The DOI matches its Crossref record; 57 of the 58 references it cites were found in a registry or an index.
U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer’s disease
Open accessAbstract
Deposition of insoluble protein aggregates is a hallmark of neurodegenerative diseases. The universal presence of β-amyloid and tau in Alzheimer’s disease (AD) has facilitated advancement of the amyloid cascade and tau hypotheses that have dominated AD pathogenesis research and therapeutic development. However, the underlying etiology of the disease remains to be fully elucidated. Here we report a comprehensive study of the human brain-insoluble proteome in AD by mass spectrometry. We identify 4,216 proteins, among which 36 proteins accumulate in the disease, including U1-70K and other U1 small nuclear ribonucleoprotein (U1 snRNP) spliceosome components. Similar accumulations in mild cognitive impairment cases indicate that spliceosome changes occur in early stages of AD. Multiple U1 snRNP subunits form cytoplasmic tangle-like structures in AD but not in other examined neurodegenerative disorders, including Parkinson disease and frontotemporal lobar degeneration. Comparison of RNA from AD and control brains reveals dysregulated RNA processing with accumulation of unspliced RNA species in AD, including myc box-dependent-interacting protein 1, clusterin, and presenilin-1 . U1-70K knockdown or antisense oligonucleotide inhibition of U1 snRNP increases the protein level of amyloid precursor protein. Thus, our results demonstrate unique U1 snRNP pathology and implicate abnormal RNA splicing in AD pathogenesis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Tau-RBP interactions disrupt RNA splicing resulting in gene dysregulation and neurotoxicity (Apicco et al., 2018; Bai et al., 2013; Hsieh et al., 2019).”
From Selective removal of astrocytic APOE4 strongly protects against tau-mediated neurodegeneration and decreases synaptic phagocytosis by microglia (2021) · cites this paper as Bai et al., 2013
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“We performed a comprehensive analysis of the aggregated proteome, detecting the deposition of U1 small nuclear ribonucleoprotein (U1 snRNP) and a deficit of RNA splicing in AD brain (Bai et al., 2013; Lutz and Peng, 2018).”
From Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression (2020) · cites this paper as Bai et al., 2013
In the citing paper
“We and others have previously identified RNA splicing deficits in AD brain which could have profound impact on transcription of many genes, including tau, APP, and presenilins (Bai et al., 2013; Tollervey et al., 2011).”
From A Multi-network Approach Identifies Protein-Specific Co-expression in Asymptomatic and Symptomatic Alzheimer’s Disease (2017) · cites this paper as Bai et al., 2013
In the citing paper
“These ribonucleoproteins, constituents of the spliceosome complex responsible for RNA processing, are mislocalized in AD to the cytoplasm of neuronal cell bodies where they aggregate with NFTs and contribute to widespread alterations in RNA processing [134].”
From Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau (2021) · cites this paper as [134]
In the citing paper
“this aggregation of U1 snRNPs with tau appears to be unique to the AD brain and absent among other primary tauopathies, such as FTLD [134, 138].”
From Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau (2021) · cites this paper as [134]
In the citing paper
“previous analyses of the AD brain detergent-insoluble proteome, which have repeatedly demonstrated the association of U1 small nuclear ribonucleoproteins (U1 snRNPs) and other RNA-binding proteins with tau tangles [133–137].”
From Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau (2021) · cites this paper as [134]
In the citing paper
“Interestingly, our previous studies demonstrated that many of the U1 snRNPs colocalize with neurofibrillary tangles and paired helical filaments in AD brain [24, 32–34], and that accumulation of insoluble snRNPs correlates strongly with both amyloid and Tau pathology [32–37].”
From Deep proteomic network analysis of Alzheimer’s disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease (2018) · cites this paper as [24]
In the citing paper
“We have previously shown that U1 snRNPs are a major component of the AD insoluble proteome [24, 32–34].”
From Deep proteomic network analysis of Alzheimer’s disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease (2018) · cites this paper as [24]
In the citing paper
“Although we have previously observed that snRNP alterations are associated with deficits in RNA splicing in AD brain [24, 32]—a finding recently confirmed by others [52]”
From Deep proteomic network analysis of Alzheimer’s disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease (2018) · cites this paper as [24]
In the citing paper
“This may be due to the fact that U1 spliceosome proteins undergo a dramatic shift in solubility in AD brain, and aggregate in close proximity to neurofibrillary tangles [24, 32–34].”
