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 501–600 of 1,007
Neuroimaging-Based Brain Age Estimation: A Promising Personalized Biomarker in Neuropsychiatry
Sone, D., & Beheshti, I. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12111850 · Cited by 41
Xue, S., Lozinski, B. M., Ghorbani, S., Ta, K., D’Mello, C., Yong, V. W., & Dong, Y. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.2312-22.2023 · Cited by 44
Jusop, A. S., Thanaskody, K., Tye, G. J., Dass, S. A., Zaman, W. S. W. K., & Nordin, F. (2023) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2023.1173433 · Cited by 42
Joo, Y., Namgung, E., Jeong, H. S., Kang, I., Kim, J., Oh, S., Lyoo, I. K., Yoon, S. J., & Hwang, J. (2023) · Scientific Reports · doi:10.1038/s41598-023-49514-2 · Cited by 43
Liu, H., Lv, R., Song, F., Yang, Y., Zhang, F., Xin, L., Zhang, P., Zhang, Q., & Ding, C. (2024) · Chemical Science · doi:10.1039/d4sc00595c · Cited by 43
Wei, Y., Li, H., Li, Y., Zeng, Y., Quan, T., Leng, Y.-E., Chang, E., Bai, Y., Bian, Y., & Hou, Y. (2024) · Frontiers in Pharmacology · doi:10.3389/fphar.2024.1496661 · Cited by 43
Self-citationSpina, E., Ferrari, R. R., Pellegrini, E., Colombo, M. M., Poloni, T. E., Guaita, A., & Davin, A. (2025) · Cells · doi:10.3390/cells14030229 · Cited by 45
Mitochondrial dysfunction in cellular senescence: a bridge to neurodegenerative disease
Hruby, A. J., & Higuchi‐Sanabria, R. (2025) · npj Aging · doi:10.1038/s41514-025-00291-4 · Cited by 52
Picca, A., Calvani, R., Coelho‐Júnior, H. J., Landi, F., Bernabei, R., & Marzetti, E. (2020) · Cells · doi:10.3390/cells9030598 · Cited by 41
Zaninello, M., Palikaras, K., Sotiriou, A., Tavernarakis, N., & Scorrano, L. (2021) · Cell Death and Differentiation · doi:10.1038/s41418-021-00847-3 · Cited by 40
The Role of Artificial Intelligence in Managing Multimorbidity and Cancer
Cesario, A., D’Oria, M., Calvani, R., Picca, A., Pietragalla, A., Lorusso, D., Daniele, G., Lohmeyer, F. M., Boldrini, L., Valentini, V., et al. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11040314 · Cited by 39
Chen, C., Ai, Q., Shi, A., Wang, N., Wang, L., & Wei, Y. (2022) · Nutritional Neuroscience · doi:10.1080/1028415x.2022.2051957 · Cited by 40
Self-citationKim, S., Sharma, C., Jung, U. J., & Kim, S. R. (2023) · Biomedicines · doi:10.3390/biomedicines11051383 · Cited by 40
RNA Sequencing of Pooled Samples Effectively Identifies Differentially Expressed Genes
Ko, B., & Raamsdonk, J. M. V. (2023) · Biology · doi:10.3390/biology12060812 · Cited by 47
Pharmacological potentials of lycopene against aging and aging‐related disorders: A review
Abir, M. H., Mahamud, A. G. M. S. U., Tonny, S. H., Anu, M. S., Hossain, K. H. S., Protic, I. A., Khan, M. S. U., Baroi, A., Moni, A., & Uddin, M. J. (2023) · Food Science & Nutrition · doi:10.1002/fsn3.3523 · Cited by 40
Muscle–Brain crosstalk in cognitive impairment
Han, X., Ashraf, M., Tipparaju, S. M., & Xuan, W. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1221653 · Cited by 43
