The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Molecular aging in human prefrontal cortex is selective and continuous throughout adult life
Abstract
Background Aging leads to morphologic and functional changes in the brain and is associated with increased risk for psychiatric and neurological disorders.Methods To identify age-related transcriptional changes in the human brain, we profiled gene expression in two prefrontal cortex (PFC) areas in postmortem samples from 39 subjects, ranging in age from 13 to 79 years.Results Robust transcriptional age-related changes were identified for at least 540 genes. Gene expression correlates of aging were highly specific, and the large majority of the 22,000 transcripts investigated were unaffected by age. Across subjects, changes were progressive throughout adult life and accurately predicted chronological age. Age-upregulated transcripts were mostly of glial origin and related to inflammation and cellular defenses, whereas downregulated genes displayed mostly neuron-enriched transcripts relating to cellular communication and signaling.Conclusions Continuous changes in gene expression with increasing age revealed a "molecular profile" of aging in human PFC. The restricted scope of the transcript changes suggests cellular populations or functions that are selectively vulnerable during aging. Because age-related gene expression changes begin early in adulthood and are continuous throughout life, our results suggest the possibility of identifying early cellular mechanisms that may be engaged in preventive or detrimental age-related brain functions.
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
“Gene expression profiling studies of ageing mouse, rat, monkey and human brains have shown significant changes in the expression of synaptic genes (7–13).”
From Neural mechanisms of ageing and cognitive decline (2010) · cites this paper as [12]
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
Cluster analysis and display of genome-wide expression patterns
Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14863 · Cited by 16,184
Summaries of Affymetrix GeneChip probe level data
Irizarry, R. A. (2003) · Nucleic Acids Research · doi:10.1093/nar/gng015 · Cited by 4,837
Mapping cortical change across the human life span
Sowell, E. R., Peterson, B. S., Thompson, P. M., Welcome, S. E., Henkenius, A. L., & Toga, A. W. (2003) · Nature Neuroscience · doi:10.1038/nn1008 · Cited by 2,328
Insights into the ageing mind: a view from cognitive neuroscience
Hedden, T., & Gabrieli, J. D. E. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1323 · Cited by 2,223
Models of visuospatial and verbal memory across the adult life span.
Park, D. C., Lautenschlager, G. J., Hedden, T., Davidson, N. S., Smith, A. D., & Smith, P. K. (2002) · Psychology and Aging · doi:10.1037/0882-7974.17.2.299 · Cited by 1,929
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
Gene expression profile of aging and its retardation by caloric restriction
Lee, C.-K., Klopp, R. G., Weindruch, R., & Prolla, T. A. (1999) · Science · doi:10.1126/science.285.5432.1390 · Cited by 1,473
Longitudinal Magnetic Resonance Imaging Studies of Older Adults: A Shrinking Brain
Resnick, S. M., Pham, D. L., Kraut, M. A., Zonderman, A. B., & Davatzikos, C. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-08-03295.2003 · Cited by 1,425
