Individual muscle Coordination strategies and their role in the development of musculoskeletal disorders – COMMODE

This project is at the nexus of basic and clinical science. Our interdisciplinary approach will combine four main components:
- We will use a machine learning approach to analyse large cohorts of affected and non-affected individuals;
- Together, with classical recordings of myoelectrical activity, we will use an affordable technique to measure muscle architecture to provide a better estimate of muscle coordination strategies with the ulterior motive of introducing this approach in clinical practice;
- The studies will focus on two major MSK disorders (Achilles tendinopathy and patellofemoral pain), which are a common cause of severe long-term pain and physical disability. The investigation of different tissue pathologies (tendon and joint) will ensure knowledge gained will be transferable to many other MSK conditions where altered muscle coordination is suspected.
- As gender differences in the incidence and prevalence of MSK disorders have been shown, we will consider a possible gender effect by recruiting both males and females.

1) We showed the existence of individual muscle activation signatures
2) We developed an apporach to assess and map these signatures
3) We tested an approach to assess the neural drive to the muscle
4) We identified a difference in force distribution between muscles of the triceps surae in people with Achilles tendinopathy compared to controls

These results have been published, with mention to the ANR grant

- Task 1: 100 % completed from the initial aim – but other aims have been added to strengthen the outcomes

- Task 2: 50 % completed from the initial aim. Data have been collected and are currently analysed.

- Task 3: 75 % completed from the initial aim.
We have published one article. We are waiting for the Australian borders to re-open such that we can collect the second part of the data at the University of Queensland (Foreign partner of the project).

- 5 articles already published in peer-reviewed journals
journals.physiology.org/doi/full/10.1152/japplphysiol.01101.2018

royalsocietypublishing.org/doi/10.1098/rsif.2020.0770

journals.physiology.org/doi/abs/10.1152/japplphysiol.00635.2020

journals.lww.com/acsm-msse/Fulltext/2020/05000/Force_sharing_within_the_Triceps_Surae__An.9.aspx
www.sciencedirect.com/science/article/pii/S1050641121000353

- Note that 2 of these articles have been published as a preprint
www.biorxiv.org/content/10.1101/2021.02.19.431376v1

www.biorxiv.org/content/10.1101/2020.07.23.217034v2

- Results of 1 article highlighted in the New York Times
www.nytimes.com/2019/10/23/well/move/something-in-the-way-we-move.html

- Results of 1 article have been highlighted in the Blog of the Société de Biomécanique
www.biomecanique.org/index.php/fr/blog/41-test-1

- An article has been written to explain how human movement is produced to kids and teens. This article is currently in press in Frontiers for Young Minds (open access).

Each individual differs from any other, i.e. there are distinctive patterns or characteristics by which an individual can be identified. If we consider movement patterns, this may be thought of as an individual movement signature. Surprisingly, within both a research and clinical setting, individual differences in the way participants move or in the way they respond to an intervention are often ignored. Multiple domains share the same transformative conviction: approaches reporting average group data are obsolete in the precision medicine era.

Muscle coordination refers to the distribution of force among muscles to produce a motor task. Owing to considerable redundancy in the musculoskeletal (MSK) system, there are many available muscle coordination strategies that can achieve a given task. As such, non-personalised approaches may conceal important differences between individuals and lead to a conclusion that all individuals use a similar coordination strategy and/or adapt similarly to a specific treatment; these conclusions being only true “on-average.”

Our primary testable hypothesis is that each individual has unique muscle coordination strategies that will have specific mechanical effects on his/her MSK system. As such, some strategies would make people more at risk of developing MSK disorders than others. This hypothesis was presented in an invited review published by our team. Specifically, we will address the following aims:
- Aim1. To identify individual muscle coordination strategies on a cohort of asymptomatic participants.
- Aim 2. To determine whether coordination strategies between heads of the quadriceps differ in people with patellofemoral pain compared with controls (2.1) and whether particular muscle coordination strategies are associated with recovery (2.2).
- Aim 3. To determine whether coordination strategies between heads of the triceps surae differ in people with Achilles tendinopathy compared with controls (3.1) and whether particular muscle coordination strategies are associated with recovery (3.2).

This project is at the nexus of basic and clinical science. Our interdisciplinary approach will combine four main components:
- We will use a machine learning approach to analyse large cohorts of affected and non-affected individuals;
- Together, with recordings of myoelectrical activity, we will use an affordable technique to measure muscle architecture to provide a better estimate of muscle coordination strategies with the ulterior motive of introducing this approach in clinical practice;
- The studies will focus on two major MSK disorders (Achilles tendinopathy and patellofemoral pain), which are a common cause of severe long-term pain and physical disability. The investigation of different tissue pathologies (tendon and joint) will ensure knowledge gained will be transferable to many other MSK conditions where altered muscle coordination is suspected.
- As gender differences in the incidence and prevalence of MSK disorders have been shown, we will consider a possible gender effect by recruiting both males and females.

This project will mark a change away from the research paradigm, whereby individual differences are considered noise, to one whereby individual differences are considered relevant information. If muscle coordination strategies predispose an individual to the development of future symptoms or to the non-resolution of symptoms, one may be able to screen or identify individuals who are at high risk and introduce personalized interventions. This is particularly important to prevent the first episode of pain, as history of pain is the strongest predictor of future MSK pain. This project is a necessary first step toward an ambitious prospective clinical study.

A previous iteration of this project was ranked 2nd on the waiting list in 2018. This project will take benefit of artificial intelligence for data analysis; which is one of the strategic priorities of the French government.