. (2021) · Acta Biomaterialia · doi:10.1016/j.actbio.2021.06.024 · Cited by 32
LRRK2 Kinase Inhibitor Rejuvenates Oxidative Stress‐Induced Cellular Senescence in Neuronal Cells
Ho, D. H., Nam, D., Seo, M. K., Park, S. W., Seol, W., & Son, I. (2021) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2021/9969842 · Cited by 33
Inflammasome activation in neurodegenerative diseases
Ravichandran, K. A., & Heneka, M. T. (2021) · Essays in Biochemistry · doi:10.1042/ebc20210021 · Cited by 37
Oligodendrocytes and myelin: Active players in neurodegenerative brains?
Chen, J., Wang, F., Huang, N., Xiao, L., & Mei, F. (2022) · Developmental Neurobiology · doi:10.1002/dneu.22867 · Cited by 37
Lee, J., Kim, S. W., & Kim, K.-T. (2022) · Cells · doi:10.3390/cells11121902 · Cited by 34
Wang, Z., Wang, W., Zhu, C., Gao, X., & Chu, W. (2022) · Frontiers in Nutrition · doi:10.3389/fnut.2022.861097 · Cited by 34
Wang, E., Wang, N., Zou, Y., Muhammad, F., Zhou, Y., Yang, H., Liu, Y., & Li, H. (2022) · Food Research International · doi:10.1016/j.foodres.2022.111696 · Cited by 34
Chiou, K. L., DeCasien, A. R., Rees, K. P., Testard, C., Spurrell, C. H., Gogate, A. A., Pliner, H. A., Tremblay, S., Mercer, A., Whalen, C. J., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01197-0 · Cited by 36
Ernest James Phillips, T., & Maguire, E. (2021) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2021.652593 · Cited by 33
Kim, J., Um, H., Kim, N. H., & Kim, D. (2023) · Bioactive Materials · doi:10.1016/j.bioactmat.2023.01.006 · Cited by 33
Dihydroxy‐Metabolites of Dihomo‐γ‐linolenic acid drive ferroptosis‐mediated neurodegeneration
Sarparast, M., Pourmand, E., Hinman, J., Vonarx, D., Reason, T., Zhang, F., Paithankar, S., Chen, B., Borhan, B., Watts, J. L., et al. (2023) · ACS Central Science · doi:10.1021/acscentsci.3c00052 · Cited by 33
Neurologic complications of coronavirus and other respiratory viral infections
Cavallieri, F., Sellner, J., Zedde, M., & Moro, E. (2022) · Handbook of clinical neurology · doi:10.1016/b978-0-323-91532-8.00004-5 · Cited by 32
Role of Sirtuin 3 in Degenerative Diseases of the Central Nervous System
Zhang, H., Dai, S., Yang, Y., Wei, J., Li, X., Luo, P., & Jiang, X. (2023) · Biomolecules · doi:10.3390/biom13050735 · Cited by 33
Yang, S., Xiu, M., Li, X., Shi, Y., Wang, S., Wan, S., Han, S., Yang, D., Liu, Y., & He, J. (2023) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2023.124609 · Cited by 35
Senescent Microglia Represent a Subset of Disease-Associated Microglia in P301S Mice
Ng, P. Y., Zhang, C., Li, H., & Baker, D. J. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-230109 · Cited by 38
Sex differences in microglia function in aged rats underlie vulnerability to cognitive decline
Ince, L. M., Darling, J. S., Sanchez, K. G., Bell, K. S., Melbourne, J. K., Davis, L. K., Nixon, K., Gaudet, A. D., & Fonken, L. K. (2023) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2023.09.009 · Cited by 33
Bermejo‐Pareja, F., & del Ser, T. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13020536 · Cited by 39
Photobiomodulation in the aging brain: a systematic review from animal models to humans
Rodríguez‐Fernández, L., Zorzo, C., & Arias, J. L. (2024) · GeroScience · doi:10.1007/s11357-024-01231-y · Cited by 36
Ravikrishnan, A., Wijaya, I., Png, E., Chng, K. R., Ho, E. X. P., Ng, A. H. Q., Naim, A. N. M., Gounot, J.-S., Guan, S. P., Lee, J. H., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-52097-9 · Cited by 39
Trajectory of Cognitive Decline Before and After Stroke in 14 Population Cohorts
Lo, J., Crawford, J. D., Lipnicki, D. M., Lipton, R. B., Katz, M. J., Preux, P., Guerchet, M., d’Orsi, E., Quialheiro, A., Rech, C. R., et al. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.37133 · Cited by 33
The Hallmarks of Ageing in Microglia
Carr, L. M., Mustafa, S., & Collins‐Praino, L. E. (2025) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-025-01564-y · Cited by 37
