Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

A non-invasive digital biomarker for the detection of rest disturbances in the SOD1G93A mouse model of ALS

E. Golini, M. Rigamonti, View ORCID ProfileF. Iannello, C. De Rosa, F. Scavizzi, M. Raspa, View ORCID ProfileS. Mandillo
doi: https://doi.org/10.1101/2019.12.27.889246
E. Golini
1IBBC-CNR, CNR Campus International Development (EMMA-INFRAFRONTIER-IMPC), Monterotondo Scalo (Rome), Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
M. Rigamonti
2Tecniplast SpA, Buguggiate (VA), Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
F. Iannello
2Tecniplast SpA, Buguggiate (VA), Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for F. Iannello
  • For correspondence: fabio.iannello@tecniplast.it
C. De Rosa
1IBBC-CNR, CNR Campus International Development (EMMA-INFRAFRONTIER-IMPC), Monterotondo Scalo (Rome), Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
F. Scavizzi
1IBBC-CNR, CNR Campus International Development (EMMA-INFRAFRONTIER-IMPC), Monterotondo Scalo (Rome), Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
M. Raspa
1IBBC-CNR, CNR Campus International Development (EMMA-INFRAFRONTIER-IMPC), Monterotondo Scalo (Rome), Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
S. Mandillo
1IBBC-CNR, CNR Campus International Development (EMMA-INFRAFRONTIER-IMPC), Monterotondo Scalo (Rome), Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for S. Mandillo
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease that affects both central and peripheral nervous system, leading to the degeneration of motor neurons, which eventually results in muscle atrophy, paralysis and death. Sleep disturbances are common in patients with ALS, leading to even further deteriorated quality of life. Investigating methods to potentially assess sleep and rest disturbances in animal models of ALS is thus of crucial interest.

We used an automated home cage monitoring system (DVC®) to capture activity patterns that can potentially be associated with sleep and rest disturbances and thus to the progression of ALS in the SOD1G93A mouse model. DVC® enables non-intrusive 24/7 long term animal activity monitoring, which we assessed together with body weight decline and neuromuscular function deterioration measured by grid hanging and grip strength tests in male and female mice from 7 until 24 weeks of age.

We show that as the ALS progresses over time in SOD1G93A mice, activity patterns during day time start becoming irregular, with frequent activity bouts that are neither observed in control mice nor in SOD1G93A at a younger age. The increasing irregularities of activity patterns during day time are quantitatively captured by designing a novel digital biomarker, referred to as Rest Disturbance Index (RDI). We show that RDI is a robust measure capable of detecting rest/sleep-related disturbances during the disease progression earlier than conventional methods, such as the grid hanging test. Moreover RDI highly correlates with grid hanging and body weight decline, especially in males.

The non-intrusive long-term continuous monitoring of animal activity enabled by DVC® has been instrumental in discovering activity patterns potentially correlated with sleep and rest disturbances in the SOD1G93A mouse model of the ALS disease.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted December 27, 2019.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
A non-invasive digital biomarker for the detection of rest disturbances in the SOD1G93A mouse model of ALS
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
A non-invasive digital biomarker for the detection of rest disturbances in the SOD1G93A mouse model of ALS
E. Golini, M. Rigamonti, F. Iannello, C. De Rosa, F. Scavizzi, M. Raspa, S. Mandillo
bioRxiv 2019.12.27.889246; doi: https://doi.org/10.1101/2019.12.27.889246
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
A non-invasive digital biomarker for the detection of rest disturbances in the SOD1G93A mouse model of ALS
E. Golini, M. Rigamonti, F. Iannello, C. De Rosa, F. Scavizzi, M. Raspa, S. Mandillo
bioRxiv 2019.12.27.889246; doi: https://doi.org/10.1101/2019.12.27.889246

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (4382)
  • Biochemistry (9594)
  • Bioengineering (7091)
  • Bioinformatics (24861)
  • Biophysics (12615)
  • Cancer Biology (9956)
  • Cell Biology (14354)
  • Clinical Trials (138)
  • Developmental Biology (7948)
  • Ecology (12105)
  • Epidemiology (2067)
  • Evolutionary Biology (15988)
  • Genetics (10925)
  • Genomics (14739)
  • Immunology (9869)
  • Microbiology (23670)
  • Molecular Biology (9484)
  • Neuroscience (50866)
  • Paleontology (369)
  • Pathology (1539)
  • Pharmacology and Toxicology (2683)
  • Physiology (4014)
  • Plant Biology (8657)
  • Scientific Communication and Education (1508)
  • Synthetic Biology (2394)
  • Systems Biology (6435)
  • Zoology (1346)