Decoding metabolic signatures in Alzheimer’s disease: a mitochondrial perspective
Bano, D., Ehninger, D., & Bagetta, G. (2023) · Cell Death Discovery · doi:10.1038/s41420-023-01732-3 · Cited by 41
Infection and chronic disease activate a systemic brain-muscle signaling axis
Yang, S., Tian, M., Dai, Y., Wang, R., Yamada, S., Feng, S., Wang, Y., Chhangani, D., Ou, T., Li, W., et al. (2024) · Science Immunology · doi:10.1126/sciimmunol.adm7908 · Cited by 58
Mitochondria as a promising target for developing novel agents for treating Alzheimer's disease
Shevtsova, E. F., Maltsev, A. V., Vinogradova, D. V., Shevtsov, P. N., & Бачурин, С. О. (2020) · Medicinal Research Reviews · doi:10.1002/med.21715 · Cited by 42
Talebi, M., Talebi, M., Kakouri, E., Farkhondeh, T., Pourbagher‐Shahri, A. M., Tarantilis, P. Α., & Samarghandian, S. (2021) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2021.01.042 · Cited by 42
Rahman, M. A., Dash, R., Sohag, A. A. M., Alam, M., Rhim, H., Ha, H., Moon, I. S., Uddin, M. J., & Hannan, M. A. (2021) · Marine Drugs · doi:10.3390/md19030167 · Cited by 40
Laval, K., & Enquist, L. W. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.658695 · Cited by 43
A guide to senolytic intervention in neurodegenerative disease
Lee, S., Wang, E. Y., Steinberg, A. B., Walton, C. C., Chinta, S. J., & Andersen, J. K. (2021) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2021.111585 · Cited by 43
Using Explainable Machine Learning to Improve Intensive Care Unit Alarm Systems
González‐Nóvoa, J. A., Busto, L., Rodriguez-Andina, J. J., Fariña, J., Segura, M., Gómez, V., Vila, D., & Veiga, C. (2021) · Sensors · doi:10.3390/s21217125 · Cited by 39
5-Lipoxygenase as an emerging target against age-related brain disorders
Yan, M., Zhang, S., Li, C.-T., Liu, Y., Zhao, J., Wang, Y., Yang, Y., & Zhang, L. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101359 · Cited by 39
Saul, D., & Kosinsky, R. L. (2021) · Cells · doi:10.3390/cells10113126 · Cited by 39
Current opinions on mitophagy in fungi
Shen, Z.-F., Li, L., Zhu, X., Liu, X., Klionsky, D. J., & Lin, F. (2022) · Autophagy · doi:10.1080/15548627.2022.2098452 · Cited by 41
Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease
Pan, D., Zeng, A., Yang, B., Lai, G., Hu, B., Song, X., Jiang, T., & Initiative, A. D. N. (2022) · Advanced Science · doi:10.1002/advs.202204717 · Cited by 39
Disrupting pathologic phase transitions in neurodegeneration
Hurtle, B. T., Xie, L., & Donnelly, C. J. (2023) · Journal of Clinical Investigation · doi:10.1172/jci168549 · Cited by 40
Recent Developments in Coumarin Derivatives as Neuroprotective Agents
Mishra, P. S., Kumar, A., Kaur, K., & Jaitak, V. (2023) · Current Medicinal Chemistry · doi:10.2174/0929867331666230714160047 · Cited by 39
Tóth, E. E., Ihász, F., Barquín, R. R., & Szabó, A. (2023) · Journal of Aging and Physical Activity · doi:10.1123/japa.2022-0427 · Cited by 50
