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TDP-43 represses cryptic exon inclusion in the FTD-ALS gene UNC13A
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Abstract
A hallmark pathological feature of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is the depletion of RNA-binding protein TDP-43 from the nucleus of neurons in the brain and spinal cord 1 . A major function of TDP-43 is as a repressor of cryptic exon inclusion during RNA splicing 2–4 . Single nucleotide polymorphisms in UNC13A are among the strongest hits associated with FTD and ALS in human genome-wide association studies 5,6 , but how those variants increase risk for disease is unknown. Here we show that TDP-43 represses a cryptic exon-splicing event in UNC13A . Loss of TDP-43 from the nucleus in human brain, neuronal cell lines and motor neurons derived from induced pluripotent stem cells resulted in the inclusion of a cryptic exon in UNC13A mRNA and reduced UNC13A protein expression. The top variants associated with FTD or ALS risk in humans are located in the intron harbouring the cryptic exon, and we show that they increase UNC13A cryptic exon splicing in the face of TDP-43 dysfunction. Together, our data provide a direct functional link between one of the strongest genetic risk factors for FTD and ALS ( UNC13A genetic variants), and loss of TDP-43 function.
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![Extended Data Fig. 1 Splicing analysis using MAJIQ demonstrates inclusion of cryptic exon between exon 20 and exon 21 of UNC13A. (a, b) Depletion of TDP-43 introduces two alternative 3′ splicing acceptors in the intron 20–21: one is near chr19:17642591(ΔΨ = 0.05246) and the other one is near chr19:17642541(ΔΨ = 0.49267). (c, d) An alternative 5′ splicing donor is also introduced near chr19:17642414 (ΔΨ = 0.7763). See Supplementary Note 2. (a, c) Splice graphs showing the inclusion of the cryptic exon (CE) between exon 20 and exon 21 of UNC13A. (b, d) Violin plots corresponding to (a and c) respectively. Each violin in (b and d) represents the posterior probability distribution of the expected relative inclusion (PSI or Ψ) for the color matching junction in the splice graph. The tails of each violin represent the 10th and 90th percentile. The box represents the interquartile range with the line in the middle indicating the median. The white circles mark the expected PSI (E[Ψ]). The change in the relative inclusion level of each junction between two conditions is referred to as ΔΨ or ΔPSI13. (e) The three versions of cryptic exons resulting from the loss of TDP-43. (f) Visualization of RNA-sequencing alignment between exon 20 and exon 21 in UNC13A (hg38). Libraries were generated as described in Fig. 1a. CE, cryptic exon. (g) iCLIP for TDP-43 (from Tollervey et al.17) indicates that TDP-43 binds to intron 20–21. The sequence shown is an example of a region in intron 20-21 that is frequently bound by TDP-43 (shown by mapped reads from ERR039843, ERR039845 and ERR039855).](/paper-figures/e09b8b1b7b414e2db64d4c2ce3b2a015/tdp-43-represses-cryptic-exon-inclusion-in-the-ftd-als-gene-unc13a-figure-5.jpg)


![Extended Data Fig. 4 Validation of additional splicing targets. (a–f) Depletion of TDP-43 introduces cryptic exons into KALRN mRNA and SYT7 mRNA; In RAPGEF6, TDP-43 depletion leads to a decrease in the usage of the exon AE (for alternative exon) between exon 21 and exon 22 of the isoform ENST0000509018.6. Exon AE does exist in some other isoforms of RAPGEF6, indicating the depletion of TDP-43 could lead to changes in isoform composition. (b, d, f) Violin plots corresponding to (a, c, e), respectively. Each violin in (b, d, f) represents the posterior probability distribution of the expected relative inclusion (PSI or Ψ) for the color matching junction in the splice graph. The tails of each violin represent the 10th and 90th percentile. The box represents the interquartile range with the line in the middle indicating the median. The white circles mark the expected PSI (E[Ψ]). The change in the relative inclusion level of each junction between two conditions is referred to as ΔΨ or ΔPSI13. (g–i) RT-qPCR analyses confirmed changes in exon usage upon TDP-43 depletion in iPSC-derived neurons. RPLP0 and GAPDH were used to normalize RT-PCR. (n = 3 independent cell culture experiments for each condition, two sided-Welch Two Sample t-test, mean ± s.e.m.). Source data](/paper-figures/6512f554878642428e6dace0f98cf27b/tdp-43-represses-cryptic-exon-inclusion-in-the-ftd-als-gene-unc13a-figure-8.jpg)






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“The most common genes identified in clinical practice include SOD1, C9ORF72, TARDBP, FUS, and OPTNTD-P43 (55–57, 73, 74).”