From Deep proteomic network analysis of Alzheimer’s disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease (2018) · cites this paper as [24]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics
Hardy, J., & Selkoe, D. J. (2002) · Science · doi:10.1126/science.1072994 · Cited by 13,864
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
Amyloid oligomers exacerbate tau pathology in a mouse model of tauopathy
Selenica, M.-L. B., Brownlow, M., Jimenez, J. P., Lee, D. C., Pena, G., Dickey, C. A., Gordon, M. N., & Morgan, D. (2013) · Neurodegenerative Diseases · doi:10.1159/000337230 · Cited by 10,359
Mild Cognitive Impairment: Clinical Characterization and Outcome
Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999) · Archives of Neurology · doi:10.1001/archneur.56.3.303 · Cited by 8,980
Spillantini, M. G., Schmidt, M. L., Lee, V. M.-Y., Trojanowski, J. Q., Jakes, R., & Goedert, M. (1997) · Nature · doi:10.1038/42166 · Cited by 8,382
Mutation in the α-Synuclein Gene Identified in Families with Parkinson's Disease
Polymeropoulos, M. H., Lavedan, C., Leroy, E., Ide, S. E., Dehejia, A., Dutra, A., Pike, B., Root, H., Rubenstein, J., Boyer, R., et al. (1997) · Science · doi:10.1126/science.276.5321.2045 · Cited by 8,240
Ubiquitinated TDP-43 in Frontotemporal Lobar Degeneration and Amyotrophic Lateral Sclerosis
Neumann, M., Sampathu, D. M., Kwong, L. K., Truax, A. C., Micsenyi, M. C., Chou, T. T., Bruce, J., Schuck, T., Grossman, M., Clark, C. M., et al. (2006) · Science · doi:10.1126/science.1134108 · Cited by 6,576
Mitochondrial Dysfunction and Oxidative Stress in Neurodegenerative Diseases
Lin, M. T., & Beal, M. F. (2006) · Nature · doi:10.1038/nature05292 · Cited by 6,455
Glenner, G. G., & Wong, C. W. (1984) · Biochemical and Biophysical Research Communications · doi:10.1016/s0006-291x(84)80190-4 · Cited by 5,404
Mirra, S. S., Heyman, A., McKeel, D., Sumi, S. M., Crain, B. J., Brownlee, L. M., Vogel, F. S., Hughes, J. P., Belle, G. V., Berg, L., et al. (1991) · Neurology · doi:10.1212/wnl.41.4.479 · Cited by 4,961
Cited by
Sorted by citations
Scotti, M. M., & Swanson, M. S. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.3 · Cited by 1,163
Johnson, E. C. B., Dammer, E. B., Duong, D. M., Ping, L., Zhou, M., Yin, L., Higginbotham, L. A., Guajardo, A., White, B., Troncoso, J. C., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0815-6 · Cited by 1,001
Self-citationConnecting genetic risk to disease end points through the human blood plasma proteome
Suhre, K., Arnold, M., Bhagwat, A. M., Cotton, R. J., Engelke, R., Raffler, J., Sarwath, H., Thareja, G., Wahl, A., DeLisle, R. K., et al. (2017) · Nature Communications · doi:10.1038/ncomms14357 · Cited by 800
Stress granules and neurodegeneration
Wolozin, B., & Ivanov, P. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0222-5 · Cited by 810
Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression
Bai, B., Wang, X., Li, Y., Chen, P.-C., Yu, K., Dey, K. K., Yarbro, J. M., Han, X., Lutz, B. M., Rao, S., et al. (2020) · Neuron · doi:10.1016/j.neuron.2019.12.015 · Cited by 565
“We performed a comprehensive analysis of the aggregated proteome, detecting the deposition of U1 small nuclear ribonucleoprotein (U1 snRNP) and a deficit of RNA splicing in AD brain (Bai et al., 2013; Lutz and Peng, 2018).”