Baek, S. Y., & Kim, M. R. (2020) · Marine Drugs · doi:10.3390/md18070372 · Cited by 33
Mutation spectrum of amyotrophic lateral sclerosis in Central South China
Liu, Z., Yuan, Y., Wang, M., Ni, J., Li, W., Huang, L., Hu, Y., Liu, P., Hou, X., Hou, X., et al. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.06.008 · Cited by 33
Incident stroke in patients with Alzheimer’s disease: systematic review and meta-analysis
Pinho, J., Quintas-Neves, M., Dogan, I., Reetz, K., Reich, A., & Costa, A. S. (2021) · Scientific Reports · doi:10.1038/s41598-021-95821-x · Cited by 35
Kim, M., Hwang, E., Kim, K. J., Maeng, S., Heo, H. J., Park, J. H., & Kim, D. (2021) · Antioxidants · doi:10.3390/antiox11010001 · Cited by 33
Effects of Glucagon-like peptide 1 (GLP-1) analogs in the hippocampus
Diz-Chaves, Y., Herrera-Pérez, S., González-Matías, L. C., & Mallo, F. (2022) · Vitamins and hormones · doi:10.1016/bs.vh.2021.12.005 · Cited by 33
Zhang, S., Zhao, J., Quan, Z., Li, H., & Qing, H. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.853911 · Cited by 35
de Soysa, Y., Therrien, M., Walker, A. C., & Stevens, B. (2022) · Seminars in Immunology · doi:10.1016/j.smim.2022.101651 · Cited by 34
Cellular enlargement - A new hallmark of aging?
Davies, D., van den Handel, K., Bharadwaj, S., & Lengefeld, J. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.1036602 · Cited by 32
Genetic enhancement: an avenue to combat aging-related diseases
Cai, Y., Ji, Z., Wang, S., Zhang, W., Qu, J. T., Belmonte, J. C. I., & Liu, G. (2022) · Life Medicine · doi:10.1093/lifemedi/lnac054 · Cited by 33
Single-cell and spatial RNA sequencing identify perturbators of microglial functions with aging
Dong, Y., Jain, R. W., Lozinski, B. M., D’Mello, C., Visser, F., Ghorbani, S., Zandee, S., Brown, D. I., Prat, A., Xue, M., et al. (2022) · Nature Aging · doi:10.1038/s43587-022-00205-z · Cited by 32
Liu, Y. (2023) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-023-01340-w · Cited by 32
Sex modifies the relationship between age and neurovascular coupling in healthy adults
Koep, J. L., Bond, B., BARKER, A. R., Ruediger, S. L., Pizzey, F. K., Coombes, J. S., & Bailey, T. G. (2023) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x231167753 · Cited by 32
Zhang, S., & Kiarasi, F. (2024) · Phytotherapy Research · doi:10.1002/ptr.8176 · Cited by 35
Molecular hallmarks of ageing in amyotrophic lateral sclerosis
Jagaraj, C. J., Shadfar, S., Kashani, S. A., Saravanabavan, S., Farzana, F., & Atkin, J. D. (2024) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-024-05164-9 · Cited by 39
Evolving Landscape of Parkinson’s Disease Research: Challenges and Perspectives
Tenchov, R., Sasso, J. M., & Zhou, Q. A. (2025) · ACS Omega · doi:10.1021/acsomega.4c09114 · Cited by 38
Brain aging and rejuvenation at single-cell resolution
Sun, E., Nagvekar, R., Pogson, A. N., & Brunet, A. (2025) · Neuron · doi:10.1016/j.neuron.2024.12.007 · Cited by 35
Spatial transcriptomics of the aging mouse brain reveals origins of inflammation in the white matter
Wang, L., Cui, C., Lee, C. T., Bodogai, M., Yang, N., Shi, C., Irfanoglu, M. O., Occean, J. R., Afrin, S., Sarker, N., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-58466-2 · Cited by 40
Chai, H., Huang, X., Xiong, G., Huang, J., Pels, K. K., Meng, L., Han, J., Tang, D., Pan, G., Deng, L., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02658-7 · Cited by 35
Sharma, A., Bajaj, P., Bhandari, A., & Kaur, G. (2020) · Neurochemistry International · doi:10.1016/j.neuint.2020.104891 · Cited by 32
Induced Pluripotency: A Powerful Tool for In Vitro Modeling
Záhumenská, R., Nosáľ, V., Smolár, M., Okajčeková, T., Škovierová, H., Strnádel, J., & Halášová, E. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21238910 · Cited by 34
Phenolic acid metabolites of polyphenols act as inductors for hormesis in C. elegans
Dilberger, B., Weppler, S., & Eckert, G. P. (2021) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2021.111518 · Cited by 38