From Modulation of the gut–brain axis via the gut microbiota: a new era in treatment of amyotrophic lateral sclerosis (2023) · cites this paper as [73]
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Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247
Self-citationTHE GENETICS OF CAENORHABDITIS ELEGANS
Brenner, S. (1974) · Genetics · doi:10.1093/genetics/77.1.71 · Cited by 15,220
The Human Genome Browser at UCSC
Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M., & Haussler, A. D. (2002) · Genome Research · doi:10.1101/gr.229102 · Cited by 10,400
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
LocusZoom: regional visualization of genome-wide association scan results
Pruim, R. J., Welch, R. P., Sanna, S., Teslovich, T. M., Chines, P. S., Gliedt, T. P., Boehnke, M., Abecasis, G. R., & Willer, C. J. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq419 · Cited by 2,707
Limbic-predominant age-related TDP-43 encephalopathy (LATE): consensus working group report
Nelson, P. T., Dickson, D. W., Trojanowski, J. Q., Jack, C. R., Boyle, P. A., Arfanakis, K., Rademakers, R., Alafuzoff, I., Attems, J., Brayne, C., et al. (2019) · Brain · doi:10.1093/brain/awz099 · Cited by 1,547
Self-citationLong pre-mRNA depletion and RNA missplicing contribute to neuronal vulnerability from loss of TDP-43
Polymenidou, M., Lagier-Tourenne, C., Hutt, K. R., Huelga, S. C., Moran, J., Liang, T. Y., Ling, S.-C., Sun, E., Wancewicz, E., Mazur, C., et al. (2011) · Nature Neuroscience · doi:10.1038/nn.2779 · Cited by 1,335
Characterizing the RNA targets and position-dependent splicing regulation by TDP-43
Tollervey, J. R., Curk, T., Rogelj, B., Briese, M., Cereda, M., Kayikci, M., König, J., Hortobágyi, T., Nishimura, A. L., Župunski, V., et al. (2011) · Nature Neuroscience · doi:10.1038/nn.2778 · Cited by 1,165
TDP-43 and FUS/TLS: emerging roles in RNA processing and neurodegeneration
Lagier-Tourenne, C., Polymenidou, M., & Cleveland, D. W. (2010) · Human Molecular Genetics · doi:10.1093/hmg/ddq137 · Cited by 1,021
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Self-citationBye, C. R., Qian, E. L., Lim, K., Daniszewski, M., Garton, F. C., Trần-Lê, B. C., Liang, H. H., Lin, T., Lock, J. G., Crombie, D. E., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-02118-7 · Cited by 24
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Self-citationWoodburn, B. M. D., Kanchi, K., Zhou, S., Colaianni, N. R., Joseph, S., & Swanstrom, R. I. (2022) · Journal of Virology · doi:10.1128/jvi.00957-22 · Cited by 23
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Cao, M. C., Ryan, B., Wu, J., Curtis, M. A., Faull, R. L. M., Dragunow, M., & Scotter, E. L. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106245 · Cited by 23
Grima, N., Liu, S., Southwood, D., Henden, L., Smith, A., Lee, A., Rowe, D. B., D’Silva, S., Blair, I. P., & Williams, K. L. (2023) · Neuropathology and Applied Neurobiology · doi:10.1111/nan.12943 · Cited by 25
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Cao, M. C., & Scotter, E. L. (2022) · Disease Models & Mechanisms · doi:10.1242/dmm.049418 · Cited by 25
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Su, W., Gu, X., Duan, Q., Jiang, Z., Gao, X., Shang, H., & Chen, Y. (2022) · BMC Medicine · doi:10.1186/s12916-022-02411-3 · Cited by 27