Flagged first, then by citations
Research works printed but not linked: 1
- Sastre, 1994, Density of alpha-2A adrenoceptors and Gi proteins in the human brain, J Pharmacol Exp Ther, 269, 1062
Cited by
Sorted by citations
Items 101–200 of 236
Redox lipidomics to better understand brain aging and function
Pamplona, R., Borrás, C., Jové, M., Pradas, I., Ferrer, I., & Viña, J. (2019) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2019.03.016 · Cited by 39
Pacifico, R., MacMullen, C., Walkinshaw, E., Zhang, X., & Davis, R. L. (2018) · PLoS ONE · doi:10.1371/journal.pone.0209405 · Cited by 35
Huffman, K. J. (2012) · Frontiers in Genetics · doi:10.3389/fgene.2012.00212 · Cited by 35
McKinney, B. C., Lin, C.-W., Oh, H., Tseng, G. C., Lewis, D. A., & Sibille, E. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.107 · Cited by 34
Self-citationFerreira, M., Francisco, S., Soares, A. R., Nobre, A., Pinheiro, M. M., Reis, A., Neto, S. C., Rodrigues, A. J., Sousa, N., Moura, G. R., et al. (2021) · Aging · doi:10.18632/aging.203379 · Cited by 34
Arnsten, A. F. T., Tredici, K. D., Barthélemy, N. R., Gabitto, M. I., van Dyck, C. H., Lein, E. S., Braak, H., & Datta, D. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70404 · Cited by 39
Nicotine Modulates Cognitive Function in D-Galactose-Induced Senescence in Mice
Majdi, A., Sadigh‐Eteghad, S., Talebi, M., Farajdokht, F., Erfani, M., Mahmoudi, J., & GJEDDE, A. H. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00194 · Cited by 35
The Role of Neoteny in Human Evolution: From Genes to the Phenotype
Somel, M., Tang, L., & Khaitovich, P. (2011) · Primatology monographs · doi:10.1007/978-4-431-54011-3_3 · Cited by 35
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
Lin, C., Chang, L., Tseng, G. C., Kirkwood, C. M., Sibille, E. L., & Sweet, R. A. (2015) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2015.00030 · Cited by 35
Self-citationRevisiting nicotine’s role in the ageing brain and cognitive impairment
Majdi, A., Kamari, F., Vafaee, M. S., & Sadigh‐Eteghad, S. (2017) · Reviews in the Neurosciences · doi:10.1515/revneuro-2017-0008 · Cited by 35
Yuan, Y., Chen, Y. P., Ni, S., Xu, A. G., Tang, L., Vingron, M., Somel, M., & Khaitovich, P. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-347 · Cited by 33
A cross-laboratory comparison of expression profiling data from normal human postmortem brain
Mistry, M., & Pavlidis, P. (2010) · Neuroscience · doi:10.1016/j.neuroscience.2010.01.016 · Cited by 32
Self-citationMajor aging-associated RNA expressions change at two distinct age-positions
Gheorghe, M., Snoeck, M. M. J., Emmerich, M., Bäck, T., Goeman, J. J., & Raz, V. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-132 · Cited by 29
Decreased activity and increased aggregation of brain calcineurin during aging
Aǵbaş, A., Zaidi, A., & Michaelis, E. K. (2005) · Brain Research · doi:10.1016/j.brainres.2005.08.008 · Cited by 31
Stroke Induces a BDNF-Dependent Improvement in Cognitive Flexibility in Aged Mice
Houlton, J., Zhou, L. Y. Y., Barwick, D., Gowing, E. K., & Clarkson, A. N. (2019) · Neural Plasticity · doi:10.1155/2019/1460890 · Cited by 31
Regional vulnerability to lipoxidative damage and inflammation in normal human brain aging
Domínguez-González, M., Puigpinós, M., Jové, M., Naudí, A., Portero‐Otín, M., Pamplona, R., & Ferrer, I. (2018) · Experimental Gerontology · doi:10.1016/j.exger.2018.07.023 · Cited by 29
