IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-37630-6.html
   My bibliography  Save this article

Integrated transcriptome landscape of ALS identifies genome instability linked to TDP-43 pathology

Author

Listed:
  • Oliver J. Ziff

    (The Francis Crick Institute
    University College London
    University College London NHS Foundation Trust)

  • Jacob Neeves

    (The Francis Crick Institute
    University College London)

  • Jamie Mitchell

    (The Francis Crick Institute
    University College London)

  • Giulia Tyzack

    (The Francis Crick Institute
    University College London)

  • Carlos Martinez-Ruiz

    (University College London Cancer Institute)

  • Raphaelle Luisier

    (Genomics and Health Informatics Group, Idiap Research Institute)

  • Anob M. Chakrabarti

    (The Francis Crick Institute)

  • Nicholas McGranahan

    (University College London Cancer Institute)

  • Kevin Litchfield

    (University College London Cancer Institute)

  • Simon J. Boulton

    (The Francis Crick Institute)

  • Ammar Al-Chalabi

    (Psychology and Neuroscience, King’s College London)

  • Gavin Kelly

    (The Francis Crick Institute)

  • Jack Humphrey

    (Icahn School of Medicine at Mount Sinai)

  • Rickie Patani

    (The Francis Crick Institute
    University College London
    University College London NHS Foundation Trust)

Abstract

Amyotrophic Lateral Sclerosis (ALS) causes motor neuron degeneration, with 97% of cases exhibiting TDP-43 proteinopathy. Elucidating pathomechanisms has been hampered by disease heterogeneity and difficulties accessing motor neurons. Human induced pluripotent stem cell-derived motor neurons (iPSMNs) offer a solution; however, studies have typically been limited to underpowered cohorts. Here, we present a comprehensive compendium of 429 iPSMNs from 15 datasets, and 271 post-mortem spinal cord samples. Using reproducible bioinformatic workflows, we identify robust upregulation of p53 signalling in ALS in both iPSMNs and post-mortem spinal cord. p53 activation is greatest with C9orf72 repeat expansions but is weakest with SOD1 and FUS mutations. TDP-43 depletion potentiates p53 activation in both post-mortem neuronal nuclei and cell culture, thereby functionally linking p53 activation with TDP-43 depletion. ALS iPSMNs and post-mortem tissue display enrichment of splicing alterations, somatic mutations, and gene fusions, possibly contributing to the DNA damage response.