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McKeever, P. M., Sababi, A. M., Sharma, R., Xu, Z., Xiao, S., McGoldrick, P., Ketela, T., Sato, C., Moreno, D., Visanji, N. P., et al. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.101007 · Cited by 21
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Ran, X., Wang, M., Huang, J., Kuang, N., Tian, P., Wu, J., Feng, F., Luo, Y., & Huang, N. (2026) · Ageing Research Reviews · doi:10.1016/j.arr.2026.103133 · Cited by 24
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Cabrera-Rodríguez, R., Pérez-Yanes, S., González‐Montelongo, R., Lorenzo-Salazar, J. M., Estévez‐Herrera, J., García-Luis, J., Íñigo-Campos, A., Rubio‐Rodríguez, L. A., Muñoz‐Barrera, A., Trujillo‐González, R., et al. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23116180 · Cited by 18
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Nakamura, R., Tohnai, G., Nakatochi, M., Atsuta, N., Watanabe, H., Ito, D., Katsuno, M., Hirakawa, A., Izumi, Y., Morita, M., et al. (2023) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2022-330851 · Cited by 17
Zhang, X., Das, T., Chao, T. F., Trinh, V., Carmen‐Orozco, R. P., Ling, J. P., Kaláb, P., & Hayes, L. R. (2024) · iScience · doi:10.1016/j.isci.2024.110109 · Cited by 20
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Yen, Y.-P., Lung, T.-H., Liau, E. S., Wu, C., Huang, G., Hsu, F.-Y., Chang, M., Yang, Z.-D., Huang, C.-Y., Zheng, Z., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-59117-2 · Cited by 16
Devoy, A., Price, G., Giorgio, F. D., Bunton-Stasyshyn, R. K. A., Thompson, D., Gasco, S., Allan, A. J., Codner, G. F., Nair, R., Tibbit, C., et al. (2021) · iScience · doi:10.1016/j.isci.2021.103463 · Cited by 18
Sánchez‐Tejerina, D., Llauradó, A., Sotoca, J., López‐Diego, V., Vidal-Taboada, J. M., Salvadó, M., & Morales, R. J. (2023) · Cells · doi:10.3390/cells12081180 · Cited by 16
RNA-binding deficient TDP-43 drives cognitive decline in a mouse model of TDP-43 proteinopathy
Necarsulmer, J., Simon, J. M., Evangelista, B., Chen, Y., Tian, X., Nafees, S., Gonzalez, A. M., Jiang, H., Wang, P., Ajit, D., et al. (2023) · eLife · doi:10.7554/elife.85921 · Cited by 32
Chiò, A., Moglia, C., Canosa, A., Manera, U., Grassano, M., Vasta, R., Palumbo, F., Gallone, S., Brunetti, M., Barberis, M., et al. (2023) · Neurology · doi:10.1212/wnl.0000000000207367 · Cited by 16
Pfaff, A. L., Bubb, V. J., Quinn, J. P., & Kõks, S. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241411548 · Cited by 17
Zibold, J., Lessard, L., Picard, F., da Silva, L. A. G., Zadorozhna, Y., Streichenberger, N., Belotti, E., Osseni, A., Emerit, A., Errazuriz-Cerda, E., et al. (2023) · Brain · doi:10.1093/brain/awad410 · Cited by 16
Koike, Y. M. (2024) · Neuroscience Research · doi:10.1016/j.neures.2024.05.001 · Cited by 17
Self-citationRothstein, J. D., Warlick, C., & Coyne, A. N. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.12.571299 · Cited by 19
Cui, Y., Arnold, F. J., Li, J. S., Wu, J., Wang, D., Philippe, J., Colwin, M. R., Michels, S., Chen, C., Sallam, T., et al. (2025) · Nature Genetics · doi:10.1038/s41588-024-02057-2 · Cited by 15
Efficient Gene Expression in Human Stem Cell Derived-Cortical Organoids Using Adeno Associated Virus
Cho, A., Bright, F., Morey, N., Au, C. G., Ittner, L. M., & Ke, Y. D. (2022) · Cells · doi:10.3390/cells11203194 · Cited by 17