Arnsten, A. F. T., Ishizawa, Y., & Xie, Z. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02057-4 · Cited by 30
Huang, Y., Yan, J., Lubet, R. A., Kensler, T. W., & Sutter, T. R. (2005) · Physiological Genomics · doi:10.1152/physiolgenomics.00258.2005 · Cited by 28
Silvestri, E., Lombardi, A., de Lange, P., Glinni, D., Senese, R., Cioffi, F., Lanni, A., Goglia, F., & Moreno, M. (2010) · BioMed Research International · doi:10.1155/2011/810242 · Cited by 29
Normal ageing of the brain: Histological and biological aspects
Teissier, T., Boulanger, É., & Deramecourt, V. (2020) · Revue Neurologique · doi:10.1016/j.neurol.2020.03.017 · Cited by 37
An emerging role for microRNAs in sexually dimorphic neurobiological systems
Pak, T. R., Rao, Y. S., Prins, S. A., & Mott, N. N. (2013) · Pflügers Archiv - European Journal of Physiology · doi:10.1007/s00424-013-1227-y · Cited by 24
Sheoran, S., Vints, W. A. J., Valatkevičienė, K., Kušleikienė, S., Gleiznienė, R., Česnaitienė, V. J., Himmelreich, U., Levin, O., & Masiulis, N. (2023) · GeroScience · doi:10.1007/s11357-023-00732-6 · Cited by 28
Lee, C. H., Park, J. H., Choi, J. H., Yoo, K., Ryu, P. D., & Won, M. (2011) · Experimental Gerontology · doi:10.1016/j.exger.2011.05.002 · Cited by 23
Cabré, R., Naudí, A., Domínguez-González, M., Jové, M., Ayala, V., Mota‐Martorell, N., Pradas, I., Nogueras, L., Rué, M., Portero‐Otín, M., et al. (2017) · The Journals of Gerontology Series A · doi:10.1093/gerona/glx164 · Cited by 26
The Future of Neuroepigenetics in the Human Brain
Mitchell, A., Roussos, P., Peter, C. J., Tsankova, N. M., & Akbarian, S. (2014) · Progress in molecular biology and translational science · doi:10.1016/b978-0-12-800977-2.00008-5 · Cited by 24
Różycka, A., Charzyńska, A., Misiewicz, Z., Stępniewski, T. M., Sobolewska, A., Kossut, M. M., & Liguz‐Lecznar, M. (2019) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.9b00220 · Cited by 24
McKinney, B. C., Lin, C., Rahman, T., Oh, H., Lewis, D. A., Tseng, G. C., & Sibille, E. L. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0372-2 · Cited by 21
Self-citationKhatir, I., Brunet, M. A., Meller, A., Amiot, F., Patel, T., Lapointe, X., Avila Lopez, J., Guilloy, N., Castonguay, A., Husain, M. A., et al. (2023) · Cells · doi:10.3390/cells12040615 · Cited by 22
Epigenetics Components of Aging in the Central Nervous System
Zhao, Y., Jordan, I. K., & Lunyak, V. V. (2013) · Neurotherapeutics · doi:10.1007/s13311-013-0229-y · Cited by 25
Nikolova, Y. S., Iruku, S. P., Lin, C., Drabant, E. M., Puralewski, R., French, B. J., Hariri, A. R., & Sibille, E. L. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.01377 · Cited by 21
Self-citationChronic stress alters the expression levels of longevity-related genes in the rat hippocampus
Sánchez-Hidalgo, A. C., Muñoz, M., Herrera, A. J., Espinosa‐Oliva, A. M., Stowell, R. D., Ayala, A., Machado, A., Venero, J. L., & de Pablos, R. M. (2016) · Neurochemistry International · doi:10.1016/j.neuint.2016.04.009 · Cited by 23
Comprehensive transcriptional profiling of porcine brain aging
Chen, J., Zou, Q., Lv, D., Raza, M. A., Wang, X., Li, P., Chen, Y., Xi, X., Wen, A., Zhu, L., et al. (2019) · Gene · doi:10.1016/j.gene.2019.01.019 · Cited by 21
Age-by-disease biological interactions: implications for late-life depression