Advances in fucoxanthin chemistry and management of neurodegenerative diseases
Li, N., Gao, X., Zheng, L., Huang, Q., Zeng, F., Chen, H., Farag, M. A., & Zhao, C. (2022) · Phytomedicine · doi:10.1016/j.phymed.2022.154352 · Cited by 34
Progress of advanced nanomaterials in diagnosis of neurodegenerative diseases
Chen, J., Zhou, Z., Luo, S.-H., Liu, G., Xiang, J., & Tian, Z. (2022) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2022.114717 · Cited by 32
Zebrafish: A Model Deciphering the Impact of Flavonoids on Neurodegenerative Disorders
Mhalhel, K., Sicari, M., Pansera, L., Chen, J., Levanti, M. B., Diotel, N., Rastegar, S., Germanà, A., & Montalbano, G. (2023) · Cells · doi:10.3390/cells12020252 · Cited by 44
Hernando, S., Santos‐Vizcaíno, E., Igartúa, M., & Hernández, R. M. (2023) · Wiley Interdisciplinary Reviews Nanomedicine and Nanobiotechnology · doi:10.1002/wnan.1898 · Cited by 32
Sultana, M. A., Hia, R. A., Akinsiku, O., & Hegde, V. K. (2023) · Biology · doi:10.3390/biology12071019 · Cited by 31
Molecular inhibition of RAS signalling to target ageing and age-related health
Laskovs, M., Partridge, L., & Slack, C. (2022) · Disease Models & Mechanisms · doi:10.1242/dmm.049627 · Cited by 36
Impact of Nut Consumption on Cognition across the Lifespan
Nishi, S. K., Sala‐Vila, A., Júlvez, J., Sabaté, J., & Ros, E. (2023) · Nutrients · doi:10.3390/nu15041000 · Cited by 33
A new perspective on Alzheimer’s disease: m6A modification
Xia, L., Zhang, F., Li, Y., Mo, Y., Zhang, L., Li, Q., Luo, M., Hou, X., Du, Z., Deng, J., et al. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1166831 · Cited by 32
Regulatory mechanism of circular RNAs in neurodegenerative diseases
Xiao, F., He, Z., Wang, S., Li, J., Fan, X., Yan, T., Yang, M., & Yang, D. (2023) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14499 · Cited by 30
Sex biology in amyotrophic lateral sclerosis
Zamani, A., Thomas, E., & Wright, D. K. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102228 · Cited by 35
Diniz, L. P., Araújo, A. P. B., Carvalho, C. F., Matias, I. C. P., Hayashide, L. D. S., Marques, M., Pessoa, B., de Andrade, C. B. V., Vargas, G., Queiroz, D. D., et al. (2024) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2024.167470 · Cited by 36
Liu, L., Zhang, X., Chai, Y., Zhang, J., Deng, Q., & Chen, X. (2025) · Cell Death and Disease · doi:10.1038/s41419-025-07336-2 · Cited by 41
Bellelli, F., Angioni, D., Arosio, B., Vellas, B. J., & Barreto, P. D. S. (2025) · Ageing Research Reviews · doi:10.1016/j.arr.2025.102699 · Cited by 34
Autophagy and Cellular Senescence in Alzheimer's Disease: Key Drivers of Neurodegeneration
Hussain, M. S., Agrawal, N., Ilma, B., Rekha, M. M., Nayak, P. P., Kaur, M., Khachi, A., Goyal, K., Rekha, A., Gupta, S., et al. (2025) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.70503 · Cited by 35
Ha, T.-Y., Choi, Y. R., Noh, H. R., Cha, S., Kim, J.-B., & Park, S. M. (2021) · Molecular Brain · doi:10.1186/s13041-021-00834-2 · Cited by 31
Gillispie, G. J., Sah, E., Krishnamurthy, S., Ahmidouch, M. Y., Zhang, B., & Orr, M. E. (2021) · Life · doi:10.3390/life11020153 · Cited by 31
Stress Granules and Acute Ischemic Stroke: Beyond mRNA Translation
Aramburu-Núñez, M., Custodia, A., Pérez-Mato, M., Iglesias-Rey, R., Campos, F., Castillo, J., Ouro, A., Romaus-Sanjurjo, D., & Sobrino, T. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23073747 · Cited by 27
Chen, Y., Yu, S., Zhang, G., Hou, Y., Gu, X., Ou, R., Shen, Y., Song, W., Chen, X., Zhao, B., et al. (2022) · European Journal of Neurology · doi:10.1111/ene.15509 · Cited by 31
Self-citationZhao, Y., Liu, W., Zhang, D., Shen, J., Huang, X., Xiao, L., Chen, X., Lin, X., Du, S., Liu, J., et al. (2022) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2022.157763 · Cited by 31
Subtirelu, R. C., Teichner, E. M., Su, Y., Al‐Daoud, O., Patel, M., Patil, S., Writer, M., Werner, T. J., Revheim, M.-E. R., Høilund‐Carlsen, P. F., et al. (2023) · Life · doi:10.3390/life13102044 · Cited by 32