BackgroundMethodInfluentialSelf-citationRaja, W. K., Mungenast, A. E., Lin, Y.-T., Ko, T., Abdurrob, F., Seo, J., & Tsai, L.-H. (2016) · PLOS ONE · doi:10.1371/journal.pone.0161969 · Cited by 569
Johnson, E. C. B., Carter, E. K., Dammer, E. B., Duong, D. M., Gerasimov, E. S., Liu, Y., Liu, J., Betarbet, R., Ping, L., Yin, L., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-021-00999-y · Cited by 561
Self-citationNuclear speckles: molecular organization, biological function and role in disease
Gałgański, Ł., Urbanek-Trzeciak, M. O., & Krzyżosiak, W. J. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx759 · Cited by 489
A new view of transcriptome complexity and regulation through the lens of local splicing variations
Vaquero-Garcia, J., Barrera, A., Gazzara, M. R., González-Vallinas, J., Lahens, N. F., Hogenesch, J. B., Lynch, K. W., & Barash, Y. (2016) · eLife · doi:10.7554/elife.11752 · Cited by 488
Seyfried, N. T., Dammer, E. B., Swarup, V., Nandakumar, D., Duong, D. M., Yin, L., Deng, Q., Nguyen, T., Hales, C. M., Wingo, T., et al. (2017) · Cell Systems · doi:10.1016/j.cels.2016.11.006 · Cited by 477
Self-citationRaj, T., Li, Y. I., Wong, G., Humphrey, J., Wang, M., Ramdhani, S., Wang, Y.-C., Ng, B., Gupta, I., Haroutunian, V., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0238-1 · Cited by 410
Self-citationPosttranslational Modifications Mediate the Structural Diversity of Tauopathy Strains
Arakhamia, T., Lee, C. E., Carlomagno, Y., Kumar, M., Duong, D. M., Wesseling, H., Kundinger, S. R., Wang, K., Williams, D., Deture, M. A., et al. (2020) · Cell · doi:10.1016/j.cell.2020.01.027 · Cited by 410
Self-citationInteraction of tau with the RNA-Binding Protein TIA1 Regulates tau Pathophysiology and Toxicity
Vanderweyde, T. E., Apicco, D. J., Youmans-Kidder, K., Ash, P. E. A., Cook, C. N., da Rocha, E. L., Jansen‐West, K. R., Frame, A. A., Citro, A., Leszyk, J., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.04.045 · Cited by 346
Wang, C., Xiong, M., Gratuze, M., Bao, X., Shi, Y., Andhey, P. S., Manis, M., Schroeder, C., Yin, Z., Madore, C., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.03.024 · Cited by 334
Amyloid-Beta Protein Clearance and Degradation (ABCD) Pathways and their Role in Alzheimer’s Disease
Baranello, R., Bharani, K., Padmaraju, V., Chopra, N., Lahiri, D., Greig, N., Pappolla, M., & Sambamurti, K. (2015) · Current Alzheimer Research · doi:10.2174/1567205012666141218140953 · Cited by 331
Machine learning identifies candidates for drug repurposing in Alzheimer’s disease
Rodriguez, S., Hug, C., Todorov, P., Moret, N., Boswell, S. A., Evans, K., Zhou, G., Johnson, N. T., Hyman, B. T., Sorger, P. K., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21330-0 · Cited by 299
Proteomic landscape of Alzheimer’s Disease: novel insights into pathogenesis and biomarker discovery
Bai, B., Vanderwall, D., Li, Y., Wang, X., Poudel, S., Wang, H., Dey, K. K., Chen, P., Yang, K., & Peng, J. (2021) · Molecular Neurodegeneration · doi:10.1186/s13024-021-00474-z · Cited by 260
Self-citationProteomic differences in amyloid plaques in rapidly progressive and sporadic Alzheimer’s disease
Drummond, E., Nayak, S., Faustin, A., Pires, G., Hickman, R. A., Askenazi, M., Cohen, M., Haldiman, T., Kim, C., Han, X., et al. (2017) · Acta Neuropathologica · doi:10.1007/s00401-017-1691-0 · Cited by 239
Spliceosome-targeted therapies trigger an antiviral immune response in triple-negative breast cancer
Bowling, E. A., Wang, J. H., Gong, F., Wu, W., Neill, N. J., Kim, I. S., Tyagi, S., Orellana, M. C., Kurley, S. J., Domínguez-Vidaña, R., et al. (2021) · Cell · doi:10.1016/j.cell.2020.12.031 · Cited by 227
Johnson, E. C. B., Dammer, E. B., Duong, D. M., Yin, L., Thambisetty, M., Troncoso, J. C., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2018) · Molecular Neurodegeneration · doi:10.1186/s13024-018-0282-4 · Cited by 225
Self-citationTau Protein Interaction Partners and Their Roles in Alzheimer’s Disease and Other Tauopathies