McKinney, B. C., Oh, H., & Sibille, E. L. (2012) · Frontiers in Genetics · doi:10.3389/fgene.2012.00237 · Cited by 20
Self-citationGenomic studies in ageing research: the need to integrate genetic and gene expression approaches
Passtoors, W. M., Beekman, M., Gunn, D. A., Boer, J. M., Heijmans, B. T., Westendorp, R. G. J., Zwaan, B. J., & Slagboom, P. E. (2008) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2007.01904.x · Cited by 20
Whole-Exome Sequencing of an Exceptional Longevity Cohort
Nygaard, H. B., Erson-Omay, Z., Wu, X., Kent, B. A., Bernales, C. Q., Evans, D. M., Farrer, M. J., Vilariño‐Güell, C., & Strittmatter, S. M. (2018) · The Journals of Gerontology Series A · doi:10.1093/gerona/gly098 · Cited by 20
Enhanced cAMP/PKA pathway by seabuckthorn fatty acids in aged rats
Hu, R., Yuan, B.-X., Wei, X.-Z., Zhao, L., Tang, J., & Dong, C. (2006) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2006.11.016 · Cited by 19
Chen, R., Routh, B. N., Gaudet, A. D., & Fonken, L. K. (2023) · Journal of Biological Rhythms · doi:10.1177/07487304231178950 · Cited by 21
Rate of brain aging and APOE ε4 are synergistic risk factors for Alzheimer’s disease
Glorioso, C. A., Pfenning, A. R., Lee, S. S., Bennett, D. A., Sibille, E. L., Kellis, M., & Guarente, L. (2019) · Life Science Alliance · doi:10.26508/lsa.201900303 · Cited by 18
Self-citationSharing and Reusing Gene Expression Profiling Data in Neuroscience
Wan, X., & Pavlidis, P. (2007) · Neuroinformatics · doi:10.1007/s12021-007-0012-5 · Cited by 18
Self-citationLarge-scale estimates of cellular origins of mRNAs: Enhancing the yield of transcriptome analyses
Sibille, E. L., Arango, V., Joeyen-Waldorf, J., Wang, Y., Leman, S., Surget, A., Belzung, C., Mann, J. J., & Lewis, D. A. (2007) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.08.009 · Cited by 17
Self-citationHorta, B. C., Perilo, C. S., Costa, D. C., Nogueira-Machado, J. A., & Chaves, M. M. (2005) · Gerontology · doi:10.1159/000088699 · Cited by 17
Chen, Y., Hunter, E., Arbabi, K., Guet-McCreight, A., Consens, M. E., Felsky, D., Sibille, E. L., & Tripathy, S. J. (2023) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.01.013 · Cited by 16
Self-citationAlves, G. S., Carvalho, A. F., Sudo, F. K., Oertel‐Knöchel, V., Knöchel, C., de Carvalho, L. D. A., Laks, J., Engelhardt, E., & Pantel, J. (2015) · CNS & Neurological Disorders - Drug Targets · doi:10.2174/1871527313666141130202923 · Cited by 17
Resilient protein co-expression network in male orbitofrontal cortex layer 2/3 during human aging
Pabba, M., Scifo, E., Kapadia, F., Nikolova, Y. S., Ma, T., Mechawar, N., Tseng, G. C., & Sibille, E. L. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.06.023 · Cited by 13
Self-citationHoulton, J., Barwick, D., & Clarkson, A. N. (2020) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2020.107355 · Cited by 16
Passtoors, W. M., Boer, J. M., Goeman, J. J., van den Akker, E. B., Deelen, J., Zwaan, B. J., Scarborough, A., van der Breggen, R., Vossen, R. H. A. M., Houwing‐Duistermaat, J. J., et al. (2012) · PLoS ONE · doi:10.1371/annotation/d4d3b1fb-35e0-4c4d-89bc-e6a839504e54 · Cited by 14
Dynamic changes in neuronal and glial GAL4 driver expression during Drosophila aging
Delandre, C., McMullen, J. P. D., & Marshall, O. J. (2025) · Genetics · doi:10.1093/genetics/iyaf014 · Cited by 13