Chen, K., Gao, T., Liu, Y., Zhu, K., Wang, T., & Zeng, P. (2024) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.09.017 · Cited by 15
Role of the UNC13 family in human diseases: A literature review
Ansari, U., Chen, V., Sedighi, R., Syed, B., Muttalib, Z., Ansari, K., Ansari, F., Nadora, D., Razick, D., & Lui, F. (2023) · AIMS neuroscience · doi:10.3934/neuroscience.2023029 · Cited by 18
MATR3 pathogenic variants differentially impair its cryptic splicing repression function
Khan, M., Chen, X. X., Dias, M., Santos, J. R., Kour, S., You, J., van Bruggen, R., Youssef, M., Wan, Y., Liu, Z., et al. (2024) · FEBS Letters · doi:10.1002/1873-3468.14806 · Cited by 14
Cheng, F., Chapman, T. R., Zhang, S., Morsch, M., Chung, R. S., Lee, A., & Rayner, S. L. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102246 · Cited by 16
Keeley, O., & Coyne, A. N. (2024) · Nucleus · doi:10.1080/19491034.2024.2349085 · Cited by 16
Ko, Y., Lokareddy, R. K., Doll, S. G., Yeggoni, D. P., Girdhar, A., Mawn, I., Klim, J. R., Rizvi, N. F., Meyers, R. E., Gillilan, R. E., et al. (2024) · Journal of Molecular Biology · doi:10.1016/j.jmb.2024.168751 · Cited by 16
Dang, M., Wu, L., & Zhang, X. (2025) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2025.141677 · Cited by 16
Gao, J., Ding, M., Qin, S., Shukla, D., Vicuna, L., Liang, J., & Wang, X. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03089-8 · Cited by 15
Bera, M., Grushin, K. S., Sundaram, R. V. K., Hinzen, J. S., Chen, J., Chatterjee, A., Radhakrishnan, A., Lee, S., Padmanarayana, M., Coleman, J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-62420-7 · Cited by 15
Targeting RTN4/NoGo-Receptor reduces levels of ALS protein ataxin-2
Rodriguez, C. M., Bechek, S. C., Jones, G. L., Nakayama, L., Akiyama, T., Kım, G., Solow-Cordero, D. E., Strittmatter, S. M., & Gitler, A. D. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111505 · Cited by 15
Self-citationMora, S., Stuckert, A., Friis, R. V. H., Pietersz, K. L., Noes‐Holt, G., Montañana-Rosell, R., Wang, H., Sørensen, A. T., Selvan, R., Verhaagen, J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48925-7 · Cited by 14
MBNL‐dependent impaired development within the neuromuscular system in myotonic dystrophy type 1
Tahraoui‐Bories, J., Mérien, A., González‐Barriga, A., Lainé, J., Leteur, C., Polvèche, H., Carteron, A., de Lamotte, J. D., Nicoleau, C., Polentes, J., et al. (2022) · Neuropathology and Applied Neurobiology · doi:10.1111/nan.12876 · Cited by 14
Ashok, C., Kimble, A. L., Tyburski, J. D., Leclair, N. K., Zuberi, A. R., Murphy, M., Jellison, E. R., Reese, B., Hu, X., Lutz, C. M., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.13.571184 · Cited by 13
Arnold, F. J., Cui, Y., Michels, S., Colwin, M. R., Stockford, C. M., Ye, W., Tam, O. H., Menon, S., Situ, W. G., Ehsani, K. C. K., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.22.576709 · Cited by 14
Faravelli, I., Rinchetti, P., Tambalo, M., Simutin, I., Mapelli, L., Mancinelli, S., Miotto, M., Rizzuti, M., D’Angelo, A., Cordiglieri, C., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-67725-1 · Cited by 14
Hu, Y., Hruscha, A., Pan, C., Schifferer, M., Schmidt, M. K., Nuscher, B., Giera, M. A., Kostidis, S., Burhan, Ö. P., van Bebber, F., et al. (2024) · Molecular Neurodegeneration · doi:10.1186/s13024-024-00735-7 · Cited by 16