Sinsky, J., Pichlerova, K., & Hanes, J. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22179207 · Cited by 220
Tau aggregates are RNA-protein assemblies that mislocalize multiple nuclear speckle components
Lester, E., Ooi, F. K., Bakkar, N., Ayers, J. I., Woerman, A. L., Wheeler, J., Bowser, R. P., Carlson, G. A., Prusiner, S. B., & Parker, R. (2021) · Neuron · doi:10.1016/j.neuron.2021.03.026 · Cited by 212
Defective control of pre–messenger RNA splicing in human disease
Chabot, B., & Shkreta, L. (2016) · The Journal of Cell Biology · doi:10.1083/jcb.201510032 · Cited by 220
Wang, H., Dey, K. K., Chen, P.-C., Li, Y., Niu, M., Cho, J.-H., Wang, X., Bai, B., Jiao, Y., Chepyala, S. R., et al. (2020) · Molecular Neurodegeneration · doi:10.1186/s13024-020-00384-6 · Cited by 210
Self-citationHsieh, Y.-C., Guo, C., Yalamanchili, H. K., Abreha, M., Al-Ouran, R., Li, Y., Dammer, E. B., Lah, J. J., Levey, A. I., Bennett, D. A., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.08.104 · Cited by 196
Self-citationUnderstanding Alzheimer Disease at the Interface between Genetics and Transcriptomics
Verheijen, J., & Sleegers, K. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.02.007 · Cited by 192
Deregulation of purine metabolism in Alzheimer's disease
Ansoleaga, B., Jové, M., Schlüter, A., Garcia‐Esparcia, P., Moreno, J. R., Pujol, A., Pamplona, R., Portero‐Otín, M., & Ferrer, I. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.08.004 · Cited by 163
Daguenet, É., Dujardin, G., & Valcárcel, J. (2015) · EMBO Reports · doi:10.15252/embr.201541116 · Cited by 159
RNA binding proteins co-localize with small tau inclusions in tauopathy
Maziuk, B. F., Apicco, D. J., Cruz, A. L., Jiang, L., Ash, P. E. A., da Rocha, E. L., Zhang, C., Yu, W. H., Leszyk, J., Abisambra, J. F., et al. (2018) · Acta Neuropathologica Communications · doi:10.1186/s40478-018-0574-5 · Cited by 151
Watson, C. N., Belli, A., & Pietro, V. D. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00364 · Cited by 154
Gupta, V. B., Chitranshi, N., den Haan, J., Mirzaei, M., You, Y., Lim, J. K. H., Basavarajappa, D. K., Godinez, A., Angelantonio, S. D., Sachdev, P. S., et al. (2020) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2020.100899 · Cited by 149
Mirzaei, M., Gupta, V. B., Chick, J. M., Greco, T. M., Wu, Y., Chitranshi, N., Wall, R. V., Hone, E., Deng, L., Dheer, Y., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-12858-7 · Cited by 141
Implications of polyadenylation in health and disease
Curinha, A., Bráz, S., Pereira‐Castro, I., Cruz, A., & Moreira, A. (2014) · Nucleus · doi:10.4161/nucl.36360 · Cited by 144
Adusumalli, S., Ngian, Z., Lin, W., Benoukraf, T., & Ong, C. (2019) · Aging Cell · doi:10.1111/acel.12928 · Cited by 144
Hinrich, A. J., Jodelka, F. M., Chang, J. L., Brutman, D., Bruno, A. M., Briggs, C. A., James, B. D., Stutzmann, G. E., Bennett, D. A., Miller, S. A., et al. (2016) · EMBO Molecular Medicine · doi:10.15252/emmm.201505846 · Cited by 127
Self-citationThe miRNome of Alzheimer's disease: consistent downregulation of the miR-132/212 cluster
Pichler, S., Gu, W., Hartl, D., Gasparoni, G., Leidinger, P., Keller, A., Meese, E., Mayhaus, M., Hampel, H., & Riemenschneider, M. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.09.019 · Cited by 108
Bai, B., Tan, H., Pagala, V., High, A. A., Ichhaporia, V. P., Hendershot, L. M., & Peng, J. (2016) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/bs.mie.2016.10.007 · Cited by 119
Self-citationSystems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau
Rayaprolu, S., Higginbotham, L., Bagchi, P., Watson, C. M., Zhang, T., Levey, A. I., Rangaraju, S., & Seyfried, N. T. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-020-00840-3 · Cited by 118
Self-citationStilling, R. M., Benito, E., Barth, J., Gertig, M., Capece, V., Burckhardt, S., Bonn, S., & Fischer, A. (2014) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2014.00373 · Cited by 114