Jiang, T., Ruan, N., Luo, P., Wang, Q., Wei, X., Li, Y., Dai, Y., Li, L., Lv, J., Liu, Y., et al. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102320 · Cited by 43
Lorenzo, D. D. (2024) · ChemMedChem · doi:10.1002/cmdc.202400180 · Cited by 46
Microbial signatures and therapeutic strategies in neurodegenerative diseases
Rob, M., Yousef, M., Lakshmanan, A. P., Mahboob, A., Terranegra, A., & Châari, A. (2025) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2025.117905 · Cited by 43
Hearing Loss in Neurological Disorders
Li, S., Cheng, C., Lü, L., Ma, X., Zhang, X., Li, A., Chen, J., Qian, X., & Gao, X. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.716300 · Cited by 39
Convergent pathways of the gut microbiota–brain axis and neurodegenerative disorders
Gubert, C., Gasparotto, J., & Morais, L. H. (2022) · Gastroenterology report · doi:10.1093/gastro/goac017 · Cited by 40
Kou, R.-W., Xia, B., Han, R., Li, Z., Yang, J.-R., Yin, X., Gao, Y., & Gao, J. (2022) · Food & Function · doi:10.1039/d2fo02854a · Cited by 41
Pappalettera, C., Cacciotti, A., Nucci, L., Miraglia, F., Rossini, P. M., & Vecchio, F. (2022) · GeroScience · doi:10.1007/s11357-022-00710-4 · Cited by 38
DNA Damage-Mediated Neurotoxicity in Parkinson’s Disease
Wang, Z., Li, Y., Pu, J., & Zhang, B. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24076313 · Cited by 43
Jing, J. L., Cheng, T. Y. N., Natali, F., Eisenhaber, F., & Alfatah, M. (2022) · Cells · doi:10.3390/cells11050862 · Cited by 36
Shang, X., Zhang, X., Huang, Y., Zhu, Z., Zhang, X., Liu, J., Wang, W., Tang, S., Yu, H., Ge, Z., et al. (2022) · EClinicalMedicine · doi:10.1016/j.eclinm.2022.101413 · Cited by 37
GDF11 slows excitatory neuronal senescence and brain ageing by repressing p21
Wang, D.-X., Dong, Z.-J., Deng, S., Tian, Y.-M., Xiao, Y., Li, X., Ma, X.-R., Li, L., Li, P., Chang, H., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43292-1 · Cited by 41
Guan, Y., Tang, G., Li, L., Shu, J., Zhao, Y., Huang, L., & Tang, J. (2024) · Archives of Pharmacal Research · doi:10.1007/s12272-023-01484-9 · Cited by 41
Zhang, M., Wang, W., Ye, Q., Fu, Y., Li, X., Yang, K., Gao, F., Zhou, A., Wei, Y., Tian, S., et al. (2024) · Alzheimer s Research & Therapy · doi:10.1186/s13195-024-01384-0 · Cited by 43
Self-citationGhassab, F. T., Mahmoudi, F. S., Tinjani, R. T., Meibodi, A. E., Zali, M. R., & Yadegar, A. (2024) · Life Sciences · doi:10.1016/j.lfs.2024.122748 · Cited by 40
New therapies on the horizon: Targeted protein degradation in neuroscience
Gregory, J. A., Hickey, C. M., Chavez, J. D., & Cacace, A. M. (2024) · Cell chemical biology · doi:10.1016/j.chembiol.2024.08.010 · Cited by 42
TGF-β Signaling in Microglia: A Key Regulator of Development, Homeostasis and Reactivity
Li, L., Sun, B., Harris, O. A., & Luo, J. (2024) · Biomedicines · doi:10.3390/biomedicines12112468 · Cited by 38
COVID-19 and Parkinson’s Disease: Are We Dealing with Short-term Impacts or Something Worse?