Dykstra, M. M., Weskamp, K., Gómez, N., Waksmacki, J., Tank, E. M. H., Glineburg, M. R., Snyder, A. G., Pinarbasi, E. S., Bekier, M. E., Li, X., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2024.115113 · Cited by 19
TDP‐43 Cryptic RNAs in Perry Syndrome: Differences across Brain Regions and TDP‐43 Proteinopathies
Pickles, S. R., Bejarano, J. G., Narayan, A., Daughrity, L. M., Cidfuentes, C. M., Reeves, M. M., Yue, M., Otero, P. C., Ayuso, V. E., Dunmore, J. H., et al. (2025) · Movement Disorders · doi:10.1002/mds.30104 · Cited by 14
Self-citationDrug repurposing in amyotrophic lateral sclerosis (ALS)
Carroll, E., Scaber, J., Huber, K., Brennan, P. E., Thompson, A. G., Turner, M. R., & Talbot, K. (2025) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2025.2474661 · Cited by 14
Pathogenic TDP-43 in amyotrophic lateral sclerosis
Chong, Z. Z., & Souayah, N. (2025) · Drug Discovery Today · doi:10.1016/j.drudis.2025.104351 · Cited by 13
Manini, A., Casiraghi, V., Brusati, A., Maranzano, A., Gentile, F., Colombo, E., Bonetti, R., Peverelli, S., Invernizzi, S., Gentilini, D., et al. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1067954 · Cited by 13
Loss of amyotrophic lateral sclerosis risk factor SCFD1 causes motor dysfunction in Drosophila
Borg, R. M., Purkiss, A., Cacciottolo, R., Herrera, P., & Cauchi, R. J. (2023) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.02.005 · Cited by 13
Nguyen, T. B., Miramontes, R., Chillon-Marinas, C., Maimon, R., Vazquez-Sanchez, S., Lau, A. L., McClure, N. R., England, W. E., Singha, M., Stocksdale, J. T., et al. (2023) · doi:10.1101/2023.10.31.565004 · Cited by 15
Kawakami, Y., Iguchi, Y., Li, J., Amakusa, Y., Yoshimura, T., Chikuchi, R., Yokoi, S., Iida, M., Riku, Y., Iwasaki, Y., et al. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf261 · Cited by 12
Guo, C., Chen, K., Vatsavayai, S. C., Akiyama, T., Liu, C., Zeng, Y., Sianto, O., Yang, E., Bombosch, J., Powell, R., et al. (2026) · Science Translational Medicine · doi:10.1126/scitranslmed.aeb8517 · Cited by 13
Self-citationRavits, J., Ferrey, D., Gündoğdu, B., Qayoumi, W., & Zale, C. (2026) · JAMA · doi:10.1001/jama.2026.6385 · Cited by 15
HnRNP Pathologies in Frontotemporal Lobar Degeneration
Jiang, X., Gatt, A. P., & Lashley, T. (2023) · Cells · doi:10.3390/cells12121633 · Cited by 13
Piccolo, L. L., Umegawachi, T., Yeewa, R., Potikanond, S., Nimlamool, W., Prachayasittikul, V., Gotoh, Y., Yoshida, H., Yamaguchi, M., & Jantrapirom, S. (2023) · Neurotherapeutics · doi:10.1007/s13311-023-01406-z · Cited by 12
HIV-1 Vpu induces neurotoxicity by promoting Caspase 3-dependent cleavage of TDP-43
Yang, J., Li, Y., Li, H., Zhang, H., Guo, H., Zheng, X., Yu, X., & Wei, W. (2024) · EMBO Reports · doi:10.1038/s44319-024-00238-y · Cited by 12
Metadata
- Authors
- Ma, X. R., Prudencio, M., Koike, Y., Vatsavayai, S. C., Kim, G., Harbinski, F., Briner, A., Rodriguez, C. M., Guo, C., Akiyama, T., Schmidt, H. B., Cummings, B. B., Wyatt, D. W., Kurylo, K., Miller, G., Mekhoubad, S., Sallee, N., Mekonnen, G., Ganser, L., Rubien, J. D., Jansen-West, K., Cook, C. N., Pickles, S., Oskarsson, B., Graff-Radford, N. R., Boeve, B. F., Knopman, D. S., Petersen, R. C., Dickson, D. W., Shorter, J., Myong, S., Green, E. M., Seeley, W. W., Petrucelli, L., & Gitler, A. D.