Noncoding translation mitigation
Kesner, J. S., Chen, Z., Shi, P., Aparicio, A. O., Murphy, M. R., Guo, Y., Trehan, A., Lipponen, J. E., Recinos, Y., Myeku, N., et al. (2023) · Nature · doi:10.1038/s41586-023-05946-4 · Cited by 116
Hales, C. M., Dammer, E. B., Deng, Q., Duong, D. M., Gearing, M., Troncoso, J. C., Thambisetty, M., Lah, J. J., Shulman, J. M., Levey, A. I., et al. (2016) · PROTEOMICS · doi:10.1002/pmic.201600057 · Cited by 99
Self-citationMoving beyond amyloid and tau to capture the biological heterogeneity of Alzheimer’s disease
Young‐Pearse, T. L., Lee, H., Hsieh, Y., Chou, V., & Selkoe, D. J. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2023.03.005 · Cited by 102
Brain pathology in myotonic dystrophy: when tauopathy meets spliceopathy and RNAopathy
Caillet‐Boudin, M., Fernández-Gómez, F.-J., Tran, H., Dhaenens, C., Buée, L., & Sergeant, N. (2014) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2013.00057 · Cited by 107
Piras, I. S., Krate, J., Delvaux, E., Nolz, J., Mastroeni, D., Persico, A. M., Jepsen, W. M., Beach, T. G., Huentelman, M. J., & Coleman, P. D. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-181113 · Cited by 100
Wang, H., Yang, Y., Li, Y., Bai, B., Wang, X., Tan, H., Liu, T., Beach, T. G., Peng, J., & Wu, Z. (2015) · Journal of Proteome Research · doi:10.1021/pr500882h · Cited by 96
Self-citationSFPQ and Tau: critical factors contributing to rapid progression of Alzheimer’s disease
Younas, N., Zafar, S., Shafiq, M., Noor, A., Siegert, A., Arora, A. S., Galkin, A. P., Zafar, A., Schmitz, M., Stadelmann, C., et al. (2020) · Acta Neuropathologica · doi:10.1007/s00401-020-02178-y · Cited by 94
Aggregates of Small Nuclear Ribonucleic Acids ( snRNAs ) in Alzheimer's Disease
Hales, C. M., Dammer, E. B., Diner, I., Yi, H., Seyfried, N. T., Gearing, M., Glass, J. D., Montine, T. J., Levey, A. I., & Lah, J. J. (2014) · Brain Pathology · doi:10.1111/bpa.12133 · Cited by 89
Self-citationLSD1 protects against hippocampal and cortical neurodegeneration
Christopher, M. A., Myrick, D. A., Barwick, B. G., Engstrom, A., Porter‐Stransky, K. A., Boss, J. M., Weinshenker, D., Levey, A. I., & Katz, D. J. (2017) · Nature Communications · doi:10.1038/s41467-017-00922-9 · Cited by 89
Self-citationCombating deleterious phase transitions in neurodegenerative disease
Darling, A. L., & Shorter, J. (2021) · Biochimica et Biophysica Acta (BBA) - Molecular Cell Research · doi:10.1016/j.bbamcr.2021.118984 · Cited by 87
Hypoxia-induced autophagy as an additional mechanism in human osteosarcoma radioresistance
Feng, H., Wang, J., Chen, W., Shan, B., Guo, Y., Xu, J., Wang, L., Guo, P., & Zhang, Y. (2016) · Journal of bone oncology · doi:10.1016/j.jbo.2016.03.001 · Cited by 86
Dysregulation of RNA Splicing in Tauopathies
Apicco, D. J., Zhang, C., Maziuk, B. F., Jiang, L., Ballance, H. I., Boudeau, S., Ung, C. Y., Li, H., & Wolozin, B. L. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.11.093 · Cited by 81
Bishof, I., Dammer, E. B., Duong, D. M., Kundinger, S. R., Gearing, M., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2018) · Journal of Biological Chemistry · doi:10.1074/jbc.ra118.001747 · Cited by 80
Self-citationNon-Coding RNAs in Psychiatric Disorders and Suicidal Behavior
Yoshino, Y., & Dwivedi, Y. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.543893 · Cited by 85
Quadros, A. R. A. D. A., Li, Z., Wang, X., Ndayambaje, I. S., Aryal, S., Ramesh, N., Nolan, M., Jayakumar, R., Han, Y., Stillman, H., et al. (2024) · Acta Neuropathologica · doi:10.1007/s00401-023-02655-0 · Cited by 77
Self-citationModeling Neurodegenerative Microenvironment Using Cortical Organoids Derived from Human Stem Cells
Yan, Y., Song, L., Bejoy, J., Zhao, J., Kanekiyo, T., Bu, G., Zhou, Y., & Li, Y. (2018) · Tissue Engineering Part A · doi:10.1089/ten.tea.2017.0423 · Cited by 84
Self-citationDrummond, E. S., Nayak, S., Ueberheide, B., & Wisniewski, T. (2015) · Scientific Reports · doi:10.1038/srep15456 · Cited by 78