Victorino, D. B., Guimarães‐Marques, M., Nejm, M. B., Scorza, F. A., & Scorza, C. A. (2020) · Journal of Parkinson s Disease · doi:10.3233/jpd-202073 · Cited by 37
Role of Long Noncoding RNAs in Parkinson’s Disease: Putative Biomarkers and Therapeutic Targets
Lv, Q.-K., Wang, Z., Zhong, Z., & Huang, W. (2020) · Parkinson s Disease · doi:10.1155/2020/5374307 · Cited by 37
Lawn, T., Aman, Y., Rukavina, K., Sideris-Lampretsas, G., Howard, M. A., Ballard, C. G., Chaudhuri, К. R., & Malcangio, M. (2020) · Pain · doi:10.1097/j.pain.0000000000002111 · Cited by 41
Blood-brain barrier dysfunction as a potential therapeutic target for neurodegenerative disorders
Uprety, A. R., Kang, Y., & Kim, S. Y. (2021) · Archives of Pharmacal Research · doi:10.1007/s12272-021-01332-8 · Cited by 39
Natural Phyto-Antioxidant Albumin Nanoagents to Treat Advanced Alzheimer’s Disease
Dou, Y., Zhao, D., Yang, F., Tang, Y., & Chang, J. K. (2021) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.1c07281 · Cited by 38
Guo, M., Ji, X., & Liu, J. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.919343 · Cited by 40
Thrush, K., Bennett, D. A., Gaiteri, C., Horvath, S., van Dyck, C. H., Higgins‐Chen, A., & Levine, M. E. (2022) · Aging · doi:10.18632/aging.204196 · Cited by 38
JNK Signaling in Drosophila Aging and Longevity
Gan, T., Fan, L., Zhao, L., Misra, M., Liu, M., Zhang, M., & Su, Y. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22179649 · Cited by 39
Human IPSC 3D brain model as a tool to study chemical-induced dopaminergic neuronal toxicity
Pamies, D., Wiersma, D., Katt, M. E., Zhao, L., Burtscher, J., Harris, G., Smirnova, L., Searson, P. C., Härtung, T., & Högberg, H. T. (2022) · Neurobiology of Disease · doi:10.1016/j.nbd.2022.105719 · Cited by 39
Bhaskaran, S., Kumar, G., Thadathil, N., Piekarz, K. M., Mohammed, S., Domínguez-López, S., Qaisar, R., Walton, D. A., Brown, J. L., Murphy, A., et al. (2022) · Redox Biology · doi:10.1016/j.redox.2022.102550 · Cited by 36
The toxic metal hypothesis for neurological disorders
Pamphlett, R., & Bishop, D. (2023) · Frontiers in Neurology · doi:10.3389/fneur.2023.1173779 · Cited by 44
Evans, J. A., Mendonca, P., & Soliman, K. F. A. (2023) · Brain Sciences · doi:10.3390/brainsci13081144 · Cited by 39
New horizons in Parkinson’s disease in older populations
Chhetri, J. K., Mei, S., Wang, C., & Chan, P. (2023) · Age and Ageing · doi:10.1093/ageing/afad186 · Cited by 38
Entropy-Based Machine Learning Model for Fast Diagnosis and Monitoring of Parkinson’s Disease
Belyaev, M. A., Murugappan, M., Velichko, A., & Korzun, D. G. (2023) · Sensors · doi:10.3390/s23208609 · Cited by 37
Plant-Derived Nanovesicles: A Promising Frontier in Tissue Repair and Antiaging
Zheng, Y., Wang, T., Zhang, J., Wei, S., Wu, Z., Li, J., Shi, B., Sun, Z., Xu, W., & Zhu, J. (2025) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.5c01547 · Cited by 40
Calcium-activated potassium channels: implications for aging and age-related neurodegeneration
Trombetta-Lima, M., Krabbendam, I. E., & Dolga, A. M. (2020) · The International Journal of Biochemistry & Cell Biology · doi:10.1016/j.biocel.2020.105748 · Cited by 38
Allende, M. L., Zhu, H., Kono, M., Hoachlander-Hobby, L. E., Huso, V. L., & Proia, R. L. (2021) · Cellular Signalling · doi:10.1016/j.cellsig.2020.109879 · Cited by 37
Challenges and Opportunities of Targeting Astrocytes to Halt Neurodegenerative Disorders
Valori, C. F., Possenti, A., Brambilla, L., & Rossi, D. (2021) · Cells · doi:10.3390/cells10082019 · Cited by 39