- Affiliations
- Stanford Medicine (US)
- Mayo Clinic (US)
- University of California, San Francisco (US)
- Maze (United States) (US)
- The University of Queensland (AU)
- Johns Hopkins University (US)
- University of Pennsylvania (US)
- Mayo Clinic in Florida (US)
- Corresponding author
- Petrucelli, Leonard
- Gitler, Aaron D.
- ORCID
- Ma, X. Rosa
- Prudencio, Mercedes
- Koike, Yuka
- Vatsavayai, Sarat C.
- Kim, Garam
- Briner, Adam
- Rodriguez, Caitlin M.
- Guo, Caiwei
- Akiyama, Tetsuya
- Schmidt, H. Broder
- Cummings, Beryl B.
- Wyatt, David W.
- Kurylo, Katherine
- Miller, Georgiana
- Ganser, Laura
- Rubien, Jack D.
- Cook, Casey N.
- Pickles, Sarah
- Oskarsson, Björn
- Boeve, Bradley F.
- Knopman, David S.
- Petersen, Ronald C.
- Dickson, Dennis W.
- Shorter, James
- Myong, Sua
- Green, Eric M.
- Seeley, William W.
- Petrucelli, Leonard
- Gitler, Aaron D.
- Venue
- Nature
- Published
- 2022-02-23
- Volume
- 603
- Issue
- 7899
- Pages
- 124-130
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC8891019
- OpenAlex
- W4213441627
- Cited by
- 574
- References
- 53
- Citations by year
- 2026: 126 · 2025: 151 · 2024: 121 · 2023: 107 · 2022: 57
- FWCI
- 57.66
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- ALS Association
- BrightFocus Foundation (A2020279F)
- Takeda Science Foundation
- Johns Hopkins University
- Target ALS
- Rainwater Charitable Foundation
- National Institutes of Health (W81XWH)
- University of California, San Francisco (P30AG062422, P01AG019724)
- Wu Tsai Neurosciences Institute, Stanford University
- Stanford Research Computing Center, Stanford University
- National Institute on Aging (RF1AG064690, R01AG063780, U01AG057195, U01AG006786, RF1AG071326, T32AG047126, U19AG063911, P01AG019724, P30AG062422, P30AG062677)
- National Human Genome Research Institute (T32HG000044)
- National Institute of General Medical Sciences (F32GM139268, T32GM007231)
- National Institute of Neurological Disorders and Stroke (F32NS116208, P01NS084974, R01NS104437, RF1NS120992, RF1NS113636, R35NS097273, R35NS097263, U54NS123743)
- Robert Packard Center for ALS Research, Johns Hopkins University
- Topics
- Health Sciences › Medicine › Clinical Neurology › Amyotrophic Lateral Sclerosis Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Keywords
- TDP-43, UNC13A, RNA splicing, amyotrophic lateral sclerosis, frontotemporal dementia, single nucleotide polymorphisms, genetic risk factors, RNA-binding proteins, motor neurons, intronic variants, induced pluripotent stem cells
- MeSH terms
- Amyotrophic Lateral Sclerosis, DNA-Binding Proteins, Exons, Humans, Motor Neurons, Nerve Tissue Proteins, Genome-Wide Association Study, Frontotemporal Dementia
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