Xue, S., Gong, R., He, F., Yan-qin, L., Wang, Y., Tan, T., & Luo, S. (2019) · Science Advances · doi:10.1126/sciadv.aax5349 · Cited by 77
Huang, J.-L., Qin, M.-C., Zhou, Y., Xu, Z., Yang, S., Zhang, F., Zhong, J., Liang, M.-K., Chen, B., Zhang, W., et al. (2018) · Aging · doi:10.18632/aging.101387 · Cited by 78
Nuclear ULK1 promotes cell death in response to oxidative stress through PARP1
Joshi, A., Iyengar, R., Joo, J. H., Li-Harms, X. J., Wright, C., Marino, R., Winborn, B. J., Phillips, A., Temirov, J., Sciarretta, S., et al. (2016) · Cell Death & Differentiation · doi:10.1038/cdd.2015.88 · Cited by 72
Self-citationAlternative splicing in Alzheimer’s disease
Biamonti, G., Amato, A. M., Belloni, E., Matteo, A. D., Infantino, L., Pradella, D., & Ghigna, C. (2019) · Aging Clinical and Experimental Research · doi:10.1007/s40520-019-01360-x · Cited by 78
Wang, Z., Zhang, F., He, J., Wu, P., Tay, L. W. R., Cai, M., Nian, W., Weng, Y., Qin, L., Chang, J. T., et al. (2017) · Developmental Cell · doi:10.1016/j.devcel.2017.09.012 · Cited by 74
Self-citationBernstein, A. I., Lin, Y., Street, R. C., Lin, L., Dai, Q., Yu, L., Bao, H., Gearing, M., Lah, J. J., Nelson, P. T., et al. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw109 · Cited by 73
Self-citationGallart‐Palau, X., Lee, B. S. T., Adav, S. S., Qian, J., Serra, A., Park, J. E., Lai, M. K. P., Chen, C., Kalaria, R. N., & Sze, S. K. (2016) · Molecular Brain · doi:10.1186/s13041-016-0205-7 · Cited by 72
Wang, S., Yu, L., Yang, H., Li, C., Hui, Z., Xu, Y., & Zhu, X. (2016) · PLoS ONE · doi:10.1371/journal.pone.0151397 · Cited by 72
Splicing alterations in healthy aging and disease
Angarola, B. L., & Anczuków, O. (2021) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1643 · Cited by 73
RNA Dynamics in Alzheimer’s Disease
Rybak‐Wolf, A., & Plass, M. (2021) · Molecules · doi:10.3390/molecules26175113 · Cited by 72
Biomaterial design inspired by membraneless organelles
Liu, J., Zhorabek, F., & Chau, Y. (2022) · Matter · doi:10.1016/j.matt.2022.07.001 · Cited by 71
Alternative Splicing in Alzheimer’s Disease
Love, J. E., Hayden, E. J., & Rohn, T. T. (2015) · Journal of Parkinson’s Disease and Alzheimer’s Disease · doi:10.13188/2376-922x.1000010 · Cited by 69
Splicing and neurodegeneration: Insights and mechanisms
Nik, S., & Bowman, T. V. (2019) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1532 · Cited by 68
Nourse, J. P., Spada, S., & Danckwardt, S. (2020) · Biomolecules · doi:10.3390/biom10060915 · Cited by 68
The intellectual disability gene PQBP1 rescues Alzheimer’s disease pathology
Tanaka, H., Kondo, K., Chen, X., Homma, H., Tagawa, K., Kerever, A., Aoki, S., Saito, T., Saido, T. C., Muramatsu, S., et al. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0253-8 · Cited by 64
McMillan, P. J., Strovas, T. J., Baum, M., Mitchell, B. K., Eck, R. J., Hendricks, N., Wheeler, J. M., Latimer, C. S., Keene, C. D., & Kraemer, B. C. (2021) · Acta Neuropathologica Communications · doi:10.1186/s40478-021-01219-1 · Cited by 64
Wang, Z.-H., Liu, P., Liu, X., Manfredsson, F. P., Sandoval, I. M., Yu, S. P., Wang, J., & Ye, K. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.07.018 · Cited by 69
Aggregation Properties of the Small Nuclear Ribonucleoprotein U1-70K in Alzheimer Disease
Diner, I., Hales, C. M., Bishof, I., Rabenold, L., Duong, D. M., Yi, H., Laur, O., Gearing, M., Troncoso, J., Thambisetty, M., et al. (2014) · Journal of Biological Chemistry · doi:10.1074/jbc.m114.562959 · Cited by 63
Self-citationProteomics of protein post-translational modifications implicated in neurodegeneration
Ren, R., Dammer, E. B., Wang, G., Seyfried, N. T., & Levey, A. I. (2014) · Translational Neurodegeneration · doi:10.1186/2047-9158-3-23 · Cited by 63
Self-citationA network approach to clinical intervention in neurodegenerative diseases
Santiago, J. A., & Potashkin, J. A. (2014) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2014.10.002 · Cited by 62