Roles of Long Non-coding RNAs in the Development of Aging-Related Neurodegenerative Diseases
Ni, Y., Xu, H., & Liu, Y. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2022.844193 · Cited by 37
Age and sex differentially shape brain networks in Parkinson's disease
Chen, Z., Wu, B., Li, G., Zhou, L., Zhang, L., & Liu, J. (2023) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14149 · Cited by 35
Epigenetic clocks in neurodegenerative diseases: a systematic review
Yang, T., Xiao, Y., Cheng, Y., Huang, J., Wei, Q., Li, C., & Shang, H. (2023) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2022-330931 · Cited by 40
Challenges of Repurposing Tetracyclines for the Treatment of Alzheimer’s and Parkinson’s Disease
Markulin, I., Matasin, M., Turk, V. E., & Salković-Petrisic, M. (2022) · Journal of Neural Transmission · doi:10.1007/s00702-021-02457-2 · Cited by 36
Heart Matters: Cardiac Dysfunction and Other Autonomic Changes in Parkinson’s Disease
Gonçalves, V. C., Cuenca-Bermejo, L., Fernandez-Villalba, E., Martin-Balbuena, S., da Silva Fernandes, M. J., Scorza, C. A., & Herrero, M.-T. (2022) · The Neuroscientist · doi:10.1177/1073858421990000 · Cited by 37
Feter, N., Leite, J. S., Caputo, E. L., Cardoso, R. K., & Rombaldi, A. J. (2021) · Revista Brasileira de Epidemiologia · doi:10.1590/1980-549720210018 · Cited by 36
From Lysosomal Storage Disorders to Parkinson’s Disease – Challenges and Opportunities
Mächtel, R., Boros, F. A., Dobert, J. P., Arnold, P., & Zunke, F. (2022) · Journal of Molecular Biology · doi:10.1016/j.jmb.2022.167932 · Cited by 37
Mitochondrion: A bridge linking aging and degenerative diseases
Zhang, L., Wu, J., Zhu, Z., He, Y., & Fang, R. (2023) · Life Sciences · doi:10.1016/j.lfs.2023.121666 · Cited by 38
Zhao, P., Wu, T., Tian, Y., You, J. E., & Cui, X. (2024) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2024.115323 · Cited by 44
Umapathy, S., Pan, I., Issac, P. K., Kumar, M. S. K., Giri, J. P., Guru, A., & Arockiaraj, J. (2024) · Molecular Neurobiology · doi:10.1007/s12035-024-04253-x · Cited by 37
Burkhart, A., Helgudóttir, S. S., Mahamed, Y. A., Fruergaard, M. B., Holm-Jacobsen, J. N., Haraldsdóttir, H., Dahl, S. E., Pretzmann, F., Routhe, L. G., Lambertsen, K. L., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-78204-w · Cited by 37
Large language model-based biological age prediction in large-scale populations
Li, Y., Huang, Q. Z., Jiang, J., Du, X., Xiang, W., Zhang, S., Pan, Z., Zhao, L., Cui, Y., Ke, L., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03856-8 · Cited by 42
Klotho Pathways, Myelination Disorders, Neurodegenerative Diseases, and Epigenetic Drugs
Moos, W. H., Faller, D. V., Glavas, I. P., Harpp, D. N., Kanara, I., Mavrakis, A. N., Pernokas, J., Pernokas, M., Pinkert, C. A., Powers, W. R., et al. (2020) · BioResearch open access · doi:10.1089/biores.2020.0004 · Cited by 37
Blood DNA methylation signatures to detect dementia prior to overt clinical symptoms
Fransquet, P. D., Lacaze, P., Saffery, R., Phung, J., Parker, E., Shah, R., Murray, A., Woods, R. L., & Ryan, J. (2020) · Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring · doi:10.1002/dad2.12056 · Cited by 36
Yen, P.-L., How, C. M., & Liao, V. H. (2020) · Chemosphere · doi:10.1016/j.chemosphere.2020.128594 · Cited by 37
He, S., Zhong, S., Liu, G., & Yang, J. (2020) · Neurodegenerative Diseases · doi:10.1159/000511083 · Cited by 36
Perspective: Estrogen and the Risk of Cognitive Decline: A Missing Choline(rgic) Link?