Benítez, M. J., Retana, D., Ordóñez‐Gutiérrez, L., Colmena, I., Goméz, M. J., Álvarez, R., Ciorraga, M., Dopazo, A., Wandosell, F. G., & Garrido, J. J. (2024) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-024-05485-9 · Cited by 17
El-Kashef, N., Gomes, I., Mercer‐Chalmers‐Bender, K., Schneider, P. M., Rothschild, M. A., & Juebner, M. (2015) · Forensic Science Medicine and Pathology · doi:10.1007/s12024-015-9717-1 · Cited by 13
Reciprocal phylogenetic conservation of molecular aging in mouse and human brain
Oh, S., Tseng, G. C., & Sibille, E. L. (2009) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2009.08.004 · Cited by 14
Self-citationSenatorov, V. V., Friedman, A. R., Milikovsky, D. Z., Ofer, J., Saar‐Ashkenazy, R., Charbash, A., Jahan, N., Chin, G., Mihaly, E., Lin, J. M., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/537431 · Cited by 13
Bathla, S., Datta, D., Liang, F., Barthélemy, N. R., Wiseman, R., Slusher, B. S., Asher, J. L., Zeiss, C. J., Ekanayake‐Alper, D., Holden, D., et al. (2023) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12431 · Cited by 11
Yang, Y., Liang, S., Li, Y., Gao, F., Cao, Y. Y., Zhao, X., Gao, G., & Li, L. (2019) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s190845 · Cited by 13
Wang, K., Cui, J., Cai, Y., Wang, F., Li, Y., Tao, W., & Xiang, H. (2009) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-009-9404-4 · Cited by 12
Datta, D., & Arnsten, A. F. T. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.14477 · Cited by 11
Shared co-expression networks in frontal cortex of the normal aged brain and schizophrenia
Kim, S., Jo, Y., Webster, M. J., & Lee, D. (2018) · Schizophrenia Research · doi:10.1016/j.schres.2018.09.010 · Cited by 12
Boiangiu, R. Ş., Brinza, I., Honceriu, I., Mihăşan, M., & Hriţcu, L. (2023) · Biomolecules · doi:10.3390/biom14010023 · Cited by 12
Electrophysiology and morphology of human cortical supragranular pyramidal cells in a wide age range
Barzó, P., Szöts, I., Tóth, M., Csajbók, É., Molnár, G., & Tamás, G. (2025) · eLife · doi:10.7554/elife.100390.3 · Cited by 10
New cellular and molecular approaches to ageing brain
Tripathi, A. (2012) · Annals of Neurosciences · doi:10.5214/ans.0972.7531.190410 · Cited by 11
Safdar, A., Zakaria, R., Aziz, C. B. A., Rashid, U., & Azman, K. F. (2019) · Biogerontology · doi:10.1007/s10522-019-09854-x · Cited by 11
Dalgard, C. L., Jacobowitz, D. M., Singh, V. K., Saleem, K. S., Ursano, R. J., Starr, J. M., & Pollard, H. B. (2014) · Brain Research · doi:10.1016/j.brainres.2014.12.031 · Cited by 9
Comprehensive gene expression analyses of the rat prefrontal cortex after oxysterol treatment
Loke, S. Y., Tanaka, K., & Ong, W. (2013) · Journal of Neurochemistry · doi:10.1111/jnc.12142 · Cited by 9
Tonoki, A., Nagai, S., Yu, Z., Tong, Y. A., Lyu, S., Hou, X., Onuki, K., Yabana, K., Takahashi, H., & Itoh, M. (2022) · Aging Cell · doi:10.1111/acel.13691 · Cited by 7
Kedmi, M., & Orr‐Urtreger, A. (2010) · AGE · doi:10.1007/s11357-010-9155-7 · Cited by 8
Weissleder, C., Kondo, M., Yang, C., Fung, S. J., Rothmond, D. A., Wong, M. W. K., Halliday, G. M., Herman, M. M., Kleinman, J. E., Webster, M. J., et al. (2017) · European Journal of Neuroscience · doi:10.1111/ejn.13623 · Cited by 8
Age‐dependent increase in Kalirin‐9 and Kalirin‐12 transcripts in human orbitofrontal cortex
Grubisha, M. J., Lin, C., Tseng, G. C., Penzes, P., Sibille, E. L., & Sweet, R. A. (2016) · European Journal of Neuroscience · doi:10.1111/ejn.13351 · Cited by 8