Chen, P., Han, X., Shaw, T. I., Fu, Y., Sun, H., Niu, M., Wang, Z., Jiao, Y., Teubner, B. J. W., Eddins, D. M., et al. (2022) · Nature Aging · doi:10.1038/s43587-022-00290-0 · Cited by 60
Self-citationTan, H., Wu, Z., Wang, H., Bai, B., Li, Y., Wang, X., Zhai, B., Beach, T. G., & Peng, J. (2014) · PROTEOMICS · doi:10.1002/pmic.201400171 · Cited by 58
Self-citationGuennewig, B., Lim, J., Marshall, L. L., McCorkindale, A. N., Paasila, P. J., Patrick, E., Kril, J. J., Halliday, G. M., Cooper, A. A., & Sutherland, G. T. (2021) · Scientific Reports · doi:10.1038/s41598-021-83872-z · Cited by 59
RNA dysregulation in neurodegenerative diseases
Li, Y., & Sun, S. (2025) · The EMBO Journal · doi:10.1038/s44318-024-00352-6 · Cited by 65
Self-citationKarri, V., Ramos, D., Bauzá‐Martinez, J., Odena, M. A., de Oliveira, E., Coort, S. L., Evelo, C. T., Mariman, E. C. M., Schuhmacher, M., & Kumar, V. (2018) · Journal of Proteomics · doi:10.1016/j.jprot.2018.06.020 · Cited by 65
Hales, C. M., Seyfried, N. T., Dammer, E. B., Duong, D., Yi, H., Gearing, M., Troncoso, J. C., Mufson, E. J., Thambisetty, M., Levey, A. I., et al. (2014) · Molecular Neurodegeneration · doi:10.1186/1750-1326-9-15 · Cited by 58
Self-citationSaurat, N. G., Minotti, A. P., Rahman, M. T., Sikder, T., Zhang, C., Cornacchia, D., Jungverdorben, J., Ciceri, G., Betel, D., & Studer, L. (2024) · Cell stem cell · doi:10.1016/j.stem.2024.06.001 · Cited by 60
Levites, Y., Dammer, E. B., Ran, Y., Tsering, W., Duong, D. M., Abreha, M. H., Gadhavi, J. D., Lolo, K., Trejo‐Lopez, J. A., Phillips, J., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101669 · Cited by 57
Self-citationCholinergic Surveillance over Hippocampal RNA Metabolism and Alzheimer's-Like Pathology
Kolisnyk, B., Al‐Onaizi, M., Soreq, L., Barbash, S., Bekenstein, U., Haberman, N., Hanin, G., Kish, M. T., da Silva, J. S., Fahnestock, M. L., et al. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw177 · Cited by 55
Prema, A., Thenmozhi, A. J., Manivasagam, T., Essa, M. M., Akbar, M. D., & Akbar, M. D. (2016) · PLoS ONE · doi:10.1371/journal.pone.0165955 · Cited by 58
Huang, Y., Driedonks, T. A. P., Cheng, L., Turchinovich, A., Rajapaksha, H., Arab, T., Powell, B. H., Pletniková, O., Redding‐Ochoa, J., Troncoso, J. C., et al. (2022) · Journal of Alzheimer s Disease · doi:10.3233/jad-220322 · Cited by 58
A multiomic approach to characterize the temporal sequence in Alzheimer's disease-related pathology
Marttinen, M., Paananen, J., Neme, A., Mitra, V., Takalo, M., Natunen, T., Paldanius, K. M. A., Mäkinen, P. M., Bremang, M., Kurki, M., et al. (2018) · Neurobiology of Disease · doi:10.1016/j.nbd.2018.12.009 · Cited by 55
Satoh, J.-I., Yamamoto, Y., Asahina, N., Kitano, S., & Kino, Y. (2014) · Disease Markers · doi:10.1155/2014/123165 · Cited by 53
Mills, J. D., van Vliet, E. A., Chen, B. J., Janitz, M., Anink, J. J., Baayen, J. C., Idema, S., Devore, S., Friedman, D., Diehl, B., et al. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2019.104612 · Cited by 48
Enrichment of Detergent-insoluble Protein Aggregates from Human Postmortem Brain
Diner, I., Nguyen, T. T. H., & Seyfried, N. T. (2017) · Journal of Visualized Experiments · doi:10.3791/55835 · Cited by 52
Self-citationRamos‐Miguel, A., Hercher, C., Beasley, C. L., Barr, A. M., Bayer, T. A., Falkai, P., Leurgans, S. E., Schneider, J. A., Bennett, D. A., & Honer, W. G. (2015) · Molecular Neurodegeneration · doi:10.1186/s13024-015-0061-4 · Cited by 45
Self-citationPatel, R. J., Brophy, C., Hickling, M., Neve, J., & Furger, A. (2019) · BMC Medical Genomics · doi:10.1186/s12920-019-0509-4 · Cited by 45
The Neat Dance of COVID-19: NEAT1, DANCR, and Co-Modulated Cholinergic RNAs Link to Inflammation
Meydan, C., Madrer, N., & Soreq, H. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.590870 · Cited by 48
Caldas, P., Luz, M., Baseggio, S., Andrade, R., Sobral, D., & Grosso, A. R. (2024) · Communications Biology · doi:10.1038/s42003-024-05779-5 · Cited by 49
