eprintid: 10129734
rev_number: 22
eprint_status: archive
userid: 608
dir: disk0/10/12/97/34
datestamp: 2021-06-17 11:52:25
lastmod: 2021-12-06 23:32:56
status_changed: 2021-06-17 11:52:25
type: article
metadata_visibility: show
creators_name: Mejia Maza, A
creators_name: Jarvis, S
creators_name: Lee, WC
creators_name: Cunningham, TJ
creators_name: Schiavo, G
creators_name: Secrier, M
creators_name: Fratta, P
creators_name: Sleigh, JN
creators_name: Fisher, EMC
creators_name: Sudre, CH
title: NMJ-Analyser identifies subtle early changes in mouse models of neuromuscular disease
ispublished: pub
divisions: UCL
divisions: B02
divisions: C07
divisions: D07
divisions: F85
divisions: C08
divisions: D09
divisions: F99
divisions: D14
divisions: GA3
divisions: G17
keywords: Amyotrophic lateral sclerosis, Diseases of the nervous system, Neuromuscular junction, Peripheral nervous system
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abstract: The neuromuscular junction (NMJ) is the peripheral synapse formed between a motor neuron axon terminal and a muscle fibre. NMJs are thought to be the primary site of peripheral pathology in many neuromuscular diseases, but innervation/denervation status is often assessed qualitatively with poor systematic criteria across studies, and separately from 3D morphological structure. Here, we describe the development of 'NMJ-Analyser', to comprehensively screen the morphology of NMJs and their corresponding innervation status automatically. NMJ-Analyser generates 29 biologically relevant features to quantitatively define healthy and aberrant neuromuscular synapses and applies machine learning to diagnose NMJ degeneration. We validated this framework in longitudinal analyses of wildtype mice, as well as in four different neuromuscular disease models: three for amyotrophic lateral sclerosis (ALS) and one for peripheral neuropathy. We showed that structural changes at the NMJ initially occur in the nerve terminal of mutant TDP43 and FUS ALS models. Using a machine learning algorithm, healthy and aberrant neuromuscular synapses are identified with 95% accuracy, with 88% sensitivity and 97% specificity. Our results validate NMJ-Analyser as a robust platform for systematic and structural screening of NMJs, and pave the way for transferrable, and cross-comparison and high-throughput studies in neuromuscular diseases.
date: 2021-06-10
date_type: published
official_url: https://doi.org/10.1038/s41598-021-91094-6
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1870809
doi: 10.1038/s41598-021-91094-6
pii: 10.1038/s41598-021-91094-6
lyricists_name: Fisher, Elizabeth
lyricists_name: Fratta, Pietro
lyricists_name: Lee, Weaverly Colleen Co
lyricists_name: Schiavo, Giampietro
lyricists_name: Secrier, Maria
lyricists_name: Sleigh, James
lyricists_name: Sudre, Carole
lyricists_id: EMCFI97
lyricists_id: PFRAT57
lyricists_id: WCCLE97
lyricists_id: GSCHI71
lyricists_id: MSECR66
lyricists_id: JSLEI96
lyricists_id: SUDRE45
actors_name: Barczynska, Patrycja
actors_id: PBARC91
actors_role: owner
full_text_status: public
publication: Scientific Reports
volume: 11
number: 1
article_number: 12251
event_location: England
citation:        Mejia Maza, A;    Jarvis, S;    Lee, WC;    Cunningham, TJ;    Schiavo, G;    Secrier, M;    Fratta, P;             ... Sudre, CH; + view all <#>        Mejia Maza, A;  Jarvis, S;  Lee, WC;  Cunningham, TJ;  Schiavo, G;  Secrier, M;  Fratta, P;  Sleigh, JN;  Fisher, EMC;  Sudre, CH;   - view fewer <#>    (2021)    NMJ-Analyser identifies subtle early changes in mouse models of neuromuscular disease.                   Scientific Reports , 11  (1)    , Article 12251.  10.1038/s41598-021-91094-6 <https://doi.org/10.1038/s41598-021-91094-6>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10129734/1/Schiavo_s41598-021-91094-6.pdf