Bortz, J., Klatt, K. C., & Wallace, T. C. (2021) · Advances in Nutrition · doi:10.1093/advances/nmab145 · Cited by 38
Deciphering therapeutic options for neurodegenerative diseases: insights from SIRT1
Wang, R., Wu, Y., Liu, R., Liu, M., Li, Q., Ba, Y., & Huang, H. (2022) · Journal of Molecular Medicine · doi:10.1007/s00109-022-02187-2 · Cited by 38
The Structure and Function of Glial Networks: Beyond the Neuronal Connections
Peng, H.-R., Zhang, Y.-K., & Zhou, J. (2022) · Neuroscience Bulletin · doi:10.1007/s12264-022-00992-w · Cited by 35
Neurodegeneration and inflammation crosstalk: Therapeutic targets and perspectives
Mohamed, W. M. Y., Kumar, J., Alghamdi, B. S. A., Wadan, A.-H. S., & Yamashita, T. (2022) · IBRO Neuroscience Reports · doi:10.1016/j.ibneur.2022.12.003 · Cited by 40
Antiplatelet drugs: Potential therapeutic options for the management of neurodegenerative diseases
Beura, S. K., Dhapola, R., Panigrahi, A. R., Yadav, P., Kumar, R., HariKrishnaReddy, D., & Singh, S. K. (2023) · Medicinal Research Reviews · doi:10.1002/med.21965 · Cited by 37
Advances and Applications of Brain Organoids
Li, Y., Zeng, P.-M., Wu, J., & Luo, Z. (2023) · Neuroscience Bulletin · doi:10.1007/s12264-023-01065-2 · Cited by 40
Neural cell state shifts and fate loss in ageing and age-related diseases
Traxler, L., Lucciola, R., Herdy, J. R., Jones, J. R., Mertens, J., & Gage, F. H. (2023) · Nature Reviews Neurology · doi:10.1038/s41582-023-00815-0 · Cited by 37
Xia, J., Yang, L., Huang, C.-Y., Deng, S., Yang, Z., Zhang, Y., Zhang, C., & Song, C. (2023) · Marine Drugs · doi:10.3390/md21070398 · Cited by 37
Transplanting old organs promotes senescence in young recipients
Iske, J., Roesel, M. J., Martin, F., Schroeter, A., Matsunaga, T., Maenosono, R., Tripathi, U., Xiao, Y., Nian, Y., Caldarone, B. J., et al. (2023) · American Journal of Transplantation · doi:10.1016/j.ajt.2023.10.013 · Cited by 35
Vicente-Zurdo, D., Rosales‐Conrado, N., & León‐González, M. E. (2023) · Talanta · doi:10.1016/j.talanta.2023.125519 · Cited by 36
Kim, K. Y., Shin, K. Y., & Chang, K. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25105307 · Cited by 35
SANTO: a coarse-to-fine alignment and stitching method for spatial omics
Li, H., Lin, Y., He, W., Han, W., Xu, X., Xu, C., Gao, E., Zhao, H., & Gao, X. (2024) · Nature Communications · doi:10.1038/s41467-024-50308-x · Cited by 37
Potential roles of telomeres and telomerase in neurodegenerative diseases
Wang, J., Liu, Y., Xia, Q., Xia, Q., Wang, B., Yang, C., Liang, J., & Liu, X. (2020) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2020.07.046 · Cited by 37
Single-Cell Oxidative Stress Events Revealed by a Renewable SERS Nanotip
Chen, J., Wang, J., Geng, Y., Jing, Y., Shi, W., Liang, C., Xu, W., & Xu, S. (2021) · ACS Sensors · doi:10.1021/acssensors.1c00395 · Cited by 35
Diagnostic and Therapeutic Potential of Exosomal MicroRNAs for Neurodegenerative Diseases
He, M., Zhang, H., Tang, Z., & Gao, S. (2021) · Neural Plasticity · doi:10.1155/2021/8884642 · Cited by 34
Wang, H., Karuppan, M. K. M., Devadoss, D., Nair, M., Chand, H. S., & Lakshmana, M. K. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.06.003 · Cited by 35
A NIR fluorescent probe for the in vitro and in vivo selective detection of hydrogen peroxide
Ge, C., Yang, Y., Pengfei, T., Shi, H., Jin, Y., Yuyang, S., Yun, Y., & Feng, R. (2021) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2021.130831 · Cited by 36
Understanding the aging hypothalamus, one cell at a time
Hajdarovic, K. H., Yu, D., & Webb, A. E. (2022) · Trends in Neurosciences · doi:10.1016/j.tins.2022.10.004 · Cited by 34
Past and Future Directions for Research on Cellular SenescencePreprint
Zhu, Y. Z., Anastasiadis, Z. P., Espíndola‐Netto, J. M., Evans, T. S., Tchkonia, T., & Kirkland, J. L. (2023) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a041205 · Cited by 37
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