Deconstructing and targeting the genomic architecture of human neurodegeneration
Jager, P. L. D., Yang, H., & Bennett, D. A. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0240-z · Cited by 46
Self-citationBottero, V., & Potashkin, J. A. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20215403 · Cited by 47
RNA induces unique tau strains and stabilizes Alzheimer’s disease seeds
Zwierzchowski-Zarate, A. N., Mendoza‐Oliva, A., Kashmer, O. M., Collazo-Lopez, J. E., White, C. L., & Diamond, M. I. (2022) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2022.102132 · Cited by 48
Köhler, J., Schüler, M., Gauler, T. C., Nöpel‐Dünnebacke, S., Ahrens, M., Hoffmann, A.-C., Kasper, S., Nensa, F., Gomez, B., Hahnemann, M. L., et al. (2015) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-015-2095-y · Cited by 44
Yagensky, O., Kohansal-Nodehi, M., Gunaseelan, S., Rabe, T., Zafar, S., Zerr, I., Härtig, W., Urlaub, H., & Chua, J. J. E. (2019) · eLife · doi:10.7554/elife.47498 · Cited by 43
Metadata
- Authors
- Bai, B., Hales, C. M., Chen, P.-C., Gozal, Y., Dammer, E. B., Fritz, J. J., Wang, X., Xia, Q., Duong, D. M., Street, C., Cantero, G., Cheng, D., Jones, D. R., Wu, Z., Li, Y., Diner, I., Heilman, C. J., Rees, H. D., Wu, H., Lin, L., Szulwach, K. E., Gearing, M., Mufson, E. J., Bennett, D. A., Montine, T. J., Seyfried, N. T., Wingo, T. S., Sun, Y. E., Jin, P., Hanfelt, J., Willcock, D. M., Levey, A., Lah, J. J., & Peng, J.
- Affiliations
- St. Jude Children's Research Hospital (US)
- Emory University (US)
- Departments of Structural Biology and Developmental Neurobiology and
- Human Genetics,
- University of California, Los Angeles (US)
- Biostatistics and Bioinformatics,
- Rush University Medical Center (US)
- University of Washington (US)
- University of Kentucky (US)
- ORCID
- Bai, Bing
- Hales, Chadwick M.
- Chen, Ping-Chung
- Dammer, Eric B.
- Wang, Xusheng
- Xia, Qiangwei
- Duong, Duc M.
- Cantero, Gloria
- Cheng, Dongmei
- Jones, Drew R.
- Wu, Zhiping
- Li, Yuxin
- Wu, Hao
- Gearing, Marla
- Mufson, Elliott J.
- Bennett, David A.
- Montine, Thomas J.
- Seyfried, Nicholas T.
- Wingo, Thomas S.
- Sun, Yi E.
- Jin, Peng
- Hanfelt, John
- Levey, Allan
- Lah, James J.
- Peng, Junmin
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2013-09-10
- Volume
- 110
- Issue
- 41
- Pages
- 16562-16567
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3799305
- OpenAlex
- W2075426349
- Semantic Scholar
- b4638372c5d5e262f0ad2963dd66aed83aac9d24
- Cited by
- 335
- References
- 58
- Citations by year
- 2026: 20 · 2025: 34 · 2024: 23 · 2023: 29 · 2022: 23 · 2021: 43 · 2020: 29 · 2019: 24 · 2018: 27 · 2017: 24 · 2016: 30 · 2015: 12 · 2014: 17
- FWCI
- 13.55
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- American Lebanese Syrian Associated Charities
- National Institutes of Health
- Instituto de Salud Carlos III
- National Institute on Aging (P01AG014449, F32AG038259, R01AG015819, P30AG010161, R01AG043375, P50AG005136, P50AG025688)
- National Institute of Mental Health (R01MH082068)
- National Cancer Institute (P30CA021765)
- National Institute of General Medical Sciences (P01GM081621, T32GM008169)
- National Institute of Neurological Disorders and Stroke (T32NS007480, F32NS007480, P30NS055077, F30NS057902)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- Alzheimer's disease, U1 snRNP, U1-70K, RNA splicing, spliceosome, protein aggregates, amyloid precursor protein, unspliced RNA, mild cognitive impairment, antisense oligonucleotides, clusterin, presenilin 1, neurodegeneration
- MeSH terms
- Alzheimer Disease, Brain, Chromatography, Liquid, Fluorescent Antibody Technique, Humans, Immunohistochemistry, Blotting, Western, Spliceosomes, Alternative Splicing, Ribonucleoprotein, U1 Small Nuclear, Reverse Transcriptase Polymerase Chain Reaction, Proteome, Proteomics, Tandem Mass Spectrometry, High-Throughput Nucleotide Sequencing
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