Concurrent tau pathologies in frontotemporal lobar degeneration with TDP‐43 pathology
Koga, S., Zhou, X., Murakami, A., Fernandez De Castro, C., Baker, M. C., Rademakers, R., & Dickson, D. W. (2022) · Neuropathology and Applied Neurobiology · doi:10.1111/nan.12778 · Cited by 30
The Beneficial Role of Sirtuin 1 in Preventive or Therapeutic Options of Neurodegenerative Diseases
Liu, H., Xu, S., Wang, C., Deng, Y. L., Xu, B., Yang, T., Sun, J., & Liu, W. (2022) · Neuroscience · doi:10.1016/j.neuroscience.2022.09.021 · Cited by 30
López-Granero, C., Polyanskaya, L., Ruiz‐Sobremazas, D., Barrasa, Á., Aschner, M., & Alique, M. (2023) · Biomolecules · doi:10.3390/biom14010035 · Cited by 33
Cannabidiol and neurodegeneration: From molecular mechanisms to clinical benefits
Jha, S. K., Nelson, V. K., Suryadevara, P. R., Panda, S. P., Pullaiah, C. P., Nuli, M. V., Kamal, M., Imran, M., Ausali, S., Abomughaid, M. M., et al. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102386 · Cited by 32
Han, F., Liu, X., Yang, Y., & Liu, X. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120905 · Cited by 47
Incidence and mortality of ALS: a 42-year population-based nationwide study
Levison, L. S., Blicher, J. U., & Andersen, H. (2024) · Journal of Neurology · doi:10.1007/s00415-024-12743-0 · Cited by 36
Ruffo, P., Traynor, B. J., & Conforti, F. L. (2025) · Journal of Neurology · doi:10.1007/s00415-025-12975-8 · Cited by 34
Targeting the hallmarks of aging: mechanisms and therapeutic opportunities
Sanada, F., Hayashi, S., & Morishita, R. (2025) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2025.1631578 · Cited by 40
Liver exerkine reverses aging- and Alzheimer’s-related memory loss via vasculature
Bieri, G., Pratt, K. J. B., Fuseya, Y., Aghayev, T., Sucharov, J., Horowitz, A. M., Philp, A. R., Fonseca-Valencia, K., Chu, R., Phan, M., et al. (2026) · Cell · doi:10.1016/j.cell.2026.01.024 · Cited by 35
Gerardo, B., Cabral-Pinto, M. M. S., Nogueira, J., Pinto, P., Almeida, A. A., Pinto, E., Reis, A. P. M., Diniz, L., Moreira, P. I., Simões, M. R., et al. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17176051 · Cited by 30
Troncoso-Escudero, P., Sepúlveda, D., Pérez-Arancibia, R., Parra, A. V., Arcos, J., Grünenwald, F., & Vidal, R. L. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.571185 · Cited by 31
Inflammation Drives Alzheimer's Disease: Emphasis on 5-lipoxygenase Pathways
Siddiqui, A., Akhtar, S., Shah, Z., Othman, I., & Kumari, Y. (2020) · Current Neuropharmacology · doi:10.2174/1570159x18666200924122732 · Cited by 30
de Sá, R. V., Luna, M. C., & Pasterkamp, R. J. (2021) · Tissue Engineering Part C Methods · doi:10.1089/ten.tec.2020.0337 · Cited by 31
Alzheimer’s disease: a tale of two diseases?
Nardini, E., Hogan, R., Flamier, A., & Bernier, G. (2021) · Neural Regeneration Research · doi:10.4103/1673-5374.308070 · Cited by 33
Narendran, S., Pereira, F., Yerramothu, P., Apicella, I., Wang, S.-B., Ambati, K., Hirahara, S., Kim, Y., Ambati, M., Ambati, V. L., et al. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00537-z · Cited by 31
Personalizing the Care and Treatment of Alzheimer’s Disease: An Overview
Štrac, D. Š., Konjevod, M., Šagud, M., Perković, M. N., Erjavec, G. N., Vuić, B., Šimić, G., Vukić, V., Mimica, N., & Pivac, N. (2021) · Pharmacogenomics and Personalized Medicine · doi:10.2147/pgpm.s284615 · Cited by 30
The Role of SIRT3 in the Osteoporosis
Hu, S., & Wang, S. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.893678 · Cited by 31
Progressive Multiple Sclerosis
Amezcua, L. (2022) · CONTINUUM Lifelong Learning in Neurology · doi:10.1212/con.0000000000001157 · Cited by 34
Khreis, H., Bredell, C., Fung, K. W., Hong, L., Szybka, M., Phillips, V., Abbas, A., Lim, Y., Andersen, Z. J., Woodcock, J., et al. (2022) · Environment International · doi:10.1016/j.envint.2022.107596 · Cited by 34
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