Self-citationArnsten, A. F. T., Perone, I., Wang, M., Yang, S., Uchendu, S., Bolat, D., & Datta, D. (2025) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2025.1610350 · Cited by 7
Balivada, S., Ganta, C. K., Zhang, Y., Pawar, H. N., Ortiz, R. J., Becker, K. G., Khan, A. M., & Kenney, M. (2017) · Physiological Genomics · doi:10.1152/physiolgenomics.00131.2016 · Cited by 7
Xin, Y., Chu, T., Zhou, S., & Xu, A. (2023) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2023.110821 · Cited by 6
Najafi, H., Naseri, M., Zahiri, J., Totonchi, M., & Sadeghizadeh, M. (2019) · ASN NEURO · doi:10.1177/1759091419854627 · Cited by 6
Harrison, P. J., Laatikainen, L. M., Tunbridge, E. M., & Eastwood, S. L. (2010) · Neuropathology and Applied Neurobiology · doi:10.1111/j.1365-2990.2010.01098.x · Cited by 6
Wang, X. (2013) · 癌症:英文版 · doi:10.5732/cjc.012.10114 · Cited by 6
Parallel changes in gene expression in aged human and mouse cortex
Sharman, E. H., Sharman, K. G., & Bondy, S. C. (2005) · Neuroscience Letters · doi:10.1016/j.neulet.2005.07.042 · Cited by 6
Electrophysiology and morphology of human cortical supragranular pyramidal cells in a wide age rangePreprint
Barzó, P., Szöts, I., Tóth, M., Csajbók, É., Molnár, G., & Tamás, G. (2024) · eLife · doi:10.7554/elife.100390 · Cited by 11
Cao, K., Ryvkin, P., Hwang, Y.-C., Johnson, F. B., & Wang, L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074578 · Cited by 5
Cox, L. A., Puppala, S., Chan, J., Zimmerman, K. D., Hamid, Z., Ampong, I., Huber, H. F., Li, G., Jadhav, A. Y. L., Wang, B., et al. (2022) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.08.009 · Cited by 6
Compositional perspectives on human brain aging
Arhondakis, S., & Κοσσίδα, Σ. (2011) · Biosystems · doi:10.1016/j.biosystems.2011.01.005 · Cited by 5
Effect of trehalose on miR-132 and SIRT1 in the hippocampus of aged rats
Shafiei, B., Afgar, A., Nematollahi, M. H., Shabani, M., & Nazari‐Robati, M. (2023) · Neuroscience Letters · doi:10.1016/j.neulet.2023.137418 · Cited by 5
Genome-wide transcriptome profiling and development of age prediction models in the human brain
Zarrella, J., & Tsurumi, A. (2024) · Aging · doi:10.18632/aging.205609 · Cited by 4
Anticipated Brain Molecular Aging in Major Depression
Douillard‐Guilloux, G., Guilloux, J., Lewis, D. A., & Sibille, E. L. (2012) · American Journal of Geriatric Psychiatry · doi:10.1097/jgp.0b013e318266b7ad · Cited by 4
Self-citationNeurobiological Mechanisms of Cognitive Decline Correlated with Brain Aging
Zhang, X., An, H., Chen, Y., & Shu, N. (2023) · Advances in experimental medicine and biology · doi:10.1007/978-981-99-1627-6_10 · Cited by 4
Age‐Associated Transcriptomic and Epigenetic Alterations in Mouse Hippocampus
Bilgic, M., Obata, R., Panfil, V., Zhu, Z., Saeki, M., Gotoh, Y., & Kishi, Y. (2025) · Aging Cell · doi:10.1111/acel.70233 · Cited by 5
Brain Aging: Key Theories and Neurophysiological Insights
Tretyakova, V. D., & Pultsina, K. I. (2025) · Clinical Psychology and Special Education · doi:10.17759/cpse.2024130401 · Cited by 3
“Cerebellar Challenge” for Older Adults: Evaluation of a Home-Based Internet Intervention
Gallant, Z., & Nicolson, R. I. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00332 · Cited by 3
Can photobiomodulation enhance brain function in older adults?