Suggested Citation

  • Oliver J. Ziff & Jacob Neeves & Jamie Mitchell & Giulia Tyzack & Carlos Martinez-Ruiz & Raphaelle Luisier & Anob M. Chakrabarti & Nicholas McGranahan & Kevin Litchfield & Simon J. Boulton & Ammar Al-C, 2023. "Integrated transcriptome landscape of ALS identifies genome instability linked to TDP-43 pathology," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37630-6
    DOI: 10.1038/s41467-023-37630-6
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-37630-6
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-37630-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Smyth Gordon K, 2004. "Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-28, February.
    2. Michael Schubert & Bertram Klinger & Martina Klünemann & Anja Sieber & Florian Uhlitz & Sascha Sauer & Mathew J. Garnett & Nils Blüthgen & Julio Saez-Rodriguez, 2018. "Perturbation-response genes reveal signaling footprints in cancer gene expression," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
    3. Katannya Kapeli & Gabriel A. Pratt & Anthony Q. Vu & Kasey R. Hutt & Fernando J. Martinez & Balaji Sundararaman & Ranjan Batra & Peter Freese & Nicole J. Lambert & Stephanie C. Huelga & Seung J. Chun , 2016. "Distinct and shared functions of ALS-associated proteins TDP-43, FUS and TAF15 revealed by multisystem analyses," Nature Communications, Nature, vol. 7(1), pages 1-14, November.
    4. Barry Slaff & Caleb M. Radens & Paul Jewell & Anupama Jha & Nicholas F. Lahens & Gregory R. Grant & Andrei Thomas-Tikhonenko & Kristen W. Lynch & Yoseph Barash, 2021. "MOCCASIN: a method for correcting for known and unknown confounders in RNA splicing analysis," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    5. Anna-Leigh Brown & Oscar G. Wilkins & Matthew J. Keuss & Sarah E. Hill & Matteo Zanovello & Weaverly Colleen Lee & Alexander Bampton & Flora C. Y. Lee & Laura Masino & Yue A. Qi & Sam Bryce-Smith & Ar, 2022. "TDP-43 loss and ALS-risk SNPs drive mis-splicing and depletion of UNC13A," Nature, Nature, vol. 603(7899), pages 131-137, March.
    6. Athurva Gore & Zhe Li & Ho-Lim Fung & Jessica E. Young & Suneet Agarwal & Jessica Antosiewicz-Bourget & Isabel Canto & Alessandra Giorgetti & Mason A. Israel & Evangelos Kiskinis & Je-Hyuk Lee & Yuin-, 2011. "Somatic coding mutations in human induced pluripotent stem cells," Nature, Nature, vol. 471(7336), pages 63-67, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aaron C Ericsson & J Wade Davis & William Spollen & Nathan Bivens & Scott Givan & Catherine E Hagan & Mark McIntosh & Craig L Franklin, 2015. "Effects of Vendor and Genetic Background on the Composition of the Fecal Microbiota of Inbred Mice," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-19, February.
    2. Hossain, Ahmed & Beyene, Joseph & Willan, Andrew R. & Hu, Pingzhao, 2009. "A flexible approximate likelihood ratio test for detecting differential expression in microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3685-3695, August.
    3. Xiaohong Li & Guy N Brock & Eric C Rouchka & Nigel G F Cooper & Dongfeng Wu & Timothy E O’Toole & Ryan S Gill & Abdallah M Eteleeb & Liz O’Brien & Shesh N Rai, 2017. "A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-22, May.
    4. Kerr Kathleen F., 2012. "Optimality Criteria for the Design of 2-Color Microarray Studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(1), pages 1-9, January.
    5. Ambroise Jérôme & Bearzatto Bertrand & Robert Annie & Macq Benoit & Gala Jean-Luc, 2012. "Combining Multiple Laser Scans of Spotted Microarrays by Means of a Two-Way ANOVA Model," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-20, February.
    6. J. McClatchy & R. Strogantsev & E. Wolfe & H. Y. Lin & M. Mohammadhosseini & B. A. Davis & C. Eden & D. Goldman & W. H. Fleming & P. Conley & G. Wu & L. Cimmino & H. Mohammed & A. Agarwal, 2023. "Clonal hematopoiesis related TET2 loss-of-function impedes IL1β-mediated epigenetic reprogramming in hematopoietic stem and progenitor cells," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    7. Alexandra Gyurdieva & Stefan Zajic & Ya-Fang Chang & E. Andres Houseman & Shan Zhong & Jaegil Kim & Michael Nathenson & Thomas Faitg & Mary Woessner & David C. Turner & Aisha N. Hasan & John Glod & Ro, 2022. "Biomarker correlates with response to NY-ESO-1 TCR T cells in patients with synovial sarcoma," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    8. Sora Yoon & Seon-Young Kim & Dougu Nam, 2016. "Improving Gene-Set Enrichment Analysis of RNA-Seq Data with Small Replicates," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-16, November.
    9. Yu Lianbo & Gulati Parul & Fernandez Soledad & Pennell Michael & Kirschner Lawrence & Jarjoura David, 2011. "Fully Moderated T-statistic for Small Sample Size Gene Expression Arrays," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-22, September.
    10. Chaofeng Yuan & Wensheng Zhu & Xuming He & Jianhua Guo, 2019. "A mixture factor model with applications to microarray data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 60-76, March.
    11. Nan Li & Matthew N. McCall & Zhijin Wu, 2017. "Establishing Informative Prior for Gene Expression Variance from Public Databases," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 160-177, June.
    12. Brian Caffo & Liu Dongmei & Giovanni Parmigiani, 2004. "Power Conjugate Multilevel Models with Applications to Genomics," Johns Hopkins University Dept. of Biostatistics Working Paper Series 1062, Berkeley Electronic Press.
    13. Nott, David J. & Yu, Zeming & Chan, Eva & Cotsapas, Chris & Cowley, Mark J. & Pulvers, Jeremy & Williams, Rohan & Little, Peter, 2007. "Hierarchical Bayes variable selection and microarray experiments," Journal of Multivariate Analysis, Elsevier, vol. 98(4), pages 852-872, April.
    14. Adrian B. Levine & Liana Nobre & Anirban Das & Scott Milos & Vanessa Bianchi & Monique Johnson & Nicholas R. Fernandez & Lucie Stengs & Scott Ryall & Michelle Ku & Mansuba Rana & Benjamin Laxer & Java, 2024. "Immuno-oncologic profiling of pediatric brain tumors reveals major clinical significance of the tumor immune microenvironment," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    15. Santu Ghosh & Alan M. Polansky, 2022. "Large-Scale Simultaneous Testing Using Kernel Density Estimation," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 808-843, August.
    16. Qianxing Mo & Faming Liang, 2010. "Bayesian Modeling of ChIP-chip Data Through a High-Order Ising Model," Biometrics, The International Biometric Society, vol. 66(4), pages 1284-1294, December.
    17. Ahmed Hossain & Hafiz T.A. Khan, 2016. "Identification of genomic markers correlated with sensitivity in solid tumors to Dasatinib using sparse principal components," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(14), pages 2538-2549, October.
    18. Alexander Kaever & Manuel Landesfeind & Kirstin Feussner & Burkhard Morgenstern & Ivo Feussner & Peter Meinicke, 2014. "Meta-Analysis of Pathway Enrichment: Combining Independent and Dependent Omics Data Sets," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-12, February.
    19. Erick Armingol & Hratch M. Baghdassarian & Cameron Martino & Araceli Perez-Lopez & Caitlin Aamodt & Rob Knight & Nathan E. Lewis, 2022. "Context-aware deconvolution of cell–cell communication with Tensor-cell2cell," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    20. Iqbal Mahmud & Guimei Tian & Jia Wang & Tarun E. Hutchinson & Brandon J. Kim & Nikee Awasthee & Seth Hale & Chengcheng Meng & Allison Moore & Liming Zhao & Jessica E. Lewis & Aaron Waddell & Shangtao , 2023. "DAXX drives de novo lipogenesis and contributes to tumorigenesis," Nature Communications, Nature, vol. 14(1), pages 1-20, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37630-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.