IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-36282-w.html
   My bibliography  Save this article

Genome-wide host-pathogen analyses reveal genetic interaction points in tuberculosis disease

Author

Listed:
  • Jody Phelan

    (London School of Hygiene and Tropical Medicine)

  • Paula Josefina Gomez-Gonzalez

    (London School of Hygiene and Tropical Medicine)

  • Nuria Andreu

    (London School of Hygiene and Tropical Medicine)

  • Yosuke Omae

    (The University of Tokyo)

  • Licht Toyo-Oka

    (The University of Tokyo)

  • Hideki Yanai

    (Japan Anti-Tuberculosis Association)

  • Reiko Miyahara

    (National Center for Global Health and Medicine)

  • Supalert Nedsuwan

    (Chiangrai Prachanukroh Hospital)

  • Paola Florez Sessions

    (Genome Institute of Singapore)

  • Susana Campino

    (London School of Hygiene and Tropical Medicine)

  • Neneh Sallah

    (London School of Hygiene and Tropical Medicine)

  • Julian Parkhill

    (University of Cambridge)

  • Nat Smittipat

    (National Science and Technology Development Agency)

  • Prasit Palittapongarnpim

    (National Science and Technology Development Agency)

  • Taisei Mushiroda

    (RIKEN Center for Integrative Medical Sciences)

  • Michiaki Kubo

    (RIKEN Center for Integrative Medical Sciences)

  • Katsushi Tokunaga

    (The University of Tokyo)

  • Surakameth Mahasirimongkol

    (Ministry of Public Health)

  • Martin L. Hibberd

    (London School of Hygiene and Tropical Medicine)

  • Taane G. Clark

    (London School of Hygiene and Tropical Medicine
    London School of Hygiene & Tropical Medicine)

Abstract

The genetics underlying tuberculosis (TB) pathophysiology are poorly understood. Human genome-wide association studies have failed so far to reveal reproducible susceptibility loci, attributed in part to the influence of the underlying Mycobacterium tuberculosis (Mtb) bacterial genotype on the outcome of the infection. Several studies have found associations of human genetic polymorphisms with Mtb phylo-lineages, but studies analysing genome-genome interactions are needed. By implementing a phylogenetic tree-based Mtb-to-human analysis for 714 TB patients from Thailand, we identify eight putative genetic interaction points (P

Suggested Citation

  • Jody Phelan & Paula Josefina Gomez-Gonzalez & Nuria Andreu & Yosuke Omae & Licht Toyo-Oka & Hideki Yanai & Reiko Miyahara & Supalert Nedsuwan & Paola Florez Sessions & Susana Campino & Neneh Sallah & , 2023. "Genome-wide host-pathogen analyses reveal genetic interaction points in tuberculosis disease," Nature Communications, Nature, vol. 14(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-36282-w
    DOI: 10.1038/s41467-023-36282-w
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-36282-w
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-36282-w?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. Francesc Coll & Ruth McNerney & José Afonso Guerra-Assunção & Judith R. Glynn & João Perdigão & Miguel Viveiros & Isabel Portugal & Arnab Pain & Nigel Martin & Taane G. Clark, 2014. "A robust SNP barcode for typing Mycobacterium tuberculosis complex strains," Nature Communications, Nature, vol. 5(1), pages 1-5, December.
    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. Anna G. Green & Chang Ho Yoon & Michael L. Chen & Yasha Ektefaie & Mack Fina & Luca Freschi & Matthias I. Gröschel & Isaac Kohane & Andrew Beam & Maha Farhat, 2022. "A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Arianne Lovey & Sheetal Verma & Vaishnavi Kaipilyawar & Rodrigo Ribeiro-Rodrigues & Seema Husain & Moises Palaci & Reynaldo Dietze & Shuyi Ma & Robert D. Morrison & David. R. Sherman & Jerrold J. Elln, 2022. "Early alveolar macrophage response and IL-1R-dependent T cell priming determine transmissibility of Mycobacterium tuberculosis strains," Nature Communications, Nature, vol. 13(1), pages 1-12, 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_s41467-023-36282-w. 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.