Chan, A. S.-Y., Yeung, M. K.-C., & Lee, T. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-815305-5.00031-2 · Cited by 3
Wang, X. (2012) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2012.01.001 · Cited by 4
Molecular and Cellular Evidence for Age by Disease Interactions: Updates and Path Forward
Shukla, R., Oh, H., & Sibille, E. L. (2019) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2019.06.001 · Cited by 2
Self-citationEndogenous Defenses that Protect Dopamine Neurons
Leak, R. K., & Zigmond, M. J. (2008) · Elsevier eBooks · doi:10.1016/b978-0-12-374028-1.00013-0 · Cited by 2
Sharman, E. H. (2010) · Humana Press eBooks · doi:10.1007/978-1-60761-602-3_5 · Cited by 2
Tripp, A. C., Kota, R. S., Lewis, D. A., & Sibille, E. L. (2010) · Cited by 2
Self-citationFinding the pathology of major depression through effects on gene interaction networks
Gaiteri, C. (2011) · D-Scholarship@Pitt (University of Pittsburgh) · Cited by 2
A Population-scale Single-cell Spatial Transcriptomic Atlas of the Human CortexPreprint
Han, L., Liu, Z., Wang, L., Liu, Y., Wei, Y., Ma, J., He, Y., Zuo, Y., Fang, J., Yang, H., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.13.681959 · Cited by 3
Liharska, L. E., & Charney, A. W. (2024) · Current topics in behavioral neurosciences · doi:10.1007/7854_2024_466 · Cited by 1
Datta, D., Wang, M., & Arnsten, A. F. T. (2026) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2026.1750092 · Cited by 1
Zupo, L., Adinolfi, A., Pieraccioli, M., Guerra, M., Corvino, V., Ria, F., Ceci, V., Chiurchiù, V., Gaetani, L., Sperandei, S., et al. (2026) · Cell Death Discovery · doi:10.1038/s41420-026-03051-9 · Cited by 1
Altered GABA function in Major Depression
French, B. J., Seney, M. L., & Sibille, E. L. (2014) · Springer eBooks · doi:10.1007/978-1-4939-1056-4_13 · Cited by 1
Self-citationAusgewählte altersbedingte Erkrankungen
Behl, C., & Ziegler, C. (2015) · Springer eBooks · doi:10.1007/978-3-662-48250-6_4 · Cited by 1
Silvestri, E., Lombardi, A., de Lange, P., Glinni, D., Senese, R., Cioffi, F., Lanni, A., Goglia, F., & Moreno, M. (2014) · Apple Academic Press eBooks · doi:10.1201/b17137-4 · Cited by 1
Hogeveen, J., Campbell, E. M., Mullins, T. S., Robertson‐Benta, C. R., Quinn, D. K., Mayer, A. R., & Cavanagh, J. F. (2024) · Brain Communications · doi:10.1093/braincomms/fcae250 · Cited by 1
Metadata
- Authors
- Erraji-Benchekroun, L., Underwood, M. D., Arango, V., Galfalvy, H., Pavlidis, P., Smyrniotopoulos, P., Mann, J. J., & Sibille, E.
- Affiliations
- New York State Psychiatric Institute (US)
- Columbia University (US)
- Corresponding author
- Sibille, Etienne
- Venue
- Biological Psychiatry
- Publisher
- Elsevier BV
- Published
- 2005-03
- Volume
- 57
- Issue
- 5
- Pages
- 549-558
- ISSN
- 0006-3223 (ISSN-L)
- OpenAlex
- W2151431569
- Cited by
- 236
- References
- 58
- Citations by year
- 2026: 3 · 2025: 11 · 2024: 10 · 2023: 13 · 2022: 6 · 2021: 3 · 2020: 10 · 2019: 15 · 2018: 11 · 2017: 12 · 2016: 12 · 2015: 13 · 2014: 13 · 2013: 18 · 2012: 14
- FWCI
- 3.39
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biological Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Mental Health (T32MH020004, MH 62185, R01MH064168, MH64168, R01 MH40210, R01MH040210, F32MH63559, F32MH063559, K01MH067721, P50MH062185)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- brain aging, prefrontal cortex, age-related gene expression, transcriptome, neuroinflammation, neuronal gene expression, age prediction, postmortem brain, adult neuroplasticity
- MeSH terms
- Adolescent, Adult, Age Factors, Aged, Aging, Female, Humans, Longevity, Male, Middle Aged, Neuroglia, Neurons, Postmortem Changes, RNA, Messenger, Gene Expression, Prefrontal Cortex, Gene Expression Regulation, Developmental, Reverse Transcriptase Polymerase Chain Reaction, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling
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