CE37 - Neurosciences intégratives et cognitives

Cross-frequency coupling analysis in amyotrophic lateral sclerosis as potential biomarker and therapeutic target – FrequALS

Submission summary

Amyotrophic lateral sclerosis (ALS) is characterized by the degeneration of upper and lower motor neurons (UMN & LMN), located in the cerebral cortex, and the brainstem and spinal cord, respectively. ALS diagnosis mostly relies on LMN signs, which are also common to other diseases. In addition, the gold standard to assess therapy efficacy remains primarily based on LMN evaluation, excluding UMN assessment. This is partly because LMN degeneration can mask UMN signs, making it more difficult to faithfully detect UMN dysfunction, which delays treatment initiation and limits early inclusion in clinical trials. To circumvent this limitation, we here propose to evaluate cortical dysfunction (Ct Dysf) to improve ALS diagnosis. Methods relying on transcranial magnetic stimulation (TMS) and magnetic resonance imaging (MRI) revealed early cortical dysfunction in ALS, that precedes the onset of LMN signs, negatively correlates with survival and is not present in diseases that solely target LMN. Thus, in combination with LMN signs, Ct Dysf could help ensure diagnosis and prognosis of ALS. While TMS and MRI are limited in their routine clinical application, for physiological and technical reasons, electroencephalogram (EEG) has the potential to meet the need for a quantitative and reliable biomarker of Ct Dysf thanks to its high time resolution and recent methodological advances, including source imaging (improving spatial resolution) and quantitative modulation index (MI) of cross frequency coupling (CFC). Importantly, EEG can be easily implemented in both patients and animal models, thereby facilitating translational multicentric research and paving the way for the assessment of new therapies with a greater chance of success.
Building on our preliminary data, we hypothesize that altered CFC can serve as an early and quantitative biomarker of Ct Dysf in ALS. Accordingly, we have gathered German and French preclinical and clinical teams with well-known expertise in ALS, the assessment of Ct Dysf, EEG and brain connectome, to reach the objectives of FrequALS: 1) test whether altered CFC may represent a novel and early biomarker of Ct Dysf in patients with ALS and presymptomatic gene mutation carriers; 2) determine the temporal, spatial and cellular origins of altered CFC and Ctx Dysf using various mouse models of ALS and 3) generate and compare computational models of cellular and synaptic origins of Ct Dysf in ALS mouse models and patients. We anticipate finding a significant impairment of CFC in ALS patients and presymptomatic mutation carriers compared to healthy controls, and to identify a worsening of this feature from presymptomatic to symptomatic stages, particularly in the sensorimotor areas, which are the first to be affected in ALS. In parallel, we expect to unravel the cellular and circuit basis of altered CFC in ALS, in order to therapeutically target identified cell types in future studies. Finally, we aim to deliver a generic whole-brain oscillatory dynamics model, able to render CFC maps and parameter sets, specific for different human and mouse controls and ALS patients and models.
CFC analysis of EEG encompasses all the required features to be rapidly added to the currently available ALS diagnosis toolset. Building on previously established, strong collaborations between our preclinical and clinical teams, FrequALS is thus providing groundwork for a strongly improved ALS diagnostic pipeline and will unravel novel circuit-based therapeutic targets.

Project coordination


The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.


LIB Laboratoire d'Imagerie Biomédicale
LMU Klinikum der Universität München / Liebscher lab
UKU Universitätsklinikum Ulm / Klinik für Neurologie

Help of the ANR 781,480 euros
Beginning and duration of the scientific project: January 2022 - 